Guided computing device repair systems, methods, and apparatus

Abstract

Embodiments of the disclosure provided herein include methods, computer-readable media, apparatus, and systems for facilitating the diagnosis and repair of one or more performance conditions associated with a computing device.

Description

[Technical Field]

[0001] Cross-reference to related applications: This application claims the benefit of U.S. Provisional Patent Application No. 62 / 971,413, filed on 7 February 2020, which is incorporated herein by reference in its entirety. [Background technology]

[0002] Customers typically communicate with customer service representatives to diagnose or determine the problems or issues they are experiencing, and customer service representatives typically communicate with customers, often remotely and with limited knowledge of the problems or issues the customer wishes to resolve, in order to provide service to the customer. There is no effective diagnostic system that can link the customer's experience to the diagnostic data received from the customer's device. The applicant has identified several additional shortcomings and problems associated with conventional customer service representative systems. Through applied efforts, ingenuity, and innovation, many of these identified problems have been resolved by developing solutions included in embodiments of the present invention, many of which are described in detail herein. [Overview of the Initiative] [Problems that the invention aims to solve]

[0003] We provide a guided computing device repair system, method, and apparatus. [Means for solving the problem]

[0004] In general, embodiments of the disclosure provided herein include methods, systems, apparatus, and computer program products for facilitating the diagnosis and repair of one or more performance conditions related to computing devices, such as mobile computing devices. Embodiments of the disclosure may include a guided customer service interface for improving the diagnosis and determination of customer problems or issues.

[0005] In general, embodiments of the present invention provided herein include methods, computer-readable media, apparatus, and systems for providing customer service. In some exemplary embodiments, a method is provided which includes receiving a first dataset associated with a first mobile computing device via a first network. The first dataset may include one or more data values ​​associated with the first mobile computing device. In some embodiments, the method may include determining a plurality of performance states of the first mobile computing device. The plurality of performance states may include at least one performance state for one or more of a plurality of operating categories. At least the first performance state may be associated with a first operating category, which may be a first diagnostic indicator associated with the first mobile computing device. In some embodiments, the method may include displaying a first graphical user interface on a screen. The first graphical user interface may include visual representations associated with two or more of a plurality of operating categories, including a first operating category. The visual representations may be associated with a first operating category and include a first visual representation of a first diagnostic indicator. The first visual representation of a first diagnostic indicator may visually distinguish the visual representation associated with a first operating category from the visual representation associated with a second operating category.

[0006] In some exemplary embodiments, determining a first performance state associated with a first operating category includes identifying a threshold associated with the first operating category. In some embodiments, the method may include determining the first performance state based on a comparison of one or more data values ​​with a threshold.

[0007] In some exemplary embodiments, identifying a threshold associated with a first behavioral category involves receiving an aggregated dataset associated with multiple other mobile computing devices. The aggregated dataset may contain one or more data values ​​associated with multiple mobile computing devices from multiple behavioral categories. In some embodiments, the method may include setting a threshold based on a statistical analysis of the aggregated dataset for the first behavioral category.

[0008] In some exemplary embodiments, the threshold may be defined as being less than the mean or median of the aggregated dataset for the first behavior category. In some exemplary embodiments, determining a first performance state associated with a first operating category may further include identifying a range associated with the first operating category. In some embodiments, the method may include determining a first performance state based on a comparison of one or more data values ​​with a range.

[0009] In some exemplary embodiments, determining a first performance state associated with a first behavioral category may include receiving an aggregated dataset associated with a plurality of other mobile computing devices. The aggregated dataset may include one or more data values ​​associated with a plurality of mobile computing devices from a plurality of behavioral categories. In some embodiments, the method may include training a model on the aggregated dataset to determine at least one of a plurality of performance states. In some embodiments, the method may include determining a first performance state associated with a first behavioral category by applying the first dataset to a model.

[0010] In some exemplary embodiments, the method may include receiving a second dataset associated with a plurality of second mobile computing devices. The second dataset includes one or more data values ​​associated with the plurality of second mobile computing devices from a plurality of operation categories. In some embodiments, the method may include aggregating the second dataset to generate an aggregated dataset. Determining a first performance state associated with a first operation category may include comparing one or more data values ​​in the first dataset associated with the first operation category with one or more data values ​​in the aggregated dataset associated with the first operation category.

[0011] In some exemplary embodiments, comparing one or more data values ​​in a first dataset for a first operating category with one or more data values ​​in an aggregated dataset for the first operating category may include identifying a threshold for the first operating category based on the aggregated dataset. In some embodiments, the method may include determining a first performance state based on a comparison of one or more data values ​​associated with a first mobile computing device with a threshold.

[0012] In some exemplary embodiments, identifying thresholds for a first behavior category based on an aggregated dataset may include determining the mean or median of the first behavior category based on the aggregated dataset.

[0013] In some exemplary embodiments, comparing one or more data values ​​in a first dataset associated with a first operational category with one or more data values ​​in an aggregated dataset associated with the first operational category may include identifying a range associated with the first operational category based on the aggregated data. In some embodiments, the method may include determining a first performance state based on a comparison of one or more data values ​​associated with a first mobile computing device with a range.

[0014] In some exemplary embodiments, the visual representation associated with a first behavior category may include visual representations of multiple behavior subcategories associated with the first behavior category.

[0015] In some embodiments, visual representations associated with multiple operational subcategories may include visual representations associated with a first operational subcategory. Multiple performance states may include performance states associated with the first operational subcategory. Visual representations associated with the first operational subcategory may include visual representations of diagnostic indicators associated with the first operational subcategory.

[0016] In some embodiments, the visual representation of a diagnostic indicator associated with a first operational subcategory may be visually represented in the same way as the first visual representation of the first diagnostic indicator.

[0017] In some embodiments, the visual representation of a diagnostic indicator associated with a first operational subcategory may be visually represented in a manner different from the first visual representation of the first diagnostic indicator.

[0018] In some embodiments, the first visual representation of the first diagnostic indicator may include a symbol. In some exemplary embodiments, a first visual representation of a first diagnostic indicator may indicate at least one problem from a first behavioral category or a first behavioral subcategory.

[0019] In some exemplary embodiments, the first visual representation of the first diagnostic indicator may indicate that there are no problems with the first operation category and the first operation subcategory. In some exemplary embodiments, the plurality of performance states may include a second performance state associated with a second operation subcategory. The second performance state associated with the second operation subcategory includes a second diagnostic indicator. In some embodiments, the method may include a visual representation of the plurality of operation subcategories and may include a visual representation of the second operation subcategory. The visual representation of the second operation subcategory may include a visual representation of the second diagnostic indicator. The visual representation of the second diagnostic indicator may indicate a diagnosis different from the diagnosis indicated by the first diagnostic indicator.

[0020] In some exemplary embodiments, the method includes displaying a second graphical user interface in response to receiving a selection of the first operation category. The second graphical user interface may include a second visual representation associated with the first operation category, and the second visual representation associated with the first operation category may include one or more second diagnostic indicators associated with the first performance state. The one or more second diagnostic indicators associated with the first performance state may provide additional information associated with the first performance state regarding the first diagnostic indicator.

[0021] In some exemplary embodiments, the one or more second diagnostic indicators may include a diagnostic message that includes an explanation of one or more problems associated with the first performance state.

[0022] In some exemplary embodiments, the second graphical user interface may include a plurality of historical data from a first data set for the first operation category and a time stamp associated with the historical data.

[0023] In some exemplary embodiments, a portion of the historical data from the first dataset may include one of the second diagnostic indicators associated with the first performance state. In some exemplary embodiments, the second graphical user interface may include a plurality of historical data from a first dataset for a first behavior category, a timestamp associated with the historical data, and a diagnostic indicator associated with the historical data.

[0024] In some exemplary embodiments, the diagnostic indicator associated with the historical data may be associated with only a portion of the historical data indicating a problem associated with the first mobile computing device.

[0025] In some exemplary embodiments, the method includes determining one or more diagnostic messages associated with a first performance state. In some embodiments, the method may include displaying one or more performance prompts containing one or more of the diagnostic messages on a second graphical user interface.

[0026] In some exemplary embodiments, one or more performance prompts may include one or more programmatically generated potential solutions to one or more problems of a first computing device associated with a first performance state.

[0027] In some exemplary embodiments, the method includes displaying a feedback icon associated with each of the performance prompts on a second graphical user interface. In some embodiments, the method may include determining one or more additional diagnostic messages in response to receiving a selection from one of the feedback icons. In some embodiments, the method may include updating the display of the second graphical user interface in response to receiving a selection from one of the feedback icons to display one or more of the additional diagnostic messages.

[0028] In some exemplary embodiments, the method may include, in instances where the selection of one of the feedback icons indicates a successful solution to one or more problems associated with a first performance state, one or more additional diagnostic messages may indicate a successful solution to the problem.

[0029] In some exemplary embodiments, the method may include removing a visual representation of a second diagnostic indicator associated with one or more problems in instances where the selection of one of the feedback icons indicates a successful solution to one or more problems associated with a first performance state.

[0030] In some exemplary embodiments, the method may include updating a database associated with a diagnostic message in instances where the selection of one of the feedback icons indicates a successful solution to one or more problems associated with a first performance state.

[0031] In some exemplary embodiments, the method may include displaying a second performance prompt containing a second diagnostic message in instances where the selection of one of the feedback icons indicates a failure prompt.

[0032] In some exemplary embodiments, determining a first performance state associated with a first operating category may include receiving a second dataset associated with a plurality of second mobile computing devices. The second dataset may include one or more data values ​​associated with a plurality of second mobile computing devices from the plurality of operating categories. In some embodiments, the method may include aggregating the second datasets to generate an aggregated dataset. The aggregated dataset may include one or more data values ​​associated with a plurality of mobile computing devices from the plurality of operating categories. Determining a first performance state associated with a first operating category may involve comparing one or more data values ​​from the first dataset for the first operating category with one or more data values ​​from the aggregated dataset for the first operating category.

[0033] In some exemplary embodiments, determining one or more additional diagnostic messages may determine a first additional diagnostic message and a second additional diagnostic message. The first additional diagnostic message may define a first diagnostic message resolution value, and the second additional diagnostic message may define a second diagnostic message resolution value. In some embodiments, the method may include updating the display of a second graphical user interface in response to receiving a selection of one of a feedback icon in order to display one or more of the additional diagnostic messages, and may include displaying the first additional diagnostic message if the first diagnostic message resolution value is higher than the second diagnostic message resolution value, and displaying the second additional diagnostic message if the second diagnostic message resolution value is higher than the first diagnostic message resolution value.

[0034] In some exemplary embodiments, the method may include receiving an aggregated dataset associated with a plurality of other mobile computing devices. The aggregated dataset may include one or more data values ​​associated with a plurality of other mobile computing devices corresponding to a plurality of operating categories. In some embodiments, the method may include updating a display in response to receiving a selection of one or more of the plurality of operating categories in order to display a second graphical user interface that displays information associated with one or more selected of the plurality of operating categories.

[0035] In some exemplary embodiments, the second graphical user interface may include displaying multiple data from a first dataset for a first behavior category and displaying multiple data from an aggregated dataset for the first behavior category.

[0036] In some exemplary embodiments, the method may include determining a plurality of comparative performance states for one or more of a plurality of operating categories. In some embodiments, the method may include at least a first comparative performance state associated with a first operating category which may include a first comparative diagnostic indicator that compares a first mobile computing device with a plurality of other mobile computing devices. In some embodiments, the method may include displaying a visual representation of the first comparative diagnostic indicator on a second graphical user interface.

[0037] In some exemplary embodiments, the method includes determining one or more comparative diagnostic messages associated with a first comparative performance state, and displaying one or more performance prompts containing one or more of the comparative diagnostic messages on a second graphical user interface.

[0038] In some exemplary embodiments, the method includes displaying a feedback icon for each of the performance prompts on a second graphical user interface. In some embodiments, the method may include determining one or more additional comparative diagnostic messages in response to receiving a selection from one of the feedback icons. In some embodiments, the method may include updating the display of the second graphical user interface in response to receiving a selection from one of the feedback icons to display one or more of the additional comparative diagnostic messages.

[0039] In some exemplary embodiments, determining multiple performance states further includes determining at least one performance state by comparing the most recent data from a first dataset associated with an operation category with historical data from a predetermined period prior to the time associated with the most recent data.

[0040] In some exemplary embodiments, a first performance state is determined at least in part by problems identified in a first dataset that exists over a predetermined period of time. A first diagnostic indicator may define the nature of the problem. In some exemplary embodiments, the period may be one of 7, 14, 21, or 30 days.

[0041] In some exemplary embodiments, determining multiple performance states may include identifying thresholds for a first behavioral category based on historical data, and determining a first performance state based on a comparison of a first dataset with the thresholds.

[0042] In some exemplary embodiments, the method includes determining one or more diagnostic messages associated with a first performance state, and displaying one or more performance prompts, each containing one of the one or more diagnostic messages.

[0043] In some exemplary embodiments, the method includes displaying a feedback icon for each performance prompt. In some embodiments, the method may include determining one or more additional diagnostic messages in response to receiving a selection of one or more of the feedback icons. In some embodiments, the method may include updating the display of a graphical user interface in response to receiving a selection from one of the feedback icons in order to display one or more of the additional diagnostic messages.

[0044] In some exemplary embodiments, determining multiple performance states of a first mobile computing device may include identifying a range of a first operational category based on historical data, and determining a first performance state based on a comparison of a first dataset with the range.

[0045] In some exemplary embodiments, the method includes determining one or more diagnostic messages associated with a first performance state, and displaying one or more performance prompts, each containing one of the one or more diagnostic messages.

[0046] In some exemplary embodiments, the method includes displaying a feedback icon for each of the performance prompts. In some embodiments, the method may include determining one or more additional diagnostic messages in response to receiving a selection of one or more of the feedback icons, and updating the display of a graphical user interface in response to receiving a selection from one of the feedback icons to display one or more of the additional diagnostic messages.

[0047] In some exemplary embodiments, the method includes establishing an transmit connection with a customer in response to a communication request from the customer associated with a first mobile computing device. In some embodiments, the method may include receiving at least a portion of a first dataset via the transmit connection. In some embodiments, the method may include determining one or more diagnostic messages associated with a first performance state. In some embodiments, the method may include establishing a communication connection with a customer. Establishing the communication connection may be done in connection with displaying a first graphical user interface. In some embodiments, the method may include displaying one or more performance prompts, each containing one of the one or more diagnostic messages. In some embodiments, the method may include sending a first instruction set associated with one or more of the one or more diagnostic messages to the first mobile computing device. In some embodiments, the method may include receiving a responsive portion of the first dataset from the first mobile computing device via the transmit connection. The responsive portion of the first dataset is associated with a response from the first mobile computing device processing the first instruction set.

[0048] In some exemplary embodiments, the communication connection may be a telephone or an audio connection. In some exemplary embodiments, a portion of the first dataset may be one of several portions of the first dataset. A portion of the first dataset may include data values ​​associated with a first mobile computing device from several operational categories when a transmit connection is established.

[0049] In some exemplary embodiments, the first visual representation of the first diagnostic indicator may be, or may include, shading of the colors, symbols, status messages, and / or visual representations of the first operating category.

[0050] In some exemplary embodiments, the method may include determining one or more diagnostic messages associated with a first performance state. The one or more diagnostic messages may be determined based on an aggregated dataset associated with a plurality of other mobile computing devices.

[0051] In some exemplary embodiments, multiple other mobile computing devices may belong to the same category. In some exemplary embodiments, the method may include determining one or more diagnostic messages associated with a first performance state. The one or more diagnostic messages may be determined based on a trained model.

[0052] In some exemplary embodiments, the first visual representation of the first diagnostic indicator may include a modification of the visual representation associated with the first behavior category. In some exemplary embodiments, the first visual representation of the first diagnostic indicator may include a first icon defined on an icon representing a first behavior category.

[0053] In some exemplary embodiments, the method may include a client terminal including a screen. The client terminal may be located away from the first mobile computing device.

[0054] In some exemplary embodiments, a method may be provided for resolving one or more issues on a mobile device, comprising receiving a first dataset associated with a first mobile computing device via a first network. The first dataset may include one or more data values ​​associated with the first mobile computing device. In some embodiments, the method may include determining one or more performance states of the first mobile computing device. In some embodiments, the method may include generating and displaying one or more performance prompts based on at least one of the performance states. The one or more performance prompts may include diagnostic messages associated with the performance state.

[0055] In some exemplary embodiments, the method may include receiving instructions associated with a performance prompt via a graphical user interface. The instructions may include one of the following: instructions for a successful solution to a problem associated with one or more performance states, or instructions for an unsuccessful prompt.

[0056] In some exemplary embodiments, one or more performance states may be determined by a model. The model may be a statistical model or a trained machine learning model, which is trained on aggregated datasets from multiple other mobile computing devices.

[0057] In some exemplary embodiments, one or more performance states may be determined based on aggregated datasets from multiple other mobile computing devices.

[0058] In some exemplary embodiments, one or more performance prompts may be determined by the model. The model may be a statistical model or a trained machine learning model, which is trained on aggregated datasets from multiple other mobile computing devices.

[0059] In some exemplary embodiments, one or more performance prompts may be determined based on aggregated datasets from multiple other mobile computing devices.

[0060] In some embodiments, a method may be provided that includes receiving input from a user on a first mobile computing device. The input may be an instruction for a request to initiate a support session. In some exemplary embodiments, the method may include establishing communication between the first mobile computing device and a customer service system and sending a first dataset from the mobile computing device to the customer service system. In some exemplary embodiments, the method may include initiating one or more corrective actions on the first mobile computing device based on one or more performance prompts generated in response to the first dataset.

[0061] In some exemplary embodiments, a method may be provided that includes receiving a first dataset associated with a first mobile computing device via a first network. The first dataset may include one or more data values ​​associated with the first mobile computing device. In some embodiments, the method may include determining a plurality of performance states of the first mobile computing device. The plurality of performance states may include at least one performance state for one or more of a plurality of operating categories. In some embodiments, the method may include identifying one or more thresholds associated with the plurality of performance states. In some embodiments, the method may include determining one or more corrective actions based on a comparison of the plurality of performance states with one or more thresholds associated with the plurality of performance states. In some embodiments, the method may include establishing communication with the first mobile computing device. In some embodiments, the method may include establishing that one or more corrective actions are transmitted to the first mobile computing device.

[0062] In some exemplary embodiments, one or more corrective actions include one or more changes to the settings of the first mobile device. In some exemplary embodiments, triggering the transmission of one or more corrective actions to a first mobile computing device includes pushing the corrective actions to the first mobile device.

[0063] Next, refer to the attached drawings, which are not necessarily drawn to scale. [Brief explanation of the drawing]

[0064] [Figure 1] This specification presents exemplary systems based on several embodiments discussed herein. [Figure 2] This specification describes exemplary mobile computing devices according to several embodiments discussed herein. [Figure 3A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 3B] Figure 3A shows an example of a graphical user interface relating to the "Overview" operation category, based on several embodiments discussed herein. [Figure 4A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 4B] Figure 4A shows an example of a graphical user interface relating to the "battery" operation category in some embodiments discussed herein. [Figure 4C] Figure 4A shows an example of a graphical user interface relating to the “signal” operation category in some embodiments discussed herein. [Figure 5A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 5B] Figure 5A shows an example of a graphical user interface for the “Audio” operation category in some embodiments discussed herein. [Figure 6A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 6B] Figure 6A shows an example of a graphical user interface relating to the "battery" operation category in some embodiments discussed herein. [Figure 7A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 7B] Figure 7A shows an example of a graphical user interface relating to the "battery" operation category in some embodiments discussed herein. [Figure 8A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 8B] Figure 8A shows an example of a graphical user interface for the “Audio” operation category in some embodiments discussed herein. [Figure 9] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 10] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 11] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 12] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 13] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 14] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 15] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 16] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 17] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 18] A flowchart of an exemplary system according to some embodiments discussed herein is shown. [Figure 19A] This specification describes exemplary graphical user interfaces based on several embodiments discussed herein. [Figure 19B] Figure 19A shows an example of a graphical user interface relating to the “Settings” operation category in some embodiments discussed herein. [Figure 19C] Figure 19A shows an example of a graphical user interface relating to the “Settings” operation category in some embodiments discussed herein. [Figure 20A] This specification describes exemplary graphical user interfaces for computing devices, based on several embodiments discussed herein. [Figure 20B] An example of a graphical user interface in one of the embodiments discussed herein is shown in Figure 21A. [Figure 21A] This specification describes exemplary graphical user interfaces for computing devices, based on several embodiments discussed herein. [Figure 21B] An example of a graphical user interface in Figure 22A, according to some embodiments discussed herein, is shown. [Modes for carrying out the invention]

[0065] Herein, some embodiments of the present invention are fully described below with reference to the accompanying drawings, which illustrate some, but not all, embodiments of the present invention. In fact, the present invention can be embodied in many different forms and should not be construed as being limited to the embodiments described herein, but rather these embodiments are provided to satisfy the legal requirements to which this disclosure is applicable. Throughout, similar figures refer to similar elements.

[0066] <Terminology> Where used herein, “data,” “content,” “information,” and similar terms may be used interchangeably to refer to data that can be transmitted, received, and / or stored in accordance with embodiments of the present invention. Therefore, the use of any such terms should not be considered to limit the spirit and scope of embodiments of the present invention. Furthermore, where a computing device is described herein to receive data from another computing device, it will be understood that the data may be received directly from the other computing device or indirectly through one or more intermediate computing devices, such as one or more servers, relays, routers, network access points, base stations, hosts, etc., which may also be referred to herein as “network.” Similarly, where a computing device is described herein to transmit data to another computing device, it will be understood that the data may be transmitted directly to the other computing device or indirectly through one or more intermediate computing devices, such as one or more servers, relays, routers, network access points, base stations, hosts, etc.

[0067] As used herein, the term “dataset” means any data associated with or otherwise related to a computing device, including, but not limited to, data that identifies a device, a customer, the hardware of a device, the software of a device, or the characteristics, behavioral categories, or behavioral subcategories of a device. A dataset may consist of a single set of data, or a dataset may consist of multiple parts of data, such as other datasets. Parts of a dataset may be associated with behavioral categories or behavioral subcategories. In some embodiments, a dataset may be divided chronologically. For example, a first part of a dataset may be associated with historical data, and a second part of a dataset may be associated with current or real-time data. A dataset may also include timestamps associated with the behavioral categories and / or behavioral subcategories of the data. A dataset may be associated with a single computing device, or alternatively, a dataset may be aggregated from datasets from multiple devices. Data aggregation may be performed at predetermined intervals (e.g., daily). An aggregated dataset may be further divided. For example, an aggregated dataset could be data from multiple computing devices having the same or different classifications, such as classification by device type (e.g., smartphone, laptop), manufacturer, maker, and / or model, and the aggregated dataset could have portions for each computing device's device type, manufacturer, maker, or model. The dataset may be collected at specific times and / or intervals based on one or more factors. For example, the data collection rate may depend on the operating system associated with the computing device and on the type of data and platform (e.g., iOS vs. Android®). In some embodiments, some data is collected on a schedule basis, and some is collected remotely on demand by requests sent by customer cycles.In some embodiments, the user can only completely disable data collection and limit the functionality of the guided interface. In some embodiments, the customer service system may send a request from a customer service computing device or server to a customer computing device requesting the most up-to-date data values ​​at the time of request. In some embodiments, the customer computing device may also upload some data that has been locally stored on the customer computing device since the last scheduled update (e.g., 24 hours).

[0068] As used herein, the term “operational category” refers to any category of data associated with a computing device, including but not limited to battery, signals, processor, storage, audio, settings, commands, status updates, applications, remote support, or registration. In some embodiments, an operational category may refer to a single layer of data associated with a computing device. In some embodiments, an operational category may include a data layer having one or more data layers (e.g., operational subcategories) within the category.

[0069] As used herein, the term “operational subcategory” refers to any subcategory of data associated with an operational category. An operational subcategory may belong to one operational category, or an operational subcategory may be associated with two or more operational categories. In some embodiments, an operational subcategory may include a second information layer within any operational category. For example, an operational subcategory of an audio operational category may be, but are not limited to, music volume, call volume, ringtone volume, alarm volume, system volume, Bluetooth®, Bluetooth volume, or other audio volume. As a further example, an operational subcategory of a battery operational category may be, but are not limited to, battery health, battery capacity, firmware health, battery status, performance, consumption, low battery, charge, charge alert, charge rate, discharge rate, battery charge type, battery charge rate, hibernation discharge, startup discharge, average battery life, current battery life, battery usage, voltage, current, power, temperature, current level, or level degradation. As further examples, the operational subcategories of a signal operational category may include, but are not limited to, signal strength, noise, signal quality, average signal quality, received strength signal indicator, reference signal received power, reference signal received quality, reference signal signal-to-noise ratio, cell identity, physical cell ID, and tracking area code. Operational categories and operational subcategories may refer to information at different specific layers relative to each other. For example, an operational category may also be an operational subcategory for information of a higher category. For example, an operational subcategory may also be an operational category for one or more subcategories below it.

[0070] As used herein, the term “performance state” means data indicating the operation of one or more aspects of a computing device, such as data indicating the operation of a computing device for an operational category or operational subcategory, and a performance state may include different data associated with each operational category or operational subcategory. A performance state associated with an operational category may be based on a performance state associated with data values ​​of a mobile device that falls under one or more operational subcategories within the operational category. For example, if it is determined that there is a problem associated with a computing device associated with an operational subcategory, it may be determined that there is a problem associated with the computing device for that operational category. A performance state may include one or more data values ​​such as numerical values, messages, and / or other data values ​​associated with the state (e.g., good, normal, bad, charged, discharged, working, not working). For example, the performance state of the operational subcategory of battery temperature may be “normal” or equivalent when the battery temperature is determined to be at a normal temperature. Furthermore, a performance state may include comparative performance obtained based on a comparison of data for an operational category or operational subcategory of a first computing device with data for an operational category or operational subcategory of the first computing device from a second computing device, or, as further disclosed herein, with data from an aggregated dataset. In some embodiments, the performance state may be determined as a gradient or degree (e.g., 50% function). The performance state may include one or more diagnostic indicators representing data indicating the operation of one or more aspects of the computing device. In some embodiments, the performance state may then include one or more “problems” which may be indicated by the diagnostic indicators. As used herein, terms such as “problem” and “issue” refer to any actual, possible, likely, potential, or recognized operational defect or anomaly that a user or customer service representative may attempt to resolve.

[0071] As used herein, the term “diagnostic indicator” refers to a diagnostic indicator associated with a computing device, determined in relation to a performance state. Diagnostic indicators may be determined using various embodiments described herein and may be visually represented in a graphical user interface, such as icons, colors, diagnostic messages, or other representations that convey information about a performance state to the user. For example, a normal performance state of battery temperature may have a diagnostic indicator associated with the device’s normal detection state (e.g., a green hue, checkmark, thumbs-up, “Good” or “Normal” message, or another indicator of a normal performance state). For example, a diagnostic indicator may be visualized in a graphical user interface by green text, a green-colored icon, or a background shading of an area associated with a particular color of battery temperature. As a further example, a performance state of below average, unacceptable, or otherwise defective relative to an average battery life data value may include a diagnostic indicator visually represented by yellow text, a yellow icon, and / or a yellow hue against an icon associated with the performance state indicating that the performance state involves a possible or actual problem. Diagnostic indicators may be generated for different information layers within a graphical user interface. For example, the performance status of the "Battery" operation category, which includes issues associated with the battery, may include diagnostic indicators that show diagnosed battery problems. Selecting a battery operation category in the interface may display one or more second diagnostic indicators that further refine the diagnosis, for example, into a separate subcategory. Additional examples of visual representations associated with diagnostic indicators may be icons or text displayed on a graphical user interface that are highlighted (e.g., colored, highlighted, bolded, italicized, enlarged, shaded, flashing, pulsed, or resized).Further examples of diagnostic indicators include numerous embodiments described herein, which will be understood in light of this disclosure to include any other indicators of performance status.

[0072] As used herein, the term “diagnostic message” refers to a type of diagnostic indicator that may include a message determined by the customer service system, and a diagnostic message may be displayed on a graphical user interface to describe a performance condition and / or diagnostic indicator associated with an operating category or subcategory. For example, if a customer is communicating with a customer service representative about a volume being too low, a diagnostic message may include a current or past volume setting, an explanation of why this may be a problem, and / or recommendations to provide to the customer.

[0073] As used herein, the term “performance prompt” refers to a prompt displayed on a graphical user interface that may include a diagnostic message prompting a customer service representative to discuss a performance status and / or diagnosis with the customer. Performance prompts may be generated programmatically according to the various embodiments discussed herein. In some embodiments, performance prompts may be determined based on a performance status and / or diagnostic indicators, which may facilitate further data collection and / or repair of the computing device. In some embodiments, performance prompts may provide individual actions to resolve one or more potential or actual problems diagnosed in relation to the performance status.

[0074] As used herein, the term “feedback icon” refers to an icon displayed on a graphical user interface that enables a user of the graphical user interface (e.g., a customer service representative) to provide feedback. In various embodiments, a feedback icon may be presented to collect data from the customer service representative indicating additional data collection. For example, a feedback icon may be a radio box that allows the user to check a box that may indicate that a prompt associated with a message has been resolved, or alternatively, that it has not been resolved. In some embodiments, a feedback icon may be presented, and when selected, trigger the sending of a computer program instruction configured to cause a software modification associated with the consumer computing device to address one or more performance conditions. A feedback icon may be dynamic, such as by changing its color, shape, image, or, if the icon has a message, by changing the message.

[0075] As used herein, the term “resolution value” refers to a value associated with a diagnostic message, which may be a probability, prediction, or estimate that what is addressed in the diagnostic message can diagnose or resolve a customer’s problem or issue. Resolution values ​​may define the confidence level associated with performance prompts and / or diagnostic messages. In some embodiments, resolution values ​​can facilitate the ranking of performance prompts and the selection by the computing system of which performance prompts to display to a user (e.g., a customer service representative). Resolution values ​​may be determined by analyzing or statistically modeling historical data values ​​of a first mobile computing device and / or datasets not associated with a mobile computing device. For example, if several datasets associated with a particular manufacturer and model of a mobile computing device indicate an issue in an operational subcategory (e.g., low battery level) and the issue can be resolved by an action the customer can take (e.g., plugging in the mobile computing device), or may have a higher percentage change, then diagnostic messages associated with these actions the user can take may receive higher resolution values. As a further example, and in contrast, if multiple datasets associated with a particular manufacturer and model of mobile computing device indicate an issue in an operational subcategory (e.g., low battery level) and the issue may not be resolved by an action the customer can take (e.g., replace the battery), or may have a lower percentage change, then the diagnostic messages associated with these actions the user can take may receive lower resolution values. Furthermore, resolution values ​​and associated diagnostic messages are more likely to be stored in the database, and in response to feedback that the diagnostic messages guided customer service representatives to address or resolve the customer's issue or problem, the database is updated to reflect the diagnostic messages that addressed or resolved the addressed customer issue or problem.

[0076] As used herein, the term “customer” may include, but is not limited to, clients, customers, buyers, shoppers, users, etc., who are in a position to interact with, or may interact with, a customer service representative in order to diagnose or resolve a problem or issue with one or more computing devices.

[0077] <Overview> As technology advances, customers purchasing the technology often fail to keep up with how computing devices work, making them unable to effectively diagnose problems with their computing devices or to articulate the specificity of the problem to others (e.g., customer service representatives) that would enable them to diagnose the issue. The proliferation of mobile computing devices (e.g., cell phones, smartphones, tablets) has placed technology in the hands of many customers who purchase it without understanding much of the details of how these computing devices work. This can lead to problems or issues with computing devices such as mobile computing devices, without knowing how to diagnose, address, or resolve potential problems or issues, or without understanding the connection between the symptoms customers experience and the actual problem with their computing device. In some cases, when a problem or issue occurs, customers contact customer service representatives for help, but they are unable to adequately describe the problem to the customer service representatives or provide the information necessary to resolve the computing device issue.

[0078] Customer service representatives can assist customers in resolving issues with their computing devices. Customer service representatives may be located remotely, and communication with them may be via telephone, video call, or live chat. Furthermore, the only information a customer service representative may have about a customer's problem or issue is limited to what the customer can provide. Differences in technical knowledge among customers, along with language and dialect differences, can significantly alter how customers describe their problems or issues. For example, if a smartphone screen does not need to display information (e.g., blank), one customer might describe the problem as the device not being turned on, another as the battery being dead, and yet another as the screen being broken. Additionally, customers may not have access to the technical history of the device or the software running on it, and therefore may not have access to the relevant parts of the device to attempt to diagnose or describe the problem or issue. Additionally or alternatively, customers may conduct research online to address or diagnose the problem or issue, and may present this information to customer service representatives, but this can be misleading. In some cases, multiple issues can cause complex symptoms that cannot be effectively diagnosed through external observation or a typical customer service call. Customer service representatives may be required to address all of these situations. Customer service representatives may be able to address customer issues or problems by understanding the customer's computing device and obtaining information on the appropriate questions to ask and what corrective actions should be taken. Knowledge of computing devices and questions can be obtained from several sources, such as a customer service system that can provide guidance. Traditional solutions to these problems required users to send their computing devices to a repair facility for in-person diagnosis and repair or replacement.

[0079] Customer service representatives may not be aware that a customer's description reflects the actual fault or performance condition causing the problem or issue with the computing device. For example, a fault could be in the hardware or software of the computing device, but the customer might describe a hardware problem or issue when the problem or issue is in the software (or vice versa). Furthermore, when customers describe a problem or issue, they may not be able to specify whether it is acute or chronic. Difficulty in accurately describing a problem or issue can make it difficult for customer service representatives to address them. Therefore, for example, a customer service system may remotely connect to the customer's computing device to address, diagnose, or resolve the problem or issue. Alternatively or additionally, customer service representatives may ask the customer to ship the computing device to a repair location.

[0080] This document describes a mobile device repair system, a guided customer service system, and a guided customer service interface, methods and systems for guiding customer service personnel to remotely address, diagnose, and / or resolve customer issues or problems by diagnosing one or more performance conditions associated with a computing device and computably bridging the gap between consumer experience and performance data from the device. The customer service system may use data received from a customer's computing device (e.g., a dataset), which may include historical data, recent data, and / or real-time data, which may be received one or partly. Additionally or alternatively, the customer service system may use data received from one or more other computing devices, which may be aggregated, to help address customer issues or problems. The customer service system may establish a connection with a customer's computing device and update the customer's computing device to address the issue or problem, and the computing device may send real-time data to the customer service system in response, which may indicate that the issue or problem has been resolved or may indicate additional information regarding the issue or problem. Furthermore, data exchange between customer service representatives, customer service systems, customers, and their computing devices may involve multiple iterations, and the system may programmatically determine the most likely solution to the problem and provide guided prompts to direct the solution.

[0081] Data from customer computing devices may be collected over time for use in conjunction with computing device diagnostic systems and guided customer service systems and interfaces. Regular data provision from customer computing devices to the customer service system may enable the customer service system to collect, store, and analyze data from customer devices over time to determine performance conditions that correctly indicate problems and avoid false positives. Furthermore, the analysis may guide customer service personnel when a customer requests assistance, and the customer service system may only request updates regarding recent data since the customer computing device last provided information. Additionally, having historical data from customer computing devices may enable diagnosis or analysis to determine whether a component of the customer computing device is the source of a problem or issue.

[0082] In some embodiments, the collection of data from a customer's computing device over time may require permission from the user. Permission may be granted only once by the customer, or the customer may be asked to grant permission each time data is collected, or may grant permission each time data is collected. In some embodiments, the customer may be granted permission for data collection over time so that the data collection creates a data log or collects data from an existing data log. In some embodiments, additional permission may be requested in addition to permission previously granted by the user, such as for supplemental or additional data collection initiated by a customer service representative. In some embodiments, the request for permission from the customer may be based on which behavioral category information or behavioral subcategory information is being collected. In some embodiments, the request for permission may be a communication with a customer service representative (chat, video, email, etc.) which may be generated on the customer's computing device by the customer service representative (pop-up, notification, etc.) or may be generated automatically (pop-up, notification, etc.).

[0083] For example, in one embodiment, a customer may have a power-related problem, and data related to operational categories and / or operational subcategories related to power or battery usage, such as signal strength, location, volume level, and screen brightness, may be collected over time. The data collected over time may be stored on the customer's computing device and / or in a customer service system. In some embodiments, the data collected over time may be accessible after collection, for example, by the customer, a customer service representative, or another person on the customer service system or on the customer's computing device.

[0084] A customer's computing device may include several components, and each component may have data relating to its operation. Operational data may be associated with several operation categories, each category may consist of operation subcategories. Data analysis may be performed at the operation category level or at a more granular level at the operation subcategory level. In some embodiments, data may be analyzed together, and identified performance states may be assigned to operation categories and / or subcategories. Furthermore, analyzing data at the most subtle subcategory level may determine where a problem or issue is occurring, when such analysis may not be determined by analyzing the data at the category level. Additionally, when the subtle subcategory levels of a customer's computing device are compared to the same data from another similar computing device, or from a set of similar computing devices, it may be possible to determine how the customer's computing device is performing. This can be particularly useful because addressing a customer's problem or issue for an isolated computing device can be extremely difficult.

[0085] The customer service system may store data received from computing devices in a database, and the data may be analyzed as described herein to diagnose and determine where a customer may be experiencing problems or issues with their computing devices.

[0086] Various embodiments of the present invention relate to a graphical user interface, for example, the one shown in Figure 3A, which is adaptable, intuitive, and configured to guide a customer service representative. The guidance enables the customer service representative to efficiently converse with the customer, efficiently obtain information from the customer, and, in some examples, acquire non-signal data that may be necessary to correctly analyze and diagnose the customer's problem or issue, performance status, and underlying analysis, which may translate the customer's perceived problem into an actual problem for resolution by the systems and methods described herein. The guidance may be determined by the customer service system based on a dataset from the customer's computing device, a performance status determined by the customer service system, and diagnostic indicators. Additionally or alternatively, the graphical user interface may display the dataset from the customer's computing device, the performance status, and diagnostic indicators to the customer service representative. Furthermore, the customer service system may use the data analysis to provide the customer service representative with diagnostic messages for consultation with the customer.

[0087] <System Architecture> This disclosure includes various embodiments for a system architecture associated with a customer requesting customer service from a customer service representative via a customer system. Figure 1 shows an exemplary system architecture according to various embodiments of this disclosure. The system architecture may include a computing device 100, a plurality of computing devices 110A, 110B, ... 110N (collectively referred to herein as “Computing Device 110” or “Other Computing Devices”), a network 120, and a customer service system 130. The customer service system 130 may be communicably connected to computing devices 100 and computing devices 110 via a network 104, and the customer service system 130 may include a server 132, a database 134, and a customer service computing device 136. For clarity, only one server 132, a database 134, and a customer service computing device 136 are shown in Figure 1, but it will be understood that numerous additions of each may be present in the customer service system 130. The customer service computing device 136 may include a display for displaying a graphical user interface.

[0088] Computing device 100 may be associated with a customer, such as a customer requesting service involving a problem or issue with computing device 100. While computing device 100 is shown, any number of customer devices may be associated with and / or used by a customer. Computing device 100 may be a mobile device (i.e., a mobile computing device) and / or a stationary or fixed device. For example, computing device 100 may be a mobile device such as a mobile phone (e.g., a smartphone), laptop, tablet, or similar mobile computing device and / or communication device. Additionally and / or alternatively, computing device 100 may be a conventionally stationary device such as a desktop computer or workstation.

[0089] Network 120 may include one or more wired and / or wireless networks, including, for example, wired or wireless local area networks (LANs), personal area networks (PANs), metropolitan area networks (MANs), and wide area networks (WANs), as well as any hardware, software, and / or firmware for implementing one or more networks (e.g., network routers, switches, hubs, etc.). For example, Network 120 may include cellular networks, mobile broadband, Long Term Evolution (LTE), GSM® / EDGE, UMTS / HSPA, IEEE 802.11, IEEE 802.16, IEEE 802.20, WiFi, and / or WiMAX networks. Furthermore, Network 120 may include public networks such as the Internet, private networks such as intranets, or any combination thereof, and may utilize various network protocols currently available or to be developed in the future, including but not limited to TCP / IP-based network protocols.

[0090] The customer service system 130 may receive data from computing devices 100 and 110, transmit data to them, and communicate with them. As shown in Figure 1, the customer service system 130 engages in machine-to-machine communication with computing devices 100 and 110 via one or more networks 120. Furthermore, the customer service system 130 may, among other things, utilize, generate, store, process, request, transmit, modify, and otherwise use and track datasets, performance status, diagnostic indicators, etc., received from computing devices 100 and 110. The customer service system 130 may include one or more servers 132, one or more databases 134, and one or more customer service computing devices 136. The elements of the customer service system 130 may be connected to one another directly or indirectly (e.g., via the network 120). The customer service system 130 is further described herein.

[0091] Server 132 may include circuits configured to perform some or all of the server-based processes described herein, one or more network processors, and may be any suitable network server and / or other type of processing device. In some embodiments, the customer service system 130 may function as a unified “cloud” with respect to computing device 100 and / or computing device 110. Server 132 may include several servers performing interconnection and / or distributed functions. To avoid unnecessarily complicating this disclosure, Server 132 is shown and described herein as a single server, but those skilled in the art will understand in light of this disclosure that any number of servers and / or similar computing devices may be used. In some embodiments, referring to Figure 2, Server 132 may include processing circuits 210, a user interface 216, and / or communication interfaces 218 for facilitating various functions described herein, the functions of which may be embodied as hardware, software, or a combination of hardware and software. As described herein, the processing circuit 210 may include one or more processors 212, which may include local, networked, or remote processors, or any other processing means known in the art.

[0092] Database 134 may be any suitable local or network storage device configured to store some or all of the information described herein. Database 134 may be configured to store, for example, datasets, performance status, diagnostic messages, and customer representative feedback. Thus, database 134 may include, for example, one or more database systems, backend data servers, network databases, cloud storage devices, etc. To avoid unnecessarily complicating this disclosure, database 134 is shown and described herein as a single database device, but those skilled in the art will understand in light of this disclosure that any number of databases may be used. In some embodiments, with reference to Figure 2, database 134 may include a processing circuit 210, a user interface 216, and / or a communication interface 218 for facilitating various functions described herein, the functions of which may be embodied as hardware, software, or a combination of hardware and software. As described herein, the processing circuit 210 may include one or more processors 212, which may include local, networked, or remote processors, or any other processing means known in the art.

[0093] The customer service computing device 136 may have the same components as the computing device 100 further described herein (for example with respect to Figure 2), such as a user interface 216 that can display a graphical user interface via a screen, such as a guided customer service interface according to various embodiments described herein. The customer service computing device 136 may further include a processing circuit 210 and / or a communication interface 218 for facilitating various functions described herein, which may be embodied as hardware, software, or a combination of hardware and software. As described herein, the processing circuit 210 may include one or more processors 212, which may include local, networked, or remote processors, or any other processing means known in the art. Alternatively, the customer service computing device 136 may have different components as the computing device 100. The customer service computing device 136 may be located separately from other components of the customer service system 130. The customer service computing device 136 may include, for example, one or more customer service computing devices. To avoid unnecessarily complicating this disclosure, the customer service computing device 136 is shown and described herein as a single customer service computing device; however, those skilled in the art will understand in light of this disclosure that any number of customer service computing devices may be used. In various embodiments, the customer service computing device 136 may define a client terminal accessed by a customer service representative as part of a customer service system.

[0094] A customer requesting service from the customer service system (for example, by submitting a request to initiate a customer support session) may each have one or more computing devices. These computing devices may define device classifications. Some customers may have computing devices with the same or similar classifications (e.g., one or more common classification fields such as manufacturer and type), while others may have computing devices with different classifications. For example, there are many differences in the classification of computing devices, such as type, manufacturer, maker, model, and model year. Furthermore, even if the type, manufacturer, maker, model, and model year of computing devices are the same, there may be differences in the components used during manufacturing. These classifications may be stored in a customer service system, such as database 134, and / or transmitted by each computing device to facilitate the diagnosis and resolution of one or more problems associated with the computing device, as described herein.

[0095] Figure 2 shows exemplary computing devices according to some embodiments discussed herein. Figure 2 shows, for example, each of computing device 100 and / or a plurality of computing devices 110. In some embodiments, any of the devices in the customer service system 130 may also include some or all of the components of the exemplary computing device 100 shown in Figure 2. The components, devices, or elements shown and described below with respect to Figure 2 are not essential, and therefore some may be omitted in certain embodiments. In addition, some embodiments may include further or different components, devices, or elements beyond those shown and described with respect to Figure 2.

[0096] Referring here to Figure 2, exemplary computing devices 100, 110, 132, 134, and 136 include, or can otherwise communicate with, a processing circuit 210 that can be configured to perform actions according to one or more exemplary embodiments disclosed herein. In this regard, the processing circuit 210 may be configured to perform and / or control the performance of one or more functionalities of computing device 100 according to various exemplary embodiments, and thus may provide means for performing the functionalities of computing device 100 according to various exemplary embodiments. The processing circuit 210 may be configured to perform data processing, application execution, and / or other processing and management services according to one or more exemplary embodiments. In some embodiments, computing device 100, or some of its components, such as the processing circuit 210, may be embodied or include a chip or chipset. In other words, computing device 100 or processing circuit 210 may include one or more physical packages (e.g., chips) including materials, components, and / or wires on a structural assembly (e.g., a baseboard). A structural assembly can provide physical strength, size preservation, and / or limitations on electrical interaction with respect to the component circuits it contains. Thus, the computing device 100 or processing circuit 210 may, in some cases, be configured to implement the embodiment on a single chip or as a single “system on a chip.” Therefore, in some cases, a chip or chipset may constitute means for performing one or more operations to provide the functions described herein.

[0097] In some exemplary embodiments, the processing circuit 210 may include a processor 212, and in some embodiments, such as those shown in Figure 2, it may further include a memory 214. The processing circuit 210 can communicate with a user interface 216 and / or a communication interface 218, or be otherwise controlled. Thus, the processing circuit 210 can be embodied as a circuit chip (e.g., an integrated circuit chip) configured (e.g., in hardware, software, or a combination of hardware and software) to perform the operations described herein.

[0098] The processor 212 can be embodied in several different ways. For example, the processor 212 can be embodied as a microprocessor or other processing element, coprocessor, controller, or one or more of various other computing or processing devices, including, for example, an integrated circuit such as an ASIC (Application-Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array), or a combination thereof. Although shown as a single processor, it will be understood that the processor 212 may comprise multiple processors. Multiple processors may communicate with one another in an operable manner and may be collectively configured to perform one or more functions of computing device 100 as described herein. In some exemplary embodiments, the processor 212 may be configured to execute instructions stored in memory 214 or to execute instructions that are otherwise accessible to the processor 212. Thus, whether comprised of hardware or a combination of hardware and software, the processor 212 may represent an entity (e.g., physically embodied in a circuit in the form of a processing circuit 210) that is appropriately configured and capable of performing operations in accordance with embodiments of the present invention. Therefore, for example, when the processor 212 is embodied as an ASIC, FPGA, or a combination thereof, the processor 212 may be specifically configured to perform the operations described herein. Alternatively, as another example, when the processor 212 is embodied as an executor of software instructions, the instructions may specifically configure the processor 212 to perform one or more operations described herein.

[0099] In some exemplary embodiments, memory 214 may include one or more non-temporary memory devices, such as volatile and / or non-volatile memory, which may be fixed but removable. In this regard, memory 214 may include non-temporary computer-readable storage media. Although memory 214 is shown as a single memory, it will be understood that memory 214 may include multiple memories. Memory 214 may be configured to store information, data, applications, instructions, etc., to enable the computing device 100 to perform various functions, according to one or more exemplary embodiments. For example, memory 214 may be configured to buffer input data for processing by processor 212. Additionally or alternatively, memory 214 may be configured to store instructions for execution by processor 212. As yet another alternative, memory 214 may include one or more databases that can store various files, content, or datasets. Of the contents of memory 214, applications may be stored for execution by processor 212 to perform the functionality associated with each application. In some cases, the memory 214 may communicate with one or more of the processor 212, the user interface 216, and / or the communication interface 218 via a bus for passing information between components of the computing device 104.

[0100] The user interface 216 communicates with the processing circuit 210 to receive user input instructions and / or provide the user with audible, visual, mechanical, or other outputs. Thus, the user interface 216 may include, for example, a keyboard, mouse, screen, joystick, display, touchscreen display, microphone, speaker, and / or other input / output mechanisms. Thus, in some exemplary embodiments, the user interface 216 may provide the user with access to and interaction with customer service systems and / or customer service personnel according to various exemplary embodiments.

[0101] The communication interface 218 may include one or more interface mechanisms to enable communication with other devices and / or networks. In some cases, the communication interface 218 may be any means, such as a device or circuit embodied in either hardware or a combination of hardware and software, configured to receive and / or transmit data from / to a network and / or any other device or module communicating with the processing circuit 210. For example, the communication interface 218 may be configured to enable the computing device 100 to communicate with a customer service system and / or customer service personnel via the network 120. Thus, the communication interface 218 may include, for example, an antenna (or multiple antennas) and supporting hardware and / or software to enable communication with wireless communication networks (e.g., wireless local area networks, cellular networks, and / or similar), and / or a communication modem or other hardware / software to support communication via cable, digital subscriber line (DSL), universal serial bus (USB), Ethernet®, WiFi®, Bluetooth, or other methods.

[0102] <Datasets, Modeling, and Machine Learning> The customer service system 130 receives and stores multiple types of data, including datasets, and uses the data in multiple ways. The customer service system 130 may receive datasets from computing devices. The datasets may be stored in the customer service system 130 and used to diagnose problems or issues with the customer's computing devices. Additionally or alternatively, the datasets may be used in modeling, machine learning, and AI.

[0103] Computing device 100 may provide a dataset of its data to customer service system 130 via network 120. Similarly, each of the computing devices 110 may also provide a dataset to customer service system 130 via network 300. The datasets from computing devices 110 may be stored separately in database 420, and each dataset from computing devices 110 may be used individually in diagnosing a problem or issue. Additionally or alternatively, the datasets from computing devices 110 may be aggregated into an aggregated dataset. Alternatively, the aggregated dataset may be provided to customer service system. Furthermore, the dataset from computing device 100 may or may not be included in the aggregated dataset. In one example, the aggregated dataset may be anonymized so that it is not possible to determine which computing device provided the dataset to the aggregated dataset. Furthermore, the aggregated dataset may include data values ​​from multiple behavioral categories and data values ​​from behavioral subcategories. In embodiments where one or more other computing devices 110 are being diagnosed and / or customer service is being requested, data transmitted from computing device 100 may form part of an aggregated dataset used to diagnose and repair any problems of one or more other computing devices 110.

[0104] In some embodiments, the datasets provided to the customer service system may be datasets from third parties, or datasets generated from third-party applications or websites, in addition to, or instead of, datasets provided to the customer service system by end-user computing devices. A third party may provide an entire dataset, such as data on a specific manufacturer and / or model of a computing device, and / or may provide one or more subsets of data containing data for individual devices. Third-party applications or websites may also contain data on a specific manufacturer and / or model of a computing device, and data may be collected from such third-party applications or websites, such as by querying or crawling such applications or websites. In one embodiment, social media (e.g., Facebook) may contain discussions on a specific manufacturer and / or model of a computing device, and those discussions may be crawled for specific data. In some embodiments, such data from third parties or third-party applications and websites may be used to recognize or generate trends. Trends may include trends in computing devices, such as devices on which customers may use the customer service system to request customer service. Third-party data may be indexed by any characteristics of the data, including manufacturer, model, etc. Trends may be recognized or generated by modeling or machine learning. Alternatively, trends may be provided by third parties within the collected third-party data.

[0105] The customer service engine 138 may be used in a customer service system to perform various calculations relating to the calculation of performance status, such as diagnosing one or more problems with a computing device, determining diagnostic indicators, generating performance prompts using diagnostic indicators (e.g., diagnostic messages), and otherwise facilitating the diagnosis and resolution of one or more problems associated with a computing device, such as the guided customer service systems and methods described herein. In an exemplary embodiment, the customer service engine 138 may be embodied, for example, in a server 132, operate based on data obtained from a database 134 and / or computing devices 100, 110, and receive and / or transmit information to a customer service computing device 136. The customer service engine 138 may be embodied as hardware, software, or a combination of hardware and software configured to perform one or more of the functions described herein.

[0106] Next, AI and machine learning systems and methods according to embodiments described herein will be described. AI and machine learning may be part of a customer service system and may be performed by a customer service system engine 138 capable of computing information based on various modeling techniques.

[0107] Machine learning can be used to develop specific pattern recognition algorithms (i.e., algorithms representing specific pattern recognition problems) that can be obtained based on statistical inference. In some embodiments, the customer service system 130 must receive large amounts of data (e.g., datasets) from various sources (e.g., computing device 100 and computing device 110) and make decisions on a diagnosis of a situation. In some embodiments, a “trained model” may be trained based on the algorithms and processes described herein, and the trained models described herein may be generated using processes and methods described herein and known in the art.

[0108] For example, a set of clusters may be developed using unsupervised learning, where the number of clusters and their respective sizes are based on calculating the similarity of pattern features within a previously collected training set of patterns. In another example, a classifier representing a particular classification problem or issue may be developed using supervised learning, based on a training set of patterns and the known classifications of each of them. Each training pattern is input to the classifier, and the difference between the output classification produced by the classifier and the known classifications is used to adjust the classifier coefficients to more accurately represent the problem. A classifier developed using supervised learning is also known as a trainable classifier.

[0109] In some embodiments, the dataset analysis includes a source-specific classifier that takes a source-specific representation of a dataset received from a particular source as input and generates an output that classifies the input as likely to contain relevant data references or unlikely to contain relevant data references (e.g., likely to meet or unlikely to meet a required criterion). In some embodiments, the source-specific classifier is a trainable classifier that can be optimized as more instances of the dataset for analysis are received from the particular source.

[0110] Alternatively or additionally, a trained model may be trained to extract one or more features from historical data using unsupervised learning, supervised learning, semi-supervised learning, reinforcement learning, association rule learning, Bayesian learning, and pattern recognition based on solutions for probabilistic graphical models, among other computational intelligence algorithms that can use an interactive process to extract patterns from data. In some examples, historical data may include data generated using user input, cloud-based input, etc. (e.g., user confirmation).

[0111] In some embodiments, training datasets may be selected based on computing devices that share a similar classification to the computing device being diagnosed and repaired (e.g., a training set containing only mobile devices with a specific operating system, a training set containing only mobile devices with specific hardware, or only mobile devices of a specific manufacturer or model). Using the techniques described herein, a model may be trained to generate one or more diagnostic messages and / or performance prompts associated with a mobile device, including determining one or more performance states associated with the computing device and generating resolved values ​​associated with one or more prompts, and to determine any other diagnostics, customer service, or related calculations associated with the methods and embodiments described herein. The training data may also be selected from a predetermined period, such as several days, weeks, or months prior to the present invention.

[0112] In an exemplary embodiment, a labeled dataset may be supplied to the customer service system engine 138 for training a model. The labeled dataset may include behavioral data associated with multiple computing devices and labels, such as diagnostics, diagnostic messages, and prompts, associated with the computing devices. The model may then be trained to identify and classify behavioral datasets received from computing devices as corresponding to one or more of the labeled criteria.

[0113] In some embodiments, the analysis is terminated if the system determines that the incoming dataset does not contain at least one relevant data reference. In some embodiments, the system determines whether the referenced related data is already known to the system. In some embodiments, this determination is based on whether the data representing the referenced related data is a data repository (e.g., database 134). In embodiments, if the system determines that the referenced related data is already known to the system, the analysis is terminated.

[0114] In some embodiments, a customer service system can use an LSTM network to make predictions based on a series of diagnostic events. In some embodiments, the AI ​​and models described herein utilize a “deep learning” module. Deep learning is a subset of machine learning that generates models based on training datasets provided to machine learning. Deep learning networks can be used to draw in large inputs and allow algorithms to learn which inputs are relevant to identifying whether a device has a problem or not. In some embodiments, the trained model may use clustering, anomaly detection, Hebring learning, and learning latent variable models such as expectation maximization algorithms, methods of moments (mean, covariance), as well as unsupervised learning techniques such as blind signal separation techniques including principal component analysis, independent component analysis, non-negative matrix factorization, and singular value decomposition.

[0115] In some embodiments, non-machine learning modeling techniques may be used. For example, aggregated datasets may be compiled and used to statistically compare the performance of datasets associated with a particular computing device. In some embodiments, aggregated datasets may be filtered into representative datasets (e.g., based on classifications as described above with respect to model training). One or more performance states associated with a computing device may then be determined based on a comparison between the computing device's dataset and aggregated datasets associated with several other computing devices. In one example, data values ​​associated with a computing device's dataset may be directly compared and statistically associated with datasets of several other computing devices to determine whether the computing device's performance is within an expected performance range. For example, in various embodiments, it may be determined whether a computing device falls within a predetermined standard for each of several behavioral categories with respect to an aggregated dataset (e.g., standard deviation, percentile ranking). In various embodiments, it may be determined whether a computing device falls within a predetermined standard for each of several specific data values ​​(e.g., battery life, processor speed, connection strength, and / or any other signals that can be detected and output from the computing device, such as operating system API outputs) with respect to an aggregated dataset. In some embodiments, behavioral categories may be defined by one or more specific data values. In some embodiments, a performance state may be associated with one or more specific performance parameters. In some embodiments, a performance state may be defined by multiple performance parameters (for example, a performance state that identifies a battery discharge problem may be displayed if (1) the screen is off, (2) the device is not connected, and (3) the discharge rate is greater than a predetermined threshold).In some embodiments, for example, a predetermined period may be used when performing a modeling technique such that a problem is not identified unless a performance condition indicating a problem persists for the entire predetermined period or a selected portion thereof.

[0116] In some embodiments, comparative aggregated data may be used and displayed to the user, showing a comparison between a computing device associated with a customer and several other computing devices in order to identify and intuitively communicate the similarities and differences between the computing device being analyzed and the aggregated dataset.

[0117] <Diagnosis> The customer service system 130 may diagnose problems or issues with the customer's computing device 100. The diagnosis may be based on datasets provided by the customer's computing device 100, datasets provided by the computing device 110, aggregated datasets and their analysis, any other data sources described herein (e.g., third-party data including trend data), and / or modeling described herein.

[0118] In one example, the battery temperature of a customer's computing device 100 can be compared to a threshold or range to diagnose whether there is a problem or issue. The battery temperature data may be in a dataset from the customer's computing device 100, which may include current battery temperature data values ​​and / or historical battery temperature data values. The customer service system 130 may compare the current and / or historical battery temperatures to one or more thresholds. In one example, a single threshold may be used to determine whether the battery is hot or has exceeded a high temperature. In a further example, two thresholds may be used as a range (e.g., a high temperature range and a low temperature range) to determine whether the battery has fallen outside the temperature range. The thresholds or ranges may be recommended by the manufacturer of the customer's computing device 100, set by the customer, or determined by the customer service system 130 (e.g., using modeling). In other examples, the thresholds may be the mean, moving average, or weighted average, or the median. If, in one example, the battery temperature does not exceed high temperature, or in another example, does not exceed the temperature range, the customer service system may diagnose that the customer's computing device is free from problems or issues (e.g., "normal" state). The diagnosis may determine a performance state (e.g., normal, good, healthy, etc.) indicating that there are no problems or issues. If, in one example, the battery temperature exceeds high temperature, or in another example, falls outside the temperature range, the customer service system may diagnose that the customer's computing device has problems or issues. The diagnosis may determine a performance state (e.g., problem, faulty, high, low, abnormal, unhealthy, etc.) indicating that there are problems or issues. The above examples relate to behavioral subcategories of data regarding battery temperature, but it will be understood that the use of thresholds and / or ranges to diagnose whether there are problems or issues may be used in conjunction with other behavioral categories and / or behavioral subcategories of data. In some embodiments, the range may be determined by the manufacturer as part of the battery design.In some embodiments, the range may be determined based on observations of actual deactivations having the same model. In some embodiments, the range or threshold may be pre-set, for example, determining that a problem exists when the data value is in the 10% outside the mean of the aggregated data distribution. Other thresholds and ranges relative to the mean may also be used. In various embodiments, for a biased scale (good = 1, bad = 0), the customer service system may consider a threshold based on the number of peers below the 10th percentile.

[0119] In another example, the average battery life of a customer's computing device 100 may be compared to the average battery life of other computing devices, such as other computing devices of the same manufacturer and model from the same manufacturer. The dataset from customer's computing device 100 may include data values ​​for the average battery life of an operating subcategory. The dataset from customer's computing device 100 may determine the average battery life based on a period, such as the past 7 days. Alternatively, the average battery life can be calculated from other periods, such as 14 days, 30 days, 3 months, or 1 year. Similarly, an aggregated dataset of computing devices from the same manufacturer, maker, and model may include data values ​​for average battery life. The customer service system 130 may compare the average battery life of the customer's computing device to the average battery life of the aggregated dataset. If the average battery life of customer's computing device 100 exceeds the average battery life of the aggregated dataset, the customer service system may determine a performance status (e.g., normal, good, healthy, etc.) indicating that there are no problems or issues. If the average battery life of 100 customer computing devices falls below the average battery life of an aggregated dataset, the customer service system may determine a performance status (e.g., Problem, Problem, Low, Abnormal, Unhealthy, etc.) indicating that there is or may be a problem or issue. While the above example concerns the behavioral subcategory of data related to average battery life, it should be understood that the use of thresholds and / or ranges to diagnose whether there is a problem or issue may be used in conjunction with other behavioral categories and / or behavioral subcategories of data.

[0120] In another example, a threshold or range may be determined by statistical modeling or by using machine learning. Statistical modeling or machine learning may be used with data from customer computing devices 100 and / or aggregated datasets. For example, statistical modeling or machine learning may be for data values ​​of data from one behavioral category or one behavioral subcategory of data. Alternatively, statistical modeling or machine learning may be for data values ​​of data from multiple behavioral categories and / or multiple behavioral subcategories of data.

[0121] Determining a performance state for diagnostic purposes may involve determining a diagnostic indicator that can be visually represented on a screen (e.g., the screen of the customer service computing device 136) to indicate the performance state. The diagnostic indicator may differ depending on the performance state, and / or each performance state may have a separate diagnostic indicator. Alternatively, the diagnostic indicator may be the same or similar for all performance states. For example, if a performance state is associated with a customer computing device that has no problems or issues with a data behavior category or subset of data behavior, the associated diagnostic indicator might be a green icon indicating that the computing device is, for example, healthy or good with respect to that data behavior category or subset. In some embodiments, the diagnostic indicator may define a level of specificity configured to represent the performance state within the scope of the icon or screen and within the scope associated with such icon or screen, such that the amount of information conveyed by the diagnostic indicator may be limited to the amount of available space. For example, the diagnostic indicator may be displayed in association with one or more of several behavior categories displayed on a graphical user interface. Based on the available screen and icon space, diagnostic indicators may be of limited specificity (e.g., an exclamation mark or other indicators showing problems in a behavior category) or of a higher degree of specificity (e.g., a brief description of the problem, or more specific icons showing the type of problem, the subcategory that triggered the problem, etc.).

[0122] Diagnostic indicators may be determined using various embodiments described herein and may be visually represented in a graphical user interface, for example, by visually displaying icons or colors. For example, a normal performance state of battery temperature may have a diagnostic indicator associated with a detected problem or device condition. A diagnostic indicator may be visualized by green text, a green-colored icon, or a background shading of an area associated with a particular color of battery temperature. As a further example, a performance state below average for average battery life may be a diagnostic indicator and may be visually represented by yellow text and a yellow icon to indicate that a problem has been determined to be present. Additional examples of visual representations associated with diagnostic indicators may be icons or text displayed on a graphical user interface that are highlighted, shaded, blink, pulse, or resize.

[0123] <Guided Interface> A customer service representative may interface with the customer service system 130 via a customer service computing device 136. The customer service computing device 136 may include a user interface that includes a display (also referred to as a screen) capable of displaying a graphical user interface (hereinafter referred to as a "GUI") for the customer service representative. According to various embodiments of this disclosure, the GUI may display a representation of information that can guide the customer service representative through interaction with the customer and help them resolve or address any problems or issues the customer may have.

[0124] In one example, the GUI may be directed to an overview that a customer service representative can initiate. The overview may display a visual representation of data associated with multiple behavioral categories and / or multiple behavioral subcategories of data for a customer's computing device 100. The GUI directed to the overview may also, among other things, display a visual representation of diagnostic indicators, and the visual representation of a diagnostic indicator associated with a performance condition determined to have a problem or issue may be visually distinct from other diagnostic indicators. Interface elements described herein related to performance conditions, including conveying information associated with the computing device, may be considered diagnostic indicators. Furthermore, the visual representation of multiple behavioral categories of data may be dynamic in that the visual representation of multiple behavioral categories of data may be extended to provide a visual representation of multiple behavioral subcategories of data associated with the behavioral category. The exemplary interfaces described herein may work in conjunction with each other (for example, selecting one or more icons on the GUI may cause the system to present a second GUI, including another of the GUIs described herein). Apparatus and systems according to embodiments described herein may use multiple versions of the same GUI (for example, two different interfaces displaying different information having the same layout as any one of the GUIs shown herein). In other embodiments, the exemplary interfaces disclosed herein can operate any one or more GUIs in isolation.

[0125] Figure 3A shows an exemplary graphical user interface according to some embodiments discussed herein. Referring to Figure 3A, the graphical user interface 301 (hereinafter referred to as GUI 301) may be a graphical user interface that displays information associated with the customer and the customer's computing device 100 and is displayed to the customer service representative when the customer contacts the customer service representative to request assistance. Interface 301 may include an account area 302 which may display information associated with the customer's account, such as the customer's name, the customer's telephone number, the manufacturer of the customer's computing device 100, the model of the customer's computing device 100, etc. GUI 301 may further include an operation category icon area 303 having one or more operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, 310N (collectively referred to herein as “operation category icons 310”). Each of the one or more operation category icons 310 may be associated with data from a different operation category (e.g., overview, battery, signal, storage, audio, settings, commands, status updates, applications, remote support, registration, etc.). Each operation category icon 310 may be dynamic, such as changing emphasis (e.g., shading, brightness, etc.) depending on the selection by a customer service representative or the information displayed in the GUI 301. The interface 301 may further include a computing device information area 304 having one or more operation category information areas 320A, 320B, 320C, ..., 320N (collectively referred to herein as “operation category information areas 320”). Each operation category information area 320 may include a visual representation of the associated operation category and / or one or more diagnostic indicators of the associated operation categories. For example, the diagnostic indicator of an associated category may be the same as the diagnostic indicator of an operation subcategory associated with the operation category (e.g., “exclamation mark”, “checkmark”, etc.).The operation category information area 320 may further include operation subcategory information areas 330A, 330B, 330C, ...330N (collectively referred to herein as the "operation subcategory information area 330"). Each operation subcategory information area 330 may include a visual representation of one or more diagnostic indicators, including a diagnostic indicator for the associated operation subcategory 340 and / or an operation subcategory diagnostic message 350. The operation subcategory diagnostic message 350 may include the name of the operation subcategory, a description of the operation subcategory, data values ​​associated with the operation subcategory, and / or the performance status of the operation subcategory. As described herein, the GUI may display visual representations associated with an operation category, which may include operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, operation category information areas 320A, 320B, 320C, ..., 320N, operation subcategory information areas 330A, 330B, 330C, ..., 330N, and / or any other visual representations associated with one or more operation categories.

[0126] Figure 3B shows an exemplary embodiment of the graphical user interface of Figure 3A, where the “Overview” operating category is selected according to several embodiments discussed herein. Referring to Figure 3B, GUI 301 displays information about the “Overview” operating category, which is indicated as selected by a highlighted operating category icon 310A in the operating category icon area 303. The depicted overview operating category shows information corresponding to each of several other operating categories. In Figure 3B, the computing device account area 302 displays the manufacturer and model of the computing device 301 (e.g., “Samsung Galaxy S9”). The operation category icon area 303 displays 11 operation category icons 310 associated with 11 different operation categories of data (for example, “Overview” in 310A, “Battery” in 310B, “Signal” in 310C, “Storage” in 310D, “Audio” in 310E, “Settings” in 310F, “Commands” in 310G, “Status Update” in 310H, “Applications” in 310I, “Remote Support” in 310J, and “Registration” in 310K). Setting 310F may define one or more preference or app / service-related settings for the user to control, such as music volume, call volume, or WiFi on / off. In some embodiments, Command 310G is a command to change these settings, or a command to open a settings screen when these settings cannot be changed directly. In some embodiments, there is a command to start Remote Support 310J via screen sharing or camera sharing. The computing device information area 304 displays the operation category information area 320 associated with data from five different operation categories (for example, "Battery" for 320A, "Power Adapter" for 320B, "Data Usage" for 320C, "Signal" for 320D, and "Storage" for 320E).The “Battery” operational category information area 320A is displayed in a manner that expands to show operational subcategory information areas 330 (e.g., “Current Level” in 330A, “Battery Hog” in 330B, “Battery Temperature” in 330C, “Average Battery Life” in 330D, “Firmware Health” in 330E, and “Temperature” in 330F). In the example in Figure 3B, the “Battery Hog” operational subcategory refers to an application that uses a larger amount of battery compared to other applications, which will be further described herein. In Figure 3B, each operational subcategory information area 330 includes a visual representation of a diagnostic indicator 340 and an operational subcategory diagnostic message 350. For example, the visual representation of the diagnostic indicator 340 for operational subcategory information area 330A is a green circle with a white checkmark. In addition, the operation subcategory diagnostic message 350 in the operation subcategory information area 330A includes the name of the operation subcategory (e.g., "Current Level," which is the current charge level of the battery operation category), a description of the operation subcategory (e.g., "Current Battery Charge"), a data value associated with the operation subcategory (e.g., "40%"), and / or the performance status of the operation subcategory (e.g., "40% Discharge"). Figure 3B further illustrates the "Average Battery Life" operation subcategory with diagnostic indicators 340, 350 (e.g., yellow triangles with an exclamation mark inside) indicating a problem or issue.

[0127] In the embodiments described, each operational category information area 320 is expandable to display diagnostic indicators associated with one or more subcategories within it. Selecting the “expand” icon (e.g., the arrow shown to the right of each area 320) may display additional subcategory information, and, based on the available space, may display more detailed diagnostic indicators, such as diagnostic messages 350. When collapsed, five operational categories are depicted, each displaying a low-level diagnostic indicator 340 to the right of the information area 320. In some embodiments, the diagnostic indicators may include performance prompts, as described herein. Thus, the embodiments described can intuitively guide customer service representatives to diagnose customer problems. When operating in connection with customer support sessions, the stratified operational categories can rapidly facilitate the diagnosis and triage of problems related to the described intuitive system and interface.

[0128] In some embodiments, the customer service system 130 may provide the customer service representative with additional information about behavioral categories, which may be triggered in instances where further details are needed to diagnose and / or repair the computing device. The customer service representative may, for example, select one of the behavioral category icons 310, and in response, the GUI 301 may be updated to display a second embodiment of the guided customer service interface. The customer service representative may select one of the behavioral category icons 310, for example, if the performance status and / or diagnostic indicators visually indicate that there may be a problem with the customer's computing device. The selection of one of the behavioral category icons 310 may cause a second GUI to be displayed that contains information associated with the selected behavioral category. In some embodiments, the second GUI may retain one or more features of the first GUI in which the behavioral category was selected. In one example, the GUI 301 may guide the customer service representative through the GUI 301 to determine what the problem or issue may be. Further examples of how customer service representatives may guide customers are disclosed herein, for example, how a customer's computing device 100 may be compared to other computing devices 110 of the same manufacturer and model.

[0129] Continuing to refer to Figure 3B, in some embodiments, submenus or additional diagnostic indicator options may be available. For example, GUI 301 shown in Figure 3B includes a “Device Status” interface, which includes the aforementioned operational category information areas 320, 330, and GUI 301 includes an “Activity” interface, which can display one or more additional visual representations of performance status, diagnostic indicators, and any data associated therewith. For example, the activity interface may describe a time-series list of activities performed by the customer computing device.

[0130] Figure 4A shows an exemplary graphical user interface according to several embodiments discussed herein. Referring to Figure 4A, the GUI 301 may display an account area 302, an operation category icon area 303 containing operation category icons 310 which may operate as described above with respect to embodiments of Figures 3A-3B, an operation category information area 401, an operation subcategory data visualization area 402, and an operation subcategory data comparison visualization area 403. The operation category information area 401 may have one or more operation subcategory information areas 410A, 410B, 410C, ..., 410N (collectively referred to herein as "operation subcategory information area 410"). Each of the one or more operation subcategory areas 410 may be associated with a different operation subcategory of the data described above. Each operation subcategory information area 410 may include operation subcategory diagnostic indicators such as diagnostic messages. The behavioral subcategory diagnostic message may include the name of the behavioral subcategory, a description of the behavioral subcategory, data values ​​associated with the behavioral subcategory, the performance status of the behavioral subcategory, and / or any other visual representation of a diagnostic indicator. The behavioral subcategory data visualization area 402 may include visualizations such as graphs or charts that provide a visualization of the data of the relevant behavioral subcategory. The behavioral subcategory data comparison visualization area 403 may include comparison visualizations such as graphs or charts that provide a comparison visualization that compares the data of the relevant behavioral subcategory from the customer's computing device 100 with the data of the relevant behavioral subcategory from, for example, an aggregated dataset. As described herein, the GUI may display visual representations associated with an operation category, which may include subcategories and any other visual representations associated with one or more operation categories, including operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, operation category information area 401, one or more operation subcategory information areas 410A, 410B, 410C, ..., 410N, and / or one or more subcategories.

[0131] Figure 4B shows an example of one embodiment of the graphical user interface of Figure 4A, where the “Battery” operating category is selected according to several embodiments discussed herein. Referring to Figure 4B, GUI 301 displays information about the “Battery” operating category, which is indicated as selected by a highlighted operating category icon 310B in the operating category icon area 303. In Figure 4B, the operating category information area 401 displays nine operating subcategory information areas 410 (for example, “Firmware Health” 410A, “Battery Status” 410B, “Battery Charge Type” 410C, “Battery Charge Technique” 410D, “Average Charge” 410E, “Hibernate Discharge” 410F, “Startup Discharge” 410G, “Level Degradation” 410H, and “Voltage” 410I). In Figure 4B, each operation subcategory information area 410 includes an operation subcategory diagnostic indicator 440 in the form of a diagnostic message (e.g., "Good" for "Firmware Health" in 410A). In some embodiments, the diagnostic message may be a data value (e.g., "Disconnected") or a qualitative performance status (e.g., "Good"). The operation subcategory data visualization area 402 displays a visualization of the data value (e.g., 40%) of the operation subcategory "Battery Level" with a chart. The operation subcategory data comparison visualization area 403 displays a comparison of the average battery life of other computing devices 110 having the same manufacturing and model as computing device 100 (e.g., "Other Samsung Galaxy Visualization S9 Users") with the computer's relevant operation subcategory "Average Battery Life" from the customer's computing device 100.

[0132] Similar to Figures 3A-3B, in some embodiments, selecting one or more of the operational subcategory information areas 410 may cause additional information and / or additional diagnostic indicators to be displayed for the selected subcategory. For example, subsubcategories based on the selected subcategory may be displayed. In some embodiments, one or more performance prompts may be displayed in association with one or more subcategories.

[0133] Continuing to refer to Figure 4B, in various embodiments, the system may require a certain amount of data before it can generate a performance state. This data may be required to enable the modeling or other diagnostic systems described herein to obtain a suitable sample size to facilitate the determination of the performance state. For example, in the case of a model that statistically analyzes data over a predetermined period, the predetermined period must elapse before the system can determine whether a problem persists throughout the entire period. In such an example, the system may not need to indicate a problem until the predetermined period has elapsed, and may display a temporary diagnostic indicator 445, such as the text “Learning,” to indicate that the performance state cannot yet be determined. Similarly, in embodiments where sufficient training data has not yet been collected to generate a model for determining one or more performance states, a temporary diagnostic indicator 445 may be displayed.

[0134] Figure 4C shows another exemplary embodiment of the graphical user interface of Figure 4A, where the “Signal” operating category is selected according to several embodiments discussed herein. Referring to Figure 4C, GUI 301 displays information about the “Signal” operating category, which is indicated as selected by highlighted operating category icon 310C in the operating category icon area 303. In Figure 4C, the operating category information area 401 displays seven operating subcategory information areas 410 (e.g., “Received Signal Strength Indicator (RSSI)” 410A, “Reference Signal Received Power (RSRP)” 410B, “Reference Signal Received Quality” 410C, “Reference Signal-to-Noise Ratio (RSSNR)” 410D, “Cell Identification (CI)” 410E, “Physical Cell ID (PCI)” 410F, and “Tracking Area Code” 410G). In Figure 4C, each operation subcategory information area 410 includes an operation subcategory diagnostic message (e.g., "27 dBm" for the "Received Signal Strength Indicator (RSSI)" in 410A), which may include a quantitative data value and / or a diagnostic message indicating a qualitative performance status. The operation subcategory data visualization area 402 does not display a visualization of the data value if no signal is found or data is not received by the system. The operation subcategory data comparison visualization area 403 does not display a comparison of the computer's average signal quality for the relevant operation subcategory of "Average Signal Quality" for the "Past 30 Days Average" for the customer's computing device 100 with the average signal quality of other computing devices 110 (e.g., "Other Samsung Galaxy S9 Users") that have the same manufacturing and model as computing device 100. Instead, the operational subcategory data comparison visualization area 403 displays the average signal quality of other computing devices 110 that have the same manufacturing and model as computing device 100, while omitting information from the customer's computing device 100, which in this example may occur when no data has been received from the customer's computing device 100 for the last 30 days.

[0135] The customer service system 130 may provide customer service representatives with additional information on behavioral categories, which may include diagnostic messages to guide the customer service representatives. The customer service representative may, for example, select one of the behavioral category icons 310, and in response, the GUI 301 may update to display a further embodiment of the guided customer service interface. The updated GUI 301 may provide customer service representatives with diagnostic messages to guide them by displaying messages associated with how a behavioral subcategory may cause problems or issues for the customer, and suggestions on what to discuss with the customer, in cases where the dataset may be missing data for a behavioral category or behavioral subcategory.

[0136] Figure 5A shows an exemplary graphical user interface according to some embodiments discussed herein. Referring to Figure 5A, the GUI 301 may display an account area 302, an operation category icon area 303, and a performance prompt area 501. The performance prompt area 501 may have one or more performance prompts 510A, 510B, 510C, ..., 510N (collectively referred to herein as “performance prompts 510”). Each of the one or more performance prompts 510 may be associated with a different operation subcategory of data. Each performance prompt 510 may include a diagnostic message which may include the name of the operation subcategory, a description of the operation subcategory, a data value associated with the operation subcategory, the performance status of the operation subcategory, and / or a message associated with how the operation subcategory may cause a problem or issue for the customer, as well as suggestions on what to discuss with the customer. The performance prompt 510 may further include one or more feedback icons 512 (e.g., 512A, 512B, 512C, ..., 512N). As shown herein, the GUI may display visual representations associated with an operation category, which may include subcategories and include operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, performance prompt area 501, one or more performance prompts 510A, 510B, 510C, ..., 510N, and / or one or more subcategories, and any other visual representations associated with one or more of the operation categories.

[0137] As used herein, a performance prompt may be a visualization of a diagnostic message configured to resolve one or more issues associated with a performance condition. A performance prompt may be stored as a solution to an issue that is retrieved when the customer service system engine 138 diagnoses an issue or potential issue. In some embodiments, a performance prompt may be determined based on the modeling and data analysis described herein by calculating a solution to the diagnosed issue and generating a performance prompt corresponding to the solution. The customer service system engine 138 may further determine a solution value associated with each performance prompt, display the solution value based on the likelihood of success of the performance prompt, and / or rank the performance prompts. Such ranking may create a hierarchy of performance prompts, and in some embodiments, such a hierarchy may be used to determine which performance prompts may be displayed. In some embodiments, the hierarchy may be determined based on the modeling and data analysis described herein, which may include, among other things, modeling and analysis of collected data and / or trends in collected data. The hierarchy of performance prompts can be configured to provide customer service representatives with the most likely and relevant information in an intuitive display, which can be quickly considered and referenced by drawing the customer service representative's eye to the most relevant information first (for example, by displaying performance prompts from top to bottom).Additional signals considered during performance prompt generation may include customer computing device-specific data (e.g., customer and / or other customer and / or third-party trend data such as social media trend issues, which may include trends from the customer service system, such as the number of customers who have accessed the customer service system for the same issue) and general problem-solving data (e.g., which performance prompts have successfully resolved a particular mix of symptoms experienced by the customer computing device, regardless of the specific computing device, which may also include trend data). Computing device-specific data may include data related to the specific manufacturer and model of the device, as well as broader categories specific to the customer computing device, such as the operating system, service provider, manufacturer, processor type, or any other characteristics common to multiple devices.

[0138] The various modeling processes and algorithms discussed herein may inform the selection of one or more performance prompts (e.g., based on diagnostics that may include a percentage confidence in one or more possible solutions) and / or a hierarchy of performance prompts to optimize the effectiveness and efficiency of customer service support sessions. In some embodiments where customer device data is unavailable, the customer service system may generate default performance prompts based on other data sources (e.g., internal and third-party trend information).

[0139] Performance prompts may be triggered when selecting and / or visualizing an operation category or subcategory in which a performance state identifies a problem. In some embodiments, different performance prompts may be presented for different operation categories than those within an operation category, or performance prompts may be arranged in different orders to indicate the resolved value of each performance value for the operation category in which they are presented. For example, if a device restart frequently succeeds for a problem associated with "signals" rather than for one or more operation subcategories within a signaling operation category, a "device restart" performance prompt may be presented when visualizing performance prompts for a specific one or more operation subcategories rather than for the signaling operation category. Similarly, the customer service system engine 138 may determine performance prompts and / or resolved values ​​for the operation categories or subcategories in which performance prompts may be used, such that different outputs correspond to different categories. In some embodiments, the resolved values ​​may include correlations between performance prompts and performance states determined for a computing device and the problems identified therein. In some embodiments, the resolved values ​​may include the relevance of each performance prompt from a list of performance prompts to performance states determined for a computing device and the problems identified therein. The aggregated device data described herein may include solution implementation results corresponding to the frequency of success associated with one or more solutions for problems identified in one or more performance states. Solution implementation results may be used to calculate performance prompts and / or resolution values.

[0140] In various embodiments, multiple performance prompts may be displayed simultaneously to facilitate correlation between symptoms described by the customer, data from the phone, and the selection of the most relevant performance prompt, based on customer feedback.

[0141] In various embodiments, if data for an operation category is unavailable or limited, such that some or all performance states cannot be calculated, a default list of performance prompts for that operation category may be generated. In some embodiments, the default list may be determined based, for example, on the performance prompt with the highest probability of success, calculated based on the implementation results of solutions in an aggregated dataset. The customer service system engine 138 may then collect success-related feedback for one or more performance prompts in order to calculate further performance prompts, as described below.

[0142] In some embodiments, one or more performance prompts may include feedback icons that allow a customer service representative to input the customer computing device and the results of the solution implementation of one or more performance prompts. In some embodiments, the feedback icons may allow a customer service representative to input free text about a given performance prompt and / or problem. For example, they may enter a note when closing the performance prompt. The feedback icons may additionally or alternatively allow a customer service representative to send computer-readable instructions to the consumer computing device to trigger a solution to the problem. In some embodiments, if the selection of a feedback icon indicates that the problem has been fixed (e.g., a successful performance prompt in the result of the solution implementation), the interface and performance state may be updated to reflect the solution to the problem. In some embodiments, if the selection of a feedback icon indicates that the problem has not been fixed (e.g., an unsuccessful performance prompt in the result of the solution implementation), the system may remove the performance prompt and display one or more additional performance prompts. In some embodiments, if the selection of a feedback icon indicates that the problem has not been fixed (e.g., a failed performance prompt in the implementation result of the solution), the system may add the implementation result of the solution to the dataset associated with the customer computing device and recalculate previously determined performance prompts to determine whether the failed performance prompt affects the resolved values ​​of other performance prompts (e.g., if plugging in the device does not resolve the problem, the system may also determine that a battery failure is not possible).

[0143] In various embodiments, the feedback icon may allow a customer service representative to manually enter customer feedback to input customer voices or to input new data to determine further performance prompts. In some embodiments, the system may return all performance prompts (e.g., relevant solutions and troubleshooting articles) determined and / or ranked by relevance based on the diagnostic test history on the device, similar issues on other devices of the same model / manufacturer, and / or similar issues reported by the user on other platforms (e.g., Twitter, Facebook).

[0144] Figure 5B shows an example of the graphical user interface of Figure 5A, where the “Audio” operating category is selected according to several embodiments discussed herein. Referring to Figure 5B, GUI 301 displays information about the “Audio” operating category, which is indicated as selected by a highlighted operating category icon 310E in the operating category icon area 303. In Figure 5B, the performance prompt area 501 displays five performance prompts 510, including diagnostic messages (e.g., a message associated with “Ringtone Volume” (510A), a message associated with “Alarm Volume” (510B), a message associated with “Music Volume” (510C), a message associated with “Call Volume” (510D), and a message associated with “Bluetooth” (510E)). In Figure 5B, each performance prompt 510 includes a description of the behavioral subcategory (e.g., "Ringtone Volume" (510A)), a message associated with how the behavioral subcategory might cause the customer an issue or problem, and a suggestion of what to discuss with the customer (e.g., "If this setting is set to low or 0, this may explain why the phone doesn't ring during a call. Ask the user to set the ringtone volume to 100% and have someone call them to test to see if the problem is resolved."). In Figure 5B, the message associated with how the behavioral subcategory might cause the customer an issue or problem, and the suggestion of what to discuss with the customer in performance prompt 510A, guide the customer service representative to the potential issue or problem (e.g., ringtone volume set to low or 0), provide what the customer might ask for help with ("phone doesn't ring during a call"), and guide the customer service representative on how to help the customer (e.g., "Ask the user to set the ringtone volume to 100% and have someone call them to test to see if the problem is resolved.").In the embodiments described, the dataset from the customer computing device may be missing or insufficient in one or more ways so that a default set of performance prompts is displayed without further performance status information. The GUI may be updated as data is received from the computing device or via a customer service representative and added to the dataset to determine the performance status, and the system may update the performance prompts and other diagnostic indicators to reflect the evolving performance status.

[0145] The customer service system 130 can provide customer service representatives with additional information about the operational categories, which may include displaying the performance status of the operational subcategories of the data and the historical data values ​​of the operational subcategories. The customer service representative may, for example, select one of the operational category icons 310, and in response, the GUI 301 may be updated to display a further embodiment of the guided customer service interface. The updated GUI 301 may display the performance status of the operational subcategories of the data and the historical data values ​​of the operational subcategories.

[0146] Figure 6A shows an exemplary graphical user interface according to several embodiments discussed herein. Referring to Figure 6A, the GUI 301 may display an account area 302, an operation category icon area 303, an operation category information area 320, an operation subcategory information area 330, a performance prompt area 501, a computing device information area 601, an operation subcategory usage information area 602, and / or an operation subcategory history area 603. The display account area 302, operation category icon area 303, operation category information area 320, operation subcategory information area 330, and performance prompt area 501 are described above. The computing device information area 601 may include data associated with the customer's computing device, such as manufacturer, model, phone number, customer name, customer email, carrier, storage capacity, color, operating system, and / or a unique identifier (e.g., International Mobile Device Identifier (also known as IMEI)). The operation subcategory usage information area 602 may display one or more expressions of which parts of the software and / or hardware of the computing device are using and / or influencing operation categories 610A, 610B, 610C, ..., 610N (collectively referred to herein as “operation category users 610”). Additionally or alternatively, operation category users 610 may be operation subcategories. The operation subcategory history area 603 may display timestamps (e.g., date and time) and details associated with history data values ​​630A, 630B, 630C, ..., 630N (collectively referred to herein as “history data 630”).As described herein, the GUI may include subcategories and may include operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, operation category icon area 303, operation category information area 320, operation subcategory information area 330, performance prompt area 501, computing device information area 601, operation subcategory usage information area 602, operation subcategory history area 603, display account area 302, and / or any other visual representation associated with one or more operation categories, including one or more subcategories.

[0147] Figure 6B shows an exemplary embodiment of the graphical user interface of Figure 6A, where the “Battery” operating category is selected according to several embodiments discussed herein. Referring to Figure 6B, GUI 301 displays information about the “Battery” operating category, which is indicated as selected by a highlighted operating category icon 310B within the operating category icon area 303. The computing device information area 601 displays data associated with the customer's computing device (e.g., manufacturer Samsung, model Galaxy S9, customer phone number, customer name John Doe, customer email Example@gmail.com, carrier Xfinity Mobile, storage capacity 64GB, color Midnight Black, operating system Android 9.0, and IMEI). The operating subcategory usage information area 602 displays six operating category users 610 for the operating subcategory “Battery Hog”, which represents the mobile device application using the most battery and the percentage of usage (e.g., “Google Maps” at 51% in 620A). The operation subcategory history area 603 may display eight historical data entries 630 for the most recent seven days 630A-630H. Template text is used in exemplary embodiments, and those skilled in the art will understand, in light of this disclosure, that diagnostic indicators, such as diagnostic messages, may be used in accordance with any of the embodiments described herein.

[0148] The customer service system 130 may provide the customer service representative with additional information regarding the timeline and any alerts that occurred during that time. The customer service representative may, for example, select one of the action category icons 310, and in response, the GUI 301 may be updated to display a further embodiment of the guided customer service interface. The updated GUI 301 may display the timeline and any alerts that occurred during that time.

[0149] Figure 7A shows an exemplary graphical user interface according to some embodiments discussed herein. Referring to Figure 7A, the GUI 301 may display an account area 302, an action category icon area 303, an action subcategory data comparison visualization area 403, a timeline area 701, a diagnostic indicator summary area 702, a diagnostic indicator timeline area 703, an action subcategory data area 704, and an action subcategory data area 705. As described above, the display account area 302, the action category icon area 303, and the action subcategory data comparison visualization area 403 are described above. The timeline area 701 may display one or more representations of a period (e.g., one hour, one day, one week, one month, or one year) 710A, 710B, 710C, ..., 710N (collectively referred to herein as “timeline representation 710”). The timeline representation 701 may be an icon that a customer service representative can choose to update the GUI 301 to display information associated with a selected period (e.g., filtering data to a specific number of days). The diagnostic indicator summary area 702 may display a summary of diagnostic indicators associated with the behavior category of the data, which may be a selected period (e.g., one day) or all periods displayed in the timeline area 701. The diagnostic indicator timeline area 703 may display diagnostic indicators and diagnostic messages associated with the behavior subcategory of the data, which may be a selected period (e.g., one day) or all periods displayed in the timeline area 701. The behavior subcategory data area 704 may display behavior subcategory data for the computing device 100 used in the behavior subcategory data comparison visualization area 403. The behavior subcategory data area 705 may display the same data as the behavior subcategory data area 704, but may be for a different computing device 110 or data values ​​for an aggregated dataset.As described herein, the GUI may include sub - categories and may display operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, …, 310N, account region 302, operation category icon region 303, operation sub - category data comparison visualization region 403, timeline region 701, diagnostic indicator summary region 702, diagnostic indicator timeline region 703, operation sub - category data region 704, operation sub - category data region 705, and / or any other visual representation associated with one or more of the operation categories that include one or more sub - categories.

[0150] FIG. 7B shows an exemplary embodiment of the graphical user interface of FIG. 7A, and the operation category of “Battery” is selected according to some embodiments discussed herein. Referring to FIG. 7B, the GUI 301 may display an account region 302, an operation category icon region 303, an operation sub - category data comparison visualization region 403, a timeline region 701, a diagnostic indicator summary region 702, a diagnostic indicator timeline region 703, an operation sub - category data region 704, and an operation sub - category data region 705. The timeline region 701 may display representations for 7 days (e.g., 8 日 Friday (710A), 9 日 Saturday (710B), 10 日 Sunday (710C), 11 日 Monday (710D), 12 日 Tuesday (710E), 13 日 Wednesday (710F), and 14 日 Thursday (710F)). The displayed timeline representation 701 is an icon, and the icon for Thursday (710G) is emphasized to indicate selection. The summary region 702 of the diagnostic indicator displays the number of alerts associated with Thursday (710G). The diagnostic indicator timeline region 703 shows, for the operation sub - categories of battery health, performance, power consumption, low battery, and charging alerts, 14 日 The icon for Thursday (710G) is emphasized. The summary region 702 of the diagnostic indicator displays the number of alerts associated with Thursday (710G). The diagnostic indicator timeline region 703 shows, for the operation sub - categories of battery health, performance, power consumption, low battery, and charging alerts, 14 日 The icon for Thursday (710G) is emphasized. The summary region 702 of the diagnostic indicator displays the number of alerts associated with Thursday (710G). The diagnostic indicator timeline region 703 shows, for the operation sub - categories of battery health, performance, power consumption, low battery, and charging alerts, 14 日The timeline for Thursday (710G) is displayed. The operation subcategory data area 704 displays the operation subcategory of battery health associated with customer device 100, and the operation subcategory data area 705 displays the operation subcategory of battery health associated with another computing device 110.

[0151] The customer service system 130 may provide customer service representatives with additional information about the timeline for one or more operational subcategories of the data about the timeline. For example, a customer service representative may select one of the operational category icons 310, and in response, the GUI 301 may be updated to display further embodiments of the guided customer service interface. The updated GUI 301 may display timeline details for one or more operational subcategories of the data about the timeline.

[0152] Figure 8A shows an exemplary graphical user interface according to some embodiments discussed herein. Referring to Figure 8A, the GUI 301 may display an account area 302, an operation category icon area 303, a performance prompt area 501, a timeline area 701, and / or an operation category timeline area 802. The operation category timeline area 802 may display one or more operation subcategory timeline areas 820A, 820B, ..., 820N (collectively, “operation subcategory timeline area 820”). The operation subcategory timeline area 802 may display time and historical data values ​​830A, 830B, 830C, ..., 830N (collectively, “operation subcategory time and value 830”) for a selected timeline representation 710. As described herein, the GUI may include subcategories and display operation category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, account area 302, operation category icon area 303, performance prompt area 501, timeline area 701, operation category timeline area 802, and / or any other visual representation associated with one or more operation categories that include one or more subcategories.

[0153] Figure 8B shows an example of the graphical user interface of Figure 8A, where the “Audio” activity category is selected according to several embodiments discussed herein. Referring to Figure 8B, the GUI 301 may display an account area 302, an activity category icon area 303, a performance prompt area 501, a timeline area 701, and / or an activity category timeline area 802. In Figure 8B, the timeline area 701 displays 7 days (e.g., 22 日 Friday (710A), 23 日 Saturday (710B), 24 日 Sunday (710C), 25 日 Monday (710D), 26 日 Tuesday (710E), 27 日 Wednesday (710F), and 28 日Display the representation for Thursday (710F). The displayed timeline representation 701 is an icon, and 28 indicates that it is selected. 日 The Thursday (710G) icon is highlighted. The operation category timeline area 802 displays the "Audio" operation category and six operation subcategory timeline areas 820 (for example, Music Volume 820A, Call Volume 820B, Ringtone Volume 820C, Alarm Volume 820D, System Volume 820E, and Bluetooth 820E). Furthermore, in Figure 8B, each operation subcategory timeline area 820 displays the operation subcategory time and value 830. For example, the Music Volume operation subcategory timeline area 820A displays five operation subcategory times and values ​​830: namely, the current time and value is 62% (830A), the time and value at 6:10 AM is 31% (830B), the time and value at 5:52 AM is 0% (830C), the time and value at 3:22 AM is 37% (830D), and the time and value at 3:12 AM is 75% (830E). Furthermore, the operation subcategory time and value 830 are highlighted in the performance prompt area 501 for times and values ​​that may be associated with performance states and issues identified in performance prompts 510A and 510b. For example, both performance prompt 510A and the time and value 830A are associated with the operation subcategory of music volume in Figure 8B, and with each address when the music volume is set to 0.

[0154] According to the embodiments discussed herein, diagnostic indicators can guide customer service personnel to problems or issues with a customer's computing device. Figures 9–18 show illustrative flowcharts of some, but not all, embodiments of the systems and methods described herein.

[0155] Figure 9 shows a flowchart 900 of an exemplary system according to several embodiments discussed herein. Referring to Figure 9, in step 910, the customer service system may receive a first dataset having data values ​​for multiple operating categories. As described herein, the first dataset having data values ​​for multiple operating categories may include data values ​​for multiple operating subcategories. In step 920, the customer service system may determine the performance status and performance status diagnostic indicators for the multiple operating categories. In step 930, the customer service system may display a graphical user interface having visual representations associated with the multiple operating categories having diagnostic indicators. By displaying the diagnostic indicators, a customer service representative may be guided about problems or issues with the customer's computing device.

[0156] According to various embodiments, a customer service system may determine the performance status by comparing a dataset received from a customer's computing device 100 with an aggregated dataset received from multiple computing devices 110, etc. Figure 10 shows a flowchart 1000 of an exemplary system according to some embodiments discussed herein. Referring to Figure 10, in step 1010, the customer service system may receive a first dataset having data values ​​associated with multiple operating categories. In step 1020, the customer service system may receive an aggregated dataset having data values ​​for multiple operating categories. As described herein, both the first dataset and the aggregated dataset having data values ​​for multiple operating categories may include data values ​​for multiple operating subcategories. In step 1030, the customer service system may determine the performance status and performance status diagnostic indicators for the multiple operating categories based on a comparison of the first dataset and the aggregated dataset. In step 1040, the customer service system may display a graphical user interface having a visual representation of the multiple operating categories with diagnostic indicators. The display of diagnostic indicators can guide customer service personnel about problems or issues with the customer's computing device.

[0157] In a further embodiment, the customer service system may determine a performance state based on a threshold or range for comparing a dataset received from a customer's computing device 100 with an aggregated dataset received from a plurality of computing devices 110, etc. Figure 11 shows a flowchart 1100 of an exemplary system according to some embodiments discussed herein. Referring to Figure 11, in step 1110, the customer service system may receive a first dataset having data values ​​associated with a plurality of operational categories. In step 1120, the customer service system may receive an aggregated dataset having data values ​​associated with a plurality of operational categories. As described herein, both the first dataset and the aggregated dataset having data values ​​for a plurality of operational categories may include data values ​​for a plurality of operational subcategories. In step 1130, the customer service system may identify a threshold or range based on the aggregated dataset (e.g., through calculation, a predetermined value, etc.). The determination of the threshold is further described herein. In step 1140, the customer service system may determine the performance state of the plurality of operational categories and performance state diagnostic indicators based on a comparison of the first dataset and the aggregated dataset. In step 1150, the customer service system may display a graphical user interface having visual representations of multiple operating categories with diagnostic indicators. The display of diagnostic indicators may guide the customer about problems or issues with their computing device.

[0158] In a further embodiment, the customer service system may determine a performance state based on a threshold or range for comparison between a dataset received from a customer's computing device 100 and an aggregated dataset aggregated by the customer service system from datasets associated with multiple computing devices, such as multiple computing devices 110. Figure 12 shows a flowchart 1200 of an exemplary system according to some embodiments discussed herein. Referring to Figure 12, in step 1210, the customer service system may receive a first dataset having data values ​​associated with multiple operational categories. In step 1220, the customer service system may receive a second dataset associated with multiple second mobile computing devices having data values ​​associated with multiple operational categories. In step 1230, the customer service system may aggregate the second dataset to generate an aggregated dataset. As described herein, both the first dataset having data values ​​for multiple operational categories and the aggregated dataset may contain data values ​​for multiple operational subcategories. In step 1240, the customer service system may identify a threshold or range based on the aggregated dataset. The determination of the threshold is further described herein. In step 1250, the customer service system may determine the performance status and performance status diagnostic indicators for multiple operating categories based on a comparison of the first dataset and the aggregated dataset. In step 1260, the customer service system may display a graphical user interface having a visual representation of the multiple operating categories with diagnostic indicators. The display of diagnostic indicators may guide customer service personnel regarding problems or issues with the customer's computing device.

[0159] In a further embodiment, the customer service system may determine a performance state based on a model for comparing a dataset received from a customer's computing device 100 with an aggregated dataset received from multiple computing devices 110, etc. Figure 13 shows a flowchart 1300 of an exemplary system according to some embodiments discussed herein. Referring to Figure 13, in step 1310, the customer service system may receive a first dataset having data values ​​associated with multiple operating categories. In step 1320, the customer service system may receive an aggregated dataset having data values ​​associated with multiple operating categories. As described herein, both the first dataset and the aggregated dataset having data values ​​for multiple operating categories may include data values ​​for multiple operating subcategories. In step 1330, the customer service system may train a model based on the aggregated dataset. Training a model using machine learning or AI is described herein. In step 1340, the customer service system may determine performance states and performance state diagnostic indicators for multiple operating categories based on the model. For example, thresholds or ranges may be determined based on the model. In step 1350, the customer service system may display a graphical user interface having visual representations of multiple operating categories with diagnostic indicators. The display of diagnostic indicators may guide the customer about problems or issues with their computing device.

[0160] According to the embodiments discussed herein, diagnostic indicators may guide customer service personnel to problems or issues with a customer's computing device, and GUI 301 may display data for operating categories and data for operating subcategories associated with the operating categories. Figure 14 shows an exemplary system flowchart 1400 according to some embodiments discussed herein. Referring to Figure 14, in step 1410, the customer service system may receive a first dataset having data values ​​for a plurality of operating categories. As described herein, the first dataset having data values ​​for a plurality of operating categories may include data values ​​for a plurality of operating subcategories. In step 1420, the customer service system may determine the performance status and performance status diagnostic indicators for the plurality of operating categories. In step 1430, the customer service system may display a graphical user interface having visual representations of the plurality of operating categories with diagnostic indicators, and for the first operating category, visual representations of the operating subcategories having diagnostic indicators. By displaying the diagnostic indicators, customer service personnel may be guided to problems or issues with a customer's computing device.

[0161] According to the embodiments discussed herein, a customer service representative may, for example, select an operation category on the GUI 301, and the customer service system 130 may receive the selection and update the GUI 301 to display operation subcategory data associated with the selected operation category. Figure 15 shows an exemplary system flowchart 1500 according to some embodiments discussed herein. Referring to Figure 15, in step 1510, the customer service system may receive a selection for the display of operation categories on the graphical user interface. In step 1520, the customer service system may display a second graphical user interface having information associated with the selected operation category and a visual representation of a plurality of operation subcategories having diagnostic indicators for the selected operation category. A customer service representative who has been guided by the display on the GUI 301 regarding a problem or issue with the customer's computing device may be further guided by the display of operation subcategory data on the updated GUI 301, such as diagnostic indicators for one or more of the operation subcategories of the data.

[0162] According to embodiments discussed herein, a customer service system may guide a customer service representative to speak with a customer by displaying a performance prompt accompanied by a diagnostic message, the customer service representative may provide feedback to the system regarding the success of the guidance in the diagnostic message, and if the feedback indicates that the customer's problem or issue was not resolved, the customer service system may update to display an additional diagnostic message. The diagnostic message may be displayed to the customer service representative with a performance prompt that guides the customer service representative by prompting the customer service representative to provide feedback icons for the customer service representative to provide feedback regarding a successful solution to the customer's problem or issue. The feedback icons may consist of one or more dynamic icons, such as a first icon representing a selection in which the problem or issue was resolved, and a second icon representing a selection in which the problem or issue was not resolved. Figure 16 shows an exemplary system flowchart 1600 according to some embodiments discussed herein. Referring to Figure 16, in step 1610, the customer service system may determine one or more diagnostic messages associated with a performance state. In step 1620, the customer service system may display one or more performance prompts having a diagnostic message and a feedback icon. In step 1630, the customer service system may receive a selection from the feedback icon. The feedback icon may provide feedback to the customer service system 130 from the customer service representative if the diagnostic message may have successfully resolved the customer's problem or issue. In step 1640, if the selection received from the feedback icon is a successful solution to the customer's problem or issue, the customer service system may proceed to step 1670; otherwise, the customer service system may proceed to step 1650.In step 1650, the customer service system may determine one or more additional diagnostic messages based on the selection from the feedback icons. In step 1660, the customer service system may update the display to show one or more additional performance prompts with additional diagnostic messages and feedback icons. In step 1670, the customer service system may update the display to remove the diagnostic indicator associated with the successful solution. In a further example, if the feedback from the customer service representative is consistently that the customer's problem remains unresolved, the customer service system may determine a performance prompt with a diagnostic message that is general to the customer's device and not specific to a particular behavior category or subcategory.

[0163] According to embodiments discussed herein, diagnostic messages determined by the customer service system 130 may be associated with a resolution value. The resolution value may be determined by the customer service system 130 and may be an estimate (e.g., a percentage) that the guidance in the diagnostic message displayed in the performance prompt will resolve the customer's problem or issue. Furthermore, the customer service system 130 may display diagnostic messages to the customer service representative in order from the highest resolution value (e.g., the most likely guidance to resolve the customer's problem or issue) to the lowest resolution value (e.g., the least likely guidance to resolve the customer's problem or issue). Additionally or alternatively, the customer service system 130 may display only diagnostic messages with solutions that exceed a threshold. The determination of the resolution value may be based on a dataset from the customer's computing device or aggregated data from the customer's device 110 by statistical analysis, machine learning, or AI as described herein. Figure 17 shows an exemplary system flowchart 1700 according to several embodiments discussed herein. Referring to Figure 17, in step 1710, the customer service system may determine several diagnostic messages associated with a performance state. In step 1720, the customer service system may determine the resolution value of the diagnostic message. In step 1730, the customer service system may display one or more performance prompts with a diagnostic message having the highest value and a feedback icon.

[0164] According to embodiments described herein, the customer service system 130 may establish a connection with the customer and / or the customer's computing device 100 to enable a customer service representative to send instructions to the customer and / or the customer's computing device 100 to resolve the customer's problem or issue based on guidance from the customer service system. For example, the customer service system may establish a transmission connection with the customer's computing device 100 and receive a portion of the computing device 100's dataset or an update to the computing device 100's dataset. The transmission connection may be, for example, a connection via a network 120 that can enable the transmission of data. Furthermore, the reception or update of a portion of the dataset for the computing device 100 may be triggered by the customer service system requesting data via the transmission connection. The customer service system 130 may determine one or more diagnostic messages associated with a dataset, such as for a portion of a recently received dataset or for a dataset associated with the computing device 100 that may contain a portion of a recently received dataset. Furthermore, the customer service system may establish a communication connection with the customer that can enable customer representatives and the customer to communicate with each other, such as by telephone, video chat, and / or screen sharing. Furthermore, via the communication connection, a customer service representative may provide or show the customer how to address or resolve a problem or issue. The customer service system 130 may display one or more performance prompts, which may include diagnostic messages, to guide communication with the customer service representative. In addition, the customer service system may send commands, such as via the transmission connection, to the customer's computing device 100 to provide instructions on the computing device 100, such as configuration changes, software updates, and / or firmware updates. In response to the provision of commands, the customer service system 130 may receive a responsive update of the first dataset, which may be called the responsive portion of the first dataset.

[0165] Figure 18 shows a flowchart 1800 of an exemplary system according to several embodiments discussed herein. Referring to Figure 18, in step 1810, the customer service system may establish a transmit connection. In step 1820, the customer service system may receive a trigger that triggers the transmit of a portion of the first dataset. In step 1830, the customer service system may receive a portion of the first dataset. In step 1840, the customer service system may determine one or more diagnostic messages associated with a performance condition. In step 1850, the customer service system may establish a communication connection. In step 1860, the customer service system may display a performance prompt. In step 1870, the customer service system may transmit a first set of instructions associated with a diagnostic message. In step 1880, the customer service system may receive a responsive portion of the first dataset. A customer service representative who may have been guided by the customer service system 130 regarding a problem or issue with the customer's computing device displays a performance prompt.

[0166] Figure 19A shows an exemplary graphical user interface according to some embodiments discussed herein. Referring to Figure 19A, GUI 301 may display an account area 302, an operation category icon area 303, operation category icons 310A-310I, and one or more operation category information areas 320A, 320B, 320C, ..., 320N, and may further include operation subcategory information areas 330A, 330B, 330C, ..., 330N. The operation category and subcategory information areas may include a visualization of one or more settings of the computing device. In some embodiments, GUI 301 may allow a customer service representative to modify one or more settings from the GUI. In such embodiments, the customer service system may send a command to change a setting to the customer computing device, and the customer computing device may require the customer service system to request additional permission and / or confirmation from the customer before initiating the setting change. GUI 301 may also display a selection area 1910 which may include a screen selection area 1920. The selection area 1910 may include feedback icons or dropdown boxes that allow a customer service representative to make a selection that can trigger an action on the customer's computing device 100. For example, the selection area 1910 may include a screen selection area 1920 that may allow a selection of screens that can be displayed on the customer's computing device 100.

[0167] Figure 19B shows an example of the graphical user interface of Figure 19A, where the “Settings” operation category icon 310F is selected according to several embodiments discussed herein. Referring to Figure 19B, GUI 301 displays information for the “Audio,” “Connectivity,” and “Display” operation category areas 320A, 320B, and 320C, respectively. GUI 301 also displays operation subcategory information areas 330A-330J for operation category 320A, operation subcategory information areas 330K-330P for operation category 320B, and operation subcategory information areas 330Q-330R for operation category 320C. One or more information areas associated with one or more operation categories may be selectable by a customer service representative to change the settings of the customer device. GUI 301 further displays a selection area 1910 titled “Launchable Screens,” which includes a screen selection area 1920. In this example, when a customer service representative selects the screen selection area 1920, one or more available screens for the customer computing device may be displayed to the customer service representative. A launchable screen may instruct the customer's computing device to display a screen (e.g., a menu or interface within the customer's computing device) to allow the user to view a specific set of information or to modify specific settings themselves.

[0168] Figure 19C shows an example of the graphical user interface of Figure 19A, where the “Settings” action category icon 310F is selected according to some embodiments discussed herein, and the screen selection area 1920 is also selected. In Figure 19C, the selection of the screen selection area 1920 triggers a list of screens that a customer service representative can select (e.g., “Account Settings”, “Airplane Mode Settings”, “APN Settings”, “Application Advanced Settings”, “Application Settings”, “Bluetooth Settings”, “Caption Settings”, “Date Settings”, “Device Information Settings”, “Dictionary Settings”, “Display Settings”, “Daydream Mode Settings”, “Input Method Settings”, “Input Method Subtype Settings”, “Internal Storage Settings”, “Locale Settings”, “Location Settings”, “Manage All Applications Settings”, “Manage Applications Settings”, “Memory Card Settings”, “Network Operator Settings”, “NFC Payment Settings”, “NFC Settings”, “NFC Sharing Settings”, “Print Settings”, “Search Settings”, “Security Settings”, “Main Settings”, “Sound Settings”, “Sync Settings”, “WiFi IP Settings”, “WiFi Settings”, and “Wireless Settings”). The list of screens may be limited to screens available on the customer's computing device 100, or the list of screens may include screens not available on the customer's computing device 100. In some embodiments, the list of screens may be arranged alphabetically, or ranked based on the modeling and data analysis described herein, such as ranking the screens based on which are most likely to solve a customer problem.

[0169] In some embodiments, a customer service representative may select a screen to display while assisting the customer in resolving a problem. In some embodiments, screen selection may allow the customer service representative to navigate to a screen on the customer's computing device 100, enabling the user to view the screen in real time with the customer service representative and then view and / or change settings on the customer's computing device (e.g., by selecting a setting within an action category, by remotely controlling the customer's device, or by instructing the customer to manually change a setting after the customer service representative has triggered the appropriate screen to launch). This functionality may be used in conjunction with visualizing the customer's computing device screen on the customer service representative's computing device, enabling simultaneous viewing by both parties. In some embodiments, the customer service representative's selection of a screen from the screen selection area 1920 may cause the selected screen to be displayed on the customer's computing device 100 so that the customer can see the customer service representative's selection and / or changes. In some embodiments, the customer service representative may be able to annotate the screen displayed to the customer or take screenshots. Such annotations may include instructions for the customer or indications, settings, or icons (e.g., arrows, color changes, and area highlighting) of areas that the customer service representative wants to draw the customer's attention to. In some embodiments, computing devices may not allow the customer service representative to collect certain data or modify certain settings, and annotations may help the customer provide information to the customer service representative in order to address the customer's issue. The customer may provide information during a customer service support session, which may include the customer discussing the issue via a communication connection such as a phone, voice call, or video call.

[0170] In some embodiments, a customer service representative may require customer permission to display an activatable screen or change settings, for example, as described herein. Figure 20A shows an exemplary display 2000 of a customer computing device 100 according to some embodiments discussed herein. Referring to Figure 20A, in some embodiments, the display 2000 may display a notification area 2010. The notification area 2010 may include a message and / or a permission icon. The permission icon may be a feedback icon for the customer to provide permission, which may permit one or more customer service representative-initiated actions occurring on the customer device, such as the actions described in various embodiments herein. Referring to Figure 20A, in some embodiments, there may be two or more permission icons, such as permission icon 2020A and permission icon 2020B.

[0171] Figure 20B shows an example of the display 2000 of Figure 20A according to several embodiments discussed herein. In Figure 20B, the notification area 2010 includes a message (e.g., "Remote settings change. A customer service representative is requesting you to open the Bluetooth settings screen.") and two permission icons 2020A and 2020B. Referring to Figure 20B, permission icon 2020A allows the customer to provide feedback to deny permission (e.g., "Cancel"), and permission icon 2020B allows the customer to grant permission (e.g., "Approve"). By granting permission, the customer allows a customer service representative to open the Bluetooth settings screen, in the embodiment shown in Figure 20B.

[0172] In some embodiments not shown, the notification area 2010 may include multiple messages and multiple permission icons that may allow granting different permissions. For example, messages and associated permission icons may allow the customer to select different screens of interest to a customer service representative in resolving the customer's issue. In such embodiments, the customer will provide feedback to the customer service representative in resolving the issue. Where multiple messages and / or permission icons may be displayed to the customer, in some embodiments, the ordering of the messages and / or permission icons may be selected by a customer service representative, ordered according to a set hierarchy, or ranked by modeling or machine learning. The requested permissions may be in addition to standard permissions granted to the customer device-side installation of software associated with the various processes and programs discussed herein. For example, standard permissions may, according to various embodiments, allow the collection of one or more data values ​​for initial transmission to the customer service system.

[0173] In some embodiments, after the customer grants permission to open a screen, the customer's computing device 100 opens the permitted screen. Figure 21A shows an exemplary display 2000 of the customer's computing device 100 according to some embodiments discussed herein. Referring to Figure 21A, in some embodiments, the display 2000 may display the permitted screen. The permitted screen may include a device information area 2210. The device information area 2210 may include a display of the permitted screen along with other customer computing device 100 information such as the model of the customer's computing device, the operation category name and settings, and / or the operation subcategory name and settings. Referring to Figure 21A, there may be a settings area 2220 containing one or more settings associated with the permitted screen. If the settings of the permitted screen have multiple settings associated with the permitted screen, the settings area 2220 may include sub-setting areas 2230.

[0174] Figure 21B shows an example of the display 2000 of Figure 21A according to several embodiments discussed herein. In Figure 21B, the permission screen is a Bluetooth settings screen, as shown in the device information area 2210 of Figure 21B. This device information area 2210 also provides model information about the device in Figure 21B, as well as allowing the Bluetooth setting to be changed from on to off. In some embodiments, the Bluetooth setting may be changed via a customer service representative GUI while the screen is displayed or without the screen being displayed. In Figure 21B, the settings area 2220 includes several sub-setting areas 2230A-G, each of which corresponds to a device paired with the customer's computing device 100 via Bluetooth. In the embodiments of Figure 21B, the permission granted by the user may or may not allow a customer service representative to collect data about the permission screen, change the settings displayed on the permission screen, or open further screens from the permission screen. In some embodiments, if a customer service representative does not have such permission, the customer may provide such permission through additional feedback, such as a notification area which may include the feedback icon discussed above.

[0175] In some embodiments, the notification area 2010 and / or feedback icon 2020 may allow the customer to grant permission from a customer service representative or accept a configuration change. In some embodiments, the customer service representative may request permission to collect data from the customer's computing device 100, and the customer may use the feedback icon 2020 to grant permission. In some embodiments, the customer service representative may generate a notification by pushing a configuration change to the customer's computing device 100, which may trigger the notification area 2010, allowing the customer to accept or cancel the configuration change. In some embodiments, two or more configuration changes may be pushed to the customer's computing device simultaneously.

[0176] In some embodiments, the GUI 301 may display a copy of the display 2000 of the customer's computing device 100, thereby allowing the customer service representative to see what the customer sees on the customer's computing device 100.

[0177] In some embodiments, a chat window may be present within or on the display 2000 or notification area 2010, and a customer service representative may provide instructions on how the customer can navigate to the settings screen associated with the customer's issue.

[0178] In some further embodiments, a customer service representative may trigger one or more additional diagnostic requests in addition to displaying past and current data from the customer device. For example, a customer service representative may send a command to the customer device to perform a diagnostic test on one or more hardware and / or software parts of the customer device via direct command and / or via various interaction techniques described herein (e.g., as described in relation to Figures 19A-21B). In some embodiments, a customer service representative may perform one or more long-term diagnostic tests, such as collecting one or more data values ​​on the customer device over a predetermined period of time or until a predetermined stop condition is met. In such embodiments, the long-term data values ​​typically include data not collected during the routine operation of the customer device and / or data not typically collected according to a customer service system for a fully functional device. In such embodiments, a customer service representative may trigger a long-term diagnostic test based on and in response to one or more diagnostic and / or performance prompts described herein. The data collected during a long-term diagnostic test may be data requiring additional permission from the user, as described herein, for example, and such permission may then be requested. For example, a long-term diagnostic test may collect one or more of the following: app data activity, processor activity, background data, and location information (e.g., cellular, Wi-Fi, Bluetooth, and / or GPS location). In some embodiments, user-granted permissions may expire at the end of the long-term diagnostic test. One or more reports and / or results may be sent to the customer and / or customer service representative after the long-term diagnostic test. A customer service support session may be terminated while awaiting the results of the long-term diagnostic test (e.g., the test may run longer than a typical support call, and follow-up may be required).In some embodiments, when a customer service support session ends, the results of a long-term diagnostic test may be automatically sent to the customer support service system upon completion of the long-term diagnostic test, or may be sent to the customer service system during a subsequent customer service support session. In some embodiments, completion of the long-term diagnostic test may trigger instructions to the customer service support system, which may indicate that the test is complete (e.g., instructions provided to the customer and / or customer service system), or that the data in the test is ready for transmission, or may trigger the transmission of the test results.

[0179] The subject matter described in this specification includes, but is not limited to, the following specific embodiments: 1. A method, Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. Determining multiple performance states of a first mobile computing device, wherein the multiple performance states include at least one performance state for one or more of a plurality of operating categories, and at least one first performance state associated with the first operating category includes a first diagnostic indicator associated with the first mobile computing device. A method comprising displaying a first graphical user interface on a screen, wherein the first graphical user interface includes visual representations associated with two or more of a plurality of operation categories, including a first operation category, the visual representations associated with the first operation category include a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator visually distinguishes the visual representation associated with the first operation category from the visual representation associated with a second operation category.

[0180] 2. The determination of the first performance state associated with the first operation category is Identifying the threshold associated with the first behavior category, The method according to Embodiment 1, further comprising determining a first performance state based on a comparison of one or more data values ​​with a threshold.

[0181] 3. Identifying the threshold associated with the first behavior category, Receiving an aggregated dataset associated with multiple other mobile computing devices, wherein the aggregated dataset contains one or more data values ​​associated with multiple mobile computing devices from multiple operating categories. The method according to Embodiment 2, further comprising setting a threshold based on statistical analysis of an aggregated dataset for a first behavior category.

[0182] 4. The method according to Embodiment 3, wherein the threshold is defined as being less than the mean or median of an aggregated dataset for a first behavior category. 5. The determination of the first performance state associated with the first operation category is Identifying the range associated with the first operational category, The method according to any one of embodiments 1 to 4, further comprising determining a first performance state based on a comparison between one or more data values ​​and a range.

[0183] 6. The determination of the first performance state associated with the first operation category is Receiving an aggregated dataset associated with multiple other mobile computing devices, wherein the aggregated dataset contains one or more data values ​​associated with multiple mobile computing devices from multiple operating categories. To determine at least one of several performance states, train a model based on an aggregated dataset, The method according to Embodiment 1, further comprising determining a first performance state associated with a first behavior category by applying a first dataset to a model.

[0184] 7. Receiving a second dataset associated with multiple second mobile computing devices, wherein the second dataset includes one or more data values ​​associated with multiple second mobile computing devices from multiple operation categories. This further includes aggregating a second dataset to generate an aggregated dataset, The method according to Embodiment 1, further comprising determining a first performance state associated with a first operational category by comparing one or more data values ​​of a first dataset associated with the first operational category with one or more data values ​​of an aggregated dataset associated with the first operational category.

[0185] 8. Comparing one or more data values ​​from the first dataset for the first behavior category with one or more data values ​​from the aggregated dataset for the first behavior category, Identifying thresholds for the first behavioral category based on the aggregated dataset, The method according to Embodiment 7, further comprising determining a first performance state based on a comparison between one or more data values ​​associated with a first mobile computing device and a threshold.

[0186] 9. Identifying thresholds for the first behavior category based on the aggregated dataset, The method according to embodiment 8, further comprising determining the mean or median of a first behavior category based on an aggregated dataset.

[0187] 10. Comparing one or more data values ​​from a first dataset associated with a first behavior category with one or more data values ​​from an aggregated dataset associated with the first behavior category, Based on the aggregated data, identify the range associated with the first behavior category, The method according to any one of embodiments 2 to 10, further comprising determining a first performance state based on a comparison between one or more data values ​​and ranges associated with a first mobile computing device.

[0188] 11. The method according to Embodiment 1, wherein the visual representation associated with a first action category further includes visual representations of a plurality of action subcategories associated with the first action category.

[0189] 12. The method according to Embodiment 11, wherein the visual representation associated with a plurality of operation subcategories includes a visual representation associated with a first operation subset, the plurality of performance states include performance states associated with the first operation subset, and the visual representation associated with the first operation subset includes a visual representation of a diagnostic indicator associated with the first operation subset.

[0190] 13. The method according to Embodiment 12, wherein the visual representation of the diagnostic indicator associated with the first operational subcategory is visually represented in the same way as the first visual representation of the first diagnostic indicator.

[0191] 14. The method according to Embodiment 12, wherein the visual representation of a diagnostic indicator associated with a first operational subcategory is visually represented in a manner different from the first visual representation of the first diagnostic indicator.

[0192] 15. The method according to any one of embodiments 1 to 14, wherein the first visual representation of the first diagnostic indicator includes a symbol. 16. The method according to any one of embodiments 1 to 15, wherein a first visual representation of a first diagnostic indicator indicates a problem of at least one of a first operating category or a first operating subcategory.

[0193] 17. The method according to any one of embodiments 1 to 15, wherein a first visual representation of the first diagnostic indicator indicates that there are no problems in the first operating category and the first operating subcategory.

[0194] 18. Multiple performance states further include a second performance state associated with a second operational subcategory, and the second performance state associated with the second operational subcategory includes a second diagnostic indicator. The visual representation of multiple behavioral subcategories includes the visual representation of a second behavioral subcategory, which includes the visual representation of a second diagnostic indicator. The method according to Embodiment 12, wherein the visual representation of the second diagnostic indicator indicates a diagnosis different from the diagnosis indicated by the first diagnostic indicator.

[0195] 19. The method according to any one of embodiments 1 to 18, further comprising: displaying a second graphical user interface including a second visual representation associated with the first operating category in response to receiving a selection of a first operating category, wherein the second visual representation associated with the first operating category includes one or more second diagnostic indicators associated with a first performance state, providing additional information associated with a first performance state relating to a first diagnostic indicator.

[0196] 20. The method according to Embodiment 19, wherein one or more second diagnostic indicators include a diagnostic message containing a description of one or more problems associated with a first performance state. 21. The second graphical user interface is The method according to any one of embodiments 19 to 20, further comprising: multiple historical data from a first dataset for a first operating category; and timestamps associated with the historical data.

[0197] 22. The method according to Embodiment 21, wherein a portion of the historical data from the first dataset includes one of a second diagnostic indicator associated with a first performance state. 23. The second graphical user interface is The method according to any one of embodiments 19 to 20, further comprising: multiple historical data from a first dataset for a first operating category; a timestamp associated with the historical data; and a diagnostic indicator associated with the historical data.

[0198] 24. The method according to Embodiment 23, wherein the diagnostic indicator associated with the historical data is associated with only a portion of the historical data indicating a problem associated with the first mobile computing device.

[0199] twenty five. To determine one or more diagnostic messages associated with the first performance state, The method according to embodiment 19, further comprising displaying one or more performance prompts, each containing one or more diagnostic messages, on a second graphical user interface.

[0200] 26. The method according to embodiment 25, wherein one or more performance prompts include one or more programmatically generated potential solutions to one or more problems of a first computing device associated with a first performance state.

[0201] 27. The second graphical user interface displays feedback icons associated with each performance prompt, In response to receiving a selection of one of the feedback icons, determine one or more additional diagnostic messages, The method according to any one of embodiments 25 to 26, further comprising updating the display of a second graphical user interface in response to receiving a selection from one of the feedback icons in order to display one or more of the additional diagnostic messages.

[0202] 28. The method according to Embodiment 27, wherein in an instance in which the selection of one of the feedback icons indicates a successful solution to one or more problems associated with a first performance state, one or more additional diagnostic messages indicate a successful solution to the problem.

[0203] 29. The method according to Embodiment 27, in an instance where the selection of one of the feedback icons indicates a successful solution to one or more problems associated with a first performance state, the method further comprises removing a visual representation of a second diagnostic indicator associated with one or more problems.

[0204] 30. The method according to any one of embodiments 27 to 29, wherein in an instance in which the selection of one of the feedback icons indicates a successful solution to one or more problems associated with a first performance state, the method further includes updating a database associated with a diagnostic message.

[0205] 31. The method according to Embodiment 27, wherein in an instance in which the selection of one of the feedback icons indicates a failure prompt, the method further comprises displaying a second performance prompt including a second diagnostic message.

[0206] 32. The determination of the first performance state associated with the first operation category is Receiving a second dataset associated with multiple second mobile computing devices, wherein the second dataset includes one or more data values ​​associated with multiple second mobile computing devices from multiple operation categories. Aggregating a second dataset to generate an aggregated dataset, wherein the aggregated dataset includes one or more data values ​​associated with multiple mobile computing devices from multiple operating categories, further comprising: The method according to Embodiment 27, wherein determining a first performance state associated with a first operating category includes comparing one or more data values ​​from a first dataset for the first operating category with one or more data values ​​from an aggregated dataset for the first operating category.

[0207] 33. Determining one or more additional diagnostic messages further includes determining a first additional diagnostic message and a second additional diagnostic message, wherein the first additional diagnostic message defines the first diagnostic message resolution value, and the second additional diagnostic message defines the second diagnostic message resolution value. The method according to any one of embodiments 27 to 32, further comprising updating the display of a second graphical user interface in response to receiving a selection of one of a feedback icon in order to display one or more additional diagnostic messages, by displaying a first additional diagnostic message if the first diagnostic message resolution value is higher than the second diagnostic message resolution value, and displaying a second additional diagnostic message if the second diagnostic message resolution value is higher than the first diagnostic message resolution value.

[0208] 34. Receiving an aggregated dataset associated with multiple other mobile computing devices, wherein the aggregated dataset contains one or more data values ​​associated with multiple other mobile computing devices corresponding to multiple operating categories. The method according to Embodiment 1, further comprising updating the display in response to receiving a selection of one or more of a plurality of operation categories, in order to display a second graphical user interface that displays information associated with one or more selected of a plurality of operation categories.

[0209] 35. The second graphical user interface is Displaying multiple data points from the first dataset for the first behavior category, The method according to embodiment 34, further comprising displaying multiple data from an aggregated dataset for a first behavior category.

[0210] 36. Determining multiple comparative performance states for one or more of multiple operating categories, wherein at least one comparative performance state associated with a first operating category includes a first comparative diagnostic indicator that compares a first mobile computing device with multiple other mobile computing devices; The method according to embodiment 34, further comprising displaying a visual representation of the first comparative diagnostic indicator on a second graphical user interface.

[0211] 37. Determine one or more comparative diagnostic messages associated with the first comparative performance state, The method according to embodiment 37, further comprising displaying one or more performance prompts, each containing one or more comparative diagnostic messages, on a second graphical user interface.

[0212] 38. The second graphical user interface displays feedback icons for each performance prompt, In response to receiving a selection of one of the feedback icons, determine one or more additional comparative diagnostic messages, The method according to embodiment 37, further comprising updating the display of a second graphical user interface in response to receiving a selection from one of the feedback icons in order to display one or more of the additional comparative diagnostic messages.

[0213] 39. The method according to any one of embodiments 1 to 20 or 25 to 38, wherein determining multiple performance states further comprises determining at least one performance state by comparing the most recent data from a first dataset associated with an operation category with historical data from a predetermined period prior to the time associated with the most recent data.

[0214] 40. The method according to Embodiment 39, wherein a first performance state is at least partially determined by a problem identified in a first dataset that exists over a predetermined period of time, and a first diagnostic indicator defines an indication of the problem.

[0215] 41. The method according to Embodiment 39, wherein the period is one of 7 days, 14 days, 21 days, or 30 days. 42. Determining multiple performance states is Identifying the threshold for the first behavior category based on historical data, The method according to any one of embodiments 39 to 41, further comprising determining a first performance state based on a comparison between a first dataset and a threshold.

[0216] 43. To determine one or more diagnostic messages associated with the first performance state, The method according to embodiment 42, further comprising displaying one or more performance prompts, each containing one or more diagnostic messages.

[0217] 44. Display a feedback icon for each performance prompt, In response to receiving one or a selection of one of the feedback icons, determine one or more additional diagnostic messages, The method according to embodiment 43, further comprising updating the display of the graphical user interface in response to receiving a selection from one of the feedback icons in order to display one or more additional diagnostic messages.

[0218] 45. Determining multiple performance states of the first mobile computing device, Identifying the scope of the first operation category based on historical data, The method according to any one of embodiments 39 to 42, further comprising determining a first performance state based on a comparison of a first dataset with a range.

[0219] 46. To determine one or more diagnostic messages associated with the first performance state, The method according to any one of embodiments 39-42 or 45, further comprising displaying one or more performance prompts, each containing one or more diagnostic messages.

[0220] 47. Display a feedback icon for each performance prompt, In response to receiving one or a selection of one of the feedback icons, determine one or more additional diagnostic messages, The method according to any one of embodiments 39-42 or 45, further comprising updating the display of the graphical user interface in response to receiving a selection from one of the feedback icons in order to display one or more of the additional diagnostic messages.

[0221] 48. To establish a transmission connection with a customer in response to a communication request from the customer associated with the first mobile computing device, Receiving at least a portion of the first dataset via the transmission connection, To determine one or more diagnostic messages associated with the first performance state, Establishing a communication connection with the customer, wherein the establishment of the communication connection is performed in relation to the display of the first graphical user interface. Display one or more performance prompts, each containing one or more diagnostic messages, Sending a first instruction set associated with one or more diagnostic messages to a first mobile computing device, The method according to any one of embodiments 1 to 24 or 34 to 45, further comprising receiving a responsive portion of a first dataset from a first mobile computing device via a transmit connection, wherein the responsive portion of the first dataset is associated with a response from the first mobile computing device processing a first instruction set.

[0222] 49. The method according to any one embodiment of 1 to 24, 34 to 42, or 45, wherein the communication connection further includes a telephone or audio connection. 50. The method according to any one of embodiments 48 to 49, wherein a portion of the first dataset is one of a plurality of portions of the first dataset, and the portion of the first dataset includes data values ​​associated with a first mobile computing device from a plurality of operation categories when a transmit connection is established.

[0223] 51. The method according to any one of embodiments 1 to 50, wherein the first visual representation of the first diagnostic indicator includes color. 52. The method according to any one of Embodiments 1 to 50, wherein the first visual representation of the first diagnostic indicator includes a symbol.

[0224] 53. The method according to any one of Embodiments 1 to 50, wherein the first visual representation of the first diagnostic indicator includes a status message. 54. The method according to any one of embodiments 1 to 50, wherein the first visual representation of the first diagnostic indicator includes shading the visual representation of the first operating category.

[0225] 55. The method according to any one of Embodiments 1, 2, 11-24, 39-42, 45, or 48-54, further comprising determining one or more diagnostic messages associated with a first performance state, wherein the one or more diagnostic messages are determined based on an aggregated dataset associated with a plurality of other mobile computing devices.

[0226] 56. The method according to embodiment 55, wherein multiple other mobile computing devices are of the same classification. 57. The method according to any one of embodiments 1-24, 34-42, 45, or 48-54, further comprising determining one or more diagnostic messages associated with a first performance state, wherein the one or more diagnostic messages are determined based on a trained model.

[0227] 58. The method according to any one of embodiments 1 to 57, wherein the first visual representation of the first diagnostic indicator includes a modification of the visual representation associated with the first operating category. 59. The method according to embodiment 58, wherein the first visual representation of the first diagnostic indicator includes a first icon defined on an icon representing a first operating category.

[0228] 60. The method according to any one of embodiments 1 to 59, further comprising a client terminal including a screen, wherein the client terminal is located away from the first mobile computing device.

[0229] 61. A method for solving one or more problems with a mobile device, Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. Determining one or more performance states of a first mobile computing device, A method for generating and presenting one or more performance prompts based on at least one performance state, wherein the one or more performance prompts include a diagnostic message associated with the performance state.

[0230] 62. The method according to Embodiment 61, further comprising receiving instructions associated with a performance prompt via a graphical user interface, wherein the instructions include one of instructions for a successful solution to a problem associated with one or more performance states, or instructions for an unsuccessful prompt.

[0231] 63. The method according to any one of embodiments 61 to 62, wherein one or more performance states are determined by the model. 64. The method according to Embodiment 63, wherein the model includes a statistical model.

[0232] 65. The method according to Embodiment 63, wherein the model includes a trained machine learning model, and the trained machine learning model is trained on aggregated datasets from multiple other mobile computing devices.

[0233] 66. The method according to any one of embodiments 61 to 65, wherein one or more performance states are determined based on an aggregated dataset from a plurality of other mobile computing devices.

[0234] 67. The method according to any one of embodiments 61 to 62, wherein one or more performance prompts are determined by a model. 68. The method according to embodiment 63, wherein the model includes a statistical model.

[0235] 69. The method according to embodiment 63, wherein the model includes a trained machine learning model, and the trained machine learning model is trained based on an aggregated dataset from a plurality of other mobile computing devices.

[0236] 70. The method according to any one of embodiments 61 to 69, wherein one or more performance prompts are determined based on an aggregated dataset from a plurality of other mobile computing devices.

[0237] 71. A method comprising: receiving an input from a user at a first mobile computing device, the input including an indication of a request to initiate a support session; establishing communication between the first mobile computing device and a customer service system and transmitting a first dataset from the mobile computing device to the customer service system; initiating one or more corrective actions on the first mobile computing device based on one or more performance prompts generated in response to the first dataset.

[0238] 72. A non-transitory computer-readable medium storing computer program instructions that, when executed by a processor, Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. Determining multiple performance states of a first mobile computing device via a processor, wherein the multiple performance states include at least one performance state for one or more of a plurality of operating categories, and at least one first performance state associated with the first operating category includes a first diagnostic indicator associated with the first mobile computing device. A method comprising displaying a first graphical user interface on a screen, wherein the first graphical user interface includes visual representations associated with two or more of a plurality of operation categories, including a first operation category, the visual representations associated with the first operation category include a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator visually distinguishes the visual representation associated with the first operation category from the visual representation associated with a second operation category.

[0239] 73. A customer service system, Server and A database configured to communicate with a server, A client terminal located away from a first computing device, the client terminal being configured to communicate with a server and a database, includes: The server Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. The system is configured to determine a plurality of performance states of a first mobile computing device, wherein the plurality of performance states include at least one performance state for one or more of a plurality of operating categories, and at least one first performance state associated with the first operating category includes a first diagnostic indicator associated with the first mobile computing device. The client terminal A customer service system that displays a first graphical user interface on a screen, wherein the first graphical user interface includes visual representations associated with two or more of a plurality of operation categories, including a first operation category, the visual representations associated with the first operation category include a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator is configured to display in a way that visually distinguishes the visual representation associated with the first operation category from the visual representation associated with a second operation category.

[0240] 74. A customer service system, Server and A database configured to communicate with a server, A client terminal located away from a first computing device, the client terminal being configured to communicate with a server and a database, includes: A customer service system in which a server is configured to perform the steps described in any one of Embodiments 1 to 71.

[0241] 75. A customer service system, Server and A database configured to communicate with a server, A client terminal located away from a first computing device, the client terminal being configured to communicate with a server and a database, includes: The server Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. Determining one or more performance states of a first mobile computing device, The system is configured to generate one or more performance prompts based on at least one performance state, wherein the one or more performance prompts include a diagnostic message associated with the performance state. The client terminal further A customer service system configured to display one or more performance prompts based on at least one performance state, wherein the one or more performance prompts include diagnostic messages associated with the performance state.

[0242] 76. A customer service system, Server and A database configured to communicate with a server, A client terminal located away from a first computing device, the client terminal being configured to communicate with a server and a database, includes: The server Receiving input from a user on a first mobile computing device, wherein the input includes instructions for a request to initiate a support session. Establishing communication with a first mobile computing device and receiving a first dataset from the mobile computing device, A customer service system configured to initiate one or more corrective actions on a first mobile computing device based on one or more performance prompts generated in response to a first dataset.

[0243] 77. A device is provided which includes at least a processor and memory associated with the processor having computer-coded instructions, and when a computer instruction is executed by the processor, the device, Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. Determining multiple performance states of a first mobile computing device via a processor, wherein the multiple performance states include at least one performance state for one or more of a plurality of operating categories, and at least one first performance state associated with the first operating category includes a first diagnostic indicator associated with the first mobile computing device. A device configured to display a first graphical user interface on a screen, wherein the first graphical user interface includes visual representations associated with two or more of a plurality of operation categories, including a first operation category, the visual representations associated with the first operation category include a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator displays in a way that visually distinguishes the visual representation associated with the first operation category from the visual representation associated with a second operation category.

[0244] 78. At least, a device is provided that includes a processor and a memory associated with the processor having computer - coded instructions, and when the computer instructions are executed by the processor, the device is configured to cause the device to execute the steps of any one of Embodiments 1 to 71.

[0245] 79. At least, a device is provided that includes a processor and a memory associated with the processor having computer - coded instructions, and when the computer instructions are executed by the processor, the device receives, via a first network, a first data set associated with a first mobile computing device, the first data set including one or more data values associated with the first mobile computing device; determines, via the processor, one or more performance states of the first mobile computing device; generates and displays one or more performance prompts based on at least one of the performance states, the one or more performance prompts including diagnostic messages associated with the performance states.

[0246] 80. At least, a device is provided that includes a processor and a memory associated with the processor having computer - coded instructions, and when the computer instructions are executed by the processor, the device receives an input from a user on a first mobile computing device, the input including an indication of a request to start a support session; establishes communication with the first mobile computing device and receives a transmission of a first data set from the mobile computing device. A device configured to initiate one or more corrective actions on a first mobile computing device based on one or more performance prompts generated in response to a first dataset.

[0247] 81. A method, Receiving a first dataset associated with a first mobile computing device via a first network, wherein the first dataset includes one or more data values ​​associated with the first mobile computing device. Determining multiple performance states of a first mobile computing device, wherein the multiple performance states include at least one performance state for one or more of a plurality of operating categories. Identifying one or more thresholds associated with multiple performance states, Based on a comparison of multiple performance states with one or more thresholds associated with those performance states, one or more corrective actions are determined. To establish communication with the first mobile computing device, A method comprising causing the transmission of one or more corrective actions to a first mobile computing device.

[0248] 82. The method according to Embodiment 81, wherein one or more corrective actions include one or more changes to the settings of the first mobile device. 83. The method according to any one of embodiments 81 to 82, wherein causing the transmission of one or more corrective actions to a first mobile computing device includes pushing corrective actions to the first mobile device.

[0249] Many modifications and other embodiments of the invention described herein will be conceivable to those skilled in the art, having the benefit of the teachings presented in the foregoing description and the accompanying drawings. Therefore, it should be understood that embodiments of the invention are not limited to the specific embodiments disclosed, and modifications and other embodiments are intended to be included within the scope of the appended claims. Certain terms are used herein, but they are used in a general and descriptive sense only and not for limiting purposes.

Claims

1. It is a method, Initiating a support session between the customer service system and the first mobile computing device, The customer service system receives a first dataset associated with the first mobile computing device, wherein the first dataset is associated with at least one performance state of the first mobile computing device. Displaying a first graphical user interface via a display associated with the customer service system, wherein the first graphical user interface includes a visual representation associated with at least one of a plurality of operation categories, including a first operation category, the visual representation associated with the first operation category includes a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator indicates a problem associated with the first operation category based on at least one performance state. Determining two or more diagnostic messages to resolve the problem associated with the first operating category, wherein each of the two or more diagnostic messages provides guidance, For each of the two or more diagnostic messages, the resolution value associated with each of the two or more diagnostic messages is determined, wherein the resolution value is an estimate that the guidance of the associated diagnostic message resolves the problem. The first graphical user interface of the customer service system displays two or more performance prompts, each of which includes two or more diagnostic messages and the resolution value associated with each diagnostic message, and the two or more performance prompts include a first performance prompt and a second performance prompt. For each performance prompt via the display of the customer service system, a feedback icon is displayed on or adjacent to each of the two or more performance prompts on the first graphical user interface on the screen, wherein a selection via the feedback icon triggers an indication that the guidance for resolving the problem associated with the first operational category was unsuccessful. Determining one or more additional diagnostic messages containing additional guidance for resolving the problem associated with the first operating category, In response to the instruction that the guidance regarding the first performance prompt was unsuccessful, the system includes automatically updating the screen to display one or more of the one or more additional diagnostic messages, wherein the automatic updating of the screen includes automatically updating the screen to display a first additional performance prompt containing a first additional diagnostic message in place of the first performance prompt, the first performance prompt being removed and the first additional performance prompt and the second performance prompt being displayed together. method.

2. The aforementioned at least one performance state is Receiving an aggregated dataset associated with multiple other mobile computing devices, wherein the aggregated dataset includes one or more data values ​​associated with the multiple other mobile computing devices from among the multiple operating categories. To determine the at least one performance state, a model is trained based on the aggregated dataset. The process further includes determining the at least one performance state by applying the first dataset to the model, The method according to claim 1.

3. The two or more performance prompts include one or more programmatically generated potential solutions to the problem associated with the first behavior category, The method according to claim 1.

4. The process further includes determining the at least one performance state by comparing the most recent data from the first dataset associated with the operation category with historical data from a predetermined period prior to the time associated with the most recent data. The method according to claim 1.

5. The screen displaying the first graphical user interface is associated with a remote customer service representative for the first mobile computing device. The method according to claim 1.

6. The first guidance for resolving the problem associated with the first operational category is sent to the user of the first mobile computing device after the two or more performance prompts are displayed in the first graphical user interface on the screen associated with the customer service representative. The customer service representative is instructed to select a first screen to be displayed on the first mobile computing device via the display of the customer service system. Displaying the first screen on the display of the customer service system, To display the first screen on the first mobile computing device, The customer service system receives one or more annotations to the first screen associated with the first guidance, This includes displaying one or more annotations on the first screen in real time on both the display of the customer service system and the first mobile computing device. The method according to claim 5.

7. The determination of the resolution value associated with the diagnostic message is performed by an artificial intelligence (AI) model. The method according to claim 1.

8. It is a customer service system, Server and A database configured to communicate with the aforementioned server, A client terminal located away from a first computing device, wherein the client terminal is configured to communicate with the server and the database, The aforementioned server, Initiating a support session between the customer service system and the first mobile computing device, The customer service system receives a first dataset associated with the first mobile computing device, wherein the first dataset is associated with at least one performance state of the first mobile computing device. Displaying a first graphical user interface via a display associated with the customer service system, wherein the first graphical user interface includes a visual representation associated with at least one of a plurality of operation categories, including a first operation category, the visual representation associated with the first operation category includes a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator indicates a problem associated with the first operation category based on at least one performance state. Determining two or more diagnostic messages to resolve the problem associated with the first operating category, wherein each of the two or more diagnostic messages provides guidance, For each of the two or more diagnostic messages, the resolution value associated with each of the two or more diagnostic messages is determined, wherein the resolution value is an estimate that the guidance of the associated diagnostic message resolves the problem. The first graphical user interface of the customer service system displays two or more performance prompts, each of which includes two or more diagnostic messages and the resolution value associated with each diagnostic message, and the two or more performance prompts include a first performance prompt and a second performance prompt. For each performance prompt via the display of the customer service system, a feedback icon is displayed on or adjacent to each of the two or more performance prompts on the first graphical user interface on the screen, wherein a selection via the feedback icon triggers an indication that the guidance for resolving the problem associated with the first operational category was unsuccessful. Determining one or more additional diagnostic messages containing additional guidance for resolving the problem associated with the first operating category, In response to the instruction that the guidance regarding the first performance prompt was unsuccessful, the system is configured to automatically refresh the screen to display one or more of the one or more additional diagnostic messages, wherein the automatic refresh of the screen includes automatically refreshing the screen to display a first additional performance prompt containing a first additional diagnostic message in place of the first performance prompt, and the first performance prompt is removed so that the first additional performance prompt and the second performance prompt are displayed together. Customer service system.

9. The server determines the at least one performance state Receiving an aggregated dataset associated with multiple other mobile computing devices, wherein the aggregated dataset includes one or more data values ​​associated with the multiple other mobile computing devices from among the multiple operating categories. To determine the at least one performance state, a model is trained based on the aggregated dataset. The method is further configured to determine the at least one performance state by applying the first dataset to the model, The customer service system according to claim 8.

10. The two or more performance prompts include one or more programmatically generated potential solutions to the problem associated with the first behavior category, The customer service system according to claim 8.

11. The server is further configured to determine the at least one performance state by comparing the latest data of the first dataset associated with the operation category with historical data from a predetermined period prior to the time associated with the latest data. The customer service system according to claim 8.

12. The screen displaying the first graphical user interface is associated with a remote customer service representative for the first mobile computing device. The customer service system according to claim 8.

13. The server is further configured to send first guidance for resolving the problem associated with the first operational category to the user of the first mobile computing device after the display of two or more performance prompts on the first graphical user interface on the screen associated with the customer service representative, and sending the first guidance to the user of the first mobile computing device means, The customer service representative is instructed to select a first screen to be displayed on the first mobile computing device via the display of the customer service system. Displaying the first screen on the display of the customer service system, To display the first screen on the first mobile computing device, The customer service system receives one or more annotations to the first screen associated with the first guidance, This includes displaying one or more annotations on the first screen in real time on both the display of the customer service system and the first mobile computing device. The customer service system according to claim 12.

14. The determination of the resolution value associated with the diagnostic message is performed by an artificial intelligence (AI) model. The customer service system according to claim 8.

15. A customer service device comprising at least a processor and memory associated with the processor having computer-coded instructions, wherein the instructions, when executed by the processor, are transmitted to the customer service device. To initiate a support session with the first mobile computing device, The customer service device receives a first dataset associated with the first mobile computing device, wherein the first dataset is associated with at least one performance state of the first mobile computing device. Displaying a first graphical user interface via a display associated with the customer service device, wherein the first graphical user interface includes a visual representation associated with at least one of a plurality of operating categories, including a first operating category, the visual representation associated with the first operating category includes a first visual representation of a first diagnostic indicator, and the first visual representation of the first diagnostic indicator indicates a problem associated with the first operating category based on at least one performance state. Determining two or more diagnostic messages to resolve the problem associated with the first operating category, wherein each of the two or more diagnostic messages provides guidance, For each of the two or more diagnostic messages, the resolution value associated with each of the two or more diagnostic messages is determined, wherein the resolution value is an estimate that the guidance of the associated diagnostic message resolves the problem. The first graphical user interface of the customer service device displays two or more performance prompts, each of which includes two or more diagnostic messages and the resolution value associated with each diagnostic message, and the two or more performance prompts include a first performance prompt and a second performance prompt. For each performance prompt via the display of the customer service device, a feedback icon is displayed on or adjacent to each of the two or more performance prompts on the first graphical user interface on the screen, wherein a selection via the feedback icon triggers an indication that the guidance for resolving the problem associated with the first operation category was unsuccessful. Determining one or more additional diagnostic messages containing additional guidance for resolving the problem associated with the first operating category, In response to the instruction that the guidance regarding the first performance prompt was unsuccessful, the system will automatically refresh the screen to display one or more of the one or more additional diagnostic messages, the automatic refresh of the screen including automatically refreshing the screen to display a first additional performance prompt containing the first additional diagnostic message in place of the first performance prompt, the first performance prompt being removed and the first additional performance prompt and the second performance prompt being displayed together. Customer service equipment.

16. The customer service device determines the at least one performance state. Receiving an aggregated dataset associated with multiple other mobile computing devices, wherein the aggregated dataset includes one or more data values ​​associated with the multiple other mobile computing devices from among the multiple operating categories. To determine the at least one performance state, a model is trained based on the aggregated dataset. The method is further configured to determine the at least one performance state by applying the first dataset to the model, The customer service device according to claim 15.

17. The two or more performance prompts include one or more programmatically generated potential solutions to the problem associated with the first behavior category, The customer service device according to claim 15.

18. The customer service device is further configured to determine the at least one performance state by comparing the latest data of the first dataset associated with an operation category with historical data from a predetermined period prior to the time associated with the latest data. The customer service device according to claim 15.

19. The customer service device is further configured to send first guidance for resolving the problem associated with the first operational category to the user of the first mobile computing device after the display of two or more performance prompts on the first graphical user interface on the screen associated with the customer service representative, and to send the first guidance to the user of the first mobile computing device, The customer service representative is instructed to select a first screen to be displayed on the first mobile computing device via the display of the customer service device. Displaying the first screen on the display of the customer service device, To display the first screen on the first mobile computing device, The customer service device receives one or more annotations to the first screen associated with the first guidance, This includes causing the display of the customer service device and the first mobile computing device to display one or more annotations on the first screen in real time, The customer service device according to claim 15.

20. The determination of the resolution value associated with the diagnostic message is performed by an artificial intelligence (AI) model. The customer service device according to claim 15.

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