Traffic data processing method and device, equipment and storage medium

Abstract

The invention discloses a traffic data processing method and device, equipment and a storage medium, and relates to the technical field of computers and Internet. The method comprises the following steps: acquiring flow data of a target service on at least one data collection point; processing the traffic data on the at least one data collection point location to obtain traffic indexes of a plurality of statistical dimensions; and performing account checking on the flow indexes of the plurality of statistical dimensions to obtain an account checking result. According to the method, account checking is carried out based on the flow indexes of the plurality of statistical dimensions, so that the obtained account checking result is more comprehensive and visual, and the optimization space of the target service can be exposed.

Description

Technical Field

[0001] The embodiments of the present application relate to computer technology and Internet technology, and in particular to a method, device, equipment and storage medium for processing traffic data. Background Art

[0002] With the development of Internet technology, online platforms monetize traffic through advertising, subscription services, and self-operated e-commerce businesses, and thus obtain corresponding revenue.

[0003] In related technologies, before a network platform monetizes traffic through advertising, subscription services, and self-operated e-commerce, it needs to invest certain costs to promote traffic monetization. For example, development costs, marketing promotion costs, operation and maintenance costs, etc. In related technologies, the cost and revenue of the target business are reconciled to optimize the business and increase the revenue of the target business.

[0004] In the related art, the method of reconciling the expenditure and income of the target business is relatively limited and single. Summary of the invention

[0005] The embodiment of the present application provides a method, device, equipment and storage medium for processing flow data. The technical solution provided by the embodiment of the present application is as follows:

[0006] According to one aspect of an embodiment of the present application, a method for processing flow data is provided, the method comprising:

[0007] Obtaining traffic data of a target service at at least one data collection point;

[0008] Processing the flow data at the at least one data collection point to obtain flow indicators in multiple statistical dimensions;

[0009] The flow indicators of the multiple statistical dimensions are reconciled to obtain a reconciliation result.

[0010] According to one aspect of an embodiment of the present application, a flow data processing device is provided, the device comprising:

[0011] A data acquisition module, used to acquire flow data of a target service at at least one data collection point;

[0012] A data processing module, used to process the flow data at the at least one data collection point to obtain flow indicators of multiple statistical dimensions;

[0013] The indicator reconciliation module is used to reconcile the traffic indicators of the multiple statistical dimensions to obtain a reconciliation result.

[0014] According to one aspect of an embodiment of the present application, a computer device is provided, which includes a processor and a memory, wherein a computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the above-mentioned method for processing traffic data.

[0015] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is loaded and executed by a processor to implement the above-mentioned method for processing traffic data.

[0016] According to one aspect of an embodiment of the present application, a computer program product is provided, wherein the computer program product comprises a computer program, and the computer program is loaded and executed by a processor to implement the above-mentioned method for processing traffic data.

[0017] The technical solution provided by the embodiments of the present application includes at least the following beneficial effects:

[0018] By collecting and processing the traffic data of the target business, and then reconciling the traffic indicators on multiple statistical dimensions, the reconciliation results are obtained. By reconciling the traffic indicators based on multiple statistical dimensions, the reconciliation results are more comprehensive and intuitive, which helps to expose the optimization space of the target business. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of an implementation environment of a solution provided by an embodiment of the present application;

[0020] Figure 2 This is a flowchart of the flow reconciliation system provided by an embodiment of the present application;

[0021] Figure 3 is a flow chart of a method for processing flow data provided by an embodiment of the present application;

[0022] Figure 4 It is a schematic diagram of operating system reconciliation provided by an embodiment of the present application;

[0023] Figure 5 It is a schematic diagram of the return on investment reconciliation provided by an embodiment of the present application;

[0024] Figure 6 It is a schematic diagram of revenue reconciliation provided by an embodiment of the present application;

[0025] Figure 7 is a schematic diagram of link funnels corresponding to different links provided by an embodiment of the present application;

[0026] Figure 8 is a block diagram of a flow data processing device provided by an embodiment of the present application;

[0027] Fig. 9 It is a structural block diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0029] Please refer to Figure 1 , which shows a schematic diagram of a solution implementation environment provided by an embodiment of the present application. The solution implementation environment can be implemented as a flow reconciliation system. The solution implementation environment may include: a reconciliation terminal device 10 and a reconciliation server 20.

[0030] The reconciliation terminal device 10 can be an electronic device such as a mobile phone, a tablet computer, a PC (Personal Computer), a wearable device, a VR (Virtual Reality) device, an AR (Augmented Reality) device, a vehicle-mounted device, etc., and this application does not limit this. The reconciliation terminal device 10 can run the client of the target application (such as the application of the traffic reconciliation system). The client of the target application is used to provide functions such as viewing, monitoring, and alarming of traffic indicators for multiple statistical dimensions. Optionally, the target application can be an application that needs to be downloaded and installed, or it can be in the form of a web page or a small program, and this application does not limit this.

[0031] The reconciliation server 20 is used to provide background services for the client of the target application running in the terminal device 10. In some embodiments, the background services provided by the reconciliation server 20 may include but are not limited to: obtaining traffic data, processing traffic data, storing configuration information, alarm notification, etc., and may also include other services, which are not limited in the embodiments of the present application.

[0032] Exemplarily, the reconciliation server 20 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN for short), as well as big data and artificial intelligence platforms, but is not limited to these.

[0033] For example, Figure 1As shown, the traffic reconciliation system may further include a database server 30. The database server 30 is used to provide functions such as storage, management, and query for traffic data.

[0034] The reconciliation terminal device 10 and the reconciliation server 20 can communicate with each other through a network. Optionally, both the reconciliation terminal device 10 and the reconciliation server 20 can communicate with the database server 30 through the network. The network can be a wired network or a wireless network.

[0035] Please refer to Figure 2 , which shows a flow chart of the operation of the traffic reconciliation system provided by an embodiment of the present application. Figure 2 The business terminal device 40 is used to run the client of the business application, and the business application is used to provide users with functions for operating the target business. The business server 50 is used to provide services for the client of the business application. The advertising server 60 is used to provide the business application with the function of acquiring and managing advertising resources. The traffic reconciliation system includes a reconciliation terminal device 10, a reconciliation server 20 and a database server 30. Among them, the traffic reconciliation system is used to process traffic data related to the target business, and provide users with functions such as comparison, alarm, and query of traffic indicators of different statistical dimensions.

[0036] Exemplarily, when the target service is an advertisement display service, a splash screen advertisement is displayed when the user opens the service application using the service terminal device 40. The service logic of the advertisement display service includes at least one of the following service nodes: the service terminal device 40 sends an advertisement request to the service server 50 and the advertisement server 60, the service server 50 receives and responds to the advertisement request, the advertisement server 60 receives and responds to the advertisement request, the service server 50 sends at least one first candidate advertisement to the service terminal device 40, the advertisement server 60 sends at least one second candidate advertisement to the service terminal device 40, the service terminal device 40 receives at least one first candidate advertisement, the service terminal device 40 receives at least one second candidate advertisement, the service terminal device 40 determines the target advertisement from at least one first candidate advertisement and at least one candidate second advertisement, the service terminal device 40 pulls the advertisement resource corresponding to the target advertisement, and the service terminal device 40 displays the target advertisement. The reconciliation server 20 in the traffic reconciliation system obtains the traffic data at at least one data collection point for the above-mentioned advertisement display service, and after processing and reconciling the traffic data, displays the reconciliation result on the reconciliation terminal device 10.

[0037] Please refer to Figure 3 , which shows a flow chart of a method for processing flow data provided by an embodiment of the present application. The execution subject of each step of the method may be a computer device, for example, the computer device may be Figure 1The reconciliation terminal device 10 or the reconciliation server 20 in the solution implementation environment shown. The method may include at least one of the following steps (310-330):

[0038] Step 310: Obtain traffic data of a target service at at least one data collection point.

[0039] The target business refers to the core business goals or key tasks that the business platform needs to achieve during the operation process. For example, the target business includes at least one of the following: advertising display business, service subscription business, event business, product sales business, logistics management business, live broadcast business, etc., and may also include other businesses, which are not limited in the embodiments of the present application. Among them, the advertising display business refers to the business process in which the platform obtains revenue by displaying advertisements to users. The service subscription business refers to the business process in which users pay subscription fees to obtain specified services or content. The event business refers to the business process in which the platform attracts users to participate by organizing online or offline activities. The product sales business refers to the business process of providing users with various types of products and completing transactions. The logistics management business refers to the business process of delivering products to the location specified by the user. Optionally, the business platform can be an enterprise or a business application developed by an enterprise, which is not limited in the embodiments of the present application.

[0040] Data collection points refer to specific locations or nodes used to collect, store and analyze traffic data. Optionally, the relevant technical personnel obtain the traffic data of the target business at at least one data collection point by means of tracking points. Tracking points refer to the relevant technical personnel inserting specific tracking codes to record the operations or events of users in the target business.

[0041] Traffic data refers to data related to the network, user behavior or system performance in the target service. In some embodiments, the traffic data includes various behaviors and interaction data that occur when users access the target service in the service platform.

[0042] In some embodiments, traffic data includes at least one of the following types: business traffic data, user behavior data, network traffic data, traffic source data, advertising traffic data, device traffic data, etc., and may also include other types of traffic data, which is not limited to the embodiments of the present application.

[0043] Business traffic data refers to data related to achieving target business, including but not limited to: investment budget data, budget allocation data, investment cost, etc., and may also include other business traffic data, which is not limited in the embodiments of the present application.

[0044] User behavior data is used to reflect the user's operations and behaviors in the business platform, including but not limited to: request volume, click volume, dwell time, exit business node, time data, subscription volume, purchase volume, etc., and may also include other user request data, which is not limited in the embodiments of the present application.

[0045] Network traffic data is used to indicate the transmission status of data in the network, including but not limited to: bandwidth, amount of data sent, amount of data received, delay time, packet loss rate, etc., and may also include other network traffic data, which is not limited in the embodiments of the present application.

[0046] The traffic source data is used to indicate the source of the user's request for the target service, including but not limited to: source entry, client version, activity type, etc., and may also include other traffic source data, which is not limited in the embodiment of the present application.

[0047] Advertising traffic data is used to indicate the display of advertisements on the business platform, including but not limited to: click volume, exposure volume, advertising source, cost per click, advertising revenue, etc., and may also include other advertising traffic data, which is not limited in the embodiments of the present application.

[0048] The device traffic data is used to indicate the device information of the service terminal device used by the user, including but not limited to: device type, operating system type, browser type, screen resolution, etc., and may also include other device traffic data, which is not limited in the embodiments of the present application.

[0049] In some embodiments, in the upstream and downstream of the target business, transmission data and requests flow between the client link and the server link. The client link refers to the data flow when the user operates the target business on the client of the business platform. The data flow on the client link includes but is not limited to: request data, interaction data, request transmission data, user feedback data, etc., and may also include other data, which is not limited in the embodiment of the present application. The server link refers to the data flow when processing the request received from the client. The data flow on the server link may include but is not limited to: request reception data, request processing data, business processing data, response data, etc., and may also include other data, which is not limited in the embodiment of the present application. Optionally, in the upstream and downstream of the target business, transmission data and requests flow between the client link, the server link and the external system link. The external system link refers to the data flow in the target business that interacts with an external service or an external system. Optionally, the external system can be any of the following: an advertising platform, a payment platform, an e-commerce platform, an activity platform, etc., or other external systems, which are configured by relevant technical personnel according to needs, and the embodiment of the present application does not limit this.

[0050] In some embodiments, for a target service, different links may correspond to different data collection points, or may correspond to the same data collection points, which is not limited in this embodiment of the present application.

[0051] In some embodiments, historical traffic data corresponding to at least one moment of the target business is obtained, and the historical traffic data corresponding to each moment includes traffic data at at least one data collection point. Optionally, by sending an access request for historical traffic data to a database server, the database server returns historical traffic data corresponding to at least one moment of the target business. Optionally, the historical traffic data is stored in the database server in the form of a log.

[0052] In some embodiments, after the flow data of the target business at at least one data collection point is acquired, the flow data of the target business at at least one data collection point is stored in a database server.

[0053] Step 320, processing the flow data at at least one data collection point to obtain flow indicators in multiple statistical dimensions.

[0054] The statistical dimension refers to an attribute or feature used to divide and organize traffic data. The traffic index of the statistical dimension refers to an index obtained after processing the traffic data for the statistical dimension. Optionally, the statistical dimension may include at least one of the following: time dimension, space dimension, source dimension, user dimension, product dimension, behavior dimension, etc., and may also include other statistical dimensions, which are set by relevant technical personnel according to needs, and the embodiments of the present application are not limited to this. The time dimension is used to analyze the changes in data over time, such as year, month, day, hour, etc. For example, the change trend of the click-through rate of the target business is analyzed on a monthly basis. The spatial dimension is used to perform data analysis involving geographic locations, such as countries, cities, regions, etc. For example, compare the purchase volume of a certain product in different regions. The user dimension is used to perform data analysis involving user characteristics, such as gender, age, registration time, user type, etc. For example, analyze the behavioral differences between new users and old users. The product dimension is used to perform product-related analysis, such as product category, brand, model, etc. For example, evaluate the sales performance of different product categories. The behavioral dimension is used to analyze the interaction between users and products or services, such as request volume, exposure, click-through rate, conversion rate, etc. For example, analyzing user actions on targeted ads.

[0055] In some embodiments, the traffic indicator includes at least one of the following: request volume, delivery volume, delivery rate, exposure volume, exposure rate, click volume, click rate, timeout rate, ROI (Return on investment), fill rate, and actual revenue.

[0056] The request volume refers to the total number of requests sent by the service terminal device (hereinafter referred to as the "service client") to the service server or external system. For example, in the case where the target service is an advertising display service, the request volume may refer to the number of advertising requests sent by the service client to the service server and / or advertising platform. For example, in the case where the target service is a service subscription service, the request volume refers to the number of service subscription requests sent by the service client to the service server.

[0057] The number of requests sent refers to the number of requests sent by the business client that are successfully processed and responded to by the business server and / or external system. For example, if the target business is an advertising display business, the number of requests sent refers to the number of advertising requests sent by the business client that are successfully processed and responded to by the business server and / or advertising platform. For example, if the target business is a subscription service business, the number of requests sent refers to the number of subscription service requests sent by the business client that are successfully processed and responded to by the business server.

[0058] Exposure refers to the number of times relevant information of the target service is successfully displayed on the user interface of the service client. For example, if the target service is an advertisement display service, exposure refers to the number of times the advertisement is successfully displayed on the user interface of the service client. For example, if the target service is a service subscription service, exposure refers to the number of times relevant information of the subscription service is successfully displayed on the user interface of the service client.

[0059] The exposure rate refers to the proportion of relevant content sent by the business server and / or external system for the target business that is successfully displayed. In some embodiments, the ratio of the exposure amount to the sent amount is determined as the exposure rate. That is, exposure rate = exposure amount / sent amount. For example, in the case where the target business is an advertising display business, the exposure rate refers to the proportion of advertisements actually displayed among the advertisements sent by the business server and / or external system. For example, in the case where the target business is a service subscription business, the exposure rate refers to the proportion of relevant content that is actually displayed among the relevant content of the subscription service sent by the business server.

[0060] Clicks refer to the number of times a user clicks on the relevant information of the target service displayed in the service client. For example, if the target service is an advertisement display service, clicks refer to the number of times a user clicks on the advertisement displayed in the service client. For example, if the target service is a service subscription service, clicks refer to the number of times a user clicks on the relevant information of the subscription service displayed in the service client.

[0061] The click-through rate refers to the proportion of users clicking on the relevant information of the target business displayed in the business client. In some embodiments, the ratio of the number of clicks to the number of exposures is determined as the click-through rate. That is, click-through rate = number of clicks / number of exposures. For example, in the case where the target business is an advertisement display business, the click-through rate refers to the proportion of users clicking on the advertisements displayed in the business client. For example, in the case where the target business is a service subscription business, the click-through rate refers to the proportion of users clicking on the relevant information of the subscription service displayed in the business client.

[0062] The timeout rate refers to the proportion of requests that the business server or external system fails to complete within the specified time.

[0063] ROI is used to indicate the return on investment for the target business. In some embodiments, the ratio of actual income to investment cost is determined as ROI. Investment cost includes at least one of the following costs: business implementation cost, marketing promotion cost, operation and management cost, financial cost, tool cost, etc., and may also include other costs. Relevant technical personnel will design according to the needs of the target business, and the embodiments of this application are not limited to this.

[0064] The fill rate refers to the proportion of requests sent by the service client that are responded to. In some embodiments, the ratio of the number of requests sent to the number of requests is determined as the fill rate. The actual revenue refers to the revenue actually obtained by the target service.

[0065] In some embodiments, traffic indicators may also include eCPM (Effective Cost Per Mille, advertising revenue that can be obtained for every thousand impressions) unit price. The eCPM unit price refers to the revenue obtained for every thousand times an advertisement is displayed on a business client. In some embodiments, the ratio of actual revenue to exposure is determined as the advertising revenue unit price; the value obtained by multiplying the advertising revenue unit price by one thousand is determined as eCPM. Exemplarily, if an advertisement is displayed 5,000 times in a business client, and an actual revenue of 1,500 yuan is obtained by displaying the advertisement, then the eCPM unit price is eCPM = (1,500 / 5,000) × 1,000 = 0.3 yuan.

[0066] The above method, by processing the collected traffic data, obtains traffic indicators of different statistical dimensions, provides business developers with more comprehensive traffic information, and helps business developers optimize target businesses and improve the actual benefits of target businesses.

[0067] In some embodiments, based on the reconciliation type, traffic data at at least one data collection point is processed to obtain traffic indicators of multiple statistical dimensions related to the reconciliation type.

[0068] Reconciliation refers to the comparison of upstream and downstream statistical dimensions or horizontal statistical dimensions based on the business logic implemented by the target business, the process of data interaction in the target business, and the traffic indicators in the upstream and downstream of the target business. The comparison of upstream and downstream statistical dimensions refers to the comparison of traffic indicators between different links or stages in the business logic of the target business. The comparison of horizontal statistical dimensions refers to the comparison of traffic indicators between different statistical dimensions in the target business.

[0069] In some embodiments, the traffic indicators of multiple statistical dimensions corresponding to different reconciliation types include different specific contents. In some embodiments, the reconciliation types may include, but are not limited to: front-end and back-end reconciliation, operating system reconciliation, return on investment reconciliation, revenue reconciliation, client version reconciliation, etc., and may also include other reconciliation types, which are not limited in the embodiments of the present application.

[0070] Since different reconciliation types require different traffic indicators and reconciliation rules, when processing traffic data, it is necessary to process the traffic data differently according to different reconciliation types.

[0071] In the above manner, based on different reconciliation types, the flow data is processed differently to obtain the flow indicators required by each reconciliation type, so as to facilitate reconciliation according to the reconciliation rules corresponding to different reconciliation types.

[0072] Step 330, reconcile the traffic indicators of multiple statistical dimensions to obtain a reconciliation result.

[0073] The reconciliation result refers to a data report obtained by comparing traffic indicators of multiple statistical dimensions based on different reconciliation types. A data report refers to the display and analysis of traffic data in the form of a table or graph. In some embodiments, the reconciliation result includes at least one of the following types: a data dashboard, a daily monitoring report, a traffic report, an ROI report, etc., and may also include other types, which are not limited in the embodiments of the present application.

[0074] In some embodiments, a graphical report corresponding to the reconciliation result is generated.

[0075] A graphical report refers to presenting the reconciliation results in the form of a graph. Optionally, the types of graphical reports may include, but are not limited to: a bar chart, a line chart, a pie chart, a funnel chart, a stacked chart, a heat map, etc., and may also include other graphical reports, which are not limited in the present application embodiment.

[0076] The above method presents the reconciliation results in a graphical way, allowing users to intuitively understand the data, identify problems and find optimization space.

[0077] In some embodiments, when the reconciliation result meets the alarm condition, an alarm message is generated; based on the alarm configuration information stored in the configuration center, the alarm message is sent to the corresponding recipient, wherein the alarm configuration information is used to indicate the alarm rules for the alarm information.

[0078] An alarm condition refers to a trigger mechanism for monitoring traffic indicators. The specific triggering rules are pre-set by relevant technical personnel, and the embodiments of the present application do not limit this. Optionally, the types of alarm conditions may include, but are not limited to: threshold alarms, abnormal alarms, status alarms, etc., and may also include other types, which are not limited in the embodiments of the present application. A threshold alarm refers to an alarm that is triggered when a certain traffic indicator exceeds or falls below a preset threshold. An abnormal alarm refers to an alarm that is triggered when an abnormal situation that does not conform to the normal pattern is identified by monitoring historical traffic data. A status alarm refers to an early warning that is triggered when the status of a business or traffic reconciliation system changes. Optionally, configuration information about alarm conditions is stored in a configuration center.

[0079] The configuration center is used to store various configuration information to ensure the normal operation of the flow reconciliation system. Optionally, the configuration center can be a computer device other than the reconciliation terminal device and the reconciliation server, or it can be set in the reconciliation server, which is not limited in this application.

[0080] Optionally, the alarm configuration information may include at least one of the following: alarm conditions, alarm frequency, alarm channel, alarm recipient, alarm level, etc., and may also include other content, which is not limited in the embodiments of the present application. The alarm frequency refers to how long it takes to trigger an alarm, or how long the problem lasts to repeat the alarm. The alarm channel refers to the method by which the alarm is sent, such as SMS, email, push notification, third-party monitoring tool, establishment of task nodes, etc. The alarm recipient refers to the person, team or system designated to receive the alarm information, such as developers, product personnel, operations personnel, etc.

[0081] To sum up, the technical solution provided in the embodiment of the present application collects and processes the traffic data of the target business, and then reconciles the traffic indicators on multiple statistical dimensions to obtain reconciliation results. By reconciling the traffic indicators based on multiple statistical dimensions, the reconciliation results obtained are more comprehensive and intuitive, which helps to expose the optimization space of the target business.

[0082] The different reconciliation types are described below.

[0083] (1) Front-end and back-end reconciliation

[0084] In some embodiments, when the reconciliation type is front-end and back-end reconciliation, the traffic indicators of multiple statistical dimensions related to the front-end and back-end reconciliation include: traffic indicators related to the client of the target business and traffic indicators related to the server of the target business.

[0085] In some embodiments, when the reconciliation type is front-end and back-end reconciliation, the multiple statistical dimensions related to the front-end and back-end reconciliation include two statistical dimensions: business client and business server.

[0086] Front-end and back-end reconciliation refers to the comparison between the traffic indicators corresponding to the business client and the business server. In some embodiments, when the reconciliation type is front-end and back-end reconciliation, there is a corresponding relationship between the traffic indicator of the business client and the traffic indicator of the business server used for reconciliation. Optionally, the corresponding relationship may refer to the same traffic indicator or different traffic indicators, which is not limited in the embodiments of the present application. Optionally, when the traffic indicator of the business client and the traffic indicator of the business server are different traffic indicators, the corresponding relationship may be a dependency relationship in the business logic of the target business. For example, in the front-end and back-end reconciliation, the traffic indicator of the business client may be the request volume, and the traffic indicator of the business server having a corresponding relationship with the traffic indicator may be the dispatch volume. Optionally, when the reconciliation type is front-end and back-end reconciliation, the corresponding relationship between the traffic indicator of the business client and the traffic indicator of the business server is pre-set by relevant technical personnel, which is not limited in the embodiments of the present application.

[0087] The above method, by comparing the traffic indicators of the front-end and back-end, helps relevant technical personnel to discover network performance problems, optimize network performance in a timely manner, and enhance user experience.

[0088] (2) Operating system reconciliation

[0089] In some embodiments, when the reconciliation type is operating system reconciliation, the traffic indicators of multiple statistical dimensions related to the operating system reconciliation include: traffic indicators under at least two different operating systems.

[0090] In some embodiments, when the reconciliation type is operating system reconciliation, the multiple statistical dimensions related to the operating system reconciliation include at least two different operating systems.

[0091] Depending on the device type of the business terminal device, the operating system built into the business terminal device may include at least one of the following: desktop operating system, mobile operating system, server operating system, embedded system, etc., and may also include other operating systems, which are not limited in the embodiments of the present application. Desktop operating system refers to an operating system used on a desktop device (such as a personal computer, a laptop), which may include but is not limited to: Windows, macOS, Linux, ChromeOS, etc., and may also include other desktop operating systems, which are not limited in the embodiments of the present application. Mobile operating system refers to an operating system used on a mobile device (such as a smart phone, a tablet computer or other portable device), which may include but is not limited to: Android, iOS, Harmony, Windows Phone, etc., and may also include other mobile operating systems, which are not limited in the embodiments of the present application. Server operating system refers to an operating system used on a server, which may include but is not limited to: Linux distribution, Windows Server, Unix, etc., and may also include other server operating systems, which are not limited in the embodiments of the present application. Embedded operating system refers to an operating system used on an embedded system, which may include but is not limited to: Real-Time Operating System (RTOS), embedded Linux, embedded Windows, etc., and may also include other embedded operating systems, which are not limited in the embodiments of the present application.

[0092] Optionally, the traffic indicators under different operating systems are the same traffic indicators. That is, in the case of operating system reconciliation, the same traffic indicators under different operating systems are compared.

[0093] For example, please refer to Figure 4 , which shows a schematic diagram of an operating system reconciliation provided by an embodiment of the present application, Figure 4 A line graph of the exposure rates of two different operating systems is provided. The solid line corresponds to the exposure rate of the Android operating system under the current client version, and the dotted line corresponds to the exposure rate of the iOS operating system under the current client version. Figure 4 It can be seen that the exposure rate of the Android operating system is lower than that of the iOS operating system. Therefore, it is necessary to optimize the advertising technology for the Android operating system to increase the exposure rate.

[0094] The above method helps relevant technical personnel understand the performance of the target business on each operating system by comparing the traffic indicators under different operating systems, thereby optimizing resource allocation and market strategies to increase the revenue of the target business.

[0095] (3) ROI reconciliation

[0096] In some embodiments, when the reconciliation type is return on investment reconciliation, the traffic indicators of multiple statistical dimensions related to ROI reconciliation include: strict ROI and broad ROI.

[0097] Strict ROI is a strictly defined method of calculating the return on investment, which only calculates ROI based on direct benefits and direct costs. Optionally, strict ROI = (direct benefits - direct costs) / direct costs × 100%. Strict ROI emphasizes direct benefits and direct costs in the short term, and the corresponding analysis is more accurate, but does not consider long-term indirect effects. Direct benefits refer to the benefits directly generated by the target business. For example, the benefits brought by user clicks after displaying an ad. For example, in a subscription service, the fees paid by users for the services they use. Direct costs refer to costs that can be clearly traced. For example, direct costs can be the salaries of personnel involved in the realization, maintenance and promotion of the target business or the fees paid for promoting the target business.

[0098] Broad-caliber ROI is a relatively broad way of calculating the return on investment, which calculates ROI based on direct costs, indirect costs, direct benefits and indirect benefits. Optionally, broad-caliber ROI = (direct benefits + indirect benefits - direct costs - indirect costs) × 100% / (direct costs + indirect costs). Broad-caliber ROI focuses on long-term comprehensive benefits and can evaluate the overall return of complex businesses, but the calculation may be more complicated. Indirect benefits refer to the benefits indirectly generated by the target business, which are difficult to quantify directly and have weak correlation. For example, indirect benefits may include: brand value enhancement, potential customer conversion, user word-of-mouth communication, etc. Indirect costs refer to costs that cannot be directly attributed to a certain business. For example, indirect costs may include: fixed expenses of the enterprise, public expenses, depreciation expenses, rent, management expenses, utility expenses, etc.

[0099] For example, please refer to Figure 5 , which shows a schematic diagram of ROI reconciliation provided by an embodiment of the present application, Figure 5 A line chart of strict ROI and wide ROI is provided. The solid line corresponds to the strict ROI, and the dotted line corresponds to the wide ROI. Figure 5 It can be seen that the strict ROI is higher than the broad ROI. Therefore, from a long-term development perspective, the strict ROI of the target business will show a downward trend in the later period.

[0100] By comparing the traffic indicators of strict ROI and broad ROI in the above method, relevant technical personnel can further explore optimization points with potential benefits and improve the benefits of the target business.

[0101] (4) Revenue reconciliation

[0102] In some embodiments, when the reconciliation type is revenue reconciliation, the traffic indicators of multiple statistical dimensions related to the revenue reconciliation include: expenditure of the target business and revenue of the target business.

[0103] The expenses of the target business may include, but are not limited to: expenses for different advertising spaces, development costs, promotion costs, raw material costs, maintenance costs, management costs, indirect costs, etc., and may also include other expenses, which are not limited in the embodiments of the present application. The income of the target business may include, but are not limited to: predicted income, actual income, and indirect income, etc., and may also include other income, which are not limited in the embodiments of the present application. Optionally, the predicted income is obtained based on the traffic data prediction of the content related to the display of the target business.

[0104] In the case where the target business is an advertising display business, since advertisements can be displayed through advertisement entrances at different locations in the business client, different advertisement entrances can be selected for reconciliation for front-end and back-end reconciliation, operating system reconciliation, and client version reconciliation. The advertisement entrance, also known as an advertisement slot, is an area in the business client used to display advertisements. Optionally, the advertisement entrance may include, but is not limited to: a splash screen, a play page bubble, a home page text advertisement, a home page banner advertisement, a member center activity advertisement, a play page banner advertisement, a home page banner advertisement, a home page advertisement card, a pop-up advertisement, a task center advertisement, a member payment pre-page banner advertisement, a promotional text advertisement, etc., and may also include other advertisement entrances, which are not limited in the embodiments of the present application.

[0105] For example, please refer to Figure 6 , which shows a schematic diagram of revenue reconciliation provided by an embodiment of the present application, Figure 6 A line chart of actual and predicted returns is provided. The solid line corresponds to the actual return, and the dotted line corresponds to the predicted return. Figure 6 It can be seen that the actual income is higher than the predicted income. Therefore, the predicted income is inaccurate, and the income prediction algorithm needs to be optimized to improve the accuracy of income prediction, so as to adjust the expenditure budget in time.

[0106] The above method, by comparing the expenditure and income of the target business, helps relevant technical personnel evaluate whether the investment in the target business has obtained an ideal return, and timely adjusts the allocation of expenditure budget to improve the income of the target business.

[0107] (5) Client version reconciliation

[0108] In some embodiments, when the reconciliation type is client version reconciliation, the traffic indicators of multiple statistical dimensions related to the client version reconciliation include: traffic indicators under at least two different client versions.

[0109] In some embodiments, when the reconciliation type is client version reconciliation, the multiple statistical dimensions related to the client version reconciliation include different client versions.

[0110] Different client versions refer to different versions released by developers for business applications, including at least one of the following: the current client version, the new client version, and at least one historical client version. Since different business terminal devices are compatible with different client versions, there are situations where different client versions are running at the same time. Optionally, the new client version can be gradually recommended to a part of users through grayscale release to test its compatibility and stability.

[0111] Optionally, when the reconciliation type is client version reconciliation, the same traffic indicator under different client versions is compared.

[0112] The above method can quickly find problems with different client versions by comparing the traffic indicators of different client versions, and even optimize the client to speed up the progress of the full push of the new client version.

[0113] The following describes how to process traffic data.

[0114] In some embodiments, the method of processing traffic data includes at least one of the following:

[0115] (1) Link funnel processing is used to count traffic indicators of a target service on multiple service nodes, where the target service includes multiple service nodes.

[0116] Link funnel processing refers to calculating the conversion rate or loss rate of the target at different stages or service nodes of different links. For example, the conversion rate or loss rate of the target service at different stages or service nodes of the client link, server link and external system link is calculated respectively.

[0117] Please refer to Figure 7 , which shows a schematic diagram of link funnels corresponding to different links provided by an embodiment of the present application, Figure 7 The link funnel diagrams of two different links are shown in Figure 2. Figure 7 The sub-graph (a) of corresponds to the link funnel graph corresponding to the business server link (that is, the server link). Figure 7In the sub-graph (a), the request amount, the delivery amount, the exposure amount, and the click amount decrease in sequence, and the difference between the exposure amount and the click amount increases suddenly. In other words, the user is less interested in the relevant content of the target business displayed by the business client. Figure 7 Sub-graph (b) corresponds to the business client link (that is, the client link), which is similar to sub-graph (a), and the difference in traffic indicators in the horizontal comparison between the two links is also small, indicating that the network status between the business client and the business server is better.

[0118] (2) Reconciliation difference processing is used to calculate the differences between flow indicators in multiple statistical dimensions related to the reconciliation type.

[0119] Reconciliation difference processing refers to calculating the difference between different statistical dimensions for the same traffic indicator, or the difference between different statistical dimensions for corresponding traffic indicators. For example, calculating the difference between predicted revenue and actual revenue. For example, calculating the difference between the request volume and the delivery volume.

[0120] (3) Rate calculation processing is used to calculate the rates invested in target businesses in multiple statistical dimensions. Rate calculation processing refers to calculating traffic indicators such as different advertising space expenditures, investment ratios, expenditures at different times, and indirect expenditures.

[0121] (4) Revenue calculation and processing, used to calculate the revenue obtained by the target business.

[0122] The revenue calculation process refers to the calculation of traffic indicators related to revenue, such as total revenue, direct revenue, indirect revenue, ROI, predicted revenue, etc., and may also include other traffic indicators, which are not limited in the present embodiment of the application.

[0123] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0124] Please refer to Figure 8 , which shows a block diagram of a flow data processing device provided by an embodiment of the present application. The device has the functions of implementing the above examples, and the functions can be implemented by hardware or by hardware executing corresponding software. The device can be a computer device or can be set in a computer device. Figure 8 As shown, the device 800 may include a data acquisition module 810 , a data processing module 820 and an indicator reconciliation module 830 .

[0125] The data acquisition module 810 is used to acquire the flow data of the target service at at least one data collection point.

[0126] The data processing module 820 is used to process the flow data at the at least one data collection point to obtain flow indicators in multiple statistical dimensions.

[0127] The indicator reconciliation module 830 is used to reconcile the traffic indicators of the multiple statistical dimensions to obtain a reconciliation result.

[0128] In some embodiments, the data processing module 820 is used to process the flow data at the at least one data collection point based on the reconciliation type to obtain flow indicators of multiple statistical dimensions related to the reconciliation type.

[0129] In some embodiments, when the reconciliation type is front-end and back-end reconciliation, the traffic indicators of multiple statistical dimensions related to the front-end and back-end reconciliation include: traffic indicators related to the client of the target business, and traffic indicators related to the server of the target business; when the reconciliation type is operating system reconciliation, the traffic indicators of multiple statistical dimensions related to the operating system reconciliation include: traffic indicators under at least two different operating systems; when the reconciliation type is ROI reconciliation, the traffic indicators of multiple statistical dimensions related to the ROI reconciliation include: the strict ROI and the broad ROI; when the reconciliation type is revenue reconciliation, the traffic indicators of multiple statistical dimensions related to the revenue reconciliation include: the expenditure of the target business, and the revenue of the target business; when the reconciliation type is client version reconciliation, the traffic indicators of multiple statistical dimensions related to the client version reconciliation include: traffic indicators under at least two different client versions.

[0130] In some embodiments, the processing includes at least one of the following: link funnel processing, which is used to count the traffic indicators of the target business on multiple business nodes, and the target business includes the multiple business nodes; reconciliation difference processing, which is used to calculate the difference between the traffic indicators of multiple statistical dimensions related to the reconciliation type; tariff calculation processing, which is used to count the tariffs invested in the target business in the multiple statistical dimensions; and revenue calculation processing, which is used to count the revenue obtained by the target business.

[0131] In some embodiments, the traffic indicator includes at least one of the following: request volume, delivery volume, delivery rate, exposure volume, exposure rate, click volume, click rate, timeout rate, ROI, fill rate, and actual revenue.

[0132] In some embodiments, the apparatus 800 further includes a report generation module (in Figure 8 ), which is used to generate a graphical report corresponding to the reconciliation result.

[0133] In some embodiments, the device 800 further includes an alarm determination module (in Figure 8 (not shown) is used to generate an alarm message when the reconciliation result meets the alarm condition; based on the alarm configuration information stored in the configuration center, the alarm information is sent to the corresponding recipient, wherein the alarm configuration information is used to indicate the alarm rules for the alarm information.

[0134] To sum up, the device provided in the embodiment of the present application collects and processes the traffic data of the target business, and then reconciles the traffic indicators on multiple statistical dimensions to obtain reconciliation results. By reconciling the traffic indicators based on multiple statistical dimensions, the reconciliation results obtained are more comprehensive and intuitive, which helps to expose the optimization space of the target business.

[0135] It should be noted that the device provided in the above embodiment, when implementing its functions, is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0136] Please refer to Fig. 9 , which shows a block diagram of a computer device 900 provided in one embodiment of the present application. The computer device 900 may be Figure 1 The reconciliation terminal device 10 in the implementation environment shown may also be Figure 1 The reconciliation server 20 in the illustrated implementation environment is used to implement the method for processing traffic data provided in the above embodiment. Specifically:

[0137] Typically, the computer device 900 includes a processor 910 and a memory 920 .

[0138] The processor 910 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 910 may be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), and programmable logic array (PLA). The processor 910 may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 910 may be integrated with a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 910 may also include an AI processor for processing computing operations related to machine learning.

[0139] The memory 920 may include one or more computer-readable storage media, which may be non-transitory. The memory 920 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 920 is used to store a computer program, which is configured to be executed by one or more processors to implement a method for processing flow data.

[0140] Those skilled in the art will understand that Fig. 9 The structure shown in the figure does not constitute a limitation on the computer device 900, and the computer device 900 may include more or less components than those shown in the figure, or combine some components, or adopt a different arrangement of components.

[0141] In an exemplary embodiment, a computer-readable storage medium is also provided, in which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned method for processing traffic data is implemented. Optionally, the computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a solid state drive (SSD), or an optical disk. Among them, the random access memory may include a resistance random access memory (ReRAM) and a dynamic random access memory (DRAM).

[0142] In an exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program, the computer program being stored in a computer-readable storage medium. A processor of a computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the above-mentioned method for processing flow data.

[0143] It should be noted that the collection and processing of relevant data (such as traffic data, etc.) in this application should be strictly in accordance with the requirements of relevant national laws and regulations when applied in examples, and the informed consent or separate consent of the personal information subject should be obtained, and subsequent data use and processing should be carried out within the scope of authorization of laws and regulations and the personal information subject.

[0144] It should be understood that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. In addition, the step numbers described in this article only illustrate a possible execution sequence between the steps. In some other embodiments, the above steps may not be executed in the order of the numbers, such as two steps with different numbers are executed at the same time, or two steps with different numbers are executed in the opposite order to the diagram. The embodiments of the present application are not limited to this.

[0145] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for processing flow data, characterized in that: The method comprises: Obtaining traffic data of a target service at at least one data collection point; Processing the flow data at the at least one data collection point to obtain flow indicators in multiple statistical dimensions; The flow indicators of the multiple statistical dimensions are reconciled to obtain a reconciliation result.

2. The method according to claim 1, characterized in that The processing of the flow data at the at least one data collection point to obtain flow indicators of multiple statistical dimensions includes: Based on the reconciliation type, the flow data at the at least one data collection point is processed to obtain flow indicators of multiple statistical dimensions related to the reconciliation type.

3. The method according to claim 2, characterized in that In the case where the reconciliation type is front-end and back-end reconciliation, the traffic indicators of multiple statistical dimensions related to the front-end and back-end reconciliation include: traffic indicators related to the client of the target business, and traffic indicators related to the server of the target business; In the case where the reconciliation type is operating system reconciliation, the traffic indicators of multiple statistical dimensions related to the operating system reconciliation include: traffic indicators under at least two different operating systems; In the case where the reconciliation type is a return on investment (ROI) reconciliation, the traffic indicators of multiple statistical dimensions related to the ROI reconciliation include: the strict ROI and the broad ROI; In the case where the reconciliation type is revenue reconciliation, the flow indicators of multiple statistical dimensions related to the revenue reconciliation include: expenditure of the target business and revenue of the target business; In the case where the reconciliation type is client version reconciliation, the traffic indicators of multiple statistical dimensions related to the client version reconciliation include: traffic indicators under at least two different client versions.

4. The method according to claim 2, characterized in that: The processing includes at least one of the following: Link funnel processing, used to count traffic indicators of the target service on multiple service nodes, the target service including the multiple service nodes; Reconciliation difference processing, used to calculate the difference between the flow indicators of multiple statistical dimensions related to the reconciliation type; Tariff calculation processing, used to count the tariffs invested in the target service in the multiple statistical dimensions; The revenue calculation process is used to count the revenue obtained by the target business.

5. The method according to any one of claims 1 to 4, characterized in that: The traffic indicators include at least one of the following: request volume, delivery volume, delivery rate, exposure volume, exposure rate, click volume, click rate, timeout rate, ROI, fill rate, and actual revenue.

6. The method according to any one of claims 1 to 4, characterized in that: After reconciling the traffic indicators of the multiple statistical dimensions and obtaining the reconciliation result, the process further includes: Generate a graphical report corresponding to the reconciliation result.

7. The method according to any one of claims 1 to 4, characterized in that: After reconciling the traffic indicators of the multiple statistical dimensions and obtaining the reconciliation results, the process further includes: When the reconciliation result meets the alarm condition, generating alarm information; Based on the alarm configuration information stored in the configuration center, the alarm information is sent to a corresponding receiver, wherein the alarm configuration information is used to indicate an alarm rule for the alarm information.

8. A flow data processing device, characterized in that: The device comprises: A data acquisition module, used to acquire flow data of a target service at at least one data collection point; A data processing module, used to process the flow data at the at least one data collection point to obtain flow indicators of multiple statistical dimensions; The indicator reconciliation module is used to reconcile the traffic indicators of the multiple statistical dimensions to obtain a reconciliation result.

9. A computer device, characterized in that: The computer device comprises a processor and a memory, wherein a computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to be executed by a processor to implement the method according to any one of claims 1 to 7.

11. A computer program product, characterized in that The computer program product comprises a computer program, which is loaded and executed by a processor to implement the method according to any one of claims 1 to 7.

Images