Data processing method and apparatus, medium, and electronic device

Abstract

Embodiments of the present application provide a data processing method and device, a medium and an electronic device. The method comprises: determining a jump link of a delivery channel; parsing identification information of a user contained in click data of the jump link from the click data; obtaining behavior data of the user according to the identification information of the user, and determining valid data in the click data according to the behavior data; and determining an advertisement delivery effect of the delivery channel according to the valid data. The present application can improve the accuracy of user traffic tracking.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a data processing method, a data processing device, a storage medium and an electronic device. BACKGROUND

[0002] With the popularity of the Internet and the development of network technology, e-commerce has become the most commonly used means to meet people's transaction needs.

[0003] Generally, a merchant can put his own products on an open e-commerce platform, and the e-commerce platform can also put ads to other media to attract users and increase user traffic. When the e-commerce platform puts ads to third-party media, if the order quantity of the merchant increases, it is also impossible to determine whether the order is converted from the third-party media, and it is impossible to determine which third-party media. Get detailed information. For merchants, it is impossible to adjust their own placement strategy to improve the revenue brought by ad placement.

[0004] Therefore, a method capable of accurately monitoring user traffic is needed.

[0005] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present application, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] The purpose of the embodiments of the present application is to provide a data processing method, thereby at least partially overcoming the problem of being unable to accurately track user traffic converted from an ad placement channel.

[0007] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0008] According to a first aspect of the embodiments of the present application, a data processing method is provided, comprising:

[0009] determining a jump link of a placement channel;

[0010] parsing identification information of a user contained in the click data from the click data of the jump link;

[0011] obtaining behavior data of the user according to the identification information of the user, and determining valid data in the click data according to the behavior data;

[0012] determining an ad placement effect of the placement channel according to the valid data.

[0013] In an example embodiment of the present application, the determination of valid data in the click data according to the behavior data comprises:

[0014] obtain order information, determine a target user according to the order information;

[0015] determine whether a time length between a click time recorded in the click data of the target user and a behavior occurrence time recorded in the behavior data exceeds a first preset time limit;

[0016] determine the click data whose time length between the click time and the behavior occurrence time does not exceed the first preset time limit as valid data.

[0017] In an example embodiment of the present application, the determining valid data in the click data according to the behavior data comprises:

[0018] determine an order time of the target user according to the order information;

[0019] determine whether there is behavior data and click data of the target user within a second preset time limit of the order time;

[0020] if there is behavior data and click data of the target user within the second preset time limit of the order time, determine the click data within the preset time limit of the order time as valid data.

[0021] In an example embodiment of the present application, the obtaining behavior data of the user according to the identification information comprises:

[0022] extract complete information of the target user in a saved user information table according to the identification information;

[0023] obtain browsing data and adding shopping cart data of the target user according to the complete information.

[0024] In an example embodiment of the present application, the determining valid data in the click data according to the behavior data comprises:

[0025] determine click data within a third preset time limit of a browsing time recorded in the browsing data of the target user as valid click data;

[0026] determine click data within the third preset time limit of an adding shopping cart time recorded in the adding shopping cart data of the target user as valid click data.

[0027] In an example embodiment of the present application, the determining the jump link of the delivery channel further comprises:

[0028] generate channel identification information of the delivery channel for each delivery channel;

[0029] A mapping relationship between the jump link and the channel identification information is constructed.

[0030] In an example embodiment of the present application, the determining the advertising effect of the advertising channel according to the valid data comprises:

[0031] A proportion of the valid data in the click data is calculated.

[0032] The advertising channel corresponding to the valid data is determined according to the mapping relationship.

[0033] A user conversion rate of the advertising channel is determined according to the proportion.

[0034] In an example embodiment of the present application, the determining the advertising effect of the advertising channel according to the valid data comprises:

[0035] The identification information of a product corresponding to the jump link is determined.

[0036] The valid data corresponding to the product is determined according to the identification information.

[0037] The advertising effect of the advertising channel for the product is determined according to the valid data corresponding to the product.

[0038] According to a second aspect of the embodiments of the present application, a data processing apparatus is provided, and the apparatus comprises:

[0039] A link determining unit configured to determine a jump link of an advertising channel.

[0040] A data analyzing unit configured to analyze identification information of a user contained in click data of the jump link from the click data.

[0041] A valid data determining unit configured to acquire behavior data of the user according to the identification information of the user, and determine valid data in the click data according to the behavior data.

[0042] A data analyzing unit configured to determine an advertising effect of the advertising channel according to the valid data.

[0043] According to a third aspect of the embodiments of the present application, a computer readable medium is provided, and the medium stores a computer program, and the program is executed by a processor to implement the data processing method of the first aspect of the above embodiments.

[0044] According to a fourth aspect of the embodiments of the present application, an electronic device is provided, comprising: one or more processors; a storage device configured to store one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the data processing method according to the first aspect of the embodiments described above.

[0045] The technical solutions provided by the embodiments of the present application can have the following beneficial effects:

[0046] In the technical solutions provided by some embodiments of the present application, the identification information of the user contained in the click data is parsed from the jump link of the distribution channel, the behavior data of the user is obtained according to the identification information of the user, the effective data in the click data is determined according to the behavior data, and then the advertising distribution effect of the distribution channel is determined according to the effective data; on the one hand, the effective data of each distribution channel can be accurately calculated, so as to determine the advertising effect of the distribution channel; on the other hand, the source of the user traffic can be determined, so as to determine the high-quality distribution channel, adjust the distribution strategy, and maximize the advertising distribution benefit; on the other hand, the user traffic can be more finely divided, the targeting of the advertising distribution is improved, and the user experience is improved.

[0047] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0048] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained from these drawings without creative labor for those skilled in the art. In the drawings:

[0049] Figure 1 The system architecture schematic diagram for implementing the data processing method according to the embodiments of the present application is schematically shown;

[0050] Figure 2 The flowchart of the data processing method according to the embodiments of the present application is schematically shown;

[0051] Figure 3 The flowchart of the data processing method according to another embodiment of the present application is schematically shown;

[0052] Figure 4 The flowchart of the data processing method according to another embodiment of the present application is schematically shown;

[0053] Figure 5a flow chart of a data processing method according to yet another embodiment of the present application is schematically shown;

[0054] Figure 6 a flow chart of a data processing method according to yet another embodiment of the present application is schematically shown;

[0055] Figure 7 a structural schematic diagram of a data processing apparatus according to an embodiment of the present application is schematically shown;

[0056] Figure 8 a structural schematic diagram of a computer system of an electronic device suitable for implementing an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0057] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any

[0058] Moreover, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the

[0059] The block diagrams in the drawings show only the functional entities and not necessarily the physical separate entities. That is, the functional entities can be implemented in software, or in one or more hardware modules or integrated circuits, or in different network and / or processor apparatuses and / or microcontroller apparatuses.

[0060] The flow charts shown in the drawings are only exemplary and do not necessarily include all of the content and operations / steps, nor are they necessarily performed in the order described. For example, some operations / steps can be broken down further, and some operations / steps can be combined or partially combined, so that the actual order of execution can be changed according to the actual situation.

[0061] In the present example implementation, a system architecture for implementing a data processing method is first provided. Referring to Figure 1As shown, the system architecture 100 can include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is a medium for providing a communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 can include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0062] A user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send a request instruction, etc. Various communication client applications can be installed on the terminal devices 101, 102, 103, such as e-commerce applications, shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0063] The terminal devices 101, 102, 103 can be various electronic devices with a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, laptop computers, desktop computers, etc.

[0064] The server 105 can be a server providing various services, such as a background management server supporting a shopping website browsed by a user using a terminal device 101, 102, 103 (only as an example). The background management server can analyze and process received product information query request data, etc., and feed back the processing result (such as target push information, product information - only as an example) to the terminal device.

[0065] It should be noted that the data processing method provided by the embodiments of the present application is generally executed by the server 105, and correspondingly, the data processing apparatus is generally provided in the terminal device 101.

[0066] Based on the above system architecture 100, a data processing method is provided in the present example. As shown, Figure 2 The method can include steps S210, S220, S230, S240. Among them:

[0067] Step S210, determining a jump link of a delivery channel;

[0068] Step S220, parsing identification information of a user contained in the click data from the click data of the jump link;

[0069] Step S230, obtaining behavior data of the user according to the identification information of the user, and determining valid data in the click data according to the behavior data;

[0070] Step S240, determining an advertising delivery effect of the delivery channel according to the valid data.

[0071] According to the data processing method in the example embodiment, the identification information of the user contained in the click data is parsed from the jump link of the delivery channel, the behavior data of the user is obtained according to the identification information of the user, the effective data in the click data is determined according to the behavior data, and then the advertising delivery effect of the delivery channel is determined according to the effective data; on the one hand, the effective data of each delivery channel can be accurately calculated, so as to judge the advertising effect of the delivery channel; on the other hand, the source of the user traffic can be determined, so as to determine the high-quality delivery channel, adjust the delivery strategy, and maximize the revenue of the advertising delivery; and on the other hand, the user traffic can be more finely divided, the targeting of the advertising delivery is improved, and the user experience is improved.

[0072] In the following, the data processing method in the example embodiment will be described in detail. Figures 2 to 6 The steps of the data processing method in the example embodiment will be described in detail.

[0073] As shown in FIG. 2, in step S210, the jump link of the delivery channel is determined. Figure 2

[0074] In the example embodiment, the delivery channel can include various network platforms; or it can also include various media, such as radio, television, Internet, mobile phone, etc.; the example embodiment does not make special limitation on this.

[0075] After the user enters the delivery channel, the user can click the jump link set in the delivery channel, through which the user can jump to another page, which can be an advertising page. The advertising page can include various types of products, such as daily necessities, clothing, home furnishing, etc. The user can also click a product on the advertising page, and after the user clicks the product, the user can jump to the client of the e-commerce platform to preview the detailed information of the product or purchase the product. The e-commerce platform can perform advertising delivery on various goods on its own platform and deliver the advertising on third-party media platforms. At the same time, each merchant can also deliver its goods on the e-commerce platform to improve the revenue by using the user traffic of the e-commerce platform.

[0076] The e-commerce platform can determine a jump link for each delivery channel and make the delivery channel set the jump link in its own platform. In most cases, the delivery channel can determine a jump link for the advertising to be delivered according to the information of its own platform. Therefore, after the jump link of the delivery channel is determined, the channel identification information of the delivery channel can also be generated for each delivery channel; and then the mapping relationship between the jump link and the channel identification information is constructed. Wherein:

[0077] ​The channel identification information can identify each distribution channel. The channel identification information can be a channel identification number. Furthermore, each distribution channel can be subdivided into multiple categories, a first identification number is generated for each category, and a second identification number is generated for each distribution channel in each category, and the first identification number and the second identification number are used as the channel identification information to identify each distribution channel. However, according to actual conditions, the distribution channels can also be classified in a more detailed manner, so as to divide the source channels of user traffic in a more detailed manner.

[0078] After the channel identification information of the distribution channel is determined, a mapping relationship between the jump link and the channel identification information can be constructed. The jump link of each distribution channel can contain the channel identification information of the distribution channel, or the mapping relationship between the jump link and the channel identification information of the distribution channel can be recorded. By saving the jump link and the channel identification information of the distribution channel as a key-value pair, a mapping relationship can be determined, so that after the mapping relationship is obtained, the corresponding distribution channel can be obtained according to the jump link.

[0079] In step S220, the identification information of the user contained in the click data is parsed from the click data of the jump link.

[0080] Reference Figure 2 As shown in the figure, in the example embodiment, the click data can include information of the user who clicks the jump link, such as a device identification number of the user, a username of the user when registering on the distribution channel, an identification number determined by the distribution channel for the user, and the like. The click data can also include field information in the jump link, such as a network address field of the jump link. When the user clicks the jump link, the number of times the user clicks and the time the user clicks can also be obtained, so the click data can also include the number of times the jump link is clicked and the click time of the jump link.

[0081] The distribution channel can record information generated by the click of the jump link in its own log, thereby generating click data. The click data recorded by each distribution channel can be obtained through the interface of each distribution channel. After the click data of the jump link is obtained, the click data can be parsed to parse the identification information of the user contained in the click data. The identification information of the user can be identification information used by the distribution channel to identify each user; or identification information of a terminal device used by the user, such as a device identification number.

[0082] By analyzing the click data, a plurality of fields in the click data can be determined, in which a field for obtaining user identification information in the jump link is found, and then the identification information of the user is obtained. The jump link of the delivery channel can be identified in advance, each parameter in the jump link is identified, and the information corresponding to each parameter is determined, so as to obtain the parameter corresponding to the user identification information. The parameter can be matched in the click data, and the field value of the field matched with the parameter can be used as the identification information of the user.

[0083] In step S230, the behavior data of the user is obtained according to the identification information of the user, and the valid data in the click data is determined according to the behavior data.

[0084] In the example embodiment, the behavior data of the user can include various data generated by the user on the e-commerce platform, such as browsing data, shopping data, click data, etc. However, the behavior data can also include other data, such as order data, order records, etc. of the user, which are not specially limited in the example embodiment.

[0085] According to the identification information of the user, all data containing the identification information in the log file can be found, and the found data is used as the behavior data of the user. Various behaviors of the user can be recorded through the log, such as clicking, browsing, adding to the shopping cart, etc., and then the log file is generated. Of course, various behaviors of the user can be classified, and correspond to a plurality of log files, such as browsing log, click log, etc.

[0086] After obtaining the behavior data of the user, it can be judged whether the behavior data of the user is generated after the user clicks the jump link in the delivery channel, that is, whether the behavior data of the user is related to the jump link. If the behavior data of the user is related to the jump link of the delivery channel, the click data related to the behavior data can be determined as valid data. The user clicks the jump link to generate click data, and various behaviors of the user on the e-commerce platform can also generate behavior data, so the time of the behavior data and the click data of the user can be used to determine the valid data. For example, it can be judged whether there is behavior data of the user within a specific time range of the time when the user's click data is generated, if so, the click data can be used as valid data.

[0087] Determining the valid data in the click data according to the behavior data can include steps S301-S303, as shown in Figure 3

[0088] In step S301, order information is obtained, and a target user is determined according to the order information.

[0089] ​Step S302, determining whether the time length between the click time recorded in the click data of the target user and the behavior occurrence time recorded in the behavior data exceeds a first preset time limit.

[0090] Step S303, determining the click data whose time length between the click time and the behavior occurrence time does not exceed the first preset time limit as valid data.

[0091] Reference Figure 3 As shown in step S301, the order information can include transaction information of various goods, such as amount, discount ratio, product name, etc. The order information can also include identification information of the user who places an order, such as the user's identification number, etc. The present embodiment does not make special limitations on this.

[0092] When a user purchases goods in an e-commerce platform, the information of the user and the goods can be recorded, and the transaction details can be recorded. The order details table can be obtained as order information, or the information in the order details table can be extracted as order information. However, the order information can also be recorded at the time of order completion according to the required order data, such as the identification number of the user, the transaction amount, the discount amount, the identification number of the merchant to which the goods belong, etc.

[0093] After obtaining the order information, the target user can be determined according to the order information. The target user can be determined according to the identification number of the user contained in the order information. The target user can be the user who completes the transaction. The click data of the target user can be extracted according to the identification number of the target user.

[0094] Further, in step S302, the time of each behavior occurrence recorded in the behavior data of the target user can be obtained according to the behavior data of the target user. The time of each behavior data can be recorded when each behavior data is recorded, so as to determine the behavior occurrence time. Similarly, the click time recorded in the click data of the target user can also be obtained. The click time can include the time of each click of the target user on the jump link. Further, whether the time length between the click time and the behavior occurrence time exceeds a first preset time limit can be determined. The first preset time limit can be determined according to actual needs, such as 10 days, 15 days, etc. The present embodiment does not make special limitations on this.

[0095] In step S303, if it is determined that the time length between the click time and the behavior occurrence time does not exceed the first preset time limit, the click data within the first preset time limit can be determined as valid data.

[0096] In some embodiments of the present application, determining the valid data in the behavior data and the click data can also include steps S401 to S403, as shown. Figure 4 wherein:

[0097] In step S401, the order time of the target user is determined according to the order information.

[0098] In step S402, it is determined whether the behavior data and the click data of the target user exist within a second preset time limit of the order time.

[0099] In step S403, if the behavior data and the click data of the target user exist within the second preset time limit of the order time, the click data is determined as valid data.

[0100] Reference Figure 4 In the example embodiment, for step S401, the order time of the user can include the time when the user submits an order, or the time when the purchase is determined. However, the order time of the user can also be other time, such as the time when the user pays, etc. The order information can record the order time of each order, and the order time of the target user can be determined from the order information according to the identification information of the target user.

[0101] In step S402, after the order time of the target user is determined, it is determined whether the behavior data and the click data of the target user exist within a second preset time limit of the order time. The behavior data occurring within the preset time limit can be filtered out through the behavior occurrence time recorded in each piece of behavior data. Similarly, the time when the click data is generated can be determined through the click time recorded in the click data. Then it is determined whether the behavior data and the click data exist within the second preset time limit.

[0102] In step S403, if it is determined that the behavior data and the click data of the user exist within the second preset time limit of the order time, the click data can be determined as valid data. In addition, the valid data can also be determined by other means, such as determining the click data within the preset time limit of the order time as valid data, etc. In addition, the second preset time limit can be a specific time period ending at the order time, such as the previous 10 days, the previous 15 days, etc. However, the second preset time limit can also be other time period before the order time, such as 24 hours before the order time, etc.

[0103] Continuing to refer to Figure 2 In step S240, the advertising effect of the delivery channel is determined according to the valid data.

[0104] In the example embodiment, after determining the valid data, the advertisement delivery effect of the delivery channel can be determined according to the valid data. The advertisement delivery effect of the delivery channel can be determined by various indicators, such as user conversion rate, click rate, conversion transaction amount, etc. The valid data can be data in the click data of the delivery channel that meets the condition, so the delivery channel to which the valid data belongs can be determined according to the channel identification information contained in the click data. Then, the ratio between the click data and the valid data is calculated, and the ratio is taken as the user conversion rate of the delivery channel. Alternatively, other indicators of the delivery channel can also be calculated according to the valid data, such as the order quantity and order amount of the user in the valid data to determine the order quantity, amount, etc. of the delivery channel.

[0105] In some embodiments, the advertisement delivery effect of the delivery channel can also be determined according to the ratio of the valid data in the click data; then the delivery channel corresponding to the valid data is determined according to the mapping relationship between the jump link and the channel identification information; and then the user conversion rate of the delivery channel is determined according to the ratio.

[0106] The click data of the user recorded in the delivery channel record can include information of the jump link of the delivery channel, and the delivery channel to which the click data belongs can be determined according to the mapping relationship between the jump link and the channel identification information. After determining the delivery channel of the click data, the ratio of the valid data in the click data can be determined, and the user conversion rate of each delivery channel can be determined according to the ratio. However, the user conversion rate of the delivery channel can also be calculated by other methods, such as calculating the ratio between the user quantity of the delivery channel and the user quantity in the click data to determine the user conversion rate of the delivery channel, etc.

[0107] In some embodiments of the present application, the advertisement delivery effect of the delivery channel can be determined according to the valid data by determining the identification information of the product corresponding to the jump link; then the valid data corresponding to the product is determined according to the identification information; and then the advertisement delivery effect of the delivery channel for each product is determined according to the valid data corresponding to the product.

[0108] When the user clicks the jump link, the user can be jumped to an advertisement page, which can include multiple products. These products can be the products corresponding to the jump link, and then the identification information of the product can be determined. After determining the identification information of the product, the valid data corresponding to the product can be determined through the identification information. Since the same delivery channel can deliver multiple types of products, each type of product can determine a jump link, and the jump link clicked by the user in the delivery channel is different, and the advertisement page entered is also different, so the jump link corresponding to the advertisement page containing the identification information of the product can be determined according to the identification information of the product. In the jump link of the product, the click data of the jump link can be determined, and then the valid data corresponding to the product can be determined.

[0109] According to the effective data corresponding to the commodity, the advertising effect of the delivery channel on each commodity is determined. According to the transaction volume of the commodity, the total sales of the commodity corresponding to the effective data can be determined, and then the delivery effect of the delivery channel on the commodity is determined according to the total sales, such as the income promoted by the delivery channel and the like. Determining the advertising effect of the delivery channel on each commodity can determine the commodity with the best delivery effect of the delivery channel, and then the merchant can adjust the strategy and the advertising input according to the advertising effect to improve the income.

[0110] In some embodiments of the present application, the step of obtaining the behavior data of the user according to the identification information can further include steps S501 and S502, as shown in the following. Figure 5

[0111] In step S501, the complete information of the target user is extracted from the saved user information table according to the identification information.

[0112] In step S502, the browsing data and the shopping cart data of the target user are obtained according to the complete information.

[0113] Referring to Figure 5 In step S501, after obtaining the identification information of the user from the click data, the complete information of the target user can be extracted from the user information table in the database. In detail, the identification information of the user can be included in the click data recorded by the delivery channel, which can be obtained by the delivery channel when the user clicks the jump link. According to the identification information, the complete information of the user can be found in the user information table. For example, the identification information of the user obtained through the click data is the physical device identification number of the user, and the user information containing the physical device identification number is found in the user information table through the physical device identification number, and then the user name, user identification number, network protocol address and other information of the user are obtained. The user information table can include the information recorded by the e-commerce platform when the user registers or logs in on the e-commerce platform.

[0114] ​After obtaining the complete information of the target user, in step S502, the browsing data and the cart adding data of the target user can be obtained according to the complete information of the user. In detail, the browsing data and the cart adding data of the target user can be obtained according to the username of the target user; the browsing data and the cart adding data of the target user can be obtained according to the user identification number of the target user; or the behavior data of the target user can be filtered according to other information in the complete information of the target user. The browsing data can include records generated when the target user browses the product detail page; or the browsing data can include records generated when the target user browses other pages, such as a user comment page of a product. The cart adding data can include records generated when the target user adds a product to the shopping cart, or records generated when the target user enters the shopping cart page. However, the cart adding data can also include other data, such as records of clicks of the user on the shopping cart page.

[0115] Further, after obtaining the browsing data and the cart adding data of the target user, determining the valid data in the click data according to the behavior data can include steps S601 and S602, as shown in Figure 6 .

[0116] In step S601, the click data within a third preset time limit of the browsing time recorded in the browsing data of the target user is determined as valid click data.

[0117] In step S602, the click data within a third preset time limit of the cart adding time recorded in the cart adding data of the target user is determined as valid click data.

[0118] Referring to Figure 6 , the browsing time of the target user can be determined according to the browsing data of the target user, and the cart adding time of the target user can be determined according to the cart adding data of the target user. Then, the click data within a preset time limit of the browsing time is determined as valid click data, and the click data within a preset time of the cart adding time is determined as valid data. Thus, by further refining the behavior data of the user, the influence of the click data on the user behavior data can be analyzed more finely, and the accuracy of the delivery effect analysis can be improved.

[0119] The following describes an embodiment of a device of the present application, which can be used to execute the data processing method of the present application described above. As shown in Figure 7 , the data processing device 70 can include:

[0120] A link determination unit 71 is configured to determine a jump link of a delivery channel.

[0121] The data analysis unit 74 is configured to determine the advertising delivery effect of the delivery channel according to the effective data.

[0122] The effective data determination unit 73 is configured to acquire behavior data of the user according to the identification information of the user, and determine effective data in the click data according to the behavior data.

[0123] The data analysis unit 74 is configured to determine the advertising delivery effect of the delivery channel according to the effective data.

[0124] In an exemplary embodiment of the present application, the effective data determination unit 73 comprises:

[0125] The order acquisition unit 701 is configured to acquire order information, and determine a target user according to the order information.

[0126] The first judgment unit 702 is configured to determine whether a time length between a click time recorded in the click data of the target user and a behavior occurrence time recorded in the behavior data exceeds a first preset time limit.

[0127] The first effective data determination unit 703 is configured to determine the click data with the time length between the click time and the behavior occurrence time not exceeding the first preset time limit as effective data.

[0128] In an exemplary embodiment of the present application, the effective data determination unit 73 comprises:

[0129] The order time determination unit 704 is configured to determine an order time of the target user according to the order information.

[0130] The second judgment unit 705 is configured to determine whether there is behavior data and click data of the target user within a second preset time limit of the order time.

[0131] The second effective data determination unit 706 is configured to determine the click data within the second preset time limit of the order time as effective data if there is behavior data and click data of the target user within the second preset time limit of the order time.

[0132] In an exemplary embodiment of the present application, the effective data determination unit 73 comprises:

[0133] The information acquisition unit 707 is configured to extract complete information of the target user in a saved user information table according to the identification information.

[0134] The behavior data acquisition unit 708 is configured to acquire browsing data and add-to-cart data of the target user according to the complete information.

[0135] In an example embodiment of the present application, the effective data determination unit 73 comprises:

[0136] A third effective data determination unit 709 is configured to determine the click data within a third preset time period of the browsing time recorded in the browsing data of the target user as effective click data.

[0137] A fourth effective data determination unit 710 is configured to determine the click data within the third preset time period of the add-to-cart time recorded in the add-to-cart data of the target user as effective click data.

[0138] In an example embodiment of the present application, the device further comprises:

[0139] A channel identification unit 711 is configured to generate channel identification information of each delivery channel.

[0140] A data mapping unit 712 is configured to construct a mapping relationship between the jump link and the channel identification information.

[0141] In an example embodiment of the present application, the data analysis unit 74 comprises:

[0142] A calculation unit 713 is configured to calculate the proportion of the effective data in the click data.

[0143] A channel determination unit 714 is configured to determine the delivery channel corresponding to the effective data according to the mapping relationship.

[0144] A conversion rate determination unit 715 is configured to determine the user conversion rate of the delivery channel according to the proportion.

[0145] In an example embodiment of the present application, the data analysis unit 74 comprises:

[0146] A product identification determination unit 716 is configured to determine the identification information of the product corresponding to the jump link.

[0147] A product data determination unit 717 is configured to determine the effective data corresponding to the product according to the identification information.

[0148] An effect analysis unit 718 is configured to determine the advertisement delivery effect of the delivery channel for the product according to the effective data corresponding to the product.

[0149] Since the respective functional modules of the data processing apparatus in the exemplary embodiment of the present application correspond to the steps of the exemplary embodiments of the data processing method described above, for details not disclosed in the present application apparatus embodiments, please refer to the above-described data processing method embodiments of the present application.

[0150] Reference is made below in detail to Figure 8 , which shows a structural schematic diagram of a computer system 800 of an electronic device suitable for implementing embodiments of the present application. Figure 8 The computer system 800 of the electronic device shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present application.

[0151] As shown in Figure 8 , the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 802 or programs loaded from a storage portion 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for system operation are also stored. The CPU 801, the ROM 802, and the RAM 803 are connected to each other through a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0152] The following components are connected to the I / O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output portion 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like; a storage portion 808 including a hard disk, and the like; and a communication portion 809 including a network interface card such as a LAN card, a modem, and the like. The communication portion 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is mounted on the drive 810 as necessary, so that a computer program read therefrom is installed into the storage portion 808 as necessary.

[0153] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication portion 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-described functions defined in the system of the present application are performed.

[0154] It should be noted that the computer-readable medium shown in the present application can 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, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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 application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component. In the present application, the computer-readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, which can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or component. The program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0155] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code containing one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different order than that shown in the drawings. For example, two blocks that are shown in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0156] The units described in the embodiments of the present application can be implemented by software, or by hardware, or by a combination of software and hardware. The units described can be located in a single processor, or distributed over several processors.

[0157] As another aspect, the present application also provides a computer readable medium, which can be included in the electronic device described in the above embodiments, or can exist independently without being assembled into the electronic device. The computer readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the data processing method described in the above embodiments.

[0158] For example, the electronic device can implement the steps shown in Figure 2 S210, determining a jump link of a delivery channel; S220, parsing identification information of a user contained in click data of the jump link from the click data; S230, obtaining behavior data of the user according to the identification information of the user, and determining valid data in the click data according to the behavior data; S240, determining an advertising delivery effect of the delivery channel according to the valid data.

[0159] For another example, the electronic device can implement the steps shown in Figure 3

[0160] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, such division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into several modules or units.

[0161] From the above description of the embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a U disk, a mobile hard disk, etc.) or a network, and includes several instructions to make a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) execute the methods according to the embodiments of the present application.

[0162] ​Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

[0163] It is to be understood that the application is not limited to the precise construction herein described and as shown in the attached drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is to be indicated by the appended claims, rather than the description and examples.

Claims

1. A data processing method, characterized in that, include: The redirect links for each distribution channel are determined, and each distribution channel has its own redirect link. The distribution channels include various network platforms. The distribution channels are divided into multiple categories, and a first identifier is generated for each category. A second identifier is generated for each distribution channel in each category. The first identifier and the second identifier are used as channel identification information to identify each distribution channel. Parse the user's identification information contained in the click data of the redirect link; The user's behavioral data is obtained based on the user's identification information, and the valid data in the click data is determined based on the behavioral data. The valid data refers to the data generated after the user clicks the corresponding jump link on the advertising channel. The effectiveness of advertising through the aforementioned channels is determined based on the valid data. The step of determining the valid data in the click data based on the behavioral data includes: Obtain order information and determine the target user based on the order information; Determine whether the time interval between the click time recorded in the click data of the target user and the time of the behavior recorded in the behavior data exceeds a first preset time limit; Click data whose duration between the click time and the behavior occurrence time does not exceed the first preset time limit is considered valid data. Determining the advertising performance of the delivery channel based on the valid data includes: Calculate the proportion of valid data in the click data, and determine the delivery channel corresponding to the valid data based on the mapping relationship between the jump link and the channel identification information; The user conversion rate of the advertising channel is determined based on the stated ratio. Determining the advertising performance of the delivery channel based on the valid data includes: Determine the identification information of each product corresponding to the redirect link; The valid data corresponding to each product is determined based on the identification information; Based on the valid data corresponding to the product, determine the advertising effectiveness of the delivery channel for the product.

2. The data processing method according to claim 1, characterized in that, The step of determining the valid data in the click data based on the behavioral data includes: The order placement time of the target user is determined based on the order information; Determine whether the target user's behavior data and click data exist within the second preset time period of the order placement time; If the target user's behavior data and click data exist within the second preset time period of the order placement time, the click data within the preset time period of the order placement time is determined to be valid data.

3. The data processing method according to claim 1, characterized in that, The step of obtaining the user's behavioral data based on the identification information includes: Based on the identification information, extract the complete information of the target user from the saved user information table; Based on the complete information, obtain the target user's browsing data and shopping cart data.

4. The data processing method according to claim 3, characterized in that, The step of determining the valid data in the click data based on the behavioral data includes: Click data within a third preset time period of the browsing time recorded in the browsing data of the target user is determined to be valid click data; Click data within the third preset time period recorded in the target user's shopping cart data is determined to be valid click data.

5. The data processing method according to claim 1, characterized in that, After determining the redirect link for the distribution channel, the process also includes: Construct a mapping relationship between the jump link and the channel identification information.

6. A data processing apparatus, characterized in that, include: The link determination unit is used to determine the jump links of the delivery channels, and each delivery channel has its own jump link; wherein, the delivery channels include various network platforms, the delivery channels are divided into multiple categories, a first identifier is generated for each category, and a second identifier is generated for the delivery channels in each category, so as to use the first identifier and the second identifier as channel identification information to identify each delivery channel. A data parsing unit is used to parse the user's identification information contained in the click data of the redirect link; The valid data determination unit is used to obtain user behavior data based on the user's identification information, and determine valid data in the click data based on the behavior data. The valid data refers to the data generated after the user clicks the corresponding jump link on the advertising channel. A data analysis unit is used to determine the advertising performance of the delivery channels based on the valid data. The valid data determination unit includes: An order acquisition unit is used to acquire order information and determine the target user based on the order information. The first judgment unit is used to determine whether the duration between the click time recorded in the click data of the target user and the behavior occurrence time recorded in the behavior data exceeds a first preset time limit. The first valid data determination unit is used to determine that click data whose duration between the click time and the behavior occurrence time does not exceed the first preset time limit is valid data. The data splitting unit includes: A calculation unit is used to calculate the proportion of valid data in the click data; The channel determination unit is used to determine the delivery channel corresponding to the valid data based on the mapping relationship between the jump link and the channel identification information. A conversion rate determination unit is used to determine the user conversion rate of the advertising channel based on the ratio. The data analysis unit includes: A product identifier determination unit is used to determine the identifier information of the product corresponding to the jump link; A product data determination unit is used to determine the valid data corresponding to the product based on the identification information; The effect analysis unit is used to determine the advertising effect of the delivery channel for the product based on the valid data corresponding to the product.

7. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the data processing method as described in any one of claims 1 to 5.

8. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the data processing method as described in any one of claims 1 to 5.

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