Advertisement marketing effective user screening system based on influence index

Abstract

The invention relates to the technical field of advertisement marketing, and discloses an advertisement marketing effective user screening system based on an influence index, which comprises a data acquisition module and a user screening module. According to the advertisement marketing effective user screening system based on the influence index, a data acquisition module is in network connection with a big data platform to obtain account data of all users clicking brand advertisements, sales record data of all brand commodities and exposure comment data of the brand advertisements in all propagation channels, and the data are classified to form a data set; the user screening module screens out user accounts with historical orders and new customer accounts attracted by brand advertisements, then calculates the ratio of new customers, the average watching duration, the conversion index, the average purchase number and the exposure index, quantifies the attraction degree of the brand advertisements to consumers, deeply analyzes user behaviors, and is high in screening precision and high in efficiency. The advertisement marketing strategy and the propagation channel are flexibly adjusted, and the channel analysis advertisement marketing effect is better.

Description

Technical Field

[0001] The present invention relates to the technical field of advertising and marketing, and in particular to an effective user screening system for advertising and marketing based on influence indicators. Background Art

[0002] In modern marketing, advertising marketing is an important means to promote products and services and establish brand image. In order to effectively convey its information and attract target customers, enterprises need to accurately measure the effectiveness of advertising. Return on investment is a key indicator for measuring advertising effectiveness. It indicates the ratio of the benefits brought by advertising to the cost. A high ROI usually means that the advertising investment has brought a good economic return. Click-through rate is an important indicator for measuring advertising effectiveness. It reflects the ability of an advertisement to attract users to click. A high click-through rate usually indicates that the advertising content and design are attractive to the target audience. Conversion rate refers to the probability of achieving a purchase goal after an advertisement is clicked. A high conversion rate means that the advertisement not only attracts clicks, but also successfully guides users to take further actions. Audience engagement measures the degree of user interaction with the advertising content, including comments, sharing, and likes. High engagement often means that the advertisement arouses the interest and resonance of users. Ad exposure refers to the total number of times an advertisement is displayed to the audience. Although exposure cannot directly measure the effectiveness of advertising, it is crucial to increase brand awareness and exposure. Ad frequency refers to the number of times an advertisement is viewed by the same user within a certain period of time. Moderate ad frequency helps to improve brand memorability, but too high a frequency may cause audience fatigue. The cost per click is the amount advertisers pay for each click. A lower cost per click is good for getting more traffic within a limited budget. Brand awareness reflects the audience's memory and recognition of the brand in the advertisement. A high brand awareness indicates that the advertisement effectively conveys the brand message and enhances the brand image.

[0003] At present, after the traditional advertising and marketing effective user screening system based on influence indicators divides new and old customers, it often ignores the segmentation of user behavior categories, and is unable to deeply analyze the differences between different advertising content and target audiences. The analysis of advertising and marketing conversion data is not accurate enough, which limits the reach of brand advertising. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides an effective user screening system for advertising marketing based on influence indicators, which has the advantages of in-depth analysis of user behavior with high screening accuracy and better channel analysis advertising marketing effect. It solves the problem that the traditional effective user screening system for advertising marketing based on influence indicators cannot deeply analyze user behavior and the analysis of advertising marketing conversion data is not accurate enough.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an effective user screening system for advertising marketing based on influence indicators, comprising a data collection module and a user screening module;

[0008] The data collection module is composed of a user data unit, a transaction record unit and a marketing data unit. The user data unit collects a user data set through a network connection to a big data platform. The user data set includes all user account data that click on brand advertisements. The transaction record unit collects a record data set through a network connection to a big data platform. The record data set includes sales record data of all brand products. The marketing data unit collects a marketing data set through a network connection to a big data platform. The marketing data set includes exposure and comment data of brand advertisements in all communication channels. The data collection module transmits the user data set, the record data set and the marketing data set to the user screening module through the network.

[0009] The user screening module consists of a user analysis unit, a conversion analysis unit and an exposure analysis unit. The user analysis unit screens out user accounts with historical orders and new customer accounts attracted by brand advertisements based on the user data set and the record data set, and generates a new customer ratio Xkzb and an average viewing time t accordingly, which are then transmitted to the conversion analysis unit via the network. The conversion analysis unit analyzes and generates a conversion index Zhzs and an average purchase quantity s based on the record data set, and transmits them to the exposure analysis unit via the network. The exposure analysis unit analyzes and generates an exposure index Bgzs based on the marketing data set, and then outputs a screening report.

[0010] Preferably, the expression of the user data set is {Y1 t 、Y2 t 、Y3 t 、...、Yn t}, Y1 t To Yn t The data of each user account that clicks on the brand advertisement are shown in sequence. The superscript t indicates the length of time the user watches the brand advertisement, and 1 to n indicates that there are n user accounts that click on the brand advertisement.

[0011] Preferably, the expression of the record data set is to The corresponding sales record data of the branded goods in each completed order are shown in sequence. The superscript d indicates the time point of the completed order, the subscript s indicates the sales quantity of the branded goods, and 1 to l indicates that there are l completed orders for the branded goods.

[0012] Preferably, the expression of the marketing data set is {G1 p , G2 p 、G3 p、...、Gu p}, G1 p So far p These correspond to the exposure and comment data of the brand advertisement in each communication channel. The subscript p represents the number of exposure and comments, and 1 to u represents that there are u communication channels for the brand advertisement.

[0013] Preferably, the calculation process of the new customer ratio Xkzb is as follows:

[0014] According to the record data set, the user accounts with historical orders in the user data set are screened out and marked as LY, where LY = {LY1 t LY2 t LY3 t ,...,LYi t}, the superscript t represents the duration of the user watching the brand advertisement, and 1 to i represents that there are i user accounts with historical orders in the user dataset;

[0015] According to the user account LY with historical orders, the new customer accounts attracted by brand advertisements in the user data set are screened out and marked as XY, where XY = {XY1 t 、XY2 t 、XY3 t ,...,XYk t}, the superscript t represents the duration of users watching brand advertisements, and 1 to k represents the number of new customer accounts attracted by brand advertisements;

[0016] k=ni

[0017]

[0018] In the formula, Xkzb represents the proportion of new customers, ni represents the number of n user accounts in the user data set minus the number of i user accounts with historical orders, and the number of new customers k attracted by brand advertising is obtained. The ratio of the number of new customers to the total number of user accounts is the new customer ratio.

[0019] Preferably, the calculation formula for the average viewing time t is as follows:

[0020]

[0021] In the formula, represents the average viewing time. It represents the average viewing time obtained by dividing the total viewing time of brand ads by the number of new customer accounts in the user dataset.

[0022] Preferably, the calculation process of the conversion index Zhzs is as follows:

[0023] According to the new customer account XY attracted by the brand advertisement, the sales record data of the first transaction in the order data set is screened out and marked as SJ, where: The superscript d indicates the time point of the transaction, the subscript s indicates the sales volume of the branded product, and 1 to r indicates that there are r transactions of the first purchase of branded products by new customer accounts attracted by brand advertisements;

[0024]

[0025] In the formula, Zhzs represents the conversion index, The conversion index is the ratio of completed orders from new customer accounts attracted by brand advertising who purchase brand products for the first time to the number of new customer accounts.

[0026] Preferably, the average purchase quantity The calculation formula is as follows:

[0027]

[0028] In the formula, represents the average purchase quantity, It represents the average purchase quantity obtained by dividing the total sales volume of brand products in the completed orders of all new customer accounts by the total number of orders.

[0029] Preferably, the exposure index Bgzs is calculated as follows:

[0030]

[0031] In the formula, Bgzs represents the exposure index, Represents the average number of comments obtained by dividing the total number of comments exposed by all communication channels in the marketing dataset by the number of channels Ge p represents the exposure comment data in the e-th communication channel in the marketing dataset, It means that the variance value of the u pieces of exposure comment data of the communication channel and the average number of comments is calculated through the variance formula, which is the exposure index.

[0032] Preferably, the screening report includes the new customer ratio Xkzb, the average viewing time Conversion index Zhzs, average purchase quantity And exposure index Bgzs.

[0033] Compared with the prior art, the present invention provides an effective user screening system for advertising marketing based on influence indicators, which has the following beneficial effects:

[0034] 1. The present invention obtains the user account data of all users who click on brand advertisements, the sales record data of all brand products and the exposure comment data of brand advertisements in all communication channels through the data acquisition module network connection big data platform, and classifies them into user data set, record data set and marketing data set. The user screening module screens out user accounts with historical orders and new customer accounts attracted by brand advertisements, and generates new customer proportion Xkzb and average viewing time accordingly. Conversion index Zhzs, average purchase quantity And the exposure index Bgzs, quantify the attractiveness of brand advertising to consumers, and deeply analyze user behavior with high screening accuracy.

[0035] 2. The user screening module of the present invention calculates the new customer ratio Xkzb, the average viewing time Conversion index Zhzs, average purchase quantity The exposure index Bgzs forms a screening report and outputs it to advertisers to help them truly understand consumers' click behavior, purchase behavior and comment behavior, flexibly adjust advertising marketing strategies and communication channels, more accurately locate potential high-value users, improve advertising delivery effects, reduce marketing costs, and achieve better channel analysis advertising marketing effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] After the traditional advertising and marketing effective user screening system based on influence indicators divides new and old customers, it often ignores the segmentation of user behavior categories and cannot deeply analyze the differences between different advertising contents and target audiences. The analysis of advertising and marketing conversion data is not accurate enough, which limits the reach of brand advertising. Therefore, an advertising and marketing effective user screening system based on influence indicators is provided. Please refer to Figure 1 ,The system includes a data acquisition module and a user screening module;

[0039] The data collection module consists of a user data unit, a transaction record unit, and a marketing data unit. The user data unit collects user data sets through a network connection to the big data platform. The user data set includes all user account data that click on brand ads. The expression of the user data set is {Y1t 、Y2 t 、Y3 t 、...、Yn t}, Y1 t To Yn t The corresponding data of each user account that clicks on the brand advertisement is shown in sequence. The superscript t indicates the duration of the user viewing the brand advertisement, and 1 to n indicates that there are n user accounts that click on the brand advertisement. The collected user account data directly reflects the actual click volume of the brand advertisement. The longer the user views the brand advertisement, the better the reach of the brand advertisement content.

[0040] The transaction record unit collects the record data set through the network connection big data platform. The record data set includes the sales record data of all brand products. The expression of the record data set is to The sales record data of brand products in each completed order are sequentially corresponded. The superscript d indicates the time point of the completed order, the subscript s indicates the sales quantity of the brand products, and 1 to l indicates that there are l completed orders for brand products. The collected order data is helpful for the subsequent in-depth analysis of user behavior and the rapid screening of effective users attracted by advertising marketing.

[0041] The marketing data unit collects marketing data sets through the network connection big data platform. The marketing data sets include the exposure and comment data of brand advertisements in all communication channels. The expression of marketing data sets is {G1 p , G2 p 、G3 p 、...、Gu p}, G1 p So far p The corresponding data are the exposure and comments of brand advertisements in each communication channel. The subscript p represents the number of exposure comments. 1 to u represent that there are u communication channels for brand advertisements. The number of comments collected from different channels directly reflects the degree of consumers' heated discussion about brand advertisements. The more comments there are, the higher the exposure of brand advertisements in this communication channel.

[0042] The data collection module transmits the user data set, the record data set and the marketing data set to the user screening module through the network;

[0043] The user screening module consists of a user analysis unit, a conversion analysis unit, and an exposure analysis unit. The user analysis unit screens out user accounts with historical orders and new customer accounts attracted by brand advertisements based on the user data set and the record data set, and generates new customer proportion Xkzb and average viewing time t accordingly, which are then transmitted to the conversion analysis unit through the network. The calculation process is as follows:

[0044] According to the record data set, the user accounts with historical orders in the user data set are screened out and marked as LY, where LY = {LY1 t LY2 t LY3 t ,...,LYi t}, the superscript t represents the duration of the user watching the brand advertisement, and 1 to i represents that there are i user accounts with historical orders in the user dataset;

[0045] According to the user account LY with historical orders, the new customer accounts attracted by brand advertisements in the user data set are screened out and marked as XY, where XY = {XY1 t 、XY2 t 、XY3 t ,...,XYk t}, the superscript t represents the duration of users watching brand advertisements, and 1 to k represents the number of new customer accounts attracted by brand advertisements;

[0046] k=ni

[0047]

[0048] In the formula, Xkzb represents the proportion of new customers, ni represents the number of n user accounts in the user data set minus the number of i user accounts with historical orders, and the number of new customers k attracted by brand advertising is obtained. It represents the ratio of the number of new customers to the total number of user accounts, that is, the new customer ratio. The higher the new customer ratio Xkzb, the more attractive the brand advertising is to consumers.

[0049]

[0050] In the formula, represents the average viewing time. It represents the total time that new customer accounts in the user data set watch brand ads divided by the number of new customer accounts, and the average viewing time is obtained. The longer it is, the higher the probability that potential customers will make a purchase.

[0051] The conversion analysis unit analyzes and generates conversion index Zhzs and average purchase quantity based on the recorded data set. And transmitted to the exposure analysis unit through the network, the calculation process is as follows:

[0052] According to the new customer account XY attracted by the brand advertisement, the sales record data of the first transaction in the order data set is screened out and marked as SJ, where: The superscript d indicates the time point of the transaction, the subscript s indicates the sales volume of the branded product, and 1 to r indicates that there are r transactions of the first purchase of branded products by new customer accounts attracted by brand advertisements;

[0053]

[0054] In the formula, Zhzs represents the conversion index, The conversion index is the ratio of the number of completed orders for brand products purchased by new customer accounts attracted by brand advertising to the number of new customer accounts. The higher the conversion index, the more accurate the effective users targeted by brand advertising.

[0055]

[0056] In the formula, represents the average purchase quantity, The average purchase quantity is the total sales volume of brand products in all new customer accounts divided by the total number of orders. It directly reflects the purchasing power of this group of effective users;

[0057] The exposure analysis unit analyzes and generates the exposure index Bgzs based on the marketing data set. The calculation formula is as follows:

[0058]

[0059]

[0060] In the formula, Bgzs represents the exposure index, Represents the average number of comments obtained by dividing the total number of comments exposed by all communication channels in the marketing dataset by the number of channels Gep represents the exposure comment data in the e-th communication channel in the marketing dataset. It means that the variance value of u pieces of exposure comment data and the average number of comments in the communication channel is calculated through the variance formula, which is the exposure index. The larger the exposure index is, the greater the degree of dispersion of the number of exposure comments in each communication channel is. The advertising and marketing effect of individual communication channels is the best, and additional investment can be made later. In-depth analysis of user behavior has high screening accuracy.

[0061] The exposure analysis unit calculates the new customer ratio, average viewing time, Conversion index Zhzs, average purchase quantity The exposure index Bgzs forms a screening report and outputs it to advertisers to help them truly understand consumers' click behavior, purchase behavior and comment behavior, flexibly adjust advertising marketing strategies and communication channels, more accurately locate potential high-value users, improve advertising delivery effects, reduce marketing costs, and achieve better channel analysis advertising marketing effects.

[0062] Example 1: In this experiment, the number of user accounts that click on brand advertisements is set to 100, of which the number of user accounts that have historical orders is set to 30, and the calculation process of the new customer ratio Xkzb is as follows:

[0063] k=ni=100-30=70

[0064]

[0065] In the formula, Xkzb represents the proportion of new customers, ni represents the number of n user accounts in the user data set minus the number of i user accounts with historical orders, and the number of new customers k attracted by brand advertising is 70. It represents the ratio of the number of new customers to the total number of user accounts. 0.7 is the new customer ratio.

[0066] Example 2: In this experiment, the number of completed orders for branded goods purchased by new customer accounts for the first time is set to 197, and the number of new customer user accounts is set to 83. The conversion index Zhzs calculation process is as follows:

[0067]

[0068] In the formula, Zhzs represents the conversion index, It represents the ratio of completed orders for the first purchase of brand products by new customer accounts attracted by brand advertising to the number of new customer accounts. 2.37 is the conversion index. On average, each new customer account completes 2.37 orders.

[0069] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An effective user screening system for advertising marketing based on influence indicators, characterized by: Including data collection module and user screening module; The data collection module is composed of a user data unit, a transaction record unit and a marketing data unit. The user data unit collects a user data set through a network connection to a big data platform. The user data set includes all user account data that click on brand advertisements. The transaction record unit collects a record data set through a network connection to a big data platform. The record data set includes sales record data of all brand products. The marketing data unit collects a marketing data set through a network connection to a big data platform. The marketing data set includes exposure and comment data of brand advertisements in all communication channels. The data collection module transmits the user data set, the record data set and the marketing data set to the user screening module through the network. The user screening module consists of a user analysis unit, a conversion analysis unit and an exposure analysis unit. The user analysis unit screens out user accounts with historical orders and new customer accounts attracted by brand advertisements based on the user data set and the record data set, and generates new customer proportion Xkzb and average viewing time accordingly. Then it is transmitted to the conversion analysis unit through the network, and the conversion analysis unit analyzes and generates the conversion index Zhzs and the average purchase quantity according to the recorded data set. And it is transmitted to the exposure analysis unit through the network. The exposure analysis unit analyzes and generates the exposure index Bgzs according to the marketing data set, and then outputs a screening report.

2. The advertising marketing effective user screening system based on influence indicators according to claim 1 is characterized by: The expression of the user data set is {Y1 t 、Y2 t 、Y3 t 、...、Yn t }, Y1 t To Yn t The data of each user account that clicks on the brand advertisement are shown in sequence. The superscript t indicates the length of time the user watches the brand advertisement, and 1 to n indicates that there are n user accounts that click on the brand advertisement.

3. The advertising marketing effective user screening system based on influence indicators according to claim 2 is characterized by: The expression of the record data set is to The corresponding sales record data of the branded goods in each completed order are shown in sequence. The superscript d indicates the time point of the completed order, the subscript s indicates the sales quantity of the branded goods, and 1 to l indicates that there are l completed orders for the branded goods.

4. The advertising marketing effective user screening system based on influence indicators according to claim 3 is characterized by: The expression of the marketing data set is {G1 p , G2 p 、G3 p 、...、Gu p }, G1 p So far p These correspond to the exposure and comment data of the brand advertisement in each communication channel. The subscript p represents the number of exposure and comments, and 1 to u represents that there are u communication channels for the brand advertisement.

5. The advertising marketing effective user screening system based on influence indicators according to claim 4 is characterized by: The calculation process of the new customer ratio Xkzb is as follows: According to the record data set, the user accounts with historical orders in the user data set are screened out and marked as LY, where LY = {LY1 t LY2 t LY3 t ,...,LYi t }, the superscript t represents the duration of the user watching the brand advertisement, and 1 to i represents that there are i user accounts with historical orders in the user dataset; According to the user account LY with historical orders, the new customer accounts attracted by brand advertisements in the user data set are screened out and marked as XY, where XY = {XY1 t 、XY2 t 、XY3 t ,...,XYk t }, the superscript t represents the duration of users watching brand advertisements, and 1 to k represents the number of new customer accounts attracted by brand advertisements; k=ni In the formula, Xkzb represents the proportion of new customers, ni represents the number of n user accounts in the user data set minus the number of i user accounts with historical orders, and the number of new customers k attracted by brand advertising is obtained. The ratio of the number of new customers to the total number of user accounts is the new customer ratio.

6. The advertising marketing effective user screening system based on influence indicators according to claim 5 is characterized by: The average viewing time The calculation formula is as follows: In the formula, The average viewing time. It represents the average viewing time obtained by dividing the total viewing time of brand ads by the number of new customer accounts in the user dataset.

7. The advertising marketing effective user screening system based on influence indicators according to claim 6 is characterized by: The calculation process of the conversion index Zhzs is as follows: According to the new customer account XY attracted by the brand advertisement, the sales record data of the first transaction in the order data set is screened out and marked as SJ, where: The superscript d indicates the time point of the transaction, the subscript s indicates the sales volume of the branded product, and 1 to r indicates that there are r transactions of the first purchase of branded products by new customer accounts attracted by brand advertisements; In the formula, Zhzs represents the conversion index, The conversion index is the ratio of completed orders from new customer accounts attracted by brand advertising who purchase brand products for the first time to the number of new customer accounts.

8. The advertising marketing effective user screening system based on influence indicators according to claim 7 is characterized by: The average purchase quantity The calculation formula is as follows: In the formula, represents the average purchase quantity, It represents the average purchase quantity obtained by dividing the total sales volume of brand products in the completed orders of all new customer accounts by the total number of orders.

9. The advertising marketing effective user screening system based on influence indicators according to claim 8 is characterized by: The exposure index Bgzs is calculated as follows: In the formula, Bgzs represents the exposure index, Represents the average number of comments obtained by dividing the total number of comments exposed by all communication channels in the marketing dataset by the number of channels Ge p represents the exposure comment data in the e-th communication channel in the marketing dataset, It means that the variance value of the u pieces of exposure comment data of the communication channel and the average number of comments is calculated through the variance formula, which is the exposure index.

10. The advertising marketing effective user screening system based on influence indicators according to claim 9 is characterized by: The screening report includes the new customer ratio Xkzb, average viewing time Conversion index Zhzs, average purchase quantity And exposure index Bgzs.

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