Live streaming data analysis methods and devices

Abstract

This disclosure provides a live streaming data analysis method and a live streaming data analysis device. The live streaming data analysis method may include: in response to a first account's target setting operation for a target task, obtaining a total target parameter set for the target task, the total target parameter including sub-target parameters associated with multiple second accounts, the multiple second accounts being accounts associated with the target task, the target task including a preset task time; obtaining live streaming-related data of the multiple second accounts within the preset task time of the target task; based on the live streaming-related data, determining the sub-target progress corresponding to the sub-target parameters associated with the multiple second accounts and the total target progress corresponding to the total target parameter; and based on the sub-target progress and the total target progress, determining progress analysis data of the target task.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a live streaming data analysis method and apparatus for operating promotional activities. Background Technology

[0002] Product promotional activities, especially large-scale promotions / mega-sales (such as Singles' Day), are the most crucial junctures in the operational work of e-commerce managers (also known as e-commerce staff). They enable the implementation of daily operational methodologies and the evaluation of operational effectiveness. Simultaneously, large-scale promotional activities are excellent opportunities for e-commerce teams to boost Gross Merchandise Volume (GMV). Overall resource allocation and the dedication of e-commerce staff are reflected during these events. Therefore, helping e-commerce staff achieve target GMV for large-scale promotions and further assisting merchants in achieving better performance during these events is a vital mission for any merchant's product operations.

[0003] However, at present, e-commerce staff have a relatively weak perception of merchants' performance in large-scale promotional activities. Merchants' behavior and the effects of the activities are lagging behind for e-commerce staff. Only after a period of time has passed since the event ended can the data analysis team draw a summary of the promotional activities, and its effectiveness will be greatly reduced. Summary of the Invention

[0004] This disclosure provides a live streaming data analysis method, live streaming data analysis device, electronic device, and storage medium for operating promotional activities, to at least solve the aforementioned problems.

[0005] According to a first aspect of the present disclosure, a live streaming data analysis method is provided, which may include: in response to a first account's target setting operation for a target task, obtaining a total target parameter set for the target task, the total target parameter including sub-target parameters associated with a plurality of second accounts, the plurality of second accounts being accounts associated with the target task, the target task including a preset task time; obtaining live streaming related data of the plurality of second accounts within the preset task time of the target task; based on the live streaming related data, determining sub-target progress corresponding to the sub-target parameters associated with the plurality of second accounts and a total target progress corresponding to the total target parameter; and determining progress analysis data of the target task based on the sub-target progress and the total target progress.

[0006] Optionally, in response to the first account's target setting operation for the target task, obtaining the total target parameters set for the target task may further include adjusting the sub-target parameters associated with the second account in response to receiving a correction request for the sub-target parameters associated with the second account.

[0007] Optionally, in response to the first account's target setting operation for the target task, after obtaining the total target parameters set for the target task, the method may further include: obtaining the live streaming plan data of the plurality of second accounts for the target task.

[0008] Optionally, obtaining the live streaming-related data of the plurality of second accounts within the preset task time of the target task may further include: obtaining the live streaming-related data of the target second account within the target parameter range within the preset task time based on the target parameter range, wherein the target parameter range is a reference range of the target parameters of the plurality of second accounts within a preset time period before the current time.

[0009] Optionally, determining the sub-target progress corresponding to the sub-target parameters associated with the plurality of second accounts and the total target progress corresponding to the total target parameters based on the live-streaming related data may further include: determining the statistical distribution data of the live-streaming related data of the target second account based on the live-streaming related data of the target second account within the preset task time; and determining the sub-target progress corresponding to the sub-target parameters associated with the target second account based on the live-streaming related data of the target second account and the statistical distribution data.

[0010] Optionally, after determining the progress analysis data of the target task based on the sub-target progress and the total target progress, the process may include: in response to the first account's target adjustment operation on the target task based on the progress analysis data, obtaining the adjusted total target parameter; and obtaining the total target progress corresponding to the adjusted total target parameter based on the live streaming related data of the multiple second accounts.

[0011] Optionally, after determining the progress analysis data of the target task based on the sub-target progress and the total target progress, the process may include: in response to a target adjustment operation by the first account on the sub-target parameters of a selected second account among the plurality of second accounts based on the progress analysis data, obtaining the adjusted sub-target parameters; and obtaining the sub-target progress corresponding to the adjusted sub-target parameters based on the live streaming related data of the selected second account.

[0012] Optionally, after determining the progress analysis data of the target task based on the sub-target progress and the total target progress, the method may further include: in response to the information sending operation of the first account, sending target task progress reminder information to the second account, wherein the target task progress reminder information is generated based on the progress analysis data.

[0013] Optionally, the live streaming related data may include at least one of the following: account display data of the second account during the preset task time of the target task; live streaming duration data of the second account during the preset task time of the target task; order data of the second account during the preset task time of the target task; and promotion data of the second account during the preset task time of the target task.

[0014] According to a second aspect of the present disclosure, a live streaming data analysis apparatus is provided, which may include: an acquisition module configured to, in response to a first account's target setting operation on a target task, acquire a total target parameter set for the target task, the total target parameter including sub-target parameters associated with a plurality of second accounts, the plurality of second accounts being accounts associated with the target task, the target task including a preset task time; acquire live streaming related data of the plurality of second accounts within the preset task time of the target task; and a determination module configured to, based on the live streaming related data, determine sub-target progress corresponding to the sub-target parameters associated with the plurality of second accounts and a total target progress corresponding to the total target parameter; and determine progress analysis data of the target task based on the sub-target progress and the total target progress.

[0015] Optionally, the acquisition module may be configured to: adjust the sub-target parameters associated with the second account in response to receiving a correction request for the sub-target parameters associated with the second account.

[0016] Optionally, the acquisition module can be configured to acquire live streaming plan data of the plurality of second accounts for the target task.

[0017] Optionally, the acquisition module can be configured to: acquire live streaming related data of the target second account within the target parameter range within the preset task time, based on the target parameter range, wherein the target parameter range is a reference range of the target parameters of the multiple second accounts within a preset time period before the current time.

[0018] Optionally, the determining module can be configured to: determine the statistical distribution data of the live streaming-related data of the target second account based on the live streaming-related data of the target second account within the preset task time; and determine the sub-target progress corresponding to the sub-target parameters associated with the target second account based on the live streaming-related data of the target second account and the statistical distribution data.

[0019] Optionally, the acquisition module is configured to acquire the adjusted total target parameter in response to the first account's target adjustment operation on the target task based on the progress analysis data; the determination module may be configured to acquire the total target progress corresponding to the adjusted total target parameter based on the live streaming related data of the multiple second accounts.

[0020] Optionally, the acquisition module can be configured to acquire the adjusted sub-target parameters in response to a target adjustment operation of the first account on the sub-target parameters of a selected second account among the plurality of second accounts based on the progress analysis data; the determination module can be configured to acquire the sub-target progress corresponding to the adjusted sub-target parameters based on the live streaming related data of the selected second account.

[0021] Optionally, the live data analysis device may further include a sending module configured to: in response to the information sending operation of the first account, send target task progress reminder information to the second account, wherein the target task progress reminder information is generated based on the progress analysis data.

[0022] Optionally, the live streaming related data may include at least one of the following: account display data of the second account during the preset task time of the target task; live streaming duration data of the second account during the preset task time of the target task; order data of the second account during the preset task time of the target task; and promotion data of the second account during the preset task time of the target task.

[0023] According to a third aspect of the present disclosure, an electronic device is provided, the electronic device may include: at least one processor; at least one memory storing computer-executable instructions, wherein the computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform the live data analysis method as described above.

[0024] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided that stores instructions which, when executed by at least one processor, cause the at least one processor to perform the live data analysis method as described above.

[0025] According to a fifth aspect of the present disclosure, a computer program product is provided, wherein instructions in the computer program product are executed by at least one processor in an electronic device to perform the live data analysis method as described above.

[0026] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects:

[0027] By setting target tasks through the first account and analyzing and diagnosing task progress based on the live streaming data from the second account, data analysis capabilities can be provided to the e-commerce staff (first account) for the merchants they are responsible for (second account), improving the completion rate of target tasks by both the first and second accounts during the target task period. Furthermore, by analyzing the task progress of the second account during the target task period, problems in the second account's task completion process can be identified, allowing the first account to promptly detect any anomalies.

[0028] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0029] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0030] Figure 1 This is a flowchart illustrating a live data analysis method according to an embodiment of the present disclosure;

[0031] Figure 2 This is a flowchart of a live data analysis method according to an embodiment of the present disclosure;

[0032] Figure 3 This is a schematic diagram of a first user interface according to an embodiment of the present disclosure;

[0033] Figure 4 This is a schematic diagram of a second user interface according to an embodiment of the present disclosure;

[0034] Figure 5 This is a schematic diagram of a third user interface according to an embodiment of the present disclosure;

[0035] Figure 6 This is a block diagram of a live data analysis apparatus according to an embodiment of the present disclosure;

[0036] Figure 7 This is a schematic diagram of the structure of a live data analysis device according to an embodiment of the present disclosure;

[0037] Figure 8 This is a block diagram of an electronic device according to an embodiment of the present disclosure.

[0038] Throughout the accompanying drawings, it should be noted that the same reference numerals are used to denote the same or similar elements, features, and structures. Detailed Implementation

[0039] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0040] The following description, provided with reference to the accompanying drawings, is intended to aid in a full understanding of embodiments of the present disclosure as defined by the claims and their equivalents. Various specific details are included to aid understanding, but these details are to be considered exemplary only. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Furthermore, for clarity and brevity, descriptions of well-known functions and structures are omitted.

[0041] The terms and words used in the following description and claims are not limited to their literal meaning, but are intended solely by the inventors to achieve a clear and consistent understanding of this disclosure. Therefore, it will be apparent to those skilled in the art that the following description of various embodiments of this disclosure is provided for illustrative purposes only and is not intended to limit the purpose of this disclosure as defined by the claims and their equivalents.

[0042] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0043] In related technologies, for example, some operational products, while possessing the product form of merchant operation tools and industry data analysis, only provide data without diagnostics or operational actions. E-commerce staff need to process this data further and complete operational actions on other platforms. They also lack promotional activity targets and related progress data. Furthermore, because the data is industry-dimensional, it cannot be broken down to the e-commerce staff and merchant dimensions. Other operational products can present merchant registration information based on the merchants managed by the e-commerce staff, but the merchant registration data is not real-time, making it impossible to track promotional activity targets. They lack information on promotional activity targets, real-time data, and related diagnostics; they also cannot assess merchants' promotional inventory. Additionally, in some large-scale promotional activities on shopping platforms, merchant live streaming is not a decisive factor in GMV, so e-commerce staff do not specifically analyze live streaming or monetization; at most, they manually break down individual GMV targets for each merchant based on Key Performance Indicators (KPIs). However, for some e-commerce companies, analyzing live streaming and target GMV is a crucial step. Therefore, there is a need for more accurate, real-time, and tailored operational tools that are closer to the work scenarios of e-commerce staff to help them complete the preparation, follow-up, and review of promotional activities.

[0044] Based on this, this disclosure presents relevant data of the merchants under the responsibility of e-commerce staff to the key operational nodes of promotional activities, conducts merchant operation behavior based on the data, and combines the merchant's data in promotional activities with functions such as Chakra Live Calendar and group data analysis.

[0045] In the following, the methods and apparatus of this disclosure will be described in detail with reference to the accompanying drawings, according to various embodiments of this disclosure.

[0046] Figure 1 This is a flowchart illustrating a live data analysis method according to an embodiment of the present disclosure.

[0047] According to the live streaming data analysis method of this disclosure, e-commerce staff can manage merchants around the three stages of promotional activities (i.e., before the activity, during the activity, and after the activity). During the three different stages, merchants need to complete different tasks to do a good job in their business management. Correspondingly, e-commerce staff need to manage the merchants they are responsible for in these three stages.

[0048] Reference Figure 1Before a promotional activity, the e-commerce manager needs to plan the overall goals for the activity they are responsible for. This includes reviewing the merchants under their supervision, assessing their target performance, registration status, and live-streaming plans to ensure that both the merchants and the e-commerce manager can achieve their respective goals. Here, "goal" can refer to GMV (Gross Merchandise Volume). In this disclosure, "overall target GMV" refers to the overall GMV target set by the e-commerce manager for the selected promotional activity, while "individual target GMV" refers to the GMV of each merchant under the e-commerce manager's supervision during the promotional activity.

[0049] exist Figure 1 In this system, e-commerce staff can set overall goals for promotional activities (such as overall target GMV), and then set individual goals for each merchant they are responsible for (such as individual target GMV). Merchants can view and adjust their individual target GMV, and e-commerce staff can view the GMV set by the merchants. Merchants can register for promotional activities to determine whether they will participate, and e-commerce staff can view the merchants' registration status. Merchants can set up live streaming plans for promotional activities to determine whether to conduct live promotions during the promotion.

[0050] During promotional activities, e-commerce staff need to monitor the overall progress towards achieving targets and be able to break down problems encountered during the process. This includes issues such as the overall progress of individual merchants, problems with live streaming, and production capacity issues during live streams. This process involves analyzing and diagnosing from a holistic perspective down to the details. Simultaneously, e-commerce staff must be able to promptly detect any anomalies.

[0051] exist Figure 1 In the process, when merchants start live streaming and / or sales, e-commerce staff can track target progress and live streaming progress, and provide diagnostic suggestions to merchants based on the tracking data.

[0052] After a promotional campaign ends, the e-commerce team needs to conduct a post-campaign review and summary of the campaign's actual performance. This review should include, for example, whether the goals were achieved, what the weak points were during the campaign, what the reasons were if the goals were not achieved, and whether the campaign could have been done better if it had been achieved.

[0053] According to embodiments of this disclosure, different stages of a promotional activity are presented to e-commerce staff through different user interfaces. Each user interface integrates relevant merchant data at its corresponding activity stage, allowing e-commerce staff to view and adjust the merchant data under their responsibility in real time and provide corresponding operational actions to the merchants. The following will refer to... Figures 2 to 5 Describe in detail how to provide e-commerce staff with analytical data and corresponding operational support for the merchants they are responsible for.

[0054] Figure 2This is a flowchart of a live streaming data analysis method according to an embodiment of the present disclosure. The live streaming data analysis method according to the present disclosure can be applied to scenarios involving product promotion activities on a specific date or holiday, or promotional activities for a certain type of product.

[0055] The live streaming data analysis method disclosed herein can be executed by any electronic device. The electronic device can be the user's terminal, for example, the terminal used by an e-commerce operator to manage data when running promotional activities. The electronic device can be at least one of a smartphone, tablet, laptop, and desktop computer. The electronic device may have a target application installed for managing and analyzing the data.

[0056] Furthermore, the live streaming data analysis method disclosed herein can be applied to existing operational products, either as a part or as a module embedded therein.

[0057] Reference Figure 2 In step S201, in response to the first account's target setting operation for the target task, the total target parameters set for the target task are obtained. Here, the total target parameters may include sub-target parameters associated with multiple second accounts, which are accounts associated with the target task, and the target task may include a preset task time.

[0058] As an example, for a specific promotional campaign, an e-commerce specialist (i.e., the first account) can set a total target GMV for the campaign and corresponding sub-target GMVs for each merchant under their responsibility (i.e., the second account). Here, each merchant can include those participating in the promotion and those not participating.

[0059] Furthermore, in response to receiving a correction request for sub-target parameters associated with the second account, the sub-target parameters associated with the second account can be adjusted. For example, the first account can adjust the sub-target parameters of the second account based on the GMV set by the second account for the target task. Alternatively, the first account can also send the sub-target parameters it sets for the second account to the second account as reference data for the second account to adjust the target for the target task.

[0060] In response to the first account's target setting operation for the target task, after obtaining the total target parameters set for the target task, it can also obtain the live broadcast plan data and registration status of multiple second accounts for the target task.

[0061] In this disclosure, the first account can set the overall target parameters and sub-target parameters through the user interface, and can also view the second account's registration status for the target task and live broadcast plan data through the user interface.

[0062] Figure 3The user interface (hereinafter referred to as the first user interface) is shown for planning the overall objectives of the target task before the target task begins.

[0063] In addition to including the name of the target task (such as a promotional activity), the current activity status, and the start time of the activity, the first user interface may also include at least one of the following: a first area for setting the total transaction amount of the target goods for the target task, a second area for displaying the registration status of merchants for the target task, and a third area for displaying the live streaming plan of merchants for the target task.

[0064] The first area of ​​the first user interface may include at least one of the following: an interface for setting the overall target transaction amount for the target task; the number of merchants for whom the transaction amount has been set for the target task and the number of merchants for whom no transaction amount has been set; and the number of merchants for whom an individual target transaction amount has been set for each merchant and the number of merchants for whom no individual target transaction amount has been set for each merchant.

[0065] The second area of ​​the first user interface may include at least one of the following: the percentage of merchants who have registered for the target task, the number of registered merchants and the number of merchants who have not registered, and the number of registered merchants who have passed the review and the number of merchants who have not passed the review.

[0066] The third area of ​​the first user interface may include at least one of the following: the number of merchants who have set up live streaming plans for the target task, the number of merchants who have not set up live streaming plans, the number of merchants who have set up inventory plans and the number of merchants who have not set up inventory plans among those who have set up live streaming plans, and the total transaction amount of goods inventoryed by merchants who have set up inventory plans.

[0067] Reference Figure 3 The first user interface can be used by e-commerce staff to plan the overall goals of a promotional activity before it begins.

[0068] Before a promotional campaign begins, the e-commerce manager needs to set an overall GMV target for the campaign and also review the target GMV of the merchants under their responsibility during the campaign. When the number of merchants under the manager's responsibility is large and their performance varies significantly, the manager may primarily focus on reviewing the target performance of the top merchants who contribute the most to their sales. This target will be communicated to the merchants to guide them in setting their own goals.

[0069] Reference Figure 3 The first user interface 300 may include the name of the selected promotional activity (i.e. the target task), the current status of the selected promotional activity, the start time of the promotional activity, and a first area 301, a second area 302, and a third area 303.

[0070] In the first area 301, the overall target GMV set by the e-commerce administrator for the selected promotional activity can be displayed, along with modification markers for adjusting the overall target GMV. Furthermore, the first area 301 can display the sum of individual target GMVs set by the e-commerce administrator for the merchants under their responsibility, as well as the sum of individual GMVs set by the merchants themselves. It can also display the number of merchants for which the e-commerce administrator set individual target GMVs, the number of merchants for which the e-commerce administrator did not set individual target GMVs, the number of merchants for which they set GMVs themselves, and the number of merchants for which they did not set GMVs themselves.

[0071] For example, in the first area 301, the portion where e-commerce staff set targets for merchants may include the number of merchants who have already set targets, the number of merchants who have not yet set targets, and the total target GMV of merchants for whom targets have been set. The portion where merchants set targets for themselves may include the number of merchants who have already set targets, the number of merchants who have not yet set targets, and the total GMV set by merchants for whom targets have been set. However, the way the data in the first area 301 can be displayed is merely exemplary, and this disclosure is not limited thereto.

[0072] In the second area 302, a chart showing the registration rate percentage, the number of registered merchants, the number of non-registered merchants, the number of merchants passing the first review, and the number of merchants passing the second review can be displayed. The registration rate represents the ratio between the number of registered merchants and the total number of merchants managed by the e-commerce staff member. The number of registered merchants represents the number of merchants who have entered the registration process for the selected promotional activity, and the number of non-registered merchants represents the number of merchants who have not entered the registration process for the selected promotional activity. However, the way the data can be displayed in the second area 302 is merely exemplary, and this disclosure is not limited thereto.

[0073] In the third area 303, data regarding the merchant's live streaming plan for the selected promotional activity can be displayed. For example, a live streaming plan may refer to the situation where a merchant has set up an "event live streaming plan" associated with the promotional activity. Statistics may include the number of merchants who have not set a plan and the number of merchants who have set a plan. Furthermore, in the third area 303, for merchants who have set up a live streaming plan for the promotional activity, statistics can be provided on the merchants who have also set up inventory plans, along with the total inventory GMV, the number of merchants who have set up plans, and the number of merchants who have not. However, the way the data can be displayed in the third area 303 is merely exemplary, and this disclosure is not limited thereto.

[0074] By obtaining information about merchants' live-streaming plans for promotional activities, e-commerce staff can understand the inventory status of merchants who have set up live-streaming plans, thereby enabling them to more accurately plan the overall goals of promotional activities and the sub-goals of merchants.

[0075] In the first user interface 300, the e-commerce representative can set their overall target GMV for the selected promotional activity in the first area 301. When clicking the edit button, the e-commerce representative can enter the desired GMV value, with the unit set to yuan, ten thousand yuan, or one hundred million yuan for the representative to choose from. The completed display does not require unit formatting. The e-commerce representative can modify their overall target before the promotional activity begins.

[0076] In addition, when a certain number of merchants is selected in the first user interface, a list of merchants corresponding to that number can be displayed either by sliding out from the side of the first user interface or by a pop-up window.

[0077] For example, regarding the number of merchants displayed in the first user interface 300, clicking on a merchant number will cause a list of merchants corresponding to that number to slide out from the left side of the first user interface 300, or the corresponding merchant list to be displayed in a pop-up window. Alternatively, the merchant list can be made to disappear by clicking the close icon on the window displaying the merchant list, or by clicking on a certain area of ​​the user interface to make the merchant list disappear by sliding in. However, the above examples are merely illustrative, and this disclosure is not limited thereto.

[0078] After clicking on a merchant in the first user interface 300, a merchant list can be displayed, including at least one of the following: a filter for viewing merchants in layers, an operation for setting the total transaction amount of a single target product for a merchant (i.e., a sub-target parameter), a sending item for sending the set total transaction amount of a single target product to the merchant, a modification item for modifying merchant tags, and an export item for exporting the merchant list.

[0079] For each merchant in the merchant list, the following fields can be displayed: "Industry", "Promotion Registration Status: Retrieved from the event registration status enumeration value", "Promotion GMV Target (Set by the platform administrator)", "Promotion GMV Target (Set by the merchant)", and "Whether to set a live broadcast plan for the promotion event: Yes / No".

[0080] Filter options can include fixed fields such as: Merchant ID / Nickname, Industry, Promotion Registration Status, Whether a Target is Set (Set by Server Manager), Whether a Target is Set (Set by Merchant), Promotion GMV Target (Set by Server Manager), Promotion GMV Target (Set by Merchant), Whether a Promotion Livestream Plan is Set, etc. In addition, filter options can also include dynamic fields. Dynamic fields are unconfigured by default and can be configured through "Indicator Configuration" to be used in conjunction with fixed fields for filtering.

[0081] After clicking the corresponding filter option, you can use fixed fields and configured dynamic fields for further filtering.

[0082] After filtering merchants, you can set the GMV for a single merchant or set the GMV for multiple merchants in batches.

[0083] As an example, e-commerce staff can set targets for merchants in two ways: Individual merchant setting: Click "Edit" in the "Mega Promotion GMV Target (Staff)" field in the list to edit the target value for a single merchant. After clicking "Edit," a pop-up window will appear where you can enter the suggested target value you want to notify the merchant, choosing units such as yuan, ten thousand yuan, or one hundred million yuan. Batch upload of merchant targets: Click the "Batch Upload Mega Promotion Targets" button (e.g., located in an area of ​​the window displaying the merchant list) to upload pre-compiled merchant targets via file. Uploaded merchants must be within the scope of the e-commerce staff's responsibility. If a merchant is not under their management, targets cannot be set, and the staff will be reminded. For example, a voice or text message notification may be used to indicate whether the upload was successful or failed. You can also view merchants with problems (e.g., file downloads).

[0084] After setting goals for merchants, the goals can be notified to the merchants. In the goal setting, it can be expressed in the form of "Platform suggested goals for this promotion".

[0085] For example, the field "Promotion GMV Target (Set by E-commerce Staff)" in the merchant list can be formatted with units of yuan, ten thousand yuan, or one hundred million yuan. You can click "Edit" to edit the individual GMV target set by the e-commerce staff for each merchant. Similarly, for "Promotion GMV Target (Set by E-commerce Staff)," you can format with units of yuan, ten thousand yuan, or one hundred million yuan. You can click "Edit" to edit the GMV set by the merchant themselves.

[0086] By having the first account plan the target task and control its progress, the completion rate of the target task by both the first and second accounts can be improved.

[0087] In step S202, live streaming-related data of multiple second accounts within the preset task time of the target task is obtained. Here, the live streaming-related data may include account display data of the second account within the preset task time of the target task, live streaming duration data of the second account within the preset task time of the target task, order data of the second account within the preset task time of the target task, and promotion data of the second account within the preset task time of the target task.

[0088] Account-related data may include page views (PV) from following pages, page views from discovery pages, paid promotion exposure PV, organic traffic exposure PV, platform reward traffic PV during major promotions, and the number of short video works during major promotions.

[0089] Data related to live streaming duration may include live streaming duration (h) during the promotion period, average live streaming duration per session (h), average ACU during the promotion period, average viewing time per user (s), average viewing time per user session (s), and the percentage of viewing time guided by the follow page.

[0090] Order-related data may include total GMV during the promotion period, GMV after risk control during the promotion period, total number of orders during the promotion period, cumulative number of people placing orders during the promotion period, cumulative number of people making payments during the promotion period, and UV value of the live broadcast room.

[0091] Promotional data may include marketing expenses during the promotion period, fan promotion expenses during the promotion period, small store promotion expenses during the promotion period, marketing ROI during the promotion period, and marketing expense ratio during the promotion period. However, the above dimensions and live streaming examples are merely illustrative, and this disclosure is not limited thereto.

[0092] For each type of data, the corresponding statistical distribution data can be determined based on the live streaming data. For example, the average, maximum, minimum, median, 80th percentile, and 20th percentile of the data can be used as segmentation markers to divide the number of merchants belonging to different value ranges. For example, the number of merchants with values ​​below the average, below the median, above the 80th percentile, and below the 20th percentile.

[0093] Each data point can be visualized graphically in the user interface to represent the meaning of its respective numerical range.

[0094] In addition, based on the target parameter range, the live streaming data of the target second account within the target parameter range during the preset task time can be obtained. The target parameter range represents the reference range of the target parameters of multiple second accounts within a preset time period before the current time.

[0095] Because data varies significantly across different merchant sizes, merchants are filtered according to different target parameter ranges. This allows e-commerce staff to diagnose the merchants they are responsible for based on different strata. Multiple strata can be selected, and once selected, live-streaming related data within that range can be analyzed. For example, merchants can be filtered by stratification such as "GMV over 5 million in the past 30 days", "GMV 3-5 million in the past 30 days", "GMV 1-3 million in the past 30 days", "GMV 500,000-1 million in the past 30 days", "GMV 50,000-500,000 in the past 30 days", and "GMV 0-50,000 in the past 30 days" to select those that meet the desired analysis. However, the above analysis example is merely illustrative, and this disclosure is not limited to it.

[0096] By filtering merchant and live-streaming related data across different ranges based on target parameter ranges, e-commerce staff can more effectively analyze the performance of each merchant during promotional activities.

[0097] In step S203, based on the acquired live-streaming related data, the progress of sub-targets associated with multiple second accounts and the progress of the overall target associated with the overall target parameter are determined. For example, the progress of achieving the overall target GMV can be reflected by the proportion of each merchant's real-time accumulated GMV in the promotional activity to the overall target GMV. Similarly, the progress of achieving a single target GMV can be reflected by the proportion of a single merchant's real-time accumulated GMV in the promotional activity to that merchant's single target GMV.

[0098] In addition, the live streaming data of the target second account within the target parameter range during the preset task time can be obtained according to the target parameter range. Then, based on the live streaming data of the target second account during the preset task time, the statistical distribution data of the live streaming data of the target second account can be determined. Based on the live streaming data and statistical distribution data of the target second account, the sub-target progress corresponding to the sub-target parameters associated with the target second account can be determined.

[0099] By visualizing the statistical distribution data of merchants, e-commerce staff can more intuitively view the distribution of merchants under various data / indicators, enabling them to better control the performance of merchants in promotional activities.

[0100] In step S204, the progress analysis data of the target task is determined based on the sub-target progress and the overall target progress.

[0101] In response to the first account's adjustment of the target task based on progress analysis data, the adjusted total target parameters can be obtained, and the total target progress corresponding to the adjusted total target parameters can be obtained based on the live broadcast-related data of multiple second accounts.

[0102] In response to the first account's target adjustment operation on the sub-target parameters of a selected second account among multiple second accounts based on progress analysis data, the adjusted sub-target parameters can be obtained, and the sub-target progress corresponding to the adjusted sub-target parameters can be obtained based on the live broadcast-related data of the selected second account.

[0103] In this disclosure, the first account can adjust the overall target progress and sub-target progress through the user interface, and view live streaming related data through the user interface.

[0104] Figure 4 The user interface (hereinafter referred to as the second user interface) used to monitor the overall progress of the target task during the task's execution is shown.

[0105] The second user interface may include a fourth area for adjusting the progress of the overall target transaction volume of the target task, a fifth area for displaying the merchants' registration status for the target task and statistics on the transaction volume, and a sixth area for diagnosing merchant data.

[0106] The fourth area of ​​the second user interface may include at least one of the following: an interface for adjusting the overall target commodity transaction amount of the target task, information about the currently accumulated commodity transaction amount, and information about the current progress of the overall target commodity transaction amount.

[0107] The fifth area of ​​the second user interface may include at least one of the following: the number of merchants who have successfully registered, the number of merchants who have not registered, the number of merchants who have set a total transaction amount for the target task and the number of merchants who have not set a total transaction amount for the target task, the number of merchants who have set a single target transaction amount for a merchant and the number of merchants who have not set a single target transaction amount for a merchant, the number of merchants lagging behind the overall target transaction amount completion progress, the number of merchants lagging behind the average merchant transaction amount completion progress, the number of merchants who have completed a single target transaction amount, and the number of merchants who have not completed a single target transaction amount.

[0108] In the sixth area of ​​the second user interface, relevant live broadcast data and statistical distribution data can be displayed, and each data can be presented in a visual graphical format for each numerical range.

[0109] The second user interface can be used by e-commerce staff to monitor the progress of a promotional campaign's overall objectives during its execution. For example, while a promotion is underway, the e-commerce staff needs to constantly monitor the progress of the objectives, identify problems with merchants, and obtain methods to improve the achievement of the objectives. This process requires providing the e-commerce staff with relevant statistical data and diagnostic methods to assist them in managing merchants during the promotional campaign.

[0110] Reference Figure 4 The second user interface 400 may include the name of the selected promotion, the current status of the selected promotion, the start time of the promotion, and the fourth area 401, the fifth area 402, and the sixth area 403.

[0111] In Zone 401, the overall target GMV set by the e-commerce manager can be displayed, along with modification markers for adjusting the overall target GMV. Additionally, the current real-time accumulated GMV can be displayed, which refers to the total GMV of all merchants under the e-commerce manager's responsibility during the selected promotional period. Furthermore, the progress towards achieving the overall target GMV can be shown, for example, by using the percentage of real-time accumulated GMV to reflect the progress towards achieving the overall target GMV.

[0112] This percentage will change as cumulative GMV grows and the overall target GMV is revised. Different completion percentage ranges can be displayed using different colors. For example, if the percentage is ≥100%, it can be represented by green; if the percentage is ≥80% and <100%, it can be represented by yellow; if the percentage is ≥50% and <80%, it can be represented by orange; if the percentage is ≥20% and <50%, it can be represented by light red; and if the percentage is <20%, it can be represented by dark red. The above examples are merely illustrative, and this disclosure is not limited thereto.

[0113] In Zone 5, 402, the following statistics can be primarily presented: number of merchants who successfully registered (number of merchants approved), number of merchants who did not register (number of merchants in other situations), number of merchants with targets set by e-commerce staff, number of merchants with targets set by the merchants themselves, number of merchants lagging behind the overall GMV target set by e-commerce staff (i.e., the result of comparing the merchant's cumulative GMV during the promotional period / the individual target GMV set by the e-commerce staff with the overall target GMV target set by the e-commerce staff), number of merchants lagging behind the average target GMV target (i.e., the result of comparing the merchant's cumulative GMV during the promotional period / the individual target GMV set by the e-commerce staff with the average (referring to the average ratio of each merchant's cumulative GMV during the promotional period / the corresponding individual target GMV set by the e-commerce staff), number of merchants who have achieved their GMV targets, and number of merchants who have not achieved their GMV targets. However, the above examples are merely illustrative, and this disclosure is not limited thereto.

[0114] Because data varies significantly across different merchant sizes, a tiered filter box can be provided in Zone 6 (403) for e-commerce staff to diagnose the merchants they are responsible for based on different tiers. Multiple tiers can be selected, and the analysis below will only be performed on merchants within that range. For example, merchants can be filtered by tiers such as "GMV over 5 million in the last 30 days," "GMV 3-5 million in the last 30 days," "GMV 1-3 million in the last 30 days," "GMV 500,000-1 million in the last 30 days," "GMV 50,000-500,000 in the last 30 days," and "GMV 0-50,000 in the last 30 days" to select those that meet the desired analysis criteria. However, the above analysis example is merely illustrative, and this disclosure is not limited thereto.

[0115] In Zone 6, 403, the selected merchants can be analyzed based on different live streaming-related data.

[0116] In Zone 6, section 403, the number of merchants is shown in the "Traffic" dimension (i.e., account display-related data) for the following categories: "Follow-up Page PV," "Paid Promotion Traffic PV," "Number of Short Videos During Major Promotions," and "Organic Traffic PV." However, Figure 4The presentation format and data types shown are merely illustrative and this disclosure is not limited thereto.

[0117] In addition, when a certain number of merchants is selected in the second user interface, a list of merchants corresponding to that number can be displayed either by sliding out from the side of the second user interface or as a pop-up window.

[0118] For example, regarding the number of merchants displayed in the second user interface 400, clicking on a merchant number will cause a list of merchants corresponding to that number to slide out from the left side of the second user interface 400, or the list of merchants will be displayed in a pop-up window. Alternatively, the merchant list can be made to disappear by clicking the close icon on the window displaying the merchant list, or by clicking on a certain area of ​​the user interface to make the merchant list disappear by sliding in. However, the above examples are merely illustrative, and this disclosure is not limited thereto.

[0119] After clicking on a merchant in the second user interface 400, a merchant list can be displayed, including at least one of the following: a filter for viewing merchants in layers, an operation for setting the total transaction amount of a single target product for a merchant (i.e., a sub-target parameter), a send item for sending the set total transaction amount of a single target product to the merchant, a modification item for modifying merchant tags, and an export item for exporting the merchant list.

[0120] For each merchant in the merchant list, the following fields can be displayed: "Industry", "Promotion Registration Status: Retrieved from the event registration status enumeration value", "Promotion GMV Target (Set by the platform administrator)", "Promotion GMV Target (Set by the merchant)", and "Whether to set a live broadcast plan for the promotion event: Yes / No".

[0121] Filter options can include fixed fields such as: Merchant ID / Nickname, Industry, Promotion Registration Status, Whether a Target is Set (Set by Server Manager), Whether a Target is Set (Set by Merchant), Promotion GMV Target (Set by Server Manager), Promotion GMV Target (Set by Merchant), Whether a Promotion Livestream Plan is Set, etc. In addition, filter options can also include dynamic fields. Dynamic fields are unconfigured by default and can be configured through "Indicator Configuration" to be used in conjunction with fixed fields for filtering.

[0122] After clicking the corresponding filter option, you can use fixed fields and configured dynamic fields for further filtering.

[0123] After selecting merchants, in response to the information sending operation of the first account, a target task progress reminder can be sent to the second account. This target task progress reminder is generated based on progress analysis data. For example, after generating target task progress reminders for each merchant based on progress analysis data, the e-commerce staff can send the corresponding reminders to each merchant, allowing them to understand their progress in achieving their promotional goals.

[0124] In addition, e-commerce staff can set the GMV for a single merchant individually or in batches for multiple merchants based on the current overall goal and the progress of each sub-goal. The set GMV can then be sent to the corresponding merchants to adjust their progress in the target tasks in a timely manner.

[0125] By analyzing the second account's task progress during the target task period, problems that exist in the second account during the completion of the target task can be identified, enabling the first account to detect abnormal situations in a timely manner.

[0126] After the target task is completed, the first account can review and summarize the overall achievement of the target task through the user interface.

[0127] Figure 5 This illustrates a user interface (hereinafter referred to as the third user interface) used to review and summarize the overall achievement of the target task after its completion.

[0128] The third user interface may include a seventh area for displaying the progress of the overall target transaction volume of the target task, an eighth area for displaying the registration status of merchants for the target task and statistical data on the transaction volume, and a ninth area for displaying merchant data.

[0129] After a promotional campaign ends, e-commerce staff can view relevant data about the campaign through a third-party user interface.

[0130] Reference Figure 5 The third user interface 500 may include the name of the selected promotion, the current status of the selected promotion, the start time of the promotion, and the seventh area 501, the eighth area 502, and the ninth area 503.

[0131] In Zone 7 (501), the overall target GMV set by the e-commerce manager can be displayed. Additionally, the real-time cumulative GMV can be shown. Furthermore, the progress towards achieving the overall target GMV can be displayed, for example, by showing the percentage of real-time cumulative GMV in the overall target GMV.

[0132] In Zone 8, 502, the following statistics can be primarily presented: number of merchants who successfully registered (number of merchants approved), number of merchants who did not register (number of merchants in other situations), number of merchants with targets set by e-commerce staff, number of merchants with targets set by the merchants themselves, number of merchants lagging behind the overall GMV target set by e-commerce staff (i.e., the result of comparing the merchant's cumulative GMV during the promotional period / the individual target GMV set by the e-commerce staff with the overall target GMV target set by the e-commerce staff), number of merchants lagging behind the average target GMV target (i.e., the result of comparing the merchant's cumulative GMV during the promotional period / the individual target GMV set by the e-commerce staff with the average (referring to the average ratio of each merchant's cumulative GMV during the promotional period / the corresponding individual target GMV set by the e-commerce staff), number of merchants who have achieved their GMV targets, and number of merchants who have not achieved their GMV targets. However, the above examples are merely illustrative, and this disclosure is not limited thereto.

[0133] Because data varies significantly across different merchant sizes, a tiered filter box can be provided in Zone 9 (503) for e-commerce staff to diagnose the merchants under their responsibility according to different tiers. Multiple tiers can be selected, and the analysis below will only be performed on merchants within that range. For example, merchants can be filtered by tiers such as "GMV over 5 million in the last 30 days," "GMV 3-5 million in the last 30 days," "GMV 1-3 million in the last 30 days," "GMV 500,000-1 million in the last 30 days," "GMV 50,000-500,000 in the last 30 days," and "GMV 0-50,000 in the last 30 days" to select those that meet the desired analysis. However, the above analysis example is merely illustrative, and this disclosure is not limited thereto.

[0134] In Zone 6, 403, the selected merchants can be analyzed based on different live-streaming related data.

[0135] The elements displayed in the third user interface are similar to those in the second user interface; please refer to the description of the second user interface above. In the third user interface, the e-commerce representative cannot modify the numbers displayed on the screen.

[0136] This disclosure makes it easier to review and summarize the actual performance of the second account during the target task, so as to further improve the behavior of the first and second accounts in future tasks.

[0137] As another example, in Figures 3 to 5The user interface shown can display corresponding user interfaces based on the current status of the selected target promotional activity, according to the first account's selection. Specifically, when the target promotional activity is currently in the pre-start stage, a first user interface for planning the overall goals of the target promotional activity can be displayed. When the target promotional activity is currently in progress, a second user interface for monitoring the progress of achieving the overall goals of the target promotional activity can be displayed. When the target promotional activity is currently in the post-end stage, a third user interface for reviewing and summarizing the achievement of the overall goals of the target promotional activity can be displayed.

[0138] Basic information about promotional activities can be obtained from the interface provided by the marketing campaign product, from which e-commerce staff can select a specific promotional activity. Furthermore, the default selected promotional activities can have a priority order. For example, currently ongoing promotions have a higher priority than the most recent future promotions, and the most recent future promotions have a higher priority than the most recent past promotions. That is, when there are ongoing promotions, the "ongoing" promotions are selected first; if there are no ongoing promotions, the first future promotion is selected first; and if there are no future promotions, the last past promotion is selected first.

[0139] In this disclosure, promotional activities are divided into three stages, which can also be viewed as three states of the promotional activity: "Activity Not Started," "Activity in Progress," and "Activity Ended." When the selected promotional activity is before the start of the activity, "Activity Not Started" can be displayed, along with a color indicator, such as blue; when the selected promotional activity is in progress, "Activity in Progress" can be displayed, along with a color indicator, such as green; when the selected promotional activity has ended, "Activity Ended" can be displayed, along with a color indicator, such as gray.

[0140] The operation of the user interface described above is merely exemplary, and this disclosure is not limited thereto.

[0141] According to embodiments of this disclosure, data analysis of the merchants under their responsibility can be provided to e-commerce staff from the perspective of key nodes in promotional activities, along with corresponding operational support. By combining the status of promotional activities with data analysis, e-commerce staff can quickly identify outstanding merchants and those that need improvement. Through data accumulation, e-commerce staff can review the results of historical promotional activities, thereby improving the overall target GMV of industry promotional activities, the GMV of merchants in promotional activities, and the degree to which e-commerce staff achieve the expected GMV in promotional activities.

[0142] Figure 6This is a block diagram of a live data analysis apparatus according to an embodiment of the present disclosure.

[0143] Reference Figure 6 The live streaming data analysis device 600 may include an acquisition module 601, a determination module 602, and a transmission module 603. Each module in the live streaming data analysis device 600 may be implemented by one or more modules, and the names of the corresponding modules may vary depending on the type of module. In various embodiments, some modules in the live streaming data analysis device 600 may be omitted, or additional modules may be included. Furthermore, modules / elements according to various embodiments of this disclosure may be combined to form a single entity, and thus perform the functions of the respective modules / elements equivalently before combination. Additionally, the live streaming data analysis device 600 may also include an input module (not shown) for receiving user input. Alternatively, the acquisition module 601 may have the function of receiving user input.

[0144] The acquisition module 601 can respond to the target setting operation of the first account for the target task and acquire the total target parameters set for the target task. The total target parameters may include sub-target parameters associated with multiple second accounts, which are accounts associated with the target task. The target task may include a preset task time.

[0145] The acquisition module 601 can acquire live streaming-related data from multiple second accounts within a preset task time of the target task. For example, the live streaming-related data may include at least one of the following: account display data of the second account within the preset task time of the target task; live streaming duration data of the second account within the preset task time of the target task; order data of the second account within the preset task time of the target task; and promotion data of the second account within the preset task time of the target task.

[0146] The determination module 602 can determine the progress of sub-targets corresponding to sub-target parameters associated with multiple second accounts and the progress of the total target corresponding to the total target parameter based on the acquired live streaming related data, and determine the progress analysis data of the target task based on the sub-target progress and the total target progress.

[0147] Optionally, the acquisition module 601 may adjust the sub-target parameters associated with the second account in response to receiving a correction request for the sub-target parameters associated with the second account.

[0148] Optionally, the acquisition module 601 may acquire live streaming plan data for a target task from multiple second accounts.

[0149] Optionally, the acquisition module 601 can acquire live streaming related data of the target second account within the target parameter range within a preset task time, based on the target parameter range. The target parameter range is a reference range of target parameters for multiple second accounts within a preset time period before the current time.

[0150] Optionally, the determining module 602 can determine the statistical distribution data of the live streaming data of the target second account based on the live streaming data of the target second account within the preset task time; and determine the sub-target progress corresponding to the sub-target parameters associated with the target second account based on the live streaming data and statistical distribution data of the target second account.

[0151] Optionally, the acquisition module 601 may respond to the target adjustment operation of the first account on the target task based on the progress analysis data, and acquire the adjusted total target parameter. The determination module 602 may acquire the total target progress corresponding to the adjusted total target parameter based on the live broadcast related data of multiple second accounts.

[0152] Optionally, the acquisition module 601 may respond to the first account's target adjustment operation on the sub-target parameters of a selected second account among multiple second accounts based on progress analysis data, and acquire the adjusted sub-target parameters. The determination module 602 may acquire the sub-target progress corresponding to the adjusted sub-target parameters based on the live broadcast related data of the selected second account.

[0153] The sending module 603 can respond to the information sending operation of the first account and send target task progress reminder information to the second account, wherein the target task progress reminder information is generated based on the progress analysis data.

[0154] The above has been based on Figures 3 to 5 The analysis of live stream data has been described in detail, so it will not be described again here.

[0155] Figure 7 This is a schematic diagram of the structure of a live data analysis device in the hardware operating environment of this disclosure embodiment.

[0156] like Figure 7As shown, the live data analysis device 700 may include: a processing component 701, a communication bus 702, a network interface 703, an input / output interface 704, a memory 705, and a power supply component 704. The communication bus 702 is used to enable communication between these components. The input / output interface 704 may include a video display (such as a liquid crystal display), a microphone and speaker, and a user interaction interface (such as a keyboard, mouse, touch input device, etc.). Optionally, the input / output interface 704 may also include standard wired interfaces and wireless interfaces. The network interface 703 may optionally include standard wired interfaces and wireless interfaces (such as a Wi-Fi interface). The memory 705 may be a high-speed random access memory or a stable non-volatile memory. The memory 705 may also optionally be a storage device independent of the aforementioned processing component 701.

[0157] Those skilled in the art will understand that Figure 7 The structure shown does not constitute a limitation on the live data analysis device 700, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0158] like Figure 7 As shown, the memory 705, which serves as a storage medium, may include an operating system (such as a MAC operating system), a data storage module, a network communication module, a user interface module, a live data analysis program, and a database.

[0159] exist Figure 7 In the live data analysis device 700 shown, the network interface 703 is mainly used for data communication with external electronic devices / terminals; the input / output interface 704 is mainly used for data interaction with users; the processing component 701 and the memory 705 in the live data analysis device 700 can be set in the live data analysis device 700. The live data analysis device 700 calls the live data analysis program, materials and various APIs provided by the operating system stored in the memory 705 through the processing component 701 to execute the live data analysis method provided in the embodiments of this disclosure.

[0160] Processing component 701 may include at least one processor, and memory 705 stores a set of computer-executable instructions. When the set of computer-executable instructions is executed by at least one processor, a live data analysis method according to embodiments of the present disclosure is performed. However, the above examples are merely exemplary, and the present disclosure is not limited thereto.

[0161] For example, the input / output interface 704 can be used to receive user input, which can be mouse input, touch input, hover input, etc.

[0162] Processing component 701 can adjust the corresponding merchant data based on user input.

[0163] As an example, the input / output interface 704 can be displayed as follows: Figures 3 to 5 The user interface shown allows users to quickly analyze data from merchants' promotional activities.

[0164] The processing component 701 can control the components included in the live data analysis device 700 by executing a program.

[0165] The live streaming data analysis device 700 can receive or output images via the input / output interface 704. For example, the live streaming data analysis device 700 can output a user interface via the input / output interface 704. The user can select a target promotional activity through the video editing interface, and the corresponding user interface will be displayed according to the selected target promotional activity. The user can also input corresponding values ​​through the user interface.

[0166] As an example, the live data analysis device 700 can be a PC, tablet, personal digital assistant, smartphone, or other device capable of executing the aforementioned set of instructions. Here, the live data analysis device 700 is not necessarily a single electronic device; it can be any collection of devices or circuits capable of executing the aforementioned instructions (or instruction sets) individually or in combination. The live data analysis device 700 can also be part of an integrated control system or system manager, or it can be configured to interface with a portable electronic device locally or remotely (e.g., via wireless transmission).

[0167] In the live data analysis device 700, the processing component 701 may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller, or a microprocessor. By way of example and not limitation, the processing component 701 may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.

[0168] The processing component 701 can execute instructions or code stored in memory, wherein memory 705 can also store data. Instructions and data can also be sent and received over a network via network interface 703, wherein network interface 703 can employ any known transport protocol.

[0169] The memory 705 can be integrated with the processing component 701, for example, by placing RAM or flash memory within an integrated circuit microprocessor. Alternatively, the memory 705 can include a separate device, such as an external disk drive, a storage array, or other storage device that can be used by any database system. The memory and processing component 701 can be operatively coupled, or can communicate with each other, for example, via I / O ports, network connections, etc., enabling the processing component 701 to read data stored in the memory 705.

[0170] According to embodiments of this disclosure, an electronic device may be provided. Figure 8 This is a block diagram of an electronic device according to an embodiment of the present disclosure. The electronic device 800 may include at least one memory 802 and at least one processor 801. The at least one memory 802 stores a set of computer-executable instructions. When the set of computer-executable instructions is executed by the at least one processor 801, a live data analysis method according to an embodiment of the present disclosure is performed.

[0171] Processor 801 may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller, or a microprocessor. By way of example and not limitation, processor 801 may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.

[0172] The memory 802, which serves as a storage medium, may include an operating system (e.g., a MAC operating system), a data storage module, a network communication module, a user interface module, a live data analysis program, and a database.

[0173] The memory 802 may be integrated with the processor 801; for example, RAM or flash memory may be arranged within an integrated circuit microprocessor. Alternatively, the memory 802 may include a separate device, such as an external disk drive, a storage array, or other storage device that can be used by any database system. The memory 802 and the processor 801 may be operatively coupled, or may communicate with each other, for example, via I / O ports, network connections, etc., enabling the processor 801 to read files stored in the memory 802.

[0174] In addition, the electronic device 800 may also include a video display (such as a liquid crystal display) and a user interaction interface (such as a keyboard, mouse, touch input device, etc.). All components of the electronic device 800 can be interconnected via a bus and / or network.

[0175] As will be understood by those skilled in the art, Figure 8 The structure shown does not constitute a limitation on the structure and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0176] According to embodiments of this disclosure, a computer-readable storage medium storing instructions may also be provided, wherein when the instructions are executed by at least one processor, they cause at least one processor to perform a live data analysis method according to this disclosure. Examples of computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disc storage, hard disk drive (HDD), solid-state drive (SSD), card storage (such as multimedia cards, secure digital (SD) cards, or ultra-fast digital (XD) cards), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state drive, and any other device configured to store a computer program and any associated data, data files, and data structures in a non-transitory manner and to provide the computer program and any associated data, data files, and data structures to a processor or computer so that the processor or computer can execute the computer program. The computer program in the aforementioned computer-readable storage medium can run in an environment deployed in computer devices such as clients, hosts, agent devices, servers, etc. Furthermore, in one example, the computer program and any associated data, data files, and data structures are distributed across a networked computer system, such that the computer program and any associated data, data files, and data structures are stored, accessed, and executed in a distributed manner through one or more processors or computers.

[0177] According to embodiments of this disclosure, a computer program product may also be provided, wherein the instructions in the computer program product can be executed by the processor of a computer device to complete the above-described live data analysis method.

[0178] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0179] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A live streaming data analysis method, characterized in that, include: In response to the first account's target setting operation for the target task, the total target parameters set for the target task are obtained. The total target parameters include sub-target parameters associated with multiple second accounts, which are accounts associated with the target task. The target task includes a preset task time. Obtain live streaming-related data of the multiple second accounts within the preset task time of the target task; Based on the live streaming data, determine the sub-target progress corresponding to the sub-target parameters associated with the multiple second accounts and the total target progress corresponding to the total target parameters; Based on the progress of the sub-targets and the progress of the overall target, the progress analysis data of the target task is determined; In response to the first account's target adjustment operation on the target task based on the progress analysis data, the adjusted total target parameters are obtained; Based on the live streaming-related data from the multiple second accounts, the overall target progress corresponding to the adjusted overall target parameters is obtained. The multiple second accounts are divided and displayed according to different parameter ranges, so that the multiple second accounts can be analyzed according to different layers. The parameter range is a reference range of the parameters of the multiple second accounts within a preset time period before the current time.

2. The live streaming data analysis method according to claim 1, characterized in that, In response to the first account's target setting operation for the target task, obtaining the total target parameters set for the target task further includes: In response to receiving a correction request for the sub-target parameter associated with the second account, the sub-target parameter associated with the second account is adjusted.

3. The live streaming data analysis method according to claim 1, characterized in that, In response to the first account's target setting operation for the target task, after obtaining the total target parameters set for the target task, the method further includes: Obtain the live streaming plan data of the multiple second accounts for the target task.

4. The live streaming data analysis method according to claim 1, characterized in that, Obtaining the live streaming-related data of the multiple second accounts within the preset task time of the target task further includes: Based on the target parameter range, the live streaming related data of the target second account within the target parameter range during the preset task time is obtained. The target parameter range is a reference range of the target parameters of the multiple second accounts within a preset time period before the current time.

5. The live streaming data analysis method according to claim 4, characterized in that, Based on the live streaming-related data, determining the sub-target progress corresponding to the sub-target parameters associated with the multiple second accounts and the total target progress corresponding to the total target parameters further includes: Based on the live streaming-related data of the target second account within the preset task time, determine the statistical distribution data of the live streaming-related data of the target second account; Based on the live streaming-related data of the target second account and the statistical distribution data, the progress of the sub-target corresponding to the sub-target parameters associated with the target second account is determined.

6. The live streaming data analysis method according to claim 1, characterized in that, After determining the progress analysis data for the target task based on the sub-target progress and the overall target progress, the process includes: In response to the first account's target adjustment operation on the sub-target parameters of a selected second account among the plurality of second accounts based on the progress analysis data, the adjusted sub-target parameters are obtained; Based on the live streaming-related data of the selected second account, obtain the sub-target progress corresponding to the adjusted sub-target parameters.

7. The live streaming data analysis method according to claim 1, characterized in that, After determining the progress analysis data of the target task based on the sub-target progress and the overall target progress, the process further includes: In response to the information sending operation of the first account, a target task progress reminder message is sent to the second account, the target task progress reminder message being generated based on the progress analysis data.

8. The live streaming data analysis method according to claim 1, characterized in that, The live streaming related data includes at least one of the following: The second account displays associated data within the preset task time of the target task; The second account's live streaming duration data within the preset task time of the target task; The second account's order association data within the preset task time of the target task; The second account's promotional data within the preset task time of the target task.

9. A live streaming data analysis device, characterized in that, include: The acquisition module is configured to, in response to a first account's target setting operation for a target task, acquire the total target parameters set for the target task, the total target parameters including sub-target parameters associated with multiple second accounts, the multiple second accounts being accounts associated with the target task, the target task including a preset task time; and acquire the live streaming related data of the multiple second accounts within the preset task time of the target task. The determination module is configured to determine, based on the live streaming related data, the sub-target progress corresponding to the sub-target parameters associated with the plurality of second accounts and the total target progress corresponding to the total target parameters; Based on the sub-target progress and the overall target progress, the progress analysis data for the target task is determined. The acquisition module is configured to acquire the adjusted total target parameter in response to a target adjustment operation of the first account based on the progress analysis data; the determination module is configured to acquire the total target progress corresponding to the adjusted total target parameter based on the live streaming related data of the multiple second accounts. The multiple second accounts are divided and displayed according to different parameter ranges, so that the multiple second accounts can be analyzed according to different layers. The parameter range is a reference range of the parameters of the multiple second accounts within a preset time period before the current time.

10. The live data analysis device according to claim 9, characterized in that, The acquisition module is configured as follows: In response to receiving a correction request for the sub-target parameter associated with the second account, the sub-target parameter associated with the second account is adjusted.

11. The live data analysis device according to claim 9, characterized in that, The acquisition module is configured to acquire live streaming plan data of the plurality of second accounts for the target task.

12. The live data analysis device according to claim 9, characterized in that, The acquisition module is configured as follows: Based on the target parameter range, the live streaming related data of the target second account within the target parameter range during the preset task time is obtained. The target parameter range is a reference range of the target parameters of the multiple second accounts within a preset time period before the current time.

13. The live data analysis device according to claim 12, characterized in that, The module is configured as follows: Based on the live streaming-related data of the target second account within the preset task time, determine the statistical distribution data of the live streaming-related data of the target second account; Based on the live streaming-related data of the target second account and the statistical distribution data, the progress of the sub-target corresponding to the sub-target parameters associated with the target second account is determined.

14. The live data analysis device according to claim 9, characterized in that, The acquisition module is configured to acquire the adjusted sub-target parameters in response to a target adjustment operation of the first account on the selected second account among the plurality of second accounts based on the progress analysis data; The determination module is configured to obtain the sub-target progress corresponding to the adjusted sub-target parameters based on the live streaming-related data of the selected second account.

15. The live data analysis device according to claim 9, characterized in that, It also includes a sending module, which is configured as follows: In response to the information sending operation of the first account, a target task progress reminder message is sent to the second account, the target task progress reminder message being generated based on the progress analysis data.

16. The live data analysis device according to claim 9, characterized in that, The live streaming related data includes at least one of the following: The second account displays associated data within the preset task time of the target task; The second account's live streaming duration data within the preset task time of the target task; The second account's order association data within the preset task time of the target task; The second account's promotional data within the preset task time of the target task.

17. An electronic device, characterized in that, include: At least one processor; At least one memory that stores computer-executable instructions. The computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform the live data analysis method as described in any one of claims 1 to 8.

18. A computer-readable storage medium for storing instructions, characterized in that, When the instruction is executed by at least one processor, it causes the at least one processor to perform the live data analysis method as described in any one of claims 1 to 8.

19. A computer program product, wherein instructions in the computer program product are executed by at least one processor in an electronic device to perform the live data analysis method as claimed in any one of claims 1 to 8.

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