Computer internet marketing management system and method

Abstract

The invention discloses a computer internet marketing management system and method, and relates to the technical field of internet marketing management, and the system comprises an information acquisition module, an information analysis module, a marketing scheme making module and a marketing scheme optimization module. According to the method, the historical order information and the search keyword information of the target user and the commodity information of the merchants in the shopping platform are obtained, then the consumption attention indexes of the target user are obtained through analysis, and meanwhile the consumption sets of the target user and the merchant sets in the shopping platform are constructed; and then each consumption set of the target user is matched with each merchant set in the shopping platform, a matching result and each consumption attention index of the target user are synthesized to formulate a marketing scheme, and when the target user searches for different keywords, the shopping platform displays different merchant display pages according to the marketing scheme. And thus, the completeness and flexibility of the marketing scheme are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of Internet marketing management, and in particular to a computer Internet marketing management system and method. Background Art

[0002] With the continuous development of the Internet, users' shopping choices have gradually tended to be diversified and refined. At the same time, the competition between various shopping platforms and merchants has continued to intensify. At this time, the one-to-one precision marketing method between merchants and users can, on the one hand, meet the consumption needs of users and save users' shopping time. On the other hand, it can also achieve precise promotion of merchants, save marketing budgets, and achieve a win-win situation for users and merchants. Therefore, this application proposes a computer Internet marketing management system and method.

[0003] The prior art, such as the invention application patent with announcement number: CN116051241A, discloses an e-commerce management platform based on big data. It includes a registration and login module, an information collection module, an information analysis module, a merchant management module, a product display module, and an order management module. The information collection module is used to collect user information, product information, and product rating information, and transmit the collected information to the information analysis module, including a user information collection unit, a merchant information collection unit, and a product rating collection unit; the information analysis module includes a cloud computing unit and an edge computing unit, and uses the cloud computing unit to process big data information to obtain a computing model of the individual preferences of active users and problematic product information, and uses the edge computing unit to process short-term user behavior or tourist users, and uses the model obtained by the cloud computing unit to instantly recommend products, and transmits the results of the information analysis to the merchant management module and the product display module.

[0004] With respect to the above scheme, there are the following technical problems: 1. The current technology mainly collects user information, product information and product rating information, and then analyzes and obtains instant recommended products. Currently, it mainly analyzes the products that users have purchased, and lacks analysis of user search products and analysis of related products purchased by users. The current technology ignores this level. On the one hand, it leads to the inaccurate analysis of the instant recommended products, which affects the sales of merchants' products. On the other hand, it leads to a decline in user consumption experience, which is not conducive to the long-term development of the e-commerce platform.

[0005] 2. Current technology mainly analyzes user preferences for products based on their ratings of the products, but ignores the problem of missing information when users do not have the habit of evaluating products, and also ignores the problem of how to recommend products that users have not purchased. It also lacks analysis of product style, quality, and price, and thus cannot guarantee the accuracy and completeness of current technology. Summary of the invention

[0006] The purpose of this application is to provide a computer Internet marketing management system and method to solve the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present application adopts the following technical solutions: In the first aspect, the present application provides a computer Internet marketing management system, an information acquisition module: used to obtain the historical order information of the target user through the shopping platform and the search keyword information of the target user through the search engine, and to count the product information of each merchant on the shopping platform.

[0008] Information analysis module: used to obtain the consumption attention index of target users based on the historical order information and search keyword information, build the consumption set of target users, and build each merchant set based on the product information of each merchant in the shopping platform.

[0009] Marketing plan formulation module: used to match the consumption set of target users with the collection of merchants, and formulate marketing plans based on the matching results and the consumption attention indexes of target users.

[0010] Marketing plan optimization module: used to collect feedback from target users after the marketing implementation period is set, and then optimize the marketing plan.

[0011] Preferably, the historical order information includes commodity categories, consumption times of commodities in each category and total consumption price of commodities in each category; keyword information includes commodity category keywords and search times, commodity style keywords and search times, commodity quality and performance keywords and search times and commodity price keywords and search times; commodity information includes merchant-defined commodity information and buyer-evaluated commodity information in the shopping platform, wherein merchant-defined commodity information includes commodity categories and commodity unit prices, and seller-evaluated commodity information includes commodity quality and performance and commodity style.

[0012] Preferably, the specific process of constructing each consumption set of the target user is as follows: S1, extracting the commodity category keywords consumed and searched by the target user based on each historical order information and each keyword search information of the target user, and constructing the commodity category consumption set U of the target user j , and extract the category keywords of the related products of the products consumed and searched by the target user, and construct the target user's related product category consumption set U j ′.

[0013] S2. Extract the style keywords of each category of goods purchased and searched by the target user based on each target user's historical order information and keyword search information, and construct the target user's style consumption set F for each category of goods j ; Similarly, construct the target user's mass-energy consumption set R for each category of goods jand the target user's price consumption set W for each category of goods j .

[0014] Preferably, the merchant sets are constructed according to the commodity information of each merchant in the shopping platform, and the specific process is as follows: A1. The commodity category keywords of each merchant are extracted based on the commodity information of each merchant in the shopping platform to construct the merchant category set U in the shopping platform.

[0015] A2. Extract the product style keywords of each category of merchants based on the product information of each merchant on the shopping platform, and construct the product style set F of each category of merchants v ′, and similarly construct the commodity quality and energy set R of each category of merchants v ′ and the price set W of each category of merchants v ′, where v represents the serial number of each merchant in the shopping platform, v=1,2......e, and e is any integer greater than 2.

[0016] Preferably, the target user's consumption set and each merchant set are matched, and the specific process is as follows: Comprehensive target user's consumption set of each commodity category U j , the target user's consumption set of related product categories U j ′ and the merchant category set U in the shopping platform, according to the calculation formula: Analyze and obtain the compatibility index between target users and shopping platforms Among them, λ1 and λ2 represent the weight factor corresponding to the compatibility between the user and the merchant's products and the weight factor corresponding to the compatibility between the user and the merchant's associated products, respectively.

[0017] Comprehensive target user's style consumption set of various categories of goods F j and the product style set F of each merchant in the shopping platform v ′, the mass-energy consumption set R of each category of goods of the target user j and the product quality and energy set R of each merchant on the shopping platform v ′, according to the calculation formula: Analyze and obtain the buyer evaluation compatibility index between target users and products in each category of stores Among them, γ1 and γ2 represent the weight factors corresponding to the product styles of users and merchants and the weight factors corresponding to the product quality of users and merchants respectively.

[0018] The price consumption set Wj of each category of commodities of the comprehensive target user and the commodity price set Wj of each merchant in the shopping platform v ′, according to the calculation formula Analyze and obtain the merchant customized information adaptation index between target users and merchants of various categories

[0019] The shopping platform adaptation index of the comprehensive target user, the buyer evaluation information adaptation index of the target user and each merchant, and the merchant customized information adaptation index of the target user and each merchant are calculated according to the formula Get the recommendation index of each category of stores for target users

[0020] Preferably, a marketing plan is formulated based on the matching results and the target users' consumer attention indexes. The specific process is as follows: when the target user performs a keyword search for a category of goods on the homepage of the shopping platform, the target user's attention index for each style, each quality and energy, and each price in the category of goods is obtained based on the target user's consumer attention index, and the product attribute corresponding to the maximum value of each consumer attention index of the target user is combined with the target user's adaptation index of the merchant's customized information and the target user's buyer evaluation adaptation index of the merchant in the category to build a display page for the target user's merchant in the category, and the target user's merchant display pages of each category are obtained accordingly.

[0021] When the target user performs a price keyword search for a certain category of goods on the shopping platform, the adaptation index of the target user and the merchant customized information of the merchant in this category is obtained and sorted from large to small to build a merchant display page of this category for the target user, and based on this, the merchant display pages of each category for the target user are obtained.

[0022] When the target user searches for the quality, efficacy or style of a certain category of goods on the shopping platform, the buyer evaluation compatibility index between the target user and the merchants in this category is obtained and sorted from large to small to build a display page of merchants in this category for the target user, and based on this, the display pages of merchants in each category for the target user are obtained.

[0023] When the target user browses the homepage of the shopping platform, the recommendation index of each category of stores of the target user is obtained, and they are sorted from large to small to build the homepage page of the shopping platform of the target user, and the homepage page of the shopping platform of the target user is obtained accordingly.

[0024] Preferably, after the marketing plan is implemented for a set period, feedback from target users is collected. The specific process is as follows: the number of consumption of the target user is obtained based on the historical order information of the target user within the set period, and the number of consumption of the target user is substituted into the user consumption frequency evaluation model to output the consumption frequency characteristic value of the target user. The consumption frequency characteristic value contains data of -1 and 1. When the consumption frequency characteristic value of the target user is 1, it indicates that the marketing plan is effective for the target user, and the marketing plan corresponding to the target user is recorded as a non-optimization plan; when the consumption frequency characteristic value of the target user is -1, it indicates that the marketing plan is ineffective for the target user, and the marketing plan corresponding to the target user is recorded as a plan to be optimized.

[0025] Preferably, the marketing plan is optimized, and the specific process is as follows: for the plan to be optimized, the reasons for the decrease in the number of consumption times of target users are collected in the form of telephone interviews or questionnaires. If the reason for the decrease in the number of consumption times of target users is related to the marketing plan, continue to collect the target users' optimization opinions on the marketing plan, and adjust the marketing plan based on the target users' optimization opinions; if the reason for the decrease in the number of consumption times of target users is not related to the marketing plan, continue to implement the current marketing plan for the target users.

[0026] For plans that are not to be optimized, continue to implement the current marketing plan for target users.

[0027] In a second aspect, the present application provides a computer Internet marketing management method, including: step one, information acquisition: used to obtain the historical order information of target users through a shopping platform and the search keyword information of target users through a search engine, and to count the product information of each merchant in the shopping platform.

[0028] Step 2: Information analysis: It is used to obtain the consumption attention index of the target user according to the historical order information and the search keyword information, construct the consumption set of the target user, and construct the merchant set according to the product information of each merchant in the shopping platform.

[0029] Step 3: Formulate a marketing plan: This is used to match the target user's consumption set with each merchant set, and formulate a marketing plan based on the matching results and the target user's consumption attention index.

[0030] Step 4: Marketing plan optimization: After the marketing implementation period is set, collect feedback from target users and optimize the marketing plan.

[0031] The beneficial effects of the present application are: 1. A computer Internet marketing management system and method provided by the present application obtains the target user's historical order information, search keyword information and product information of each merchant in the shopping platform, and then analyzes and obtains the target user's consumption attention index, and at the same time constructs the target user's consumption sets and the merchant sets in the shopping platform, and then matches the target user's consumption sets and the merchant sets in the shopping platform, and formulates a marketing plan based on the comprehensive matching results and the target user's consumption attention index. When the target user searches for different keywords, the shopping platform displays different merchant display pages according to the marketing plan, thereby ensuring the completeness and flexibility of the marketing plan.

[0032] 2. This application lays the foundation for the formulation of subsequent marketing plans by analyzing the target users' historical order information, search keyword information, and merchant information on the shopping platform.

[0033] 3. This application analyzes the consumer concern indexes of target users, constructs the consumer set of target users and the product set of each merchant, matches the consumer set of target users with the product set of each merchant, and formulates a marketing plan based on the comprehensive matching results and the consumer concern indexes of target users. This application formulates targeted marketing plans for target users, thereby achieving the purpose of precision marketing and greatly reducing the time and financial costs of marketing.

[0034] 4. This application conducts a comprehensive analysis of the target users' historical order information and search keyword information, not only analyzing the product information that the target users have consumed, but also analyzing the product information that the target users are interested in, thereby ensuring the accuracy and completeness of subsequent marketing plans, while also improving the user experience of the shopping platform.

[0035] 5. This application avoids the problem of target users being unable to accurately obtain product information due to false advertising by merchants by conducting a comprehensive analysis of each merchant's customized product information and each buyer's evaluation information of the product. At the same time, different merchant recommendation pages are displayed according to the target user's search keywords, ensuring the flexibility of the marketing plan. This application mainly recommends merchants on the shopping platform to target users, avoiding the problem of a decline in the reputation of the shopping platform due to the uneven sources of recommended products, and also ensuring the exposure of high-quality merchants. At the same time, it guarantees the consumption experience of target users, which is conducive to the long-term development of the shopping platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 This is a schematic diagram of the system structure connection for this application.

[0038] Figure 2 The figure is a flowchart of the implementation steps of the present application method. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0040] Reference Figure 1 As shown, the present application provides a computer Internet marketing management system in the first aspect, including the following modules: an information acquisition module: used to obtain the historical order information of the target user through the shopping platform and the search keyword information of the target user through the search engine, and to count the product information of each merchant in the shopping platform.

[0041] In a specific example, the historical order information includes product categories, consumption times of products in each category, and total consumption price of products in each category; keyword information includes product category keywords and search times, product style keywords and search times, product quality keywords and search times, and product price keywords and search times; product information includes merchant-defined product information and buyer-evaluated product information on the shopping platform, wherein merchant-defined product information includes product category and product unit price, and seller-evaluated product information includes product quality and product style.

[0042] It should be noted that commodity quality can be expressed as commodity quality or function.

[0043] Information analysis module: used to obtain the consumption attention index of target users based on the historical order information and search keyword information, and to construct consumption sets of target users, and to construct merchant sets based on the product information of merchants in the shopping platform.

[0044] It should be noted that each consumer attention index includes the commodity category attention index, the style attention index of each category of commodities, the quality and energy attention index of each category of commodities and the price attention index of each category of commodities.

[0045] It should be noted that each consumption set includes the target user's product category consumption set, the target user's associated product category consumption set, the target user's style consumption set for each category of products, the target user's quality and energy consumption set for each category of products, and the target user's price consumption set for each category of products; each merchant set includes a merchant category set, a product style set of each category of merchants, a product quality and energy set of each category of merchants, and a product price set of each category of merchants.

[0046] In a specific example, the target user's consumption attention index is obtained by analyzing the historical order information and the search keyword information. The specific analysis process is as follows: based on the historical order information and the search keyword information, the target user's consumption times and search times for each style of each category of goods are obtained, and recorded as Y j b and Z j b, where b represents the number of each style, b = 1, 2 ... k', k' is an arbitrary integer greater than 2, j represents the number of each product category, j = 1, 2 ... k, k is an arbitrary integer greater than 2, according to the calculation formula: β j b =Y j b *ζ1+Z j b *ζ2Analysis to obtain the target user's attention index for each style of each category of goods Among them, ζ1 and ζ2 represent the weight factor corresponding to the target user's product style consumption times and the weight factor corresponding to the search times respectively; similarly, the target user's attention index on the quality and energy and the price of each type of product can be obtained by analysis.

[0047] It should be noted that 0<ζ1<1, 0<ζ2<1, ζ1+ζ2=1.

[0048] It should be noted that the factor analysis method is used to obtain the weight factors corresponding to the target user's product style consumption times and the weight factors corresponding to the search times. First, the information condensation of the spatial path attenuation of the consumption times and search times of each style in each category of products of each user is performed, and then the variance explanation rate after rotation is obtained, and the weight is obtained by dividing the cumulative variance explanation rate.

[0049] It should be noted that factor analysis is a well-known technology. It is a multivariate statistical analysis method that starts from studying the internal dependencies of variables and reduces some variables with intricate relationships to a few comprehensive factors; information concentration is expressed as calculating the median; the variance explanation rate is the amount of information extracted by the factor, and the variance explanation rate = characteristic root / total number of analysis items; the variance explanation rate after rotation is expressed as the variance explanation rate of the factor after maximum variance rotation.

[0050] In a specific example, the process of constructing the consumption sets of the target user is as follows: S1, extracting the keywords of the commodity categories consumed and searched by the target user based on the historical order information and keyword search information of the target user, and constructing the consumption sets of the commodity categories of the target user U j , and extract the category keywords of the related products of the products consumed and searched by the target user, and construct the consumption set U of each related product category of the target user j ′.

[0051] S2. Extract the style keywords of each category of goods purchased and searched by the target user based on each target user's historical order information and keyword search information, and construct the target user's style consumption set F for each category of goods j ; Similarly, construct the target user's mass-energy consumption set R for each category of goods jand the target user's price consumption set W for each category of goods j .

[0052] In a specific example, the merchant sets are constructed based on the product information of each merchant in the shopping platform. The specific process is as follows: A1. Based on the product information of each merchant in the shopping platform, the product category keywords of each merchant are extracted to construct the category set U of each merchant in the shopping platform.

[0053] A2. Extract the product style keywords of each merchant based on the product information of each merchant on the shopping platform, and construct the product style set F of each category of merchants v ′, and similarly construct the commodity quality and energy set R of each category of merchants v ′ and the price set W of each category of merchants v ′, where v represents the category number of each merchant in the shopping platform, v=1,2......e, e is any integer greater than 2.

[0054] It should be noted that merchants selling a certain type of goods on the shopping platform are recorded as a certain type of merchants. For example, merchants selling mobile phones, computers and other products are recorded as electronic merchants; merchants selling jackets, pants and other products are recorded as clothing merchants.

[0055] Marketing plan formulation module: used to match the consumption set of target users with the sets of merchants, and formulate marketing plans based on the matching results and the consumption attention indexes of target users.

[0056] In a specific example, the process of matching the consumption set of the target user with the merchant set is as follows: j , the target user's consumption set of related product categories U j ′ and the merchant category set U in the shopping platform, according to the calculation formula: Analyze and obtain the compatibility index between target users and shopping platforms Among them, λ1 and λ2 represent the weight factors corresponding to the compatibility between the user and the merchant's products and the weight factors corresponding to the compatibility between the user and the merchant's associated products, respectively.

[0057] It should be noted that 0<λ1<1, 0<λ2<1, λ1+λ2=1, wherein the setting method of λ1 and λ2 is the same as that of ζ1 and ζ2, and thus will not be described in detail.

[0058] Comprehensive target user's style consumption set of various categories of goods F j and the product style set F of each merchant in the shopping platform v ′, the mass-energy consumption set R of each category of goods of the target user j and the product quality and energy set R of each merchant on the shopping platformv ′, according to the calculation formula: Analyze and obtain the buyer evaluation compatibility index between target users and products in each category of stores Among them, γ1 and γ2 represent the weight factors corresponding to the product styles of users and merchants and the weight factors corresponding to the product quality of users and merchants respectively.

[0059] 0<γ1<1, 0<γ2<1, γ1+γ2=1, wherein the setting method of γ1 and γ2 is the same as that of ζ1 and ζ2, so it is not repeated here.

[0060] The price consumption set W of each category of goods for comprehensive target users j and the price set W of each merchant in the shopping platform v ′, according to the calculation formula Analyze and obtain the merchant customized information adaptation index between target users and merchants of various categories

[0061] The shopping platform adaptation index of the comprehensive target user, the buyer evaluation information adaptation index of the target user and each merchant, and the merchant customized information adaptation index of the target user and each merchant are calculated according to the formula Get the recommendation index of each category of stores for target users

[0062] In a specific example, the marketing plan is formulated according to the matching results and the target user's consumer attention indexes. The specific process is as follows: when the target user performs a keyword search for a category of goods on the homepage of the shopping platform, based on the target user's consumer attention indexes, the target user's attention index for each style, each quality and energy, and each price in the category of goods is obtained, and the product attribute corresponding to the maximum value of each consumer attention index of the target user, the target user and the merchant's customized information of the merchant in the category are integrated. The adaptation index and the target user and the buyer's evaluation adaptation index of the merchant in the category are comprehensively constructed to construct a display page of the merchant in the category for the target user, and the display pages of the merchant in each category of the target user are obtained accordingly.

[0063] When the target user performs a price keyword search for a certain category of goods on the shopping platform, the adaptation index of the target user and the merchant customized information of the merchant in this category is obtained and sorted from large to small to build a merchant display page of this category for the target user, and based on this, the merchant display pages of each category for the target user are obtained.

[0064] When the target user searches for the quality, efficacy or style of a certain category of goods on the shopping platform, the buyer evaluation compatibility index between the target user and the merchants in this category is obtained and sorted from large to small to build a display page of merchants in this category for the target user, and based on this, the display pages of merchants in each category for the target user are obtained.

[0065] It should be noted that when users search for a certain category of product style and quality and energy keywords, by analyzing the historical reviews of the product to determine whether it meets the user's requirements, it can effectively prevent the problem of false advertising by merchants.

[0066] When the target user browses the homepage of the shopping platform, the recommendation index of each category of stores of the target user is obtained, and they are sorted from large to small to build the homepage page of the shopping platform of the target user, and the homepage page of the shopping platform of the target user is obtained accordingly.

[0067] Marketing plan optimization module: used to collect feedback from target users after the marketing implementation period is set, and then optimize the marketing plan.

[0068] It should be noted that the duration of the set cycle is determined by the relevant work, such as one month, three months or six months.

[0069] In a specific example, after the marketing plan is implemented for a set period, feedback from each user is collected. The specific process is as follows: the number of consumptions of each user is obtained based on the historical order information of each user within the set period, and the number is substituted into the user consumption frequency evaluation model to obtain the consumption frequency characteristic value of each user. The consumption frequency characteristic value includes data of -1 and 1. When the consumption frequency characteristic value of a user is 1, it indicates that the marketing plan is effective for the user, and the marketing plan for the user is recorded as a non-optimization plan; when the consumption frequency characteristic value of a user is -1, it indicates that the marketing plan is ineffective for the user, and the marketing plan corresponding to the user is recorded as a plan to be optimized; based on this, each non-optimization plan and each plan to be optimized are obtained.

[0070] It should be noted that the user consumption frequency evaluation model expression is in a represents the consumption frequency of the target users after the implementation of the marketing plan, and a′ represents the consumption frequency of the target users before the implementation of the marketing plan.

[0071] In a specific example, the specific process of optimizing the marketing plan is as follows: for the plan to be optimized, the reasons for the decrease in the number of consumption times of target users are collected in the form of telephone interviews or questionnaires. If the reason for the decrease in the number of consumption times of target users is related to the marketing plan, the optimization opinions of the target users on the marketing plan will continue to be collected, and the marketing plan will be adjusted based on the optimization opinions of the target users; if the reason for the decrease in the number of consumption times of target users is not related to the marketing plan, the current marketing plan will continue to be implemented for the target users.

[0072] For plans that are not to be optimized, continue to implement the current marketing plan for target users.

[0073] It should be noted that the reasons for the decrease in target users' consumption frequency are collected through telephone interviews or questionnaires, including personal reasons and reasons of the shopping platform.

[0074] It should be noted that we collect optimization opinions of target users on the marketing plan and adjust the marketing plan based on the optimization opinions of target users. For example, when the target users reflect that the marketing shopping experience is too much, we appropriately reduce merchant recommendations.

[0075] In a second aspect, the present application provides a computer Internet marketing management method, including: step one, information acquisition: used to obtain the historical order information of target users through a shopping platform and the search keyword information of target users through a search engine, and to count the product information of each merchant on the shopping platform.

[0076] Step 2: Information analysis: It is used to obtain the consumption attention index of the target user according to the historical order information and the search keyword information, construct the consumption set of the target user, and construct the merchant set according to the product information of each merchant in the shopping platform.

[0077] Step 3: Marketing plan formulation module: used to match the consumption set of target users with the sets of merchants, and formulate a marketing plan based on the matching results and the consumption attention indexes of target users.

[0078] Step 4: Marketing plan optimization module: used to collect feedback from target users after the marketing implementation period is set, and then optimize the marketing plan.

[0079] The present application provides a computer Internet marketing management system and method, which obtains the target user's historical order information, search keyword information and product information of each merchant in the shopping platform, and then analyzes and obtains the target user's consumption attention index, and at the same time constructs the target user's consumption sets and the merchant sets in the shopping platform, and then matches the target user's consumption sets and the merchant sets in the shopping platform, and formulates a marketing plan based on the comprehensive matching results and the target user's consumption attention indexes. When the target user searches for different keywords, the shopping platform displays different merchant display pages according to the marketing plan, thereby ensuring the completeness and flexibility of the marketing plan.

[0080] The above contents are merely examples and explanations of the concept of the present application. The technicians in this technical field may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in the present application, they should all fall within the protection scope of the present application.

Claims

1. A computer Internet marketing management system, characterized in that: include: Information acquisition module: used to obtain the target user's historical order information through the shopping platform and the target user's search keyword information through the search engine, and to count the product information of each merchant on the shopping platform; Information analysis module: used to obtain the consumption attention index of target users according to the historical order information and search keyword information, and to construct the consumption set of target users, and to construct the merchant set according to the commodity information of each merchant in the shopping platform; Marketing plan formulation module: used to match the consumption set of target users with the sets of merchants, and formulate marketing plans based on the matching results and the consumption attention indexes of target users; Marketing plan optimization module: used to collect feedback from target users after the marketing implementation period is set, and then optimize the marketing plan.

2. A computer Internet marketing management system according to claim 1, characterized in that: The historical order information includes product categories, consumption times of products in each category and total consumption price of products in each category; keyword information includes product category keywords and search times, product style keywords and search times, product quality keywords and search times and product price keywords and search times; product information includes merchant-defined product information and buyer-evaluated product information on the shopping platform, wherein merchant-defined product information includes product category and product unit price, and seller-evaluated product information includes product quality and product style.

3. A computer Internet marketing management system according to claim 2, characterized in that: The target user's consumption attention index is obtained by analyzing the historical order information and the search keyword information. The specific analysis process is as follows: Based on each historical order information and each search keyword information, the target user's consumption times and search times for each style of each category of goods are obtained and recorded as Y j b and Z j b , where b represents the number of each style, b = 1, 2 ... k', k' is any integer greater than 2, j represents the number of each product category, j = 1, 2 ... k, k is any integer greater than 2, according to the calculation formula: β j b =Y j b *ζ1+Z j b *ζ2Analysis to obtain the target user's attention index for each style of each category of goods Among them, ζ1 and ζ2 represent the weight factor corresponding to the number of times the user consumes a product style and the weight factor corresponding to the number of times the product search style is searched, respectively; similarly, the target user's attention index to the quality and energy and the attention index to the price of each type of product are obtained by analysis.

4. A computer Internet marketing management system according to claim 3, characterized in that: The specific process of constructing each consumption set of the target user is as follows: S1. Extract the keywords of the commodity categories consumed and searched by the target user based on the target user's historical order information and keyword search information, and construct the target user's commodity category consumption set U j , and extract the category keywords of the related products of the products consumed and searched by the target user, and construct the target user's related product category consumption set U′ j ; S2. Extract the style keywords of each category of goods purchased and searched by the target user based on each target user's historical order information and keyword search information, and construct the target user's style consumption set F for each category of goods j ; Similarly, construct the target user's mass-energy consumption set R for each category of goods j and the price consumption set W j .

5. A computer Internet marketing management system according to claim 4, characterized in that: The specific process of constructing merchant sets according to the commodity information of each merchant in the shopping platform is as follows: A1. Extract keywords of product categories of each merchant based on the product information of each merchant on the shopping platform, and construct a merchant category set U on the shopping platform; A2. Extract the product style keywords of each category of merchants based on the product information of each merchant on the shopping platform, and construct the product style set F of each category of merchants v ′, and similarly construct the commodity quality and energy set R of each category of merchants v ′ and the price set W of each category of merchants v ′, where v represents the number of each merchant in the shopping platform, v=1,2......e, e is any integer greater than 2.

6. A computer Internet marketing management system according to claim 5, characterized in that: The specific process of matching the consumption set of the target user with the merchant sets is as follows: Comprehensive target user's consumption set of each commodity category U j , the target user's consumption set of related product categories U′ j And the merchant category set U in the shopping platform, according to the calculation formula: Analyze and obtain the compatibility index between target users and shopping platforms Where λ1 and λ2 represent the weight factors corresponding to the compatibility between the user and the merchant's products and the weight factors corresponding to the compatibility between the user and the merchant's associated products, respectively; Comprehensive target user's style consumption set of various categories of goods F j and the product style set F of each merchant in the shopping platform v ′, the mass-energy consumption set R of each category of goods of the target user j and the product quality and energy set R of each merchant on the shopping platform v ′, according to the calculation formula: Analyze and obtain the buyer evaluation compatibility index between target users and products in each category of stores Among them, γ1 and γ2 represent the weight factors corresponding to the product style of the user and the merchant and the weight factors corresponding to the product quality of the user and the merchant respectively; The price consumption set W of each category of goods for comprehensive target users j and the price set W of each merchant in the shopping platform v ′, according to the calculation formula Analyze and obtain the merchant customized information adaptation index between target users and merchants of various categories The shopping platform adaptation index of the comprehensive target user, the buyer evaluation information adaptation index of the target user and each merchant, and the merchant customized information adaptation index of the target user and each merchant are calculated according to the formula Get the recommendation index of each category of stores for target users 7. A computer Internet marketing management system according to claim 6, characterized in that: The marketing plan is formulated according to the matching results and the consumer attention indexes of the target users. The specific process is as follows: When the target user searches for a keyword of a certain category of goods on the homepage of the shopping platform, based on the target user's consumer attention indexes, the target user's attention indexes for each style, each quality and energy, and each price in the category of goods are obtained, and the product attributes corresponding to the maximum values ​​of the target user's consumer attention indexes are combined with the target user's adaptation index of the merchant's customized information and the target user's buyer evaluation adaptation index of the merchant in the category to construct the target user's merchant display page for the category, and the target user's merchant display pages for each category are obtained accordingly; When the target user searches for a certain category of goods by price keywords on the shopping platform, the target user and the merchant customized information of the merchant in the category are obtained, and the matching indexes are sorted from large to small to construct the merchant display page of the category for the target user, and the merchant display pages of each category for the target user are obtained accordingly; When the target user searches for the quality, efficacy or style of a certain category of goods on the shopping platform, the buyer evaluation compatibility index between the target user and the merchants in the category is obtained, and they are sorted from large to small to construct the merchant display page of the target user in the category, and the merchant display pages of each category of the target user are obtained accordingly; When the target user browses the homepage of the shopping platform, the recommendation index of each category of stores of the target user is obtained, and they are sorted from large to small to build the homepage page of the shopping platform of the target user, and the homepage page of the shopping platform of the target user is obtained accordingly.

8. A computer Internet marketing management system according to claim 7, characterized in that: After the marketing plan is implemented for a set period, feedback from target users is collected. The specific process is as follows: The target user's consumption frequency is obtained based on the target user's historical order information within a set period, and the target user's consumption frequency is substituted into the user consumption frequency evaluation model to output the target user's consumption frequency characteristic value. The consumption frequency characteristic value contains data of -1 and 1. When the target user's consumption frequency characteristic value is 1, it indicates that the marketing plan is effective for the target user, and the marketing plan corresponding to the target user is recorded as a non-optimization plan; when the target user's consumption frequency characteristic value is -1, it indicates that the marketing plan is ineffective for the target user, and the marketing plan corresponding to the target user is recorded as a plan to be optimized.

9. A computer Internet marketing management system according to claim 8, characterized in that: The specific process of optimizing the marketing plan is as follows: For the plan to be optimized, collect the reasons for the decrease in the number of consumption of target users through telephone interviews or questionnaires. If the reason for the decrease in the number of consumption of target users is related to the marketing plan, continue to collect the optimization opinions of the target users on the marketing plan, and adjust the marketing plan based on the optimization opinions of the target users; if the reason for the decrease in the number of consumption of target users is not related to the marketing plan, continue to implement the current marketing plan for the target users; For plans that are not to be optimized, continue to implement the current marketing plan for target users.

10. A computer Internet marketing management method according to claim 1, used to implement a computer Internet marketing management system according to any one of claims 1-9, characterized in that: include: Step 1: Information acquisition: used to obtain the target user's historical order information through the shopping platform and the target user's search keyword information through the search engine, and to count the product information of each merchant on the shopping platform; Step 2: Information analysis: to obtain the target user's consumption attention index according to the historical order information and the search keyword information, to construct the target user's consumption set, and to construct the merchant set according to the commodity information of each merchant in the shopping platform; Step 3: Marketing plan formulation module: used to match the consumption set of target users with the sets of merchants, and formulate a marketing plan based on the matching results and the consumption attention indexes of target users; Step 4: Marketing plan optimization module: used to collect feedback from target users after the marketing implementation period is set, and then optimize the marketing plan.

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