A data statistics method and device

Abstract

The present invention discloses a data statistics method and device, and relates to the field of computer technology. A specific implementation of the method includes: obtaining click events that trigger corresponding user behaviors, sorting the click events according to the click time, and obtaining the initial click path corresponding to the user behavior; repeatedly performing the following steps until there is no closed-loop path in the current click path, and obtaining the click path that actually triggers the user behavior: determining that there is a closed-loop path in the current click path, and the current click event in the closed-loop path is correlated with the target object; and retaining the current click event and the preceding click event of the current click event, marking the current click event and the preceding click event, and updating the current click path. This implementation method finds the closed-loop path in the current click path, and retains the click events in the closed-loop path that are correlated with the target object, thereby completely obtaining the click path that actually triggers the user behavior.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a data statistics method and device. Background Art

[0002] In order to provide better services to users, the enterprise website platform hopes to be able to count the slots that really contribute to the order. The existing statistical logic is: under the same user visit, the same pages overlap each other, only the last click event of each page is recorded, and in the case of multiple purchases, only the click path of the user's first purchase is recorded. If the user does not purchase anything within 24 hours, the corresponding click path will not be counted in the data warehouse bottom table. Based on the data recorded in the data warehouse bottom table, the click events that contribute to the order are counted, and then the contributing slots are obtained.

[0003] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art:

[0004] The statistical logic of the existing technology only records the last click event of each page, which may miss the click event that actually leads the user to place an order (not the last click event of the page). As a result, the counted click events are inconsistent with the click events that actually trigger the user to place an order, and it is impossible to accurately find the pits that contribute to the order, and it is impossible to accurately perform user behavior data analysis. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a data statistics method and device, which finds a closed-loop path in the current click path and retains click events in the closed-loop path that are relevant to the target object, thereby completely obtaining the click path that truly triggers user behavior.

[0006] To achieve the above objective, according to one aspect of an embodiment of the present invention, a data statistics method is provided.

[0007] A data statistics method according to an embodiment of the present invention includes: obtaining click events that trigger corresponding user behaviors according to target objects in task information, sorting the click events according to click time, and obtaining an initial click path corresponding to the user behaviors; repeatedly performing the following steps until there is no closed-loop path in the current click path, and obtaining the click path that actually triggers the user behaviors: determining that there is the closed-loop path in the current click path, and that the current click event in the closed-loop path is correlated with the target object; and retaining the current click event and the preceding click event of the current click event, marking the current click event and the preceding click event, and updating the current click path; wherein the initial value of the current click path is the initial click path, and the first and last click events of the closed-loop path are click events that jump to the same page.

[0008] Optionally, determining that the closed-loop path exists in the current click path includes: determining, based on the page identifier of the page to which the click event jumps, that the same page identifier exists in the page identifier set corresponding to the current click path; the click events corresponding to the same page identifier, and the click events corresponding to the page identifiers between the same page identifiers form a closed-loop path.

[0009] Optionally, determining whether the current click event in the closed-loop path is relevant to the target object includes: determining that the operation object corresponding to the current click event in the closed-loop path and the target object satisfy a set relevance determination rule, and then determining that the current click event is relevant to the target object.

[0010] Optionally, the relevance determination rule includes: any one or more of the category, store and SPU corresponding to the operation object are the same as the category, store and SPU corresponding to the target object.

[0011] Optionally, the predecessor click event is a click event whose click time is earlier than that of the current click event and belongs to the closed-loop path; the current click event and the predecessor click event are marked, including: marking the page identifier of the page to which the current click event is jumped, and marking the page identifier of the page to which the predecessor click event is jumped when the predecessor click event is triggered.

[0012] Optionally, the page identifier of the page to which the current click event is jumped is marked, and the page identifier of the page to which the previous click event is jumped is marked, including: concatenating the page identifier of the page to which the current click event is jumped with the timestamp corresponding to the current click event to obtain a new page identifier corresponding to the current click event; and concatenating the page identifier of the page to which the previous click event is jumped with the timestamp corresponding to the previous click event to obtain a new page identifier corresponding to the previous click event.

[0013] Optionally, the task information includes the time when the task occurred; obtaining the click event that triggers the corresponding user behavior includes: based on the user identifier corresponding to the task information and the time when the task occurred, tracing back the click events with the same user and the same number of visits as those corresponding to the corresponding user behavior within a set time period.

[0014] To achieve the above objective, according to another aspect of an embodiment of the present invention, a data statistics device is provided.

[0015] A data statistics device according to an embodiment of the present invention includes: an acquisition and sorting module, which is used to acquire click events that trigger corresponding user behaviors according to target objects in task information, sort the click events according to click time, and obtain an initial click path corresponding to the user behavior; a path determination module, which is used to repeatedly execute the following steps until there is no closed-loop path in the current click path, and obtain the click path that actually triggers the user behavior: determine that there is the closed-loop path in the current click path, and that the current click event in the closed-loop path is correlated with the target object; and retain the current click event and the preceding click event of the current click event, mark the current click event and the preceding click event, and update the current click path; wherein the initial value of the current click path is the initial click path, and the first and last click events of the closed-loop path are click events that jump to the same page.

[0016] Optionally, the path determination module is also used to determine, based on the page identifier of the page to which the click event jumps when the click event is triggered, whether there is an identical page identifier in the page identifier set corresponding to the current click path; and that the click events corresponding to the identical page identifier, and the click events corresponding to the page identifiers between the identical page identifiers form a closed-loop path.

[0017] Optionally, the path determination module is further used to determine that the operation object corresponding to the current click event in the closed-loop path and the target object meet a set correlation determination rule, and then determine that the current click event and the target object are correlated.

[0018] Optionally, the relevance determination rule includes: any one or more of the category, store and SPU corresponding to the operation object are the same as the category, store and SPU corresponding to the target object.

[0019] Optionally, the predecessor click event is a click event whose click time is earlier than that of the current click event and belongs to the closed-loop path; the path determination module is also used to mark the page identifier of the page to which the current click event is jumped when the current click event is triggered, and to mark the page identifier of the page to which the predecessor click event is jumped when the predecessor click event is triggered.

[0020] Optionally, the path determination module is also used to concatenate the page identifier of the page to which the current click event is jumped with the timestamp corresponding to the current click event to obtain a new page identifier corresponding to the current click event; and to concatenate the page identifier of the page to which the previous click event is jumped with the timestamp corresponding to the previous click event to obtain a new page identifier corresponding to the previous click event.

[0021] Optionally, the task information includes the time when the task occurred; the acquisition and sorting module is further used to trace back the click events with the same user and the same number of visits corresponding to the corresponding user behavior within a set time period based on the user identifier corresponding to the task information and the time when the task occurred.

[0022] To achieve the above objective, according to another aspect of an embodiment of the present invention, an electronic device is provided.

[0023] An electronic device according to an embodiment of the present invention includes: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement a data statistics method according to an embodiment of the present invention.

[0024] To achieve the above objective, according to another aspect of the embodiments of the present invention, a computer readable medium is provided.

[0025] A computer-readable medium according to an embodiment of the present invention stores a computer program, and when the program is executed by a processor, a data statistics method according to an embodiment of the present invention is implemented.

[0026] One embodiment of the above invention has the following advantages or beneficial effects: by finding the closed-loop path in the current click path and retaining the click events in the closed-loop path that are relevant to the target object, the click path that actually triggers the user behavior is completely obtained. According to the page identifier of the page that jumps when the click event is triggered, it can be judged whether the user has a return operation, and then the closed-loop path in the current click path is found based on the above judgment result, which is convenient for the subsequent identification of the click path that is actually related to the order.

[0027] Based on the set relevance judgment rules, the relevance between the click events in the closed-loop path and the target object is determined. Under the premise of not missing the click events that really contribute to the order, irrelevant click events are filtered out. Moreover, the relevance is determined by setting the relevance judgment rules, which is flexible. The page identifiers corresponding to the click events with relevance are marked, so that when searching for new closed-loop paths in the future, the marked click events will not be judged as elements of the closed-loop path again.

[0028] The page ID is concatenated with the timestamp corresponding to the click event to mark the click event related to the target object, so that the page ID corresponding to the click event is unique and will not be confused with the initial page ID, further ensuring the accuracy of the closed-loop path found. By obtaining click events of the same user, the same number of visits, and within a set time period earlier than the task occurrence time, the obtained click events are click events that trigger user behavior, ensuring the accuracy of subsequent processing.

[0029] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0031] Figure 1 is a schematic diagram of the main steps of the data statistics method according to an embodiment of the present invention;

[0032] Figure 2 is a schematic diagram of the main flow of the data statistics method according to an embodiment of the present invention;

[0033] Figure 3 is a schematic diagram of main modules of a data statistics device according to an embodiment of the present invention;

[0034] Figure 4 is an exemplary system architecture diagram to which embodiments of the present invention may be applied;

[0035] Figure 5 It is a schematic diagram of the structure of a computer device suitable for implementing the electronic device of the embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0037] The technical terms involved in the embodiments of the present invention are explained below.

[0038] SPU: Standard Product Unit, is the smallest unit of item information aggregation, a set of reusable, easy-to-retrieve standardized information, describing the characteristics of a product. For example, different colors of XX brand mobile phones belong to different SKUs (Stock Keeping Units), but they belong to the same SPU.

[0039] Position: The clickable position of an APP (or website) page, such as a search box, icon, button, etc. APP stands for application.

[0040] Visits: the number of times a user visits an app (or website). For example, if you visit an app for the first time on the day, the number of visits is 1. If you close the app and open it again, the number of visits increases by 1, and so on. The number of visits will be counted again the next day.

[0041] As described in the background technology, the existing statistical logic only records the last click event of each page jump. The same pages overlap each other. This statistical logic may miss the click events that actually lead users to place orders. The pit positions corresponding to the statistical click events are used as the pit positions that contribute to the order, which will not match the pit positions that actually lead users to place orders. For example, a user searches for mango in the search box on the homepage, then clicks on paper towels in the item recommendation function, and finally buys paper towels.

[0042] In the above statistical logic, the order of paper towels will be included in the order-related data indicators of the search box, that is, the order of paper towels is calculated as an order contributed by the search box function, but the actual situation is that the order is brought by the item recommendation function. Based on the above problem, an embodiment of the present invention provides a data statistics method, which can calculate the complete click path that truly guides users to place orders, and then correctly find the pits that contribute to the order, and the specific implementation is as follows.

[0043] Figure 1 FIG. 1 is a schematic diagram of the main steps of the data statistics method according to an embodiment of the present invention. Figure 1 As shown, the data statistics method of the embodiment of the present invention mainly includes the following steps:

[0044] Step S101: According to the target object in the task information, the click event that triggers the corresponding user behavior is obtained, and the click events are sorted according to the click time to obtain the initial click path corresponding to the user behavior. The task information is the information generated after the user purchases the target object (i.e., places an order) on the APP or website, including the task identifier and the target object identifier. The target object can be an item, service, etc.

[0045] In the embodiment, the task information is order information, and accordingly, the task identifier is the order identifier, and the target object identifier is the item identifier or the service identifier. User behavior is the behavior that occurs when a user purchases a target object, such as ordering behavior, adding to a shopping cart (i.e., adding to a shopping cart), etc. Preferably, the user behavior is ordering behavior. The click event obtained in this step is a click event that may trigger the user behavior. For example, if the target object is an item, what is obtained here is a click event that may trigger the user to place an order for the item.

[0046] After obtaining the click events, you can sort the click events according to the early and late click times, with the click events with early click times in front and the click events with late click times in the back, to get the initial click path.

[0047] Step S102: Determine whether there is a closed-loop path in the current click path. If there is a closed-loop path, execute step S103; if there is no closed-loop path, execute step S105. If the user has a return operation during the browsing process, there will be a click event that jumps to the same page in the current click path, and a closed-loop path will be formed. Therefore, it can be seen that the first and last click events of the closed-loop path are click events that jump to the same page, that is, the first click event and the last click event will jump to the same page. Among them, the initial value of the current click path is the initial click path.

[0048] When judging whether there is a closed-loop path in the current click path, the page ID of the page to which the click event is triggered can be used to judge whether there is an identical page ID in the page ID set corresponding to the current click path. If there is an identical page ID, it means there is a closed-loop path; if there is no identical page ID, it means there is no closed-loop path. A closed-loop path includes click events corresponding to the same page ID and click events corresponding to page IDs between the same page IDs.

[0049] Step S103: Determine whether the current click event in the closed-loop path is relevant to the target object. Determine whether the operation object corresponding to the current click event in the closed-loop path and the target object meet the set relevance determination rules. If both meet the relevance determination rules, it is considered that the current click event is relevant to the target object; if both do not meet the relevance determination rules, it is considered that the current click event is not relevant to the target object.

[0050] The correlation determination rule may be: any one or more of the categories, stores and SPUs corresponding to the operation object and the target object are the same.

[0051] Step S104: retain the current click event and the preceding click event of the current click event, mark the current click event and the preceding click event, update the current click path, and jump to step S102. The preceding click event is a click event that is clicked earlier than the current click event and belongs to the closed-loop path. When marking the current click event and the preceding click event, the page ID of the page to which the current click event is triggered and the page ID of the page to which the preceding click event is triggered can be marked separately. After adding the mark, update the current click path.

[0052] Step S105: taking the current click path as the click path that actually triggers the user's behavior. Through the above-mentioned cyclic processing, a current click path without a closed-loop path will eventually be obtained, and the current click path is the click path that actually triggers the user's ordering behavior.

[0053] Figure 2FIG. 1 is a schematic diagram of the main flow of the data statistics method according to an embodiment of the present invention. Figure 2 As shown, the data statistics method of the embodiment of the present invention is described by taking order information as an example, and mainly includes the following steps:

[0054] Step S201: According to the target object in the order information, obtain the click event that triggers the corresponding user behavior. In the embodiment, the order information is a record in the order table, including the order ID, target object ID and order time of the user's order. According to the order time, trace back to the user's earliest purchase-adding point in the click table. Among them, the click table records the information of the user's related click behavior, including the click location, user PIN code (Personal Identification Number), click time, etc. The purchase-adding point is the buried point triggered by the user's purchase-adding behavior. Each click behavior of the user will trigger a click buried point.

[0055] According to the timestamp of the add-to-cart point, the click events with the same user and the same number of visits as the add-to-cart event within the set time period are traced back. The click events obtained by tracing back can be used as click events that may trigger the user to place an order. Click events are recorded through tracking points in the APP or website. Each user click operation will generate a row of data records, recording the user's click location, click time, corresponding item and other information. The timestamp here is the add-to-cart timestamp reported based on the tracking point when the user clicks the add-to-cart location. This time period can be customized, for example, set to 24 hours.

[0056] It is understandable that in this step, the click event corresponding to the added-to-cart event obtained by backtracking is used as the click event that may trigger the user to place an order. In actual applications, the user can also place an order directly without going through the process of adding to the cart. Therefore, the click event corresponding to the order event with the same user and the same number of visits within a set time period can be directly backtracked according to the order time, and the click event obtained by backtracking is used as the click event that may trigger the user to place an order.

[0057] In an optional embodiment, the acquired click events can be recorded in a data table, that is, the click process of the user's order operation can be recorded in the data table. Each row of the data table records the user account, the clicked slot and slot information, the click timestamp, the item ID, the order ID, etc.

[0058] Step S202: Sort the acquired click events according to the click time to obtain the initial click path corresponding to the user behavior. After acquiring the click events, the click events can be sorted according to the early and late click time (such as click timestamp) to obtain the initial click path.

[0059] Step S203: Determine whether there is a closed-loop path in the current click path, if there is a closed-loop path, execute step S204; if there is no closed-loop path, execute step S209. The initial value of the current click path is the initial click path.

[0060] In the embodiment, it is determined whether the user has a return operation based on the page identifier corresponding to the click event in the click path (i.e., the page identifier of the page to which the click event is triggered). If there is a return operation (i.e., the same page identifier exists), a closed loop path is formed. For example, the page identifier of the home page is defined as 1, the page identifier of the search page is defined as 2, and the page identifier of the item details page is defined as 3. Then the page identifier set corresponding to the click path of the user from the home page - search page - item details page - return to the home page is {1 2 3 1}, and there are two 1s in the page identifier set, forming a closed loop path.

[0061] Step S204: determine in sequence whether the click events in the closed-loop path are correlated with the target object. If the current click event is correlated with the target object, execute step S205; otherwise, execute step S207. If there is a closed-loop path in the current click path, determine in sequence whether the click events in the closed-loop path are correlated with the target object in the order information, such as an item.

[0062] In the embodiment, the ordered item (i.e., the target object) is compared with the operation object corresponding to the click event to determine whether the click event is related to the target object. The correlation determination rule is: if the operation object corresponding to the click event is the same as the category (three-level category in the embodiment for more accurate determination of correlation), store, and SPU of the target object, then it is considered that there is correlation.

[0063] For example, if the ordered item is sneakers 1 and sneakers 2 is clicked during the order process, both are in the shoe category, so the clicked item is relevant to the ordered item; if the ordered item is a rice cooker from store 1 and other items from store 1 are clicked during the order process, the two stores are the same, so the other items are relevant to the ordered item; if the ordered item is a brand X mobile phone (black) and the brand X mobile phone (red) is clicked during the order process, the two have the same SPU, so the red mobile phone is relevant to the ordered item.

[0064] In subsequent calculations, click events with correlation can be considered to have a guiding role in the final order and contribute to the order. In a preferred embodiment, when judging whether a click event in a closed-loop path is correlated with a target object, if there are multiple click events with correlation with the target object, the click event with the latest click time in the closed-loop path is retained.

[0065] Step S205: retain the current click event and the preceding click event of the current click event. Since the click events are sorted from early to late according to the click time, the preceding click events here are all the click events preceding the current click event in the closed-loop path. For example, the current click path is: 1 2 3 4 5 6 3 7 8, where the simplified numbers represent each click operation of the user. In this click path, from 3 to 3 is a closed-loop path. Assuming that 5 in the closed-loop path is a relevant click event, then 3, 4, and 5 are all retained in this closed-loop path, among which 3 and 4 are preceding click events and are retained as the drainage path of 5.

[0066] Step S206: Mark the current click event and the previous click event, and execute step S208. Still taking the closed-loop path in step S203 as an example, if browsing the item details page in the closed-loop path is a relevant click, that is, the click event corresponding to page identifier 3 is a relevant click event, it needs to be marked. The marking logic is: splice the original page identifier with the click time of clicking the page. For example, the original page identifier is underlined and spliced ​​with the timestamp of clicking the page. The following is an example.

[0067] Assuming that the timestamp of the user browsing the item details page is 111, after marking, the page ID of the item details page becomes 3_111. Since the preceding click event also needs to be marked according to the above marking logic, the current click path is changed from 1 2 31 to 1_109 2_110 3_111. The above process realizes the recoding of the click path.

[0068] Step S207: Abandon the closed-loop path and execute step S208.

[0069] Step S208: Update the current click path and execute step S203. As mentioned above, the update here includes discarding irrelevant click events in the closed-loop path, discarding closed-loop paths where all click events are irrelevant, and updating the page identifiers corresponding to the click events.

[0070] Step S209: taking the current click path as the click path that actually triggers the user behavior.

[0071] The data statistics method of the embodiment of the present invention determines whether the user's browsing forms a closed-loop path by determining whether the page identifiers corresponding to the click events in the click path are the same, and then determines whether the items corresponding to each click event are related to the order items to determine whether the closed-loop path is an invalid branch path or a branch path that diverts traffic (contributes to orders), and marks the branch paths that contribute to orders. The click path that truly guides users to place orders is found in the above manner, and the pits corresponding to each click event in the click path are the pits that contribute to orders, ensuring the accuracy of user behavior data analysis.

[0072] The data statistics method of the present invention is further described below in conjunction with specific business scenarios. Assume that the click process of a user placing an order is:

[0073] Home page - Search Mango - Enter Mango details page - Return to home page - Search Shoes 1 - Enter the search list page - Click Shoes 1 - Enter Shoes 1 details page - Return to home page - Search Shoes 2 - Enter Shoes 2 list - Click Shoes 2 - Add to cart and place an order on Shoes 2 details page.

[0074] In the above click process, home page - search for mango - enter mango details page - return to home page, and home page - search for shoes 1 - enter the search list page - click shoes 1 - enter the shoes 1 details page - return to home page are two closed-loop paths, respectively called closed-loop path 1 and closed-loop path 2. Search for shoes 2 - enter the shoes 2 list - click shoes 2 - add to cart and place an order on the shoes 2 details page is the only way for users to place an order, which can be called the trunk path.

[0075] Closed-loop path 1 is not relevant to the last ordered shoe 2, while closed-loop path 2 is relevant to the last ordered shoe 2. Therefore, after de-looping and retaining from step S204 to step S208, the final click path is: homepage - search for shoe 1 - enter the search list page - click shoe 1 - enter the shoe 1 details page - return to homepage - search for shoe 2 - enter the shoe 2 list - click shoe 2 - add to cart and place an order on the shoe 2 details page. This click path is the click path that actually triggers the user behavior.

[0076] Through the data statistics method of the embodiment of the present invention, while recording the main path, the relevant click events are retained, which optimizes the defects of irrelevant branch paths and relevant click events being covered in the existing statistical logic, and can provide the business side with accurate analysis of the pit position and order attraction, which is important for subsequent business scenarios such as personalized recommendation and verification of the quality of marketing activities.

[0077] Figure 3 Schematic diagram of the main modules of the data statistics device according to an embodiment of the present invention. Figure 3As shown, the data statistics device 300 of the embodiment of the present invention mainly includes:

[0078] The acquisition and sorting module 301 is used to acquire the click event that triggers the corresponding user behavior according to the target object in the task information, sort the click event according to the click time, and obtain the initial click path corresponding to the user behavior. The task information is the information generated after the user purchases the target object (i.e., places an order) on the website or APP, including the task identifier and the target object identifier. The target object can be an item, service, etc.

[0079] In the embodiment, the task information is order information, and accordingly, the task identifier is the order identifier, and the target object identifier is the item identifier or the service identifier. User behavior is the behavior that occurs when a user purchases a target object, such as ordering behavior, adding to purchase behavior, etc. The click event obtained by this module is a click event that may trigger user behavior. For example, if the target object is an item, what is obtained here is a click event that may trigger the user to place an order for the item.

[0080] After obtaining the click events, you can sort the click events according to the early and late click times, with the click events with earlier click times in front and the click events with later click times in the back, to get the initial click path.

[0081] The path determination module 302 is used to repeatedly perform the following steps until there is no closed-loop path in the current click path, and obtain the click path that actually triggers the user behavior:

[0082] Determine that the closed-loop path exists in the current click path, and that the current click event in the closed-loop path is relevant to the target object; retain the current click event and the predecessor click event of the current click event, mark the current click event and the predecessor click event, and update the current click path.

[0083] If the user returns during browsing, there will be a click event that jumps to the same page in the current click path, and a closed loop path will be formed. Therefore, it can be seen that the first and last click events of the closed loop path are click events that jump to the same page, that is, the first click event and the last click event will jump to the same page.

[0084] Determine whether the operation object corresponding to the current click event in the closed-loop path and the target object meet the set correlation determination rules. If both meet the correlation determination rules, it is considered that the current click event is correlated with the target object; if both do not meet the correlation determination rules, it is considered that the current click event is not correlated with the target object.

[0085] When marking the current click event and the previous click event, the page ID of the page to which the current click event is redirected and the page ID of the page to which the previous click event is redirected can be marked respectively. After adding the mark, the current click path is updated. Through the above processing, the current click path without a closed-loop path is finally obtained, and the current click path is the click path that actually triggers the user's order behavior.

[0086] From the above description, it can be seen that by finding the closed-loop path in the current click path and retaining the click events in the closed-loop path that are relevant to the target object, the click path that actually triggers the user behavior is completely obtained.

[0087] Figure 4 An exemplary system architecture 400 is shown to which the data statistics method or data statistics device according to the embodiment of the present invention can be applied.

[0088] like Figure 4 As shown, system architecture 400 may include terminal devices 401, 402, 403, network 404 and server 405. Network 404 is used to provide a medium for communication links between terminal devices 401, 402, 403 and server 405. Network 404 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0089] Users can use terminal devices 401, 402, 403 to interact with server 405 through network 404 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 401, 402, 403, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0090] The terminal devices 401 , 402 , and 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0091] Server 405 may be a server that provides various services, such as a background management server that processes order information generated after a user accesses the APP using terminal devices 401, 402, and 403. The background management server may obtain click events obtained from the APP embedding points, and perform processes such as de-looping the click events and retaining relevant click events to obtain processing results, such as obtaining the click path that actually triggers the user behavior.

[0092] It should be noted that the data statistics method provided in the embodiment of the present application is generally executed by the server 405 , and accordingly, the data statistics device is generally set in the server 405 .

[0093] It should be understood that Figure 4 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0094] According to an embodiment of the present invention, the present invention also provides an electronic device and a computer-readable medium.

[0095] The electronic device of the present invention comprises: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement a data statistics method of an embodiment of the present invention.

[0096] The computer-readable medium of the present invention stores a computer program thereon, and when the program is executed by a processor, a data statistics method of an embodiment of the present invention is implemented.

[0097] Reference below Figure 5 , which shows a schematic diagram of the structure of a computer system 500 suitable for implementing an electronic device of an embodiment of the present invention. Figure 5 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0098] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the computer system 500 are also stored. The CPU 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0099] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage section 508 as needed.

[0100] In particular, according to the embodiments disclosed in the present invention, the process described in the main step diagram above can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the main step diagram. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-mentioned functions defined in the system of the present invention are executed.

[0101] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0102] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0103] The modules involved in the embodiments of the present invention may be implemented in software or hardware. The modules described may also be set in a processor. For example, they may be described as: a processor includes an acquisition sorting module and a path determination module. The names of these modules do not constitute a limitation on the modules themselves in some cases. For example, the acquisition sorting module may also be described as "a module that acquires click events that trigger corresponding user behaviors according to the target objects in the task information, sorts the click events according to the click time, and obtains the initial click path corresponding to the user behavior".

[0104] As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by a device, the device includes: according to the target object in the task information, obtaining the click event that triggers the corresponding user behavior, sorting the click events according to the click time, and obtaining the initial click path corresponding to the user behavior; repeatedly performing the following steps until there is no closed-loop path in the current click path, and obtaining the click path that actually triggers the user behavior: determining that there is the closed-loop path in the current click path, and the current click event in the closed-loop path is correlated with the target object; and retaining the current click event and the preceding click event of the current click event, marking the current click event and the preceding click event, and updating the current click path; wherein the initial value of the current click path is the initial click path, and the first and last click events of the closed-loop path are click events that jump to the same page.

[0105] According to the technical solution of the embodiment of the present invention, by finding a closed-loop path in the current click path and retaining click events in the closed-loop path that are relevant to the target object, the click path that actually triggers the user behavior is completely obtained.

[0106] The above product can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0107] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data statistics method, characterized in that: include: According to the target object in the task information, the click event that triggers the corresponding user behavior is obtained, and the click events are sorted according to the click time to obtain the initial click path corresponding to the user behavior; Repeat the following steps until there is no closed-loop path in the current click path, and obtain the click path that actually triggers the user behavior: Determining that the closed-loop path exists in the current click path, and that the current click event in the closed-loop path is correlated with the target object; as well as retaining the current click event and the preceding click event of the current click event, marking the current click event and the preceding click event, and updating the current click path; Among them, the initial value of the current click path is the initial click path, and the first and last click events of the closed-loop path are click events that jump to the same page.

2. The method according to claim 1, characterized in that: Determining that the closed-loop path exists in the current click path includes: According to the page identifier of the page jumped when the click event is triggered, determining whether the same page identifier exists in the page identifier set corresponding to the current click path; The click events corresponding to the same page identifier and the click events corresponding to the page identifiers between the same page identifiers form a closed loop path.

3. The method according to claim 1, characterized in that Determining whether the current click event in the closed-loop path is relevant to the target object includes: If it is determined that the operation object corresponding to the current click event in the closed-loop path and the target object meet a set correlation determination rule, then it is determined that the current click event and the target object are correlated.

4. The method according to claim 3, characterized in that The correlation determination rule includes: the category, store and SPU corresponding to the operation object have any one or more of the same as the category, store and SPU corresponding to the target object.

5. The method according to claim 2, characterized in that: The preceding click event is a click event that is earlier in time than the current click event and belongs to the closed-loop path; Marking the current click event and the previous click event includes: The page identifier of the page to which the current click event is redirected is marked, and the page identifier of the page to which the previous click event is redirected is marked.

6. The method according to claim 5, characterized in that Marking the page identifier of the page to which the current click event is redirected, and marking the page identifier of the page to which the previous click event is redirected, including: concatenating the page identifier of the page to which the current click event is redirected with the timestamp corresponding to the current click event to obtain a new page identifier corresponding to the current click event; and The page identifier of the page jumped to when the preceding click event is triggered is concatenated with the timestamp corresponding to the preceding click event to obtain a new page identifier corresponding to the preceding click event.

7. The method according to any one of claims 1 to 6, characterized in that: The task information includes the time when the task occurs; Get the click event that triggers the corresponding user behavior, including: According to the user identifier corresponding to the task information and the time when the task occurred, the click events with the same user and the same number of visits as those corresponding to the corresponding user behavior within a set time period are traced back.

8. A data statistics device, characterized in that: include: An acquisition and sorting module is used to acquire click events that trigger corresponding user behaviors according to the target objects in the task information, sort the click events according to the click time, and obtain the initial click path corresponding to the user behaviors; The path determination module is used to repeatedly perform the following steps until there is no closed-loop path in the current click path, thereby obtaining the click path that actually triggers the user behavior: Determining that the closed-loop path exists in the current click path, and that the current click event in the closed-loop path is correlated with the target object; as well as retaining the current click event and the preceding click event of the current click event, marking the current click event and the preceding click event, and updating the current click path; Among them, the initial value of the current click path is the initial click path, and the first and last click events of the closed-loop path are click events that jump to the same page.

9. The device according to claim 8, characterized in that The path determination module is further used for: According to the page identifier of the page to which the click event is jumped, determining whether the same page identifier exists in the page identifier set corresponding to the current click path; and The click events corresponding to the same page identifier and the click events corresponding to the page identifiers between the same page identifiers form a closed loop path.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

11. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

Images