Guided Computing Device Repair System, Method, and Apparatus - Patent application

Abstract

Methods, computer-readable media, apparatus, and systems are provided for facilitating the diagnosis and repair of one or more performance conditions, such as a battery, associated with a mobile computing device. The system architecture includes a computing device 100, a plurality of other computing devices 110A, 110B, . . . 110N, a network 120, and a customer service system 130. The customer service system 130 is communicatively connected to the computing device 100 and the other computing devices 110 via a network 104, and includes a server 132, a database 134, and a customer service computing device 136.

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 February 7, 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 the customers are having, and the customer service representatives typically communicate with the customers to service them, often from remote locations and with limited knowledge of the problems or issues the customers want resolved. No effective diagnostic system exists that can tie the customer's experience to diagnostic data received from the customer's device. Applicant has identified several additional deficiencies and problems associated with traditional customer service representative systems. Through applied effort, ingenuity, and innovation, many of these identified problems have been solved by developing solutions included in embodiments of the present invention, many examples of which are described in detail herein. Summary of the Invention [Problem to be solved by the invention]

[0003] A system, method, and apparatus for guided computing device repair is provided. [Means for solving the problem]

[0004] Generally, embodiments of the present disclosure provided herein include methods, systems, apparatus, and computer program products for facilitating diagnosis and repair associated with one or more performance conditions of a computing device, such as a mobile computing device. Embodiments of the present disclosure may include a guided customer service interface for improving the diagnosis and determination of a customer's problem or issue.

[0005] Generally, embodiments of the invention provided herein include methods, computer-readable media, devices, and systems for providing customer service. In some demonstrative embodiments, a method is provided that includes receiving, via a first network, a first data set associated with a first mobile computing device. The first data set 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 operational categories. The at least first performance state may be associated with a first operational 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 the plurality of operational categories, including the first operational category. The visual representations may be associated with the first operational category and include a first visual representation of the first diagnostic indicator. The first visual representation of the first diagnostic indicator may visually distinguish a visual representation associated with the first operational category from a visual representation associated with a second operational category.

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

[0007] In some demonstrative embodiments, identifying the threshold value associated with the first operational category includes 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 the plurality of mobile computing devices from a plurality of operational categories. In some embodiments, the method may include setting the threshold value based on a statistical analysis of the aggregated dataset for the first operational category.

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

[0009] In some demonstrative embodiments, determining the first performance state associated with the first operational 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 the plurality of mobile computing devices from the plurality of operational categories. In some embodiments, the method may include training a model based on the aggregated dataset to determine at least one of the plurality of performance states. In some embodiments, the method may include determining the first performance state associated with the first operational category by applying the first dataset to the model.

[0010] In some demonstrative 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 operational categories. In some embodiments, the method may include aggregating the second dataset to generate an aggregated dataset. Determining the first performance state associated with the first operational category may include comparing one or more data values ​​of the first dataset associated with the first operational category with one or more data values ​​of the aggregated dataset associated with the first operational category.

[0011] In some demonstrative embodiments, comparing one or more data values ​​of the first data set for the first operational category with one or more data values ​​of the aggregated data set for the first operational category may include identifying a threshold value for the first operational category based on the aggregated data set. In some embodiments, the method may include determining a first performance state based on a comparison of the one or more data values ​​associated with the first mobile computing device to the threshold value.

[0012] In some demonstrative embodiments, identifying a threshold value for the first motion category based on the aggregated data set may include determining a mean or median value for the first motion category based on the aggregated data set.

[0013] In some demonstrative embodiments, comparing one or more data values ​​of the first data set associated with the first operational category to one or more data values ​​of the aggregated data set 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 the one or more data values ​​and the range associated with the first mobile computing device.

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

[0015] In some embodiments, the visual representations associated with the plurality of operation subcategories may include a visual representation associated with a first operation subcategory. The plurality of performance states may include a performance state associated with the first operation subcategory. The visual representations associated with the first operation subcategory may include a visual representation of a diagnostic indicator associated with the first operation subcategory.

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

[0017] In some embodiments, the visual representation of the diagnostic indicator associated with the first operation subcategory may be visually represented differently than 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, the first visual representation of the first diagnostic indicator may indicate a problem with at least one of the first operation category or the first operation subcategory.

[0019] In some exemplary embodiments, the first visual representation of the first diagnostic indicator may indicate that the first operation category and the first operation subcategory are OK. In some demonstrative 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 may include 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 a 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 demonstrative embodiments, the method includes displaying a second graphical user interface in response to receiving a selection of the first operational category. The second graphical user interface may include a second visual representation associated with the first operational category, and the second visual representation associated with the first operational 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 related to the first diagnostic indicator.

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

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

[0023] In some demonstrative embodiments, the portion of the historical data from the first data set 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 the first data set for the first operating category, timestamps associated with the historical data, and diagnostic indicators 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 plurality of historical data that is indicative of a problem associated with the first mobile computing device.

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

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

[0027] In some exemplary embodiments, the method includes displaying, on a second graphical user interface, a feedback icon associated with 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 of the feedback icons. In some embodiments, the method may include updating a 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 demonstrative embodiments, the method may include, in instances where selection of one of the feedback icons indicates a successful resolution to one or more problems associated with the first performance state, one or more additional diagnostic messages may indicate a successful resolution to the problems.

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

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

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

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

[0033] In some exemplary embodiments, determining the 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 a display of the second graphical user interface in response to receiving a selection of one of the feedback icons 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 demonstrative embodiments, the method may include receiving an aggregated data set associated with a plurality of other mobile computing devices. The aggregated data set may include one or more data values ​​associated with the plurality of other mobile computing devices corresponding to a plurality of operational categories. In some embodiments, the method may include updating the display in response to receiving a selection of one of the one or more of the plurality of operational categories to display a second graphical user interface displaying information associated with the selected one of the one or more of the plurality of operational categories.

[0035] In some demonstrative embodiments, the second graphical user interface may include displaying a plurality of data from the first data set for the first motion category and displaying a plurality of data from the aggregated data set for the first motion category.

[0036] In some demonstrative embodiments, the method may include determining a plurality of comparative performance states for one or more of a plurality of operational categories. In some embodiments, the method may include at least a first comparative performance state associated with a first operational category, which may include a first comparative diagnostic indicator comparing the first mobile computing device to 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 example embodiments, the method includes determining one or more comparative diagnostic messages associated with the first comparative performance state and displaying, on a second graphical user interface, one or more performance prompts that include one or more of the comparative diagnostic messages.

[0038] In some exemplary embodiments, the method includes displaying, on a second graphical user interface, a feedback icon for each of the performance prompts. In some embodiments, the method may include determining one or more additional comparative diagnostic messages in response to receiving a selection of one of the feedback icons. In some embodiments, the method may include updating a 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 the plurality of performance states further includes determining at least one performance state by comparing most recent data of the first data set associated with the operation category with historical data from a predetermined period prior to the time associated with the most recent data.

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

[0041] In some demonstrative embodiments, determining the plurality of performance states may include identifying a threshold value for a first operating category based on the historical data, and determining the first performance state based on a comparison of the first data set with the threshold value.

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

[0043] 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 of the feedback icons. In some embodiments, the method may include updating a 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.

[0044] In some demonstrative embodiments, determining a plurality of performance states of the first mobile computing device may include identifying ranges for a first operating category based on historical data, and determining the first performance state based on a comparison of the first data set to the ranges.

[0045] In some demonstrative embodiments, the method includes determining one or more diagnostic messages associated with the first performance state and displaying one or more performance prompts each including 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 of the feedback icons, and updating a 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 demonstrative embodiments, a method includes establishing an outbound 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 data set via the outbound connection. In some embodiments, the method may include determining one or more diagnostic messages associated with the first performance state. In some embodiments, the method may include establishing a communication connection with the customer. Establishing the communication connection may occur in association with displaying a first graphical user interface. In some embodiments, the method may include displaying one or more performance prompts each including one of the one or more diagnostic messages. In some embodiments, the method may include transmitting a first set of instructions 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 data set from the first mobile computing device via the outbound connection. The responsive portion of the first data set is associated with a response from the first mobile computing device to processing the first set of instructions.

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

[0049] In some exemplary embodiments, the first visual representation of the first diagnostic indicator may be or may include shading a color, symbol, status message, and / or visual representation of the first operating category.

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

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

[0052] In some exemplary embodiments, the first visual representation of the first diagnostic indicator may include a modification of a 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 the first behavior category.

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

[0054] In some demonstrative embodiments, a method for resolving one or more problems on a mobile device may be provided, including receiving, via a first network, a first data set associated with the first mobile computing device. The first data set 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 a diagnostic message associated with the performance state.

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

[0056] In some demonstrative embodiments, the one or more performance states may be determined by a model, which may be a statistical model or a trained machine learning model that is trained based on an aggregated dataset from multiple other mobile computing devices.

[0057] In some demonstrative embodiments, the one or more performance states may be determined based on an aggregated data set from a plurality of other mobile computing devices.

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

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

[0060] In some exemplary embodiments, a method may be provided that includes receiving input from a user at a first mobile computing device. The input may be an indication of 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 transmitting a first data set 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 data set.

[0061] In some demonstrative embodiments, a method may be provided that includes receiving, via a first network, a first data set associated with a first mobile computing device. The first data set 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 operational 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 to the one or more thresholds associated with the plurality of performance states. In some embodiments, the method may include establishing communications with the first mobile computing device. In some embodiments, the method may include establishing a communication that triggers transmission of the one or more corrective actions to the first mobile computing device.

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

[0063] Reference is now made to the accompanying drawings, which are not necessarily drawn to scale. [Brief explanation of the drawings]

[0064] [Figure 1] 1 illustrates an exemplary system according to some embodiments discussed herein. [Figure 2] 1 illustrates an exemplary mobile computing device according to some embodiments discussed herein. [Figure 3A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 3B] 3B illustrates the example graphical user interface of FIG. 3A for the "Overview" action category, according to certain embodiments discussed herein. [Figure 4A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 4B] 4B illustrates the example graphical user interface of FIG. 4A for the "Battery" operational category, according to certain embodiments discussed herein. [Figure 4C] 4B illustrates the example graphical user interface of FIG. 4A for the "Signals" action category, according to certain embodiments discussed herein. [Figure 5A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 5B] 5B illustrates the example graphical user interface of FIG. 5A for the "Audio" action category, according to certain embodiments discussed herein. [Figure 6A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 6B] 6B illustrates the example graphical user interface of FIG. 6A for the "Battery" operational category, according to certain embodiments discussed herein. [Figure 7A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 7B] 7B illustrates the example graphical user interface of FIG. 7A for the "Battery" operational category, according to certain embodiments discussed herein. [Figure 8A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 8B] 8B illustrates the example graphical user interface of FIG. 8A for the "Audio" action category, according to certain embodiments discussed herein. [Figure 9] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 10] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 11] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 12] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 13] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 14] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 15] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 16] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 17] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 18] 1 illustrates a flow diagram of an exemplary system according to some embodiments discussed herein. [Figure 19A] 1 illustrates an exemplary graphical user interface according to certain embodiments discussed herein. [Figure 19B] 19B illustrates an example graphical user interface of FIG. 19A for the "Settings" action category, according to certain embodiments discussed herein. [Figure 19C] 19B illustrates an example graphical user interface of FIG. 19A for the "Settings" action category, according to certain embodiments discussed herein. [Figure 20A] 1 illustrates an exemplary graphical user interface of a computing device according to some embodiments discussed herein. [Figure 20B] 21B illustrates an example of the graphical user interface of FIG. 21A according to certain embodiments discussed herein. [Figure 21A] 1 illustrates an exemplary graphical user interface of a computing device according to some embodiments discussed herein. [Figure 21B] 22B illustrates an example of the graphical user interface of FIG. 22A according to certain embodiments discussed herein. DETAILED DESCRIPTION OF THE INVENTION

[0065] Certain embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the invention are shown. Indeed, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.

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

[0067] As used herein, the term "dataset" refers to any data associated with or otherwise related to a computing device, such as, but not limited to, data identifying a device, identifying a customer, identifying device hardware, identifying device software, device characteristics, operational categories, or operational subcategories. A dataset may be created from one single set of data, or a dataset may be composed of multiple portions of data, such as other datasets. A portion of a dataset may be associated with an operational category or operational subcategory. In some embodiments, a dataset may be divided chronologically. For example, a first portion of a dataset may be associated with historical data and a second portion of a dataset may be associated with current or real-time data. A dataset may also include a timestamp associated with the operational category of the data and / or the operational subcategory of the data. A dataset may be associated with one computing device, or alternatively, a dataset may be aggregated from datasets from multiple devices. Data aggregation may occur at predetermined intervals (e.g., daily). The aggregated dataset may be further divided. For example, the aggregated dataset may be data from multiple computing devices with the same or different classifications, such as classifications by device type (e.g., smartphone, laptop), manufacturer, make, and / or model, and the aggregated dataset may have a portion for each computing device's device type, manufacturer, make, 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 scheduled basis and some is collected remotely on-demand by a request sent by customer service.In some embodiments, the user can disable collection entirely and only limit the functionality of the guided interface. In some embodiments, the customer service system may send a request from the customer service computing device or server to the customer's computing device requesting the latest data values ​​for the data at the time of request. In some embodiments, the customer computing device may also upload some data stored locally 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, such as, but not limited to, battery, signal, processor, storage, audio, settings, commands, status updates, applications, remote support, or registration. In some embodiments, an operational category may refer to a single tier of data associated with a computing device. In some embodiments, an operational category may include a data tier with one or more data tiers (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 layer of information within any operational category. For example, operational subcategories for the 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, operational subcategories for the battery operational category may be, but are not limited to, battery health, battery capacity, firmware health, battery status, performance, consumption, low battery, charging, charging alert, charging 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 degraded level. As a further example, the operational subcategories of the signal operational category may be, 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. The operational category and operational subcategories may refer to information at a specific layer that differs from each other. For example, an operational category may also be an operational subcategory for information of a higher category. In one example, an operational subcategory may also be an operational category for one or more subcategories below the operational subcategory.

[0070] As used herein, the term “performance state” refers to data indicative of the operation of one or more aspects of a computing device, such as data indicative of the operation of the computing device for an operational category or operational subcategory, where the 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 a data value of a mobile device that falls into 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 the operational category. A performance state may include one or more data values, such as a numeric value, message, and / or other data value (e.g., good, normal, bad, charging, discharging, operating, not operating), associated with the state. For example, a performance state for the operational subcategory of battery temperature may be “normal” or an equivalent state when the battery temperature is determined to be at a normal temperature. Furthermore, a performance state may include comparative performance, which may be based on a comparison of data from an operational category or operational subcategory of a first computing device with data from the first computing device's operational category or operational subcategory from a second computing device, or, as further disclosed herein, data from an aggregated dataset. In some embodiments, the performance state may be determined as a gradient or degree (e.g., 50% functioning). The performance state may include one or more diagnostic indicators that represent data indicative of the operation of one or more aspects of the computing device. In some embodiments, the performance state may include one or more “problems,” which may then be indicated by the diagnostic indicators. As used herein, the terms “problem,” “issue,” and the like refer to any actual, possible, probable, potential, or perceived operational deficiency or anomaly that a user or customer service representative may attempt to resolve.

[0071] As used herein, the term “diagnostic indicator” refers to an indicator of a diagnostic associated with a computing device that is determined in association with 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 an icon, color, diagnostic message, or other representation that conveys information about a performance state to a user. For example, a normal performance state of battery temperature may have a diagnostic indicator associated with the device's normal detected state (e.g., a green hue to the graphic, a check mark, a thumbs-up, a “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 the area associated with a particular color battery temperature. As a further example, a below-average, unacceptable, or otherwise defective performance state for an average battery life data value may include a diagnostic indicator visually represented with yellow text, a yellow icon, and / or a yellow hue for the 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, a performance condition in the "Battery" operational category, which includes a problem associated with the battery, may include a diagnostic indicator that indicates a diagnosed problem with the battery. Selecting the Battery operational category in the interface may reveal one or more secondary diagnostic indicators that further refine the diagnosis, e.g., into separate subcategories. An additional example of a visual representation associated with a diagnostic indicator may be an icon or text displayed on the graphical user interface that is emphasized (e.g., colored, highlighted, bolded, italicized, enlarged, shaded, blinking, pulsating, resized, etc.).Further examples of diagnostic indicators include the numerous embodiments described herein and will be understood in light of this disclosure to include any other indicator of performance status.

[0072] As used herein, the term "diagnostic message" refers to a type of diagnostic indicator that may include a message that may be determined by a customer service system and that may be displayed on a graphical user interface to explain a performance condition and / or diagnostic indicator associated with an operational category or operational subcategory. For example, if a customer is communicating with a customer service representative about volume being too low, the diagnostic message may be the current or past setting of the volume, provide an explanation of why this may be a problem, and / or include a recommendation 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 condition and / or diagnosis with a customer. Performance prompts may be generated programmatically in accordance with various embodiments discussed herein. In some embodiments, performance prompts may be determined based on performance conditions and / or diagnostic indicators and may facilitate further data collection and / or repair of a computing device. In some embodiments, performance prompts may provide individual actions to resolve one or more potential or actual problems diagnosed associated with a performance condition.

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

[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 the diagnostic message addressed may diagnose or resolve a customer's problem or issue. The resolution value may define a confidence level associated with a performance prompt and / or a diagnostic message. In some embodiments, the resolution value may facilitate ranking of performance prompts and selection by a computing system of performance prompts to display to a user (e.g., a customer service representative). The resolution value may be determined from analyzing or statistically modeling historical data values ​​of a first mobile computing device and / or data sets not associated with the mobile computing device. For example, if multiple data sets associated with a particular make and model of a mobile computing device indicate an operational subcategory problem (e.g., low battery level) and the problem can be resolved or have a higher percentage change by an action the customer can take (e.g., plugging in the mobile computing device), then the diagnostic message associated with these actions the user can take may receive a higher resolution value. As a further example, and by contrast, if multiple data sets associated with a particular make and model of mobile computing device indicate a problem in an operational subcategory (e.g., low battery level) and the problem is not resolved by actions the customer can take (e.g., replacing the battery) or may have a lower percentage change, then the diagnostic messages associated with these actions the user can take may receive a lower resolution value. Additionally, the resolution values ​​and associated diagnostic messages are stored more frequently in the database, and in response to feedback that the diagnostic messages guided the customer service representative to address or resolve the customer's problem or issue, the database is updated to reflect the diagnostic messages that addressed or resolved the customer's problem or issue that was addressed.

[0076] As used herein, the term "customer" may include, but is not limited to, a client, customer, purchaser, shopper, user, etc., who is in a position to interact with or may interact with a customer service representative to diagnose or resolve issues or problems with one or more computing devices.

[0077] <Summary> As technology advances, customers who purchase technology often cannot keep up with how computing devices operate and are unable to effectively diagnose problems with the computing device or are unable to describe the problem with sufficient specificity to enable others (e.g., customer service representatives) to diagnose the problem with the computing device. The proliferation of mobile computing devices (e.g., mobile phones, smartphones, tablets) has placed technology in the hands of many customers who purchase the technology without understanding many of the details of how these computing devices function. This can lead to customers experiencing problems or issues with computing devices, such as mobile computing devices, without knowing how to diagnose, address, or resolve potential issues or problems, or without understanding the connection between the symptoms they experience and the actual problem with the computing device. In some cases, when a problem or issue occurs, the customer contacts a customer service representative for help, but the customer is unable to adequately describe the problem or communicate the information needed to resolve the computing device issue.

[0078] A customer service representative may help a customer resolve a problem with a computing device. The customer service representative may be located remotely from the customer, and communication with the customer service representative may be via telephone, video call, or live chat. Furthermore, the only information the customer service representative may have about a customer's issue or problem is limited to what the customer may provide. Differences in language and dialect, along with disparities in technical knowledge among customers, may significantly affect how customers may describe the problem or issue. For example, if a smartphone screen does not display information (e.g., is blank), one customer may describe the problem as the device not turning on, another customer may describe the problem as the battery dying, and another customer may describe the problem as the screen being broken. Furthermore, customers may not have access to the technical history of the operation of the device or the software running on the device and therefore may not be able to access relevant parts of the device to attempt to diagnose or describe the problem or issue. Additionally or alternatively, customers may conduct research on the internet to address or diagnose the problem or issue, and the customer may present this information to the customer service representative, which may be misleading. In some cases, multiple issues can cause complex symptoms that cannot be effectively diagnosed by external observation or a typical customer service call. A customer service representative may be required to address all of these situations. A customer service representative may be able to address a customer's issues or problems by understanding the customer's computing device and being informed about the appropriate questions to ask and what corrective actions to take. Knowledge of and questions about the computing device may come from several sources, such as, for example, a customer service system that may provide guidance. Traditional solutions to these problems have required the user to ship the computing device to a repair facility for in-person diagnosis and repair or replacement.

[0079] A customer service representative may not know for themselves whether a customer's description is of an actual fault or performance condition that is causing a problem or issue with the computing device. For example, the fault may be in the hardware or software of the computing device, but the customer may be describing a hardware problem or issue when the problem or issue is in the software (or vice versa). Furthermore, when a customer describes a problem or issue, the customer may not be able to describe whether the problem is acute or chronic. Difficulties in accurately describing the problem or issue may make it difficult for the customer service representative to address it. Thus, 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, the customer service representative may request that the customer ship the computing device to a repair location.

[0080] Described herein are methods and systems for a mobile device repair system, a guided customer service system, and a guided customer service interface that diagnose one or more performance conditions associated with a computing device and guide customer service representatives in remotely addressing, diagnosing, and / or resolving a customer's problem or issue by computationally bridging the gap between the consumer experience and performance data from the device. The customer service system may use data received from the customer's computing device (e.g., a data set), which may include historical data, recent data, and / or real-time data, and may be received in whole or in part. Additionally or alternatively, the customer service system may use data received from one or more other computing devices, which may be aggregated, to assist in addressing the customer's problem or issue. The customer service system may establish a connection with the customer's computing device and update the customer's computing device to address the problem or issue, and the computing device may responsively send real-time data to the customer service system, which may indicate that the problem or issue has been resolved or may indicate additional information regarding the problem or issue. Additionally, the exchange of data between the customer service representative, the customer service system, the customer, and the customer's computing device may require multiple iterations, and the system may programmatically determine the most likely solution to the problem and present guided prompts to direct the solution to the problem.

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

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

[0083] For example, in one embodiment, a customer may have a power issue and may collect data over time related to operational categories and / or operational subcategories related to power or battery usage, such as signal strength, location, volume level, screen brightness, etc. The data collected over time may be stored on the customer's computing device and / or may be stored in a customer service system. In some embodiments, the data collected over time may be accessible after it is collected, such as by access 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 may have data regarding the operation of each component. The operational data may be associated with several operational categories, and each category may be composed of operational subcategories. Analysis of the data may be performed at an operational category level or at a more granular level at an operational subcategory level. In some embodiments, the data may be analyzed together, and identified performance conditions may be assigned to operational categories and / or subcategories. Furthermore, analyzing data at the most nuanced subcategory level may determine where a problem or issue is occurring, when such analysis may not be determined from analyzing data at the category level. Furthermore, when the nuanced subcategory level of a customer's computing device is compared to the same data of another similar computing device, or the same data from a collection of similar computing devices, how the customer's computing device is performing may be determined. This may be particularly useful because addressing a customer's problem or issue for an isolated computing device may be very difficult.

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

[0086] Various embodiments of the present invention are directed to a graphical user interface, such as that of FIG. 3A , that is adaptive, intuitive, and configured to guide a customer service representative. The guidance enables the customer service representative to efficiently converse with and obtain information from the customer, and in some instances, obtain non-signal data that may be needed to correctly analyze and diagnose the customer's issue or problem, and the performance status and underlying analysis may translate the customer's perceived issue 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, performance status, and diagnostic indicators from the customer's computing device to the customer service representative. Furthermore, the customer service system may use analysis of the data to provide the customer service representative with a diagnostic message to discuss with the customer.

[0087] <System Architecture> The present disclosure includes various embodiments for a system architecture associated with a customer requesting customer service from a customer service representative via a customer system. FIG. 1 illustrates an exemplary system architecture according to various embodiments of the present disclosure. The system architecture may include a computing device 100, multiple 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 communicatively connected to the computing devices 100 and 110 via the network 104, and may include a server 132, a database 134, and a customer service computing device 136. For clarity, only one server 132, database 134, and customer service computing device 136 are shown in FIG. 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 with 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), a laptop, a tablet, or similar mobile computing and / or communication device. Additionally and / or alternatively, computing device 100 may be a conventionally stationary device such as a desktop computer, a workstation, etc.

[0089] Network 120 may include, for example, one or more wired and / or wireless communication networks, including a wired or wireless local area network (LAN), a personal area network (PAN), a metropolitan area network (MAN), a wide area network (WAN), etc., 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, 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 a public network, such as the Internet, a private network, such as an intranet, or any combination thereof, and may utilize various currently available or later-developed network protocols, including, but not limited to, TCP / IP-based network protocols.

[0090] Customer service system 130 may receive data from, transmit data to, and communicate with computing devices 100 and 110. As shown in FIG. 1 , customer service system 130 engages in machine-to-machine communication with computing devices 100 and 110 via one or more networks 120. Additionally, customer service system 130 may utilize, generate, store, process, request, transmit, modify, and otherwise use and track data sets, performance status, diagnostic indicators, etc. received from computing devices 100 and 110, among other things. 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. Elements of customer service system 130 may be connected to one another directly or indirectly (e.g., via network 120). Customer service system 130 is further described herein.

[0091] Server 132 may include circuitry, one or more network processors, etc. configured to perform some or all of the server-based processes described herein, and may be any suitable network server and / or other type of processing device. In some embodiments, 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 interconnected and / or distributed functions. To avoid unnecessarily complicating the present 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, with reference to FIG. 2 , server 132 may include processing circuitry 210, a user interface 216, and / or a communications interface 218 for facilitating various functions described herein, which functions may be embodied as hardware, software, or a combination of hardware and software. As described herein, processing circuitry 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, data sets, performance status, diagnostic messages, and customer representative feedback. As such, 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; however, 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 FIG. 2 , database 134 may include processing circuitry 210, a user interface 216, and / or a communications interface 218 for facilitating various functions described herein, which functions may be embodied as hardware, software, or a combination of hardware and software. As described herein, processing circuitry 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 described further herein (e.g., with respect to FIG. 2 ), such as a user interface 216 that may 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 processing circuitry 210 and / or a communication interface 218 for facilitating various functions described herein, which functions may be embodied as hardware, software, or a combination of hardware and software. As described herein, the processing circuitry 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 remotely 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 the present disclosure, customer service computing device 136 is shown and described herein as a single customer service computing device, although 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, customer service computing device 136 may define a client terminal accessed by customer service representatives as part of a customer service system.

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

[0095] 2 illustrates an exemplary computing device according to some embodiments discussed herein. For example, FIG. 2 illustrates computing device 100 and / or each of multiple computing devices 110. In some embodiments, any of the devices in customer service system 130 may also include some or all of the components of exemplary computing device 100 shown in FIG. 2. Components, devices, or elements shown and described below with respect to FIG. 2 may not be required, and thus, some may be omitted in certain embodiments. In addition, some embodiments may include additional or different components, devices, or elements beyond those shown and described with respect to FIG. 2.

[0096] 2, exemplary computing devices 100, 110, 132, 134, 136 may include or otherwise communicate with a processing circuit 210 configurable to perform actions in accordance with one or more exemplary embodiments disclosed herein. In this regard, processing circuit 210 may be configured to execute and / or control the performance of one or more functionalities of computing device 100 in accordance with various exemplary embodiments, and thus may provide a means for performing the functionality of computing device 100 in accordance with various exemplary embodiments. Processing circuit 210 may be configured to perform data processing, application execution, and / or other processing and management services in accordance with one or more exemplary embodiments. In some embodiments, computing device 100, or some of its components, such as processing circuit 210, may be embodied as 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) that include materials, components, and / or wires on a structural assembly (e.g., a baseboard). The structural assembly may provide physical strength, size conservation, and / or electrical interaction limitations for the component circuits contained therein. Accordingly, computing device 100 or processing circuit 210 may, in some cases, be configured to implement embodiments on a single chip or as a single "system-on-chip." Thus, in some cases, a chip or chipset may constitute a means for performing one or more operations to provide the functionality described herein.

[0097] 2, processing circuitry 210 may include a processor 212 and, in some embodiments such as that shown in FIG. 2, may further include memory 214. Processing circuitry 210 may communicate with or otherwise control a user interface 216 and / or a communication interface 218. Thus, processing circuitry 210 may 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 may be embodied in several different ways. For example, the processor 212 may be embodied as one or more of a variety of processing means, such as a microprocessor or other processing element, a coprocessor, a controller, or various other computing or processing devices, including, for example, an integrated circuit such as an ASIC (application-specific integrated circuit) or FPGA (field-programmable gate array), or a combination thereof. While shown as a single processor, it will be understood that the processor 212 may include multiple processors. The multiple processors may be in operative communication with one another and collectively configured to perform one or more functions of the computing device 100 as described herein. In some exemplary embodiments, the processor 212 may be configured to execute instructions stored in the memory 214 or otherwise accessible to the processor 212. Thus, whether configured by 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 the processing circuit 210) that, when appropriately configured, is capable of performing operations in accordance with embodiments of the present invention. Thus, for example, when processor 212 is embodied as an ASIC, FPGA, or the like, or a combination thereof, processor 212 may be specifically configured to perform the operations described herein. Alternatively, as another example, when processor 212 is embodied as an executor of software instructions, the instructions may specifically configure processor 212 to perform one or more operations described herein.

[0099] In some exemplary embodiments, memory 214 may include one or more non-transitory memory devices, such as, for example, volatile and / or non-volatile memory, which may be fixed or removable. In this regard, memory 214 may include a non-transitory computer-readable storage medium. While memory 214 is depicted 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., for enabling 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, which may store various files, content, or data sets. Of the contents of memory 214, applications may be stored for execution by processor 212 to perform functionality associated with the respective applications. 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] User interface 216 may be in communication with processing circuit 210 to receive user input indications at user interface 216 and / or provide audible, visual, mechanical, or other output to the user. Thus, user interface 216 may include, for example, a keyboard, a mouse, a screen, a joystick, a display, a touchscreen display, a microphone, a speaker, and / or other input / output mechanisms. Thus, user interface 216, in some exemplary embodiments, may provide a user with access to and interaction with a customer service system and / or customer service representatives, according to various exemplary embodiments.

[0101] Communications interface 218 may include one or more interface mechanisms for enabling communication with other devices and / or networks. In some cases, communications interface 218 may be any means, such as a device or circuitry 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 in communication with processing circuit 210. By way of example, communications interface 218 may be configured to enable computing device 100 to communicate with a customer service system and / or customer service representatives over network 120. Thus, communications interface 218 may include, for example, an antenna (or multiple antennas) and supporting hardware and / or software for enabling communication with a wireless communications network (e.g., a wireless local area network, a cellular network, and / or the like), and / or a communications modem or other hardware / software for supporting 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 computing device 100 data to customer service system 130 via network 120. Similarly, each of computing devices 110 may be capable of providing a dataset to customer service system 130 via network 300. Datasets from computing devices 110 may be stored separately in database 420, and each dataset from computing device 110 may be used individually in diagnosing a problem or issue. Additionally or alternatively, datasets from computing devices 110 may be aggregated into an aggregated dataset. Alternatively, the aggregated dataset may be provided to the customer service system. Furthermore, datasets from computing devices 100 may or may not be included in the aggregated dataset. In one example, the aggregated dataset may be anonymized so that the computing device that contributed the dataset to the aggregated dataset cannot be determined. Furthermore, the aggregated dataset may include data values ​​from multiple operational categories and operational subcategories. In embodiments where one or more of the other computing devices 110 are being diagnosed and / or customer service is being requested, the data transmitted from the computing device 100 may form part of an aggregated data set used to diagnose and repair any problems with the 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 for a particular manufacturer and / or model of computing device, and / or a third party may provide one or more subsets of data including data for individual devices. A third-party application or website may also include data regarding a particular manufacturer and / or model of 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 include discussions of a particular manufacturer and / or model of 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 of computing devices, such as devices for which customers may seek customer service using the customer service system. Third-party data may be indexed by any characteristic of the data, including manufacturer, model, etc. Trends may be recognized or generated by modeling or machine learning. Alternatively, the trends may be provided by a third party within the collected third party data.

[0105] The customer service engine 138 may be used in the customer service system to perform various calculations herein related to calculating performance status, such as diagnosing one or more problems with the computing device, determining diagnostic indicators, generating performance prompts using the diagnostic indicators (e.g., diagnostic messages), and otherwise facilitating the diagnosis and resolution of one or more problems associated with the 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 in, for example, the server 132, may operate based on data obtained from the database 134 and / or the computing devices 100, 110, and may receive and / or transmit information to the 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, we will describe AI and machine learning systems and methods according to embodiments described herein. The AI ​​and machine learning may be performed by a customer service system engine 138, which may be part of the customer service system and may calculate information based on various modeling techniques.

[0107] Machine learning may be used to develop specific pattern recognition algorithms (i.e., algorithms that represent specific pattern recognition problems), which may be based on statistical inference. In some embodiments, customer service system 130 receives large amounts of data (e.g., data sets) from various sources (e.g., computing device 100 and computing device 110) and must determine 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 model described herein may be generated using the 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 a calculation of the similarity of the features of patterns in 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 using a training set of patterns and their respective known classifications. Each training pattern is input into the classifier, and the difference between the output classification produced by the classifier and the known classification is used to adjust the classifier coefficients to more accurately represent the problem. Classifiers developed using supervised learning are also known as trainable classifiers.

[0109] In some embodiments, the dataset analysis includes a source-specific classifier that takes as input a source-specific representation of a dataset received from a particular source 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 required criteria or unlikely to meet required criteria). 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 a particular source.

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

[0111] In some embodiments, the training data set may be selected based on computing devices that share a similar classification as the computing device to be diagnosed and repaired (e.g., a training set including only mobile devices with a particular operating system, a training set including only mobile devices with particular hardware, only mobile devices of a particular make or model, etc.). Using the techniques described herein, a model may be trained to determine one or more performance states associated with the computing device, generate one or more diagnostic messages and / or performance prompts associated with the mobile device, including generating a resolution value associated with one or more prompts, and any other diagnostic, customer service, or related calculations associated with the methods and embodiments described herein. 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, the labeled dataset may be provided to customer service system engine 138 to train a model. The labeled dataset may include operational data associated with multiple computing devices and labels, including diagnostics, diagnostic messages, prompts, etc., associated with the computing devices. The model may then be trained to identify and classify operational datasets received from the computing devices as corresponding to one or more of the labeled criteria.

[0113] In some embodiments, if the system determines that the received data set does not include at least one relevant data reference, the analysis terminates. 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 ends.

[0114] In some embodiments, the 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 use a "deep learning" module. Deep learning is a subset of machine learning, and generates models based on training datasets provided to the machine learning. A deep learning network can be used to draw in large inputs and allow the algorithm to learn which inputs are relevant to identifying device problems or no problems. In some embodiments, the training models can use unsupervised learning techniques such as clustering, anomaly detection, Hebbling learning, and learning latent variable models such as the expectation-maximization algorithm, the method of moments (mean, covariance), and blind signal separation techniques including principal component analysis, independent component analysis, nonnegative matrix factorization, and singular value decomposition.

[0115] In some embodiments, non-machine learning modeling techniques may be used. For example, an aggregated dataset may be compiled and used to statistically compare performance to a dataset associated with a particular computing device. In some embodiments, the aggregated dataset may be filtered to a representative dataset (e.g., based on classification as described above with respect to model training). One or more performance states associated with the computing device may then be determined based on a comparison between the computing device's dataset and aggregated datasets associated with multiple other computing devices. In one example, data values ​​associated with a computing device's dataset may be directly compared and statistically correlated with the datasets of multiple 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 predetermined criteria for each of multiple operational categories relative to the aggregated dataset (e.g., standard deviation, percentile ranking, etc.). In various embodiments, it may be determined whether a computing device falls within predetermined criteria for the aggregated dataset for each of multiple 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 output). In some embodiments, an operational category may be defined by one or more specific data values. In some embodiments, a performance state may be associated with one or more particular performance parameters. In some embodiments, a performance state may be defined by multiple performance parameters (e.g., a performance state identifying a battery discharge problem may be displayed when (1) the screen is off, (2) no device is plugged in, and (3) the discharge rate is greater than a predetermined threshold).In some embodiments, a predetermined time period may be used when performing the modeling techniques, such that a problem is not identified unless, for example, a performance condition indicative of a problem persists for the entire predetermined time period, or a selected portion thereof.

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

[0117] <Diagnosis> Customer service system 130 may diagnose a problem or issue with a customer's computing device 100. The diagnosis may be based on data sets provided by the customer's computing device 100, data sets provided by computing device 110, aggregated data sets 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 the 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 can be in a dataset from the customer's computing device 100, which can include current battery temperature data values ​​and / or historical battery temperature data values. The customer service system 130 can compare the current battery temperature and / or past battery temperatures to one or more thresholds. In one example, a single threshold can be used to determine whether the battery is at or above a high temperature. In a further example, two thresholds can be used as ranges (e.g., a high and a low temperature range) to determine whether the battery has fallen outside a temperature range. The thresholds or ranges can 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 can be averages, moving averages, or weighted averages, or medians. If the battery temperature does not exceed a high temperature, in one example, or does not exceed a temperature range, in another example, the customer service system may diagnose that the customer's computing device does not have a problem or issue (e.g., a "normal" state). The diagnosis may determine a performance state (e.g., normal, good, healthy, etc.) that indicates there is no problem or issue. If the battery temperature exceeds a high temperature, in one example, or falls outside a temperature range, in another example, the customer service system may diagnose that the customer's computing device has a problem or issue. The diagnosis may determine a performance state (e.g., problem, problem, high, low, abnormal, unhealthy, etc.) that indicates there is a problem or issue. While the above example relates to an operational subcategory of data related to battery temperature, it will be understood that the use of thresholds and / or ranges to diagnose whether there is a problem or issue may be used with other operational categories of data and / or operational subcategories of data. In some embodiments, the ranges may be determined by the manufacturer as part of the battery's design.In some embodiments, the range may be determined based on observations of actual detachments with the same model. In some embodiments, the range or threshold may be preset, such as determining that a problem exists when the data value is outside 10% of the mean of the distribution of aggregated data. 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 a number below the 10th percentile of peers.

[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 make and model from the same manufacturer. The dataset from the customer's computing device 100 may include data values ​​for average battery life for operational subcategories. The dataset from the customer's computing device 100 may determine the average battery life based on a period such as the past seven days. Alternatively, the average battery life may be calculated from other periods such as 14 days, 30 days, three months, or one year. Similarly, an aggregated dataset for computing devices of the same manufacturer, make, 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 with the average battery life of the aggregated dataset. If the average battery life of the 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 the absence of a problem or issue. If the average battery life of a customer's computing device 100 is less than the average battery life of the aggregated data set, the customer service system may determine a performance state (e.g., problem, issue, low, abnormal, unhealthy, etc.) indicating that there is or may be a problem or issue. While the above example relates to an operational subcategory of data related to average battery life, it will be understood that the use of thresholds and / or ranges to diagnose whether there is a problem or issue may be used with other operational categories of data and / or operational subcategories of data.

[0120] In another example, the threshold or range may be determined by statistical modeling or by using machine learning. The statistical model or machine learning may be used with data sets from customer computing device 100 and / or aggregated data sets. In one example, the statistical modeling or machine learning may be for data values ​​of data from one operational category of data or one operational subcategory of data. Alternatively, the statistical modeling or machine learning may be for data values ​​of data from multiple operational categories of data and / or multiple operational subcategories of data.

[0121] Determining the performance state for diagnosis may include determining a diagnostic indicator that can be visually represented on a screen (e.g., the screen of customer service computing device 136) to indicate the performance state. The diagnostic indicator may vary depending on the performance state, and / or each performance state may have a separate diagnostic indicator. Alternatively, the diagnostic indicators may be the same or similar for the performance states. For example, if a performance state is associated with a customer's computing device that has no issues or problems for the data's operational category or data's operational subcategory, the associated diagnostic indicator may be a green icon indicating that the computing device is, for example, healthy or good for the data's operational category or data's operational subcategory. In some embodiments, the diagnostic indicator may define a level of specificity configured to represent the performance state within an icon or screen, and within a range 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, a diagnostic indicator may be displayed in association with one or more of multiple operational 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 point" or other indicator indicating an operational category problem), or of a greater degree of specificity (e.g., a brief description of the problem, or a more specific icon indicating 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 an icon or color. For example, a normal performance state of battery temperature may have a diagnostic indicator associated with the detected problem or device state. The diagnostic indicator may be visualized by green text, a green-colored icon, or a shading of the background of the area associated with the battery temperature of a particular color. As a further example, a below-average performance state of average battery life may be a diagnostic indicator and may be visually represented with yellow text and a yellow icon to indicate that it has been determined that a problem may exist. Additional examples of visual representations associated with diagnostic indicators may be icons or text displayed on a graphical user interface that are highlighted, shaded, blinking, pulsing, or changing size.

[0123] Guided Interface Customer service representatives may interface with customer service system 130 via customer service computing devices 136. Customer service computing devices 136 may include a user interface including a display (also referred to as a screen) that may display a graphical user interface (referred to herein as a "GUI") for the customer service representative. According to various embodiments of the present disclosure, the GUI may display representations of information that may guide the customer service representative through an interaction with a customer and assist in resolving or addressing any issues or problems the customer may have.

[0124] In one example, a 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 operational categories and / or multiple operational subcategories of data of the customer's computing device 100. The GUI directed to the overview may also display, among other things, visual representations of diagnostic indicators, where the visual representation of a diagnostic indicator associated with a performance state determined to have a problem or issue may be visually different from other diagnostic indicators. Interface elements described herein related to a performance state, including those conveying information associated with a computing device, may be considered diagnostic indicators. Furthermore, the visual representation of multiple operational categories of data may be dynamic in that the visual representation of multiple operational categories of data may be expanded to provide visual representations of multiple operational subcategories of data associated with the operational category. The example interfaces described herein may operate in conjunction with one another (e.g., selecting one or more icons on a GUI may cause the system to present a second GUI that includes another of the GUIs described herein). Apparatus and systems according to embodiments described herein may use multiple versions of the same GUI (e.g., 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 may operate in isolation from any one or more GUIs.

[0125] 3A illustrates an exemplary graphical user interface according to some embodiments discussed herein. Referring to FIG. 3A, graphical user interface 301 (referred to herein as GUI 301) displays information associated with a customer and the customer's computing device 100 and may be the graphical user interface displayed to a customer service representative when the customer contacts the customer service representative to request assistance. Interface 301 may include an account area 302 that may display information associated with the customer's account, such as the customer's name, the customer's phone number, the make of the customer's computing device 100, the manufacturer of the customer's computing device 100, and the model of the customer's computing device 100. GUI 301 may further include an action category icon area 303 having one or more action category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, . . . 310N (collectively referred to herein as "action category icons 310"). Each of the one or more operation category icons 310 may be associated with a different operation category of data (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.) in response to a selection by a customer service representative or 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 an associated operation category and / or one or more diagnostic indicators of the associated operation category. In one example, the diagnostic indicator for an associated category may be the same as the diagnostic indicator for an operation subcategory associated with the operation category (e.g., an "exclamation point," "check mark," etc.).Action category information area 320 may further include action subcategory information areas 330A, 330B, 330C,... 330N (collectively referred to herein as "action subcategory information areas 330"). Each action subcategory information area 330 may include a diagnostic indicator for the associated action subcategory 340 and / or a visual representation of one or more diagnostic indicators, including an action subcategory diagnostic message 350. Action subcategory diagnostic message 350 may include a name of the action subcategory, a description of the action subcategory, a data value associated with the action subcategory, and / or a performance status of the action subcategory. As described herein, the GUI may display visual representations associated with the action categories, which may include action category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, action category information areas 320A, 320B, 320C, ..., 320N, action subcategory information areas 330A, 330B, 330C, ..., 330N, and / or any other visual representations associated with one or more of the action categories.

[0126] 3B shows an exemplary embodiment of the graphical user interface of FIG. 3A with the "Overview" operation category selected in accordance with certain embodiments discussed herein. Referring to FIG. 3B, GUI 301 displays information about the "Overview" operation category, which is indicated as selected by a highlighted operation category icon 310A in operation category icon area 303. In the depicted overview operation category, information corresponding to each of a plurality of other operation categories is shown. In FIG. 3B, computing device account area 302 displays the manufacturer and model of computing device 301 (e.g., "Samsung Galaxy S9"). The operational category icon area 303 displays eleven operational category icons 310 associated with eleven different operational categories of data (e.g., “Overview” in 310A, “Battery” in 310B, “Signal” in 310C, “Storage” in 310D, “Audio” in 310E, “Settings” in 310F, “Commands” in 310G, “Status Updates” in 310H, “Applications” in 310I, “Remote Support” in 310J, and “Registration” in 310K). Settings 310F may define one or more preferences or app / service-related settings for the user to control, such as music volume, call volume, WiFi on / off, etc. In some embodiments, commands 310G are commands to change these settings or to open a settings screen when these settings cannot be changed directly. In some embodiments, there is a command to initiate remote support 310J via screen sharing or camera sharing. Computing device information area 304 displays, for example, operational category information area 320 associated with data for five different operational categories (e.g., 320A "Battery," 320B "Power Adapter," 320C "Data Usage," 320D "Signal," and 320E "Storage").The "Battery" operational category information area 320A is displayed to expand to display operational subcategory information areas 330 (e.g., "Current Level" 330A, "Battery Hog" 330B, "Battery Temperature" 330C, "Average Battery Life" 330D, "Firmware Health" 330E, and "Temperature" 330F). In the example of FIG. 3B , the "Battery Hog" operational subcategory refers to applications that use a greater amount of battery compared to other applications, which will be further described herein. In FIG. 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 the operational subcategory information area 330A is a green circle with a white check. Additionally, the operational subcategory diagnostic message 350 in the operational subcategory information field 330A includes the name of the operational subcategory (e.g., "Current Level," which is the current charge level of the battery operational category), a description of the operational subcategory (e.g., "Current Charge of Battery"), a data value associated with the operational subcategory (e.g., "40%"), and / or a performance status of the operational subcategory (e.g., "40%-Discharged"). Figure 3B further illustrates the "Average Battery Life" operational subcategory with diagnostic indicators 340, 350 (e.g., yellow triangles with exclamation points inside) that indicate a problem or issue.

[0127] In the depicted embodiment, each operation category information area 320 is expandable to show diagnostic indicators associated with one or more subcategories therein. Selecting an “expand” icon (e.g., the arrow shown to the right of each area 320) may display additional subcategory information and, based on available space, more detailed diagnostic indicators, such as diagnostic messages 350. When collapsed, five operation categories are depicted to show less detailed diagnostic indicators 340 on the right side of each information area 320. In some embodiments, the diagnostic indicators may include performance prompts as described herein. Thus, the depicted embodiment may intuitively guide customer service representatives in diagnosing customer problems. When operating in the context of a customer support session, the tiered operation categories may expedite the diagnosis and triage of problems related to the described intuitive system and interface.

[0128] In some embodiments, customer service system 130 may provide a customer service representative with additional information about the operation category, 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 operation category icons 310, and in response, GUI 301 may update to display a second embodiment of a guided customer service interface. The customer service representative may, for example, select one of the operation category icons 310 when performance status and / or diagnostic indicators visually represent an indication that there may be a problem with the customer's computing device. Selection of one of the operation category icons 310 may cause a second GUI to be displayed that includes information associated with the selected operation category. In some embodiments, the second GUI may retain one or more features of the first GUI from which the operation category was selected. In one example, GUI 301 may guide the customer service representative through GUI 301 to determine what the problem or issue may be. Further examples of how customer service representatives may be guided are disclosed herein, such as, for example, how a customer's computing device 100 may be compared to other computing devices 110 of the same make and model.

[0129] 3B , in some embodiments, submenus or additional diagnostic indicator options may be available. For example, the GUI 301 shown in FIG. 3B includes a “Device Status” interface that includes the operational category information areas 320, 330 described above, and the GUI 301 includes an “Activities” interface that can show one or more additional visual representations of performance states, diagnostic indicators, and any data associated therewith. For example, the Activities interface may describe a chronological list of activities performed by the customer computing device.

[0130] 4A illustrates an exemplary graphical user interface according to some embodiments discussed herein. Referring to FIG. 4A , GUI 301 may display account region 302, action category icon region 303 including action category icons 310 that may operate as described above with respect to the embodiment of FIGS. 3A-3B, action category information region 401, action subcategory data visualization region 402, and action subcategory data comparison visualization region 403. Action category information region 401 may have one or more action subcategory information regions 410A, 410B, 410C, ..., 410N (collectively referred to herein as "action subcategory information regions 410"). Each of the one or more action subcategory regions 410 may be associated with a different action subcategory of the data described above. Each action subcategory information region 410 may include an action subcategory diagnostic indicator, such as a diagnostic message. The operation subcategory diagnostic message may include the name of the operation subcategory, a description of the operation subcategory, a data value associated with the operation subcategory, a performance state of the operation subcategory, and / or any other visual representation of a diagnostic indicator. The operation subcategory data visualization area 402 may include a visualization, such as a graph or chart, that provides a visualization of the data of the related operation subcategory. The operation subcategory data comparison visualization area 403 may include a comparison visualization, such as a graph or chart, that provides a comparison visualization comparing the data of the related operation subcategory from the customer's computing device 100 with the data of the related operation subcategory from, for example, an aggregated dataset. As described herein, the GUI may display visual representations associated with the action categories, which may include subcategories, including action category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, an action category information area 401, one or more action subcategory information areas 410A, 410B, 410C, ..., 410N, and / or any other visual representation associated with one or more of the action categories, including one or more subcategories.

[0131] 4B shows an example of one embodiment of the graphical user interface of FIG. 4A, with the "Battery" operational category selected in accordance with certain embodiments discussed herein. Referring to FIG. 4B, GUI 301 displays information about the "Battery" operational category, which is indicated as selected by a highlighted operational category icon 310B in operational category icon region 303. In FIG. 4B, operational category information region 401 displays nine operational subcategory information regions 410 (e.g., "Firmware Health" 410A, "Battery Status" 410B, "Battery Charge Type" 410C, "Battery Charging Technique" 410D, "Average Charge" 410E, "Hibernate Discharge" 410F, "Boot-Up Discharge" 410G, "Low Level" 410H, and "Voltage" 410I). In FIG. 4B , each operational subcategory information area 410 includes an operational 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 operational subcategory data visualization area 402 displays a visualization of the data value (e.g., 40%) of the operational subcategory “Battery Level” with a chart. The operational subcategory data comparison visualization area 403 displays a comparison of the average battery life of other computing devices 110 having the same make and model as the customer’s computing device 100 (e.g., “Other Samsung Galaxy S9 Users”) for the associated operational subcategory “Average Battery Life” from the customer’s computing device 100.

[0132] 3A-3B, in some embodiments, selecting one or more of the behavior subcategory information regions 410 may cause additional information and / or additional diagnostic indicators to be displayed for the selected subcategory. For example, sub-subcategories 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 with reference to FIG. 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 a performance state. For example, for a model that statistically analyzes data over a predetermined period of time, the predetermined period must pass before the system can determine whether a problem persists throughout the period. In such an example, the system may not indicate a problem until the predetermined period has passed 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] 4C shows another exemplary embodiment of the graphical user interface of FIG. 4A, with the "Signals" operation category selected in accordance with certain embodiments discussed herein. Referring to FIG. 4C, GUI 301 displays information about the "Signals" operation category, which is indicated as selected by a highlighted operation category icon 310C in operation category icon region 303. In FIG. 4C, operation category information region 401 displays seven operation subcategory information regions 410 (e.g., "Received Strength Signal Indicator (RSSI)" at 410A, "Reference Signal Received Power (RSRP)" at 410B, "Reference Signal Received Quality" at 410C, "Reference Signal Signal-to-Noise Ratio (RSSNR)" at 410D, "Cell Identification (CI)" at 410E, "Physical Cell ID (PCI)" at 410F, and "Tracking Area Code" at 410G). In FIG. 4C , each operational subcategory information area 410 includes an operational subcategory diagnostic message (e.g., “27 dBm” for “Received Strength Signal Indicator (RSSI)” in 410A), which may include a quantitative data value and / or a diagnostic message indicating a qualitative performance condition. The operational subcategory data visualization area 402 does not display a visualization of a data value when no signal is found or data is not received by the system. The operational subcategory data comparison visualization area 403 does not display a comparison of the average signal quality of other computing devices 110 (e.g., “other Samsung Galaxy S9 users”) having the same make and model as the computing device 100 with the computer for the related operational subcategory of “average signal quality” for the “last 30 days average” for the customer's 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 make and model as the 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] Customer service system 130 may provide the customer service representative with additional information for the operation category, which may include a diagnostic message to guide the customer service representative. The customer service representative may, for example, select one of the operation category icons 310, and in response, GUI 301 may be updated to display further embodiments of a guided customer service interface. The updated GUI 301 may provide the customer service representative with a diagnostic message to guide the customer service representative by displaying a message associated with how the operation subcategory may cause a problem or issue for the customer and suggestions on what to discuss with the customer when the dataset may be missing data for the operation category or operation subcategory.

[0136] FIG. 5A illustrates an exemplary graphical user interface according to some embodiments discussed herein. Referring to FIG. 5A, GUI 301 may display account area 302, operational category icon area 303, and performance prompt area 501. 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 operational subcategory of data. Each performance prompt 510 may include the name of the operational subcategory, a description of the operational subcategory, a data value associated with the operational subcategory, a performance status of the operational subcategory, and / or a message associated with how the operational subcategory may cause a problem or issue to the customer, as well as a diagnostic message, which may include suggestions for discussing with the customer. 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 the action categories, which may include subcategories, including action category icons 310A, 310B, 310C, 310D, 310E, 310F, 310G, ..., 310N, a performance prompt area 501, one or more performance prompts 510A, 510B, 510C, ..., 510N, and / or any other visual representations associated with one or more of the action categories, including one or more subcategories.

[0137] As used herein, a performance prompt may be a visualization of a diagnostic message configured to resolve one or more problems associated with a performance state. Performance prompts may be stored as solutions to problems searched for when customer service system engine 138 diagnoses a problem or potential problem. In some embodiments, performance prompts may be determined based on the modeling and data analysis described herein by calculating a solution to the diagnosed problem and generating a performance prompt corresponding to the solution. Customer service system engine 138 may further determine a resolution value associated with each performance prompt, display the resolution value, and / or rank the performance prompts based on the likelihood of success of the performance prompt. 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 the customer service representative with the most likely and most relevant information in an intuitive display that can be quickly considered and referenced by drawing the customer service representative's eye to the most relevant information first (e.g., by displaying the performance prompts in a top-down order).Additional signals considered during performance prompt generation may include customer computing device-specific data (e.g., previous successes with the customer and / or other customers, which may include trends from the customer service system, such as the number of customers accessing the customer service system with the same issue, and / or third-party trend data, such as trending issues on social media) and general problem-resolution data (e.g., which performance prompts were successful in resolving a particular mix of symptoms experienced by the customer computing device, regardless of the particular computing device, which may also include trend data). Computing device-specific data may include data related to the particular make 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 a diagnosis that may include a percent confidence in one or more possible solutions) and / or a hierarchy of performance prompts to optimize the effectiveness and efficiency of a customer service support session. In some embodiments where customer device data is not available, the customer service system may generate default performance prompts based on other data sources (e.g., internal and third-party provided trend information).

[0139] A performance prompt may be triggered upon selection and / or visualization of an operation category or operation subcategory for which a performance state identifies a problem. In some embodiments, different performance prompts may be presented for operation categories that are different from operation subcategories within the operation category, or performance prompts may be ordered differently to indicate a resolution value for each performance value for the operation category for which it is presented. For example, if restarting a device is frequently successful for a problem associated with “traffic lights” but not for one or more operation subcategories within the traffic light operation category, a “Restart device” performance prompt may be shown when visualizing a performance prompt for the specific one or more operation subcategories but not for the traffic light operation category. In a similar manner, the customer service system engine 138 may determine a resolution value for a performance prompt and / or an operation category or subcategory for which the performance prompt may be used, such that different outputs correspond to different categories. In some embodiments, the resolution value may include a correlation between the performance prompt and performance state determined for the computing device and the problem identified therein. In some embodiments, the resolution value may include the relevance of each performance prompt from the list of performance prompts to the performance state determined for the computing device and the problem 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 to problems identified in one or more performance states. The 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 call, and selection of the most relevant performance prompts based on feedback from the customer.

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

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

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

[0144] 5B shows an example of the graphical user interface of FIG. 5A with the "audio" action category selected in accordance with some embodiments discussed herein. Referring to FIG. 5B, GUI 301 displays information about the "audio" action category, which is indicated as selected by a highlighted action category icon 310E in action category icon region 303. In FIG. 5B, performance prompt region 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 FIG. 5B , each performance prompt 510 includes a description of the behavior subcategory (e.g., “Ringtone Volume” (510A)), a message associated with how the behavior subcategory may cause a problem or issue for the customer, and suggestions for what to discuss with the customer (e.g., “If this setting is set to low or 0, this may explain why the phone is not ringing during a call. Have the user set the ringtone volume to 100% and have someone call to test to see if that resolves the issue.”). In FIG. 5B , the messages associated with how the behavior subcategory may cause a problem or issue for the customer and suggestions for what to discuss with the customer in performance prompt 510A guide the customer service representative to the potential problem or issue (e.g., ringtone volume is set to low or 0), provide what the customer may request assistance for (“Phone is not ringing during a call”), and guide the customer service representative how to assist the customer (e.g., “Have the user set the ringtone volume to 100% and have someone call to test to see if that resolves the issue”).In the depicted embodiment, the data set from the customer computing device may be deficient or insufficient in one or more ways such that a default set of performance prompts is displayed without further performance state information. The GUI may be updated as data is received from the computing device or via a customer service representative and added to the data set to determine the performance state, and the system may update the performance prompts and other diagnostic indicators to reflect the evolving performance state.

[0145] Customer service system 130 can provide additional information to the customer service representative about the operational categories, which may include displaying performance states of operational subcategories of data and 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, GUI 301 may update to display further embodiments of a guided customer service interface. The updated GUI 301 may display performance states of operational subcategories of data and historical data values ​​of the operational subcategories.

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

[0147] FIG. 6B shows an exemplary embodiment of the graphical user interface of FIG. 6A , with the “Battery” operational category selected in accordance with some embodiments discussed herein. Referring to FIG. 6B , GUI 301 displays information about the “Battery” operational category, which is indicated as selected by a highlighted operational category icon 310B in operational category icon area 303. 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 64 GB, color Midnight Black, operating system Android 9.0, and IMEI). Operational subcategory usage information area 602 displays six operational categories 610 for the operational subcategory “Battery Hog,” which represent the mobile device application using the largest amount of battery and the percentage of usage (e.g., “Google Maps” at 51% in 620A). The operation subcategory history area 603 may display eight history data entries 630 for the last seven days 630A-630H. Template text is used in the exemplary embodiment, 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] Customer service system 130 may provide the customer service representative with additional information about the timeline and the alerts that occurred during that time. The customer service representative may, for example, select one of the action category icons 310, and in response, GUI 301 may update to display a further embodiment of a guided customer service interface. Updated GUI 301 may display the timeline and the alerts that occurred during that time.

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

[0150] 7B illustrates an exemplary embodiment of the graphical user interface of FIG. 7A, with the "Battery" operation category selected in accordance with certain embodiments discussed herein. Referring to FIG. 7B, GUI 301 may display account region 302, operation category icon region 303, operation subcategory data comparison visualization region 403, timeline region 701, diagnostic indicator summary region 702, diagnostic indicator timeline region 703, operation subcategory data region 704, and operation subcategory data region 705. Timeline region 701 displays a 7-day (e.g., 8-month) timeline. 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 The timeline representation 701 displayed is an icon, with a 14 to indicate it is selected. 日 The icon for Thursday (710G) is highlighted. The diagnostic indicator summary area 702 日 The diagnostic indicator timeline area 703 displays the number of alerts associated with Thursday (710G). The diagnostic indicator timeline area 703 displays 14 alerts for the behavior subcategories of battery health, performance, power consumption, low battery, and charging alerts. 日The timeline for Thursday (710G) is displayed. Operational subcategory data field 704 displays the battery health operational subcategory associated with the customer device 100, and operational subcategory data field 705 displays the battery health operational subcategory associated with another computing device 110.

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

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

[0153] 8B illustrates an example of the graphical user interface of FIG. 8A, where the action category of "Audio" has been selected in accordance with certain embodiments discussed herein. Referring to FIG. 8B, GUI 301 may display account area 302, action category icon area 303, performance prompt area 501, timeline area 701, and / or action category timeline area 802. In FIG. 8B, timeline area 701 displays a timeline for a 7-day period (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The timeline representation 701 displayed is an icon, with 28 to indicate it is selected. 日 The icon for Thursday (710G) is highlighted. The action category timeline region 802 displays the "Audio" action category and six action subcategory timeline regions 820 (e.g., music volume 820A, call volume 820B, ringtone volume 820C, alarm volume 820D, system volume 820E, and Bluetooth 820E). Additionally, in FIG. 8B , each action subcategory timeline region 820 displays an action subcategory time and value 830. For example, the music volume action subcategory timeline region 820A displays five action subcategory times and values ​​830: 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). Additionally, the behavior subcategory time and value 830 is highlighted relative to the time and value that may be associated with the performance state and problem identified in the performance prompts 510A, 510b in the performance prompt area 501. For example, both the performance prompt 510A and the time and value 830A are associated with the behavior subcategory of music volume in FIG. 8B, each address when the music volume is set to 0.

[0154] According to the embodiments discussed herein, the diagnostic indicators may guide a customer service representative to a problem or issue with a customer's computing device. Figures 9-18 show example flowcharts of some, but not all, embodiments of the systems and methods described herein.

[0155] FIG. 9 shows a flow diagram 900 of an exemplary system according to some embodiments discussed herein. Referring to FIG. 9 , in step 910, a customer service system may receive a first data set having data values ​​for multiple operational categories. As described herein, the first data set having data values ​​for multiple operational categories may include data values ​​for multiple operational subcategories. In step 920, the customer service system may determine performance states and diagnostic indicators for the performance states for the multiple operational categories. In step 930, the customer service system may display a graphical user interface having visual representations associated with the multiple operational categories having diagnostic indicators. A customer service representative may be guided through the display of the diagnostic indicators regarding a problem or issue with a customer's computing device.

[0156] According to various embodiments, a customer service system may determine a performance status by comparing a data set received from a customer's computing device 100 with an aggregated data set received from, for example, multiple computing devices 110. FIG. 10 shows a flow diagram 1000 of an exemplary system according to some embodiments discussed herein. Referring to FIG. 10 , at step 1010, the customer service system may receive a first data set having data values ​​associated with multiple operational categories. At step 1020, the customer service system may receive an aggregated data set having data values ​​for the multiple operational categories. As described herein, both the first data and the aggregated data set having data values ​​for the multiple operational categories may include data values ​​for multiple operational subcategories. At step 1030, the customer service system may determine performance status and diagnostic indicators for the multiple operational categories based on a comparison of the first data set and the aggregated data set. At step 1040, the customer service system may display a graphical user interface having a visual representation of the multiple operational categories with diagnostic indicators. A customer service representative may be guided through the display of the diagnostic indicators regarding a problem or issue with the customer's computing device.

[0157] According to further embodiments, the customer service system may determine a performance state based on thresholds or ranges for comparing a data set received from a customer's computing device 100 with a received aggregated data set, such as from multiple computing devices 110. FIG. 11 shows a flow diagram 1100 of an exemplary system according to some embodiments discussed herein. Referring to FIG. 11 , at step 1110, the customer service system may receive a first data set having data values ​​associated with multiple operational categories. At step 1120, the customer service system may receive an aggregated data set having data values ​​associated with multiple operational categories. As described herein, both the first data and the aggregated data set having data values ​​for multiple operational categories may include data values ​​for multiple operational subcategories. At step 1130, the customer service system may identify thresholds or ranges (e.g., via calculation, predetermined values, etc.) based on the aggregated data set. Determining thresholds is further described herein. At step 1140, the customer service system may determine performance states and diagnostic indicators for the multiple operational categories based on the comparison of the first data set and the aggregated data set. In step 1150, the customer service system may display a graphical user interface having a visual representation of a plurality of operational categories with diagnostic indicators. A customer service representative may be guided through the display of the diagnostic indicators regarding a problem or issue with the customer's computing device.

[0158] According to further embodiments, the customer service system may determine a performance status based on thresholds or ranges for comparing a data set received from a customer's computing device 100 with an aggregated data set that the customer service system aggregates from data sets associated with multiple computing devices, such as multiple computing devices 110. FIG. 12 shows a flow diagram 1200 of an exemplary system according to some embodiments discussed herein. Referring to FIG. 12 , at step 1210, the customer service system may receive a first data set having data values ​​associated with multiple operational categories. At step 1220, the customer service system may receive a second data set associated with a plurality of second mobile computing devices having data values ​​associated with the multiple operational categories. At step 1230, the customer service system may aggregate the second data set to generate an aggregated data set. As described herein, both the first data set and the aggregated data set having data values ​​for multiple operational categories may include data values ​​for multiple operational subcategories. At step 1240, the customer service system may identify thresholds or ranges based on the aggregated data set. Determining thresholds is further described herein. At step 1250, the customer service system may determine performance states and diagnostic indicators for the plurality of operational categories based on a comparison of the first data set and the aggregated data set. At step 1260, the customer service system may display a graphical user interface having a visual representation of the plurality of operational categories with the diagnostic indicators. A customer service representative may be guided through the display of the diagnostic indicators regarding the problem or issue with the customer's computing device.

[0159] According to further embodiments, the customer service system may determine a performance state based on a model for comparison of a data set received from a customer's computing device 100 with an aggregated data set received from multiple computing devices 110, such as from multiple computing devices 110. FIG. 13 shows a flow diagram 1300 of an exemplary system according to some embodiments discussed herein. Referring to FIG. 13, in step 1310, the customer service system may receive a first data set having data values ​​associated with multiple operational categories. In step 1320, the customer service system may receive an aggregated data set having data values ​​associated with multiple operational categories. As described herein, both the first data and the aggregated data set having data values ​​for multiple operational categories may include data values ​​for multiple operational subcategories. In step 1330, the customer service system may train a model based on the aggregated data set. Training the model using machine learning or AI is described herein. In step 1340, the customer service system may determine performance states and diagnostic indicators for the multiple operational 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 a visual representation of a plurality of operational categories with diagnostic indicators. A customer service representative may be guided through the display of the diagnostic indicators regarding a problem or issue with the customer's computing device.

[0160] According to embodiments discussed herein, the diagnostic indicators may guide a customer service representative through problems or issues with a customer's computing device, and the GUI 301 may display data for operational categories of data and data for operational subcategories of data associated with the operational categories. FIG. 14 shows a flow diagram 1400 of an exemplary system according to some embodiments discussed herein. Referring to FIG. 14 , at step 1410, the customer service system may receive a first data set having data values ​​for multiple operational categories. As described herein, the first data having data values ​​for multiple operational categories may include data values ​​for multiple operational subcategories. At step 1420, the customer service system may determine performance states and diagnostic indicators for the performance states for the multiple operational categories. At step 1430, the customer service system may display a graphical user interface having visual representations of the multiple operational categories with diagnostic indicators and, for the first operational category, visual representations of the operational subcategories with diagnostic indicators. The customer service representative may be guided through problems or issues with the customer's computing device by the display of the diagnostic indicators.

[0161] According to embodiments discussed herein, a customer service representative may, for example, select an operation category on GUI 301, and customer service system 130 may receive the selection and update GUI 301 to display operation subcategory data associated with the selected operation category. FIG. 15 shows a flow diagram 1500 of an example system according to some embodiments discussed herein. Referring to FIG. 15 , at step 1510, the customer service system may receive a selection of an operation category display on a graphical user interface. At 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 multiple operation subcategories with diagnostic indicators for the selected operation category. A customer service representative who may have been guided regarding a problem or issue with a customer's computing device by the display on GUI 301 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 data.

[0162] According to embodiments discussed herein, the customer service system may display performance prompts accompanied by diagnostic messages to the customer service representative to guide the customer service representative in speaking with the customer, and the customer service representative may provide feedback to the system regarding the success of the diagnostic message guidance. If the feedback is that the customer's problem or issue is not resolved, the customer service system may update to display additional diagnostic messages. The diagnostic messages may be displayed to the customer service representative accompanied by performance prompts to guide the customer service representative by prompting the customer service representative with the diagnostic message, associated data values ​​related to either the operational category or subcategory of the data, and / or feedback icons for the customer service representative to provide feedback regarding the successful resolution of the customer's problem or issue. The feedback icons may be composed 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. FIG. 16 shows a flow diagram 1600 of an example system according to some embodiments discussed herein. Referring to FIG. 16, at 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 with 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 from the customer service representative to the customer service system 130 if the diagnostic message may have been successful in resolving the customer's problem or issue. In step 1640, if the selection received from the feedback icon is a successful resolution of 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 icon. In step 1660, the customer service system may update the display to display one or more additional performance prompts with the 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 feedback from customer service representatives is consistently that the customer's problem has not been resolved, 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 an operational category or operational subcategory.

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

[0164] According to embodiments described herein, customer service system 130 may establish a connection with a 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 to receive a portion of a dataset for the computing device 100 or an update to a dataset for the computing device 100. The transmission connection may be, for example, a connection over network 120 that may enable transmission of data. Furthermore, receipt of a portion of a dataset for the computing device 100 or an update may be triggered by the customer service system requesting data over the transmission connection. The customer service system 130 may determine one or more diagnostic messages associated with a dataset, such as for a recently received portion of a dataset or for a dataset associated with the computing device 100 that may include a recently received portion of a dataset. Furthermore, the customer service system may establish a communication connection with the customer that may enable the customer representative and the customer to communicate with each other, such as, for example, by telephone, video chat, and / or screen sharing. Additionally, via the communications connection, the customer service representative may provide or indicate to the customer how to address or resolve the problem or issue. Customer service system 130 may display one or more performance prompts, which may include diagnostic messages, to guide communication with the customer service representative. Additionally, the customer service system may send instructions, such as via the transmission connection, to the customer's computing device 100 to provide instructions on the computing device 100, such as, for example, configuration changes, software updates, and / or firmware updates. In response to providing the instructions, customer service system 130 may receive a responsiveness update of the first data set, which may be referred to as a responsiveness portion of the first data set.

[0165] FIG. 18 shows an example system flow diagram 1800 according to some embodiments discussed herein. Referring to FIG. 18 , in step 1810, the customer service system may establish a transmission connection. In step 1820, the customer service system may receive a trigger that triggers transmission of a portion of the first data set. In step 1830, the customer service system may receive the portion of the first data set. 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 the diagnostic message. In step 1880, the customer service system may receive a responsive portion of the first data set. A customer service representative, who may be guided by the customer service system 130 regarding a problem or issue with the customer's computing device, displays the performance prompt.

[0166] FIG. 19A illustrates an exemplary graphical user interface according to some embodiments discussed herein. Referring to FIG. 19A , GUI 301 may display account area 302, action category icon area 303, action category icons 310A-310I, and one or more action category information areas 320A, 320B, 320C, . . . , 320N, and may further include action subcategory information areas 330A, 330B, 330C, . . . , 330N. The action category and subcategory information areas may include visualizations 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 of the settings from the GUI. In such embodiments, the customer service system may send instructions to the customer computing device to change the settings, 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 selection area 1910, which may include screen selection area 1920. Selection area 1910 may include feedback icons or drop-down boxes that may allow the customer service representative to make selections that may trigger actions on the customer's computing device 100. For example, selection area 1910 may include a screen selection area 1920, which may allow selection of screens that may be displayed on the customer's computing device 100.

[0167] FIG. 19B illustrates an example of the graphical user interface of FIG. 19A with the “Settings” action category icon 310F selected in accordance with certain embodiments discussed herein. Referring to FIG. 19B, GUI 301 displays information about action category regions 320A, 320B, and 320C for “Audio,” “Connectivity,” and “Display,” respectively. GUI 301 also displays action subcategory information regions 330A-330J for action category 320A, action subcategory information regions 330K-330P for action category 320B, and action subcategory information regions 330Q-330R for action category 320C. One or more information regions associated with one or more action 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 the customer service representative selects screen selection area 1920, one or more available screens for the customer computing device may be displayed to the customer service representative. The 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) that allows the user to view a particular set of information or to modify a particular setting itself.

[0168] 19C illustrates an example of the graphical user interface of FIG. 19A with the "Settings" operational category icon 310F selected in accordance with certain embodiments discussed herein, and with the screen selection area 1920 also selected. In FIG. 19C, selection of the screen selection area 1920 displays a list of screens from which the customer service representative may select (e.g., "Account Settings," "Airplane Mode Settings," "APN Settings," "Advanced Application 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 Share Settings," "Print Settings," "Search Settings," "Security Settings," "Main Settings," "Sound Settings," "Sync Settings," "WiFi ... 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 that are not available on the customer's computing device 100. In some embodiments, the list of screens may be sorted alphabetically or ranked based on the modeling and data analysis described herein, such as ranking screens based on those most likely to solve the customer's problem.

[0169] In some embodiments, the customer service representative may select a screen to display while assisting the customer in resolving the issue. In some embodiments, screen selection may allow the customer service representative to navigate to a screen on the customer's computing device 100, allowing 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 operational category, by remotely controlling the customer's device, or by the customer service representative triggering the activation of the appropriate screen and then prompting the customer to manually change the setting). This functionality may be used in conjunction with visualizing the customer's computing device screen on the customer service representative's computing device, allowing 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 customer's computing device 100 to display the selected screen so that the customer can view the customer service representative's selections and / or changes. In some embodiments, the customer service representative may be able to annotate or take screenshots of the screen displayed to the customer. Such annotations may include instructions to the customer or indications, settings, or icons (e.g., arrows, color changes, and highlighting of areas) to which the customer service representative wants to draw the customer's attention. In some embodiments, the computing device may not allow the customer service representative to collect certain data or modify certain settings, and the annotations may be useful in assisting the customer in providing information to the customer service representative 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 communications connection, such as a telephone, voice connection, or video call.

[0170] In some embodiments, a customer service representative may require a customer's permission to display a launchable screen or change a setting, for example, as described herein. FIG. 20A shows an example display 2000 of a customer's computing device 100 in accordance with some embodiments discussed herein. Referring to FIG. 20A , in some embodiments, the display 2000 may display a notification area 2010. The notification area 2000 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 allow one or more customer service representative-initiated actions to occur on the customer device, such as the actions described in various embodiments herein. Referring to FIG. 20A , in some embodiments, there may be two or more permission icons, such as a permission icon 2020A and a permission icon 2020B.

[0171] FIG. 20B shows an example of the display 2000 of FIG. 20A , according to some embodiments discussed herein. In FIG. 20B , the notification area 2010 includes a message (e.g., “Remote settings change. A customer service representative has requested that you open the Bluetooth settings screen.”) and two permission icons 2020A and 2020B. Referring to FIG. 20B , the permission icon 2020A allows the customer to provide feedback to deny permission (e.g., “Cancel”), and the permission icon 2020B allows the customer to provide permission (e.g., “Accept”). By granting permission, the customer allows the customer service representative to open the Bluetooth settings screen, in the embodiment shown in FIG. 20B .

[0172] In some embodiments not shown, the notification area 2010 may include multiple messages and multiple permission icons that may enable granting different permissions. For example, the messages and associated permission icons may enable the customer to select different screens of interest to the customer service representative to potentially resolve the customer's issue. In such embodiments, the customer would provide feedback to the customer service representative as the issue is resolved. When 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, for example, be selected by the 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, the standard permissions may enable the collection of one or more data values ​​for initial transmission to a customer service system, according to various embodiments.

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

[0174] FIG. 21B shows an example of the display 2000 of FIG. 21A according to some embodiments discussed herein. In FIG. 21B, the permission screen is a Bluetooth settings screen, as shown in the device information area 2210 of FIG. 21B. This device information area 2210 also allows for changing the Bluetooth setting from on to off, as well as providing model information about the device of FIG. 21B. In some embodiments, the Bluetooth settings can be changed through a customer service representative GUI while the screen is displayed or without displaying the screen. In FIG. 21B, the settings area 2220 includes multiple sub-settings areas 2230A-G, each of which corresponds to a device paired to the customer's computing device 100 via Bluetooth. In the FIG. 21B embodiment, the permissions granted by the user may or may not allow the customer service representative to collect data about the permitted screen, change settings displayed on the permitted screen, or open additional screens from the permitted screen. In some embodiments, if the customer service representative does not have such permission, the customer may provide such permission via additional feedback, such as the notification area 2010, which may include the feedback icon 2020 discussed above.

[0175] In some embodiments, notification area 2010 and / or feedback icon 2020 may allow a customer to grant permission or accept a setting change from a customer service representative. In some embodiments, a customer service representative may ask for permission to collect data from the customer's computing device 100, and the customer may use feedback icon 2020 to grant permission. In some embodiments, a customer service representative may generate a notification by pushing a setting change to the customer's computing device 100, which may trigger notification area 2010 that allows the customer to accept or cancel the setting change. In some embodiments, two or more setting 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, allowing the customer service representative to see what the customer sees on the customer's computing device 100.

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

[0178] In some further embodiments, the customer service representative may trigger one or more additional diagnostic requests in addition to displaying previous and current data from the customer device. For example, the customer service representative may send instructions to the customer device via direct command and / or via various interaction techniques described herein (e.g., as described in connection with FIGS. 19A-21B) to perform diagnostic testing of one or more hardware and / or software portions of the customer device. In some embodiments, the customer service representative may cause one or more long-term diagnostic tests to be run, such as collecting one or more data values ​​on the customer device for 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 routine operation of the customer device and / or data not typically collected in accordance with a customer service system for a fully functional device. In such embodiments, the 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. Data collected during a long-term diagnostic test may be data that requires additional permission from the user, for example, as described herein, which permission may then be requested. For example, the long-term diagnostic test may collect one or more of app data activity, processor activity, background data, location information (e.g., cellular, WiFi, Bluetooth, and / or GPS location information), etc. In some embodiments, permissions granted to the user may expire upon completion 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 the long-term diagnostic test may be automatically transmitted to the customer service system upon completion of the long-term diagnostic test, or may be transmitted to the customer service system during a subsequent customer service support session. In some embodiments, completion of the long-term diagnostic test may trigger an instruction to the customer service support system, which may indicate that the test is complete (e.g., an instruction provided to the customer and / or the customer service system), or that the data in the test is ready for transmission, or may trigger transmission of the test results.

[0179] The subject matter described herein includes, but is not limited to, the following specific embodiments. 1. A method comprising: receiving, 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; determining a plurality of performance states of a first mobile computing device, the plurality of performance states including at least one performance state for one or more of a plurality of operational categories, and at least a first performance state associated with a first operational category including a first diagnostic indicator associated with the first mobile computing device; 1. A method comprising: displaying, on a screen, a first graphical user interface, the first graphical user interface including 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 including a first visual representation of a first diagnostic indicator, the first visual representation of the first diagnostic indicator visually distinguishing the visual representation associated with the first operation category from the visual representation associated with a second operation category.

[0180] 2. Determining a first performance state associated with a first behavior category; Identifying a threshold associated with a first behavior category; 2. The method of embodiment 1, further comprising: determining a first performance state based on a comparison of the one or more data values ​​to a threshold value.

[0181] 3. Identifying a threshold value associated with a first behavior category; receiving an aggregated data set associated with a plurality of other mobile computing devices, the aggregated data set including one or more data values ​​associated with the plurality of mobile computing devices from a plurality of operational categories; 3. The method of embodiment 2, further comprising: setting a threshold based on a statistical analysis of the aggregated data set for the first behavior category.

[0182] 4. The method of embodiment 3, wherein the threshold is defined as less than the mean or median of the aggregated data set for the first behavior category. 5. Determining a first performance state associated with a first behavior category; Identifying a range associated with a first operating category; 5. The method of any one of embodiments 1 to 4, further comprising determining a first performance state based on a comparison of one or more data values ​​to a range.

[0183] 6. Determining a first performance state associated with a first behavior category; receiving an aggregated data set associated with a plurality of other mobile computing devices, the aggregated data set including one or more data values ​​associated with the plurality of mobile computing devices from a plurality of operational categories; training a model based on the aggregated dataset to determine at least one of a plurality of performance states; 2. The method of claim 1, further comprising: determining a first performance state associated with the first behavior category by applying the first dataset to a model.

[0184] 7. receiving a second data set associated with a plurality of second mobile computing devices, the second data set including one or more data values ​​associated with the plurality of second mobile computing devices from a plurality of operational categories; aggregating the second data set to generate an aggregated data set; 2. The method of claim 1, wherein determining a first performance state associated with a first operational category further comprises 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 ​​of the first data set for the first behavior category with one or more data values ​​of the aggregated data set for the first behavior category; identifying a threshold value for a first behavior category based on the aggregated data set; 8. The method of embodiment 7, further comprising: determining a first performance state based on a comparison of one or more data values ​​associated with the first mobile computing device to a threshold value.

[0186] 9. Identifying a threshold value for a first behavior category based on the aggregated data set; 9. The method of embodiment 8, further comprising determining a mean or median value for the first behavior category based on the aggregated data set.

[0187] 10. Comparing one or more data values ​​of a first data set associated with a first behavioral category to one or more data values ​​of an aggregated data set associated with the first behavioral category; Identifying a range associated with a first behavior category based on the aggregated data; 11. The method of any one of embodiments 2 to 10, further comprising: determining a first performance state based on a comparison of one or more data values ​​associated with the first mobile computing device to a range.

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

[0189] 12. The method of embodiment 11, wherein the visual representations associated with the plurality of behavioral subcategories include a visual representation associated with a first behavioral subcategory, the plurality of performance states include a performance state associated with the first behavioral subcategory, and the visual representations associated with the first behavioral subcategory include a visual representation of a diagnostic indicator associated with the first behavioral subcategory.

[0190] 13. The method of embodiment 12, wherein the visual representation of the diagnostic indicator associated with the first behavior subcategory is visually represented in the same manner as the first visual representation of the first diagnostic indicator.

[0191] 14. The method of embodiment 12, wherein the visual representation of the diagnostic indicator associated with the first behavior subcategory is visually represented differently than the first visual representation of the first diagnostic indicator.

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

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

[0194] 18. the plurality of performance states further includes a second performance state associated with a second operational subcategory, the second performance state associated with the second operational subcategory including a second diagnostic indicator; the visual representations of the plurality of behavioral subcategories include a visual representation of a second behavioral subcategory that includes a visual representation of a second diagnostic indicator; 13. The method of embodiment 12, wherein the visual representation of the second diagnostic indicator indicates a diagnosis that is different from the diagnosis indicated by the first diagnostic indicator.

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

[0196] 20. The method of embodiment 19, wherein the one or more second diagnostic indicators include a diagnostic message including a description of one or more problems associated with the first performance state. 21. A second graphical user interface: A method according to any one of embodiments 19 to 20, further comprising a plurality of historical data from the first data set for the first motion category and a timestamp associated with the historical data.

[0197] 22. The method of embodiment 21, wherein the portion of the historical data from the first data set includes one of the second diagnostic indicators associated with the first performance state. 23. A second graphical user interface: A method according to any one of embodiments 19 to 20, further comprising: a plurality of historical data from a first data set 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 of embodiment 23, wherein the diagnostic indicator associated with the historical data is associated with only a portion of the plurality of historical data that indicates a problem associated with the first mobile computing device.

[0199] twenty five. determining one or more diagnostic messages associated with the first performance condition; 20. The method of embodiment 19, further comprising: displaying, on a second graphical user interface, one or more performance prompts including one or more of the diagnostic messages.

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

[0201] 27. displaying, on a second graphical user interface, a feedback icon associated with each of the performance prompts; determining one or more additional diagnostic messages in response to receiving a selection of one of the feedback icons; 27. The method of any one of embodiments 25 to 26, further comprising: updating a 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.

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

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

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

[0205] 31. The method of embodiment 27, wherein in an instance where selection of one of the feedback icons indicates an unsuccessful prompt, the method further includes displaying a second performance prompt including a second diagnostic message.

[0206] 32. Determining a first performance state associated with a first behavior category includes: receiving a second data set associated with a plurality of second mobile computing devices, the second data set including one or more data values ​​associated with the plurality of second mobile computing devices from a plurality of operational categories; aggregating the second data set to generate an aggregated data set, the aggregated data set including one or more data values ​​associated with a plurality of mobile computing devices from a plurality of operational categories; 28. The method of embodiment 27, wherein determining the first performance state associated with the first operational category includes comparing one or more data values ​​of the first dataset for the first operational category with one or more data values ​​of the aggregated dataset for the first operational category.

[0207] 33. Determining one or more additional diagnostic messages further includes determining a first additional diagnostic message and a second additional diagnostic message, the first additional diagnostic message defining a first diagnostic message resolution value and the second additional diagnostic message defining a second diagnostic message resolution value; A method according to any one of embodiments 27 to 32, wherein updating the display of the second graphical user interface in response to receiving a selection of one of the feedback icons to display one or more of the additional diagnostic messages further includes displaying a first additional diagnostic message when the first diagnostic message resolution value is higher than the second diagnostic message resolution value, and displaying a second additional diagnostic message when the second diagnostic message resolution value is higher than the first diagnostic message resolution value.

[0208] 34. receiving an aggregated data set associated with a plurality of other mobile computing devices, the aggregated data set including one or more data values ​​associated with the plurality of other mobile computing devices corresponding to a plurality of operating categories; 2. The method of embodiment 1, further comprising: updating the display in response to receiving a selection of one of the one or more of the plurality of operation categories to display a second graphical user interface displaying information associated with the selected one of the one or more of the plurality of operation categories.

[0209] 35. A second graphical user interface: Displaying a plurality of data from the first data set for a first motion category; 35. The method of embodiment 34, further comprising: displaying a plurality of data from the aggregated data set for the first behavior category.

[0210] 36. determining a plurality of comparative performance states for one or more of a plurality of operational categories, at least a first comparative performance state associated with a first operational category including a first comparative diagnostic indicator comparing the first mobile computing device to a plurality of other mobile computing devices; 35. The method of embodiment 34, further comprising: displaying a visual representation of the first comparative diagnostic indicator on a second graphical user interface.

[0211] 37. determining one or more comparative diagnostic messages associated with the first comparative performance state; 38. The method of embodiment 37, further comprising: displaying, on a second graphical user interface, one or more performance prompts including one or more of the comparative diagnostic messages.

[0212] 38. displaying, on the second graphical user interface, a feedback icon for each of the performance prompts; determining one or more additional comparative diagnostic messages in response to receiving a selection of one of the feedback icons; 38. The method of embodiment 37, further comprising: updating a 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.

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

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

[0215] 41. The method of embodiment 39, wherein the period is one of 7 days, 14 days, 21 days, or 30 days. 42. Determining multiple performance states is identifying a threshold value for a first operating category based on historical data; 42. The method of any one of embodiments 39 to 41, further comprising determining a first performance state based on a comparison of the first data set with a threshold value.

[0216] 43. determining one or more diagnostic messages associated with the first performance condition; 43. The method of embodiment 42, further comprising: displaying one or more performance prompts, each including one of the one or more diagnostic messages.

[0217] 44. displaying a feedback icon for each of the performance prompts; determining one or more additional diagnostic messages in response to receiving a selection of one of the feedback icons; 44. The method of embodiment 43, further comprising: updating a 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.

[0218] 45. Determining a plurality of performance states of a first mobile computing device comprises: identifying a range of a first operating category based on historical data; 43. The method of any one of embodiments 39 to 42, further comprising determining a first performance state based on a comparison of the first data set with the range.

[0219] 46. determining one or more diagnostic messages associated with the first performance condition; 46. ​​The method of any one of embodiments 39 to 42 or 45, further comprising displaying one or more performance prompts, each of which includes one of the one or more diagnostic messages.

[0220] 47. displaying a feedback icon for each of the performance prompts; determining one or more additional diagnostic messages in response to receiving a selection of one of the feedback icons; A method according to any one of embodiments 39 to 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 to display one or more of the additional diagnostic messages.

[0221] 48. Establishing an outbound 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 a first data set over a transmission connection; determining one or more diagnostic messages associated with the first performance condition; establishing a communication connection with the customer, wherein the establishing of the communication connection occurs in association with displaying a first graphical user interface; displaying one or more performance prompts each including one of the one or more diagnostic messages; transmitting a first set of instructions associated with one or more of the one or more diagnostic messages to the first mobile computing device; 46. ​​The method of any one of embodiments 1 to 24 or 34 to 45, further comprising receiving, via a transmission connection, from the first mobile computing device, a responsive portion of the first data set, the responsive portion of the first data set being associated with a response from the first mobile computing device that processes the first instruction set.

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

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

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

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

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

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

[0228] 60. The method of any one of embodiments 1-59, further comprising a client terminal including a screen, the client terminal being located remotely from the first mobile computing device.

[0229] 61. A method for solving one or more problems in a mobile device, comprising: receiving, 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; determining one or more of a plurality of performance states of the first mobile computing device; generating and presenting one or more performance prompts based on at least one of the performance states, wherein the one or more performance prompts include a diagnostic message associated with the performance state.

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

[0231] 63. The method of any one of embodiments 61-62, wherein one or more performance states are determined by a model. 64. The method of embodiment 63, wherein the model comprises a statistical model.

[0232] 65. The method of 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.

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

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

[0235] 69. The method of 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 of any one of embodiments 61-69, wherein the one or more performance prompts are determined based on an aggregated data set from a plurality of other mobile computing devices.

[0237] 71. A method comprising: receiving 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 a first mobile computing device and a customer service system and transmitting a first data set from the mobile computing device to the customer service system; and initiating one or more corrective actions on the first mobile computing device based on the one or more performance prompts generated in response to the first data set.

[0238] 72. A non-transitory computer-readable medium having stored thereon computer program instructions, the instructions, when executed by a processor, receiving, 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; determining, via the processor, a plurality of performance states of the first mobile computing device, the plurality of performance states including at least one performance state for one or more of a plurality of operational categories, and at least a first performance state associated with a first operational category including a first diagnostic indicator associated with the first mobile computing device; 1. A method comprising: displaying, on a screen, a first graphical user interface, the first graphical user interface including 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 including a first visual representation of a first diagnostic indicator, the first visual representation of the first diagnostic indicator visually distinguishing 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 comprising: A server; a database configured to communicate with the server; a client terminal located remotely from the first computing device, the client terminal configured to communicate with a server and a database, the server receiving, 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; determining a plurality of performance states of the first mobile computing device, the plurality of performance states including at least one performance state for one or more of a plurality of operational categories, and at least a first performance state associated with a first operational category including a first diagnostic indicator associated with the first mobile computing device; 1. A customer service system configured to display, on a screen, a first graphical user interface, the first graphical user interface including 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 including a first visual representation of a first diagnostic indicator, the first visual representation of the first diagnostic indicator visually distinguishing 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 comprising: A server; a database configured to communicate with the server; A customer service system including: a client terminal located remotely from a first computing device, the client terminal configured to communicate with a server and a database, and the server configured to perform the steps described in any one of embodiments 1 to 71.

[0241] 75. A customer service system comprising: A server; a database configured to communicate with the server; a client terminal located remotely from the first computing device, the client terminal configured to communicate with a server and a database, the server receiving, 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; determining one or more of a plurality of performance states of the first mobile computing device; generating one or more performance prompts based on at least one of the performance conditions, the one or more performance prompts including a diagnostic message associated with the performance condition; 1. A customer service system configured to: display one or more performance prompts based on at least one of the performance conditions, the one or more performance prompts including a diagnostic message associated with the performance condition.

[0242] 76. A customer service system comprising: A server; a database configured to communicate with the server; a client terminal located remotely from the first computing device, the client terminal configured to communicate with a server and a database, the server receiving 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 with a first mobile computing device and receiving a transmission of a first data set from the mobile computing device; and initiating one or more corrective actions on the first mobile computing device based on the one or more performance prompts generated in response to the first data set.

[0243] 77. An apparatus is provided that includes at least a processor and a memory associated with the processor having computer-coded instructions, the computer instructions, when executed by the processor, causing the apparatus to: receiving, 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; determining, via the processor, a plurality of performance states of the first mobile computing device, the plurality of performance states including at least one performance state for one or more of a plurality of operational categories, and at least a first performance state associated with a first operational category including a first diagnostic indicator associated with the first mobile computing device; 1. An apparatus configured to: display, on a screen, a first graphical user interface, the first graphical user interface including 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 including a first visual representation of a first diagnostic indicator, the first visual representation of the first diagnostic indicator visually distinguishing the visual representation associated with the first operation category from the visual representation associated with a second operation category.

[0244] 78. An apparatus is provided that includes at least a processor and a memory associated with the processor having computer-coded instructions, the computer instructions being configured to, when executed by the processor, cause the apparatus to perform the steps of any one of embodiments 1 to 71.

[0245] 79. An apparatus is provided that includes at least a processor and a memory associated with the processor having computer-coded instructions, the computer instructions, when executed by the processor, causing the apparatus to: receiving, 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; determining, via the processor, one or more of a plurality of performance states of the first mobile computing device; 1. The apparatus, configured to: generate and display one or more performance prompts based on at least one of the performance conditions, the one or more performance prompts including a diagnostic message associated with the performance condition.

[0246] 80. An apparatus is provided that includes at least a processor and a memory associated with the processor having computer-coded instructions, the computer instructions, when executed by the processor, causing the apparatus to: receiving 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 with a first mobile computing device and receiving a transmission of a first data set from the mobile computing device; and initiating one or more corrective actions on the first mobile computing device based on the one or more performance prompts generated in response to the first data set.

[0247] 81. A method comprising: receiving, 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; determining a plurality of performance states of the first mobile computing device, the plurality of performance states including at least one performance state for one or more of a plurality of operational categories; identifying one or more thresholds associated with a plurality of performance states; determining one or more corrective actions based on a comparison of the plurality of performance states to one or more thresholds associated with the plurality of performance states; establishing communication with a first mobile computing device; and causing transmission of one or more corrective actions to the first mobile computing device.

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

[0249] Many modifications and other embodiments of the inventions described herein will come to mind to one skilled in the art to which these embodiments of the invention pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. It is to be understood, therefore, that embodiments of the invention are not limited to the specific embodiments disclosed, and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

Claims

1. It is a method, Initiating a support session between the customer service system and the first mobile computing device, Displaying a first graphical user interface via a screen associated with the customer service system, which includes a visual representation associated with at least one of a plurality of operation categories, including a first operation category, wherein the visual representation associated with the first operation category includes a first visual representation of a first diagnostic indicator that indicates a problem associated with the first operation category based on the performance state of at least one of the first mobile computing devices; In the first graphical user interface of the customer service system, display at least a first performance prompt containing a first diagnostic message, a second performance prompt containing a second diagnostic message, a first feedback icon adjacent to the first performance prompt, and a second feedback icon adjacent to the second performance prompt, wherein a selection via the first feedback icon or the second feedback icon is configured to trigger an instruction indicating that a corresponding diagnostic message 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, With respect to the first performance prompt, in response to the instruction indicating that the corresponding diagnostic message was unsuccessful, the screen is automatically updated with a first additional performance prompt containing a first additional diagnostic message, thereby automatically updating the screen with one or more of the one or more additional diagnostic messages. Methods that include...

2. Determining one or more additional diagnostic messages includes determining multiple additional diagnostic messages associated with each resolution value, Automatically updating the screen includes selecting and displaying the first additional diagnostic message based on a comparison of the respective resolution values ​​of the plurality of additional diagnostic messages. The method according to claim 1.

3. The method according to claim 2, wherein each of the aforementioned resolution values ​​is determined using a trained machine learning model or artificial intelligence (AI).

4. moreover, Sending a first instruction set associated with one or more of the first diagnostic messages or the second diagnostic messages to the first mobile computing device, wherein the first instruction set causes a change to the settings of the first mobile computing device. Receiving a response portion of a first dataset associated with the first mobile computing device from the first mobile computing device, wherein the response portion is associated with the result of the change to the settings of the first mobile computing device. Determining one or more additional diagnostic messages based at least partially on the response portion of the first dataset, The method according to claim 1, including the method described in claim 1.

5. moreover, In response to the instruction indicating that the corresponding diagnostic message was unsuccessful, the implementation result of the solution is added to the dataset associated with the first mobile computing device, To determine whether the unsuccessful corresponding diagnostic message affects the resolution values ​​of one or more other previously determined performance prompts, the resolution values ​​of the one or more other previously determined performance prompts are recalculated. In response to the determination that the resolution values ​​of one or more other previously determined performance prompts are affected, the first graphical user interface is updated based on the recalculated resolution values ​​for the one or more other previously determined performance prompts. The method according to claim 1, including the method described in claim 1.

6. The method according to claim 1, wherein the one or more additional diagnostic messages include programmatically generated potential solutions for one or more problems associated with the first operating category.

7. moreover, Sending a first instruction set associated with one or more of the first diagnostic messages or the second diagnostic messages to the first mobile computing device, wherein the first instruction set causes the first mobile computing device to perform one or more corrective actions; Receiving response data from the first mobile computing device indicating the results of one or more corrective actions performed on the first mobile computing device, The method according to claim 1, including the method described in 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 the first computing device, configured to communicate with the server and the database, Equipped with, The aforementioned server, Initiating a support session between the customer service system and the first mobile computing device, Displaying a first graphical user interface via a screen associated with the customer service system, which includes a visual representation associated with at least one of a plurality of operation categories, including a first operation category, wherein the visual representation associated with the first operation category includes a first visual representation of a first diagnostic indicator that indicates a problem associated with the first operation category based on the performance state of at least one of the first mobile computing devices; In the first graphical user interface of the customer service system, display at least a first performance prompt containing a first diagnostic message, a second performance prompt containing a second diagnostic message, a first feedback icon adjacent to the first performance prompt, and a second feedback icon adjacent to the second performance prompt, wherein a selection via the first feedback icon or the second feedback icon is configured to trigger an instruction indicating that a corresponding diagnostic message 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, With respect to the first performance prompt, in response to the instruction indicating that the corresponding diagnostic message was unsuccessful, the screen is automatically updated with a first additional performance prompt containing a first additional diagnostic message, thereby automatically updating the screen with one or more of the one or more additional diagnostic messages. A customer service system configured to perform the following actions.

9. Determining one or more additional diagnostic messages includes determining multiple additional diagnostic messages associated with each resolution value, Automatically updating the screen includes selecting and displaying the first additional diagnostic message based on a comparison of the respective resolution values ​​of the plurality of additional diagnostic messages. The customer service system according to claim 8.

10. The customer service system according to claim 9, wherein each of the aforementioned resolution values ​​is determined using a trained machine learning model or artificial intelligence (AI).

11. The aforementioned server further, Sending a first instruction set associated with one or more of the first diagnostic messages or the second diagnostic messages to the first mobile computing device, wherein the first instruction set causes a change to the settings of the first mobile computing device. Receiving a response portion of a first dataset associated with the first mobile computing device from the first mobile computing device, wherein the response portion is associated with the result of the change to the settings of the first mobile computing device. Determining one or more additional diagnostic messages based at least partially on the response portion of the first dataset, The customer service system according to claim 8, configured to perform the following:

12. The aforementioned server further, In response to the instruction indicating that the corresponding diagnostic message was unsuccessful, the implementation result of the solution is added to the dataset associated with the first mobile computing device, To determine whether the unsuccessful corresponding diagnostic message affects the resolution values ​​of one or more other previously determined performance prompts, the resolution values ​​of the one or more other previously determined performance prompts are recalculated. In response to the determination that the resolution values ​​of one or more other previously determined performance prompts are affected, the first graphical user interface is updated based on the recalculated resolution values ​​for the one or more other previously determined performance prompts. The customer service system according to claim 8, configured to perform the following:

13. The customer service system according to claim 8, wherein the one or more additional diagnostic messages include programmatically generated potential solutions for one or more problems associated with the first operational category.

14. The aforementioned server further, Sending a first instruction set associated with one or more of the first diagnostic messages or the second diagnostic messages to the first mobile computing device, wherein the first instruction set causes the first mobile computing device to perform one or more corrective actions; Receiving response data from the first mobile computing device indicating the results of one or more corrective actions performed on the first mobile computing device, The customer service system according to claim 8, configured to perform the following:

15. Customer service equipment, At least one processor, The processor is associated with a memory that stores computer-coded instructions internally, When the computer-coded instruction is executed by the processor, it is sent to the customer service device. To initiate a support session between the customer service device and the first mobile computing device, Displaying a first graphical user interface via a screen associated with the customer service device, which includes a visual representation associated with at least one of a plurality of operating categories, including a first operating category, wherein the visual representation associated with the first operating category includes a first visual representation of a first diagnostic indicator that indicates a problem associated with the first operating category based on the performance state of at least one of the first mobile computing devices; The first graphical user interface of the customer service device displays at least a first performance prompt containing a first diagnostic message, a second performance prompt containing a second diagnostic message, a first feedback icon adjacent to the first performance prompt, and a second feedback icon adjacent to the second performance prompt, wherein a selection via the first feedback icon or the second feedback icon is configured to trigger an instruction indicating that a corresponding diagnostic message 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, With respect to the first performance prompt, in response to the instruction indicating that the corresponding diagnostic message was unsuccessful, the screen is automatically updated with a first additional performance prompt containing a first additional diagnostic message, thereby automatically updating the screen with one or more of the one or more additional diagnostic messages. A customer service device configured to perform the following actions.

16. Determining one or more additional diagnostic messages includes determining multiple additional diagnostic messages associated with each resolution value, Automatically updating the screen includes selecting and displaying the first additional diagnostic message based on a comparison of the respective resolution values ​​of the plurality of additional diagnostic messages. The customer service device according to claim 15.

17. The customer service device according to claim 16, wherein each of the aforementioned resolution values ​​is determined using a trained machine learning model or artificial intelligence (AI).

18. When the computer-coded instruction is executed by the processor, it further sends the customer service device the following: Sending a first instruction set associated with one or more of the first diagnostic messages or the second diagnostic messages to the first mobile computing device, wherein the first instruction set causes a change to the settings of the first mobile computing device. Receiving a response portion of a first dataset associated with the first mobile computing device from the first mobile computing device, wherein the response portion is associated with the result of the change to the settings of the first mobile computing device. Determining one or more additional diagnostic messages based at least partially on the response portion of the first dataset, The customer service device according to claim 15, configured to perform the following:

19. When the computer-coded instruction is executed by the processor, it further sends the customer service device the following: In response to the instruction indicating that the corresponding diagnostic message was unsuccessful, the implementation result of the solution is added to the dataset associated with the first mobile computing device, To determine whether the unsuccessful corresponding diagnostic message affects the resolution values ​​of one or more other previously determined performance prompts, the resolution values ​​of the one or more other previously determined performance prompts are recalculated. In response to the determination that the resolution values ​​of one or more other previously determined performance prompts are affected, the first graphical user interface is updated based on the recalculated resolution values ​​for the one or more other previously determined performance prompts. The customer service device according to claim 15, configured to perform the following:

20. The customer service device according to claim 15, wherein the one or more additional diagnostic messages include programmatically generated potential solutions for one or more problems associated with the first operating category.

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