Intelligent marketing promotion method and system based on big data

Abstract

The invention provides an intelligent marketing promotion method and system based on big data, and belongs to the technical field of advertisement marketing. The intelligent marketing promotion method based on big data comprises the following steps: acquiring historical advertisement putting data; determining advertisement putting basic benefit data in a preset time period according to the historical advertisement putting data; analyzing advertisement putting trend influence data in a preset time period according to the historical advertisement putting data; calculating comprehensive advertisement revenue data of channel parties according to the advertisement putting basic benefit data and the advertisement putting trend influence data, and determining priority data of each channel party based on the comprehensive advertisement revenue data; by adopting the scheme, the benefit of marketing promotion can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of advertising and marketing, and in particular to an intelligent marketing and promotion method and system based on big data. Background Art

[0002] At present, advertising is widely used by businesses as the main mode of marketing and promotion. Businesses increase the influence of their products and thus increase product sales by placing advertisements in various channels. With the development of technology, digital advertising is increasingly valued by channels, and the display forms of digital advertising are also diverse, such as video ads, text ads, search engine ads, etc. Different channels display digital ads in different forms and with different focuses. For example, video platforms will focus on displaying merchants' products through video ads. When merchants place advertisements through these channels, they generally choose an indefinite number of channels and selectively place advertisements of indefinite costs. Since different channels display advertisements in different ways, the customers brought by the traffic also carry the channel's labels, so that merchants can identify the traffic-drawing capabilities of each channel. In order to increase the revenue from advertising, merchants will periodically analyze the advertising effectiveness of each channel and choose a more cost-effective channel to give more cost. Summary of the invention

[0003] The present application provides an intelligent marketing promotion method and system based on big data, which can improve the effectiveness of marketing promotion.

[0004] In a first aspect, the present application provides an intelligent marketing promotion method based on big data. The method comprises: Obtaining historical advertising data; the historical advertising data includes the advertising cost data of the channel party, the advertising display form data, the advertising quantity ratio data corresponding to each advertising display form, the historical customer consultation volume data and the historical customer transaction volume data; Determine basic advertising benefit data within a preset time period according to the historical advertising delivery data; the basic advertising benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data; Analyze the advertising delivery trend impact data within a preset time period according to the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertising quantity ratio data and the historical customer consultation volume data; The comprehensive advertising revenue data of the channel party is calculated according to the basic advertising benefit data and the advertising trend impact data, and the priority data of each channel party is determined based on the comprehensive advertising revenue data; the priority data represents the priority of the merchant in placing advertisements to each channel party.

[0005] Furthermore, the basic benefit data of advertising delivery within a preset time period is determined based on the historical advertising delivery data; the basic benefit data of advertising delivery is associated with the historical customer consultation volume data and the historical customer transaction volume data, including: Determine the total customer consultation data and the total customer transaction data within a preset time period based on the historical advertising delivery data; Calculate customer conversion rate data based on the total customer consultation volume data and the total customer transaction volume data; The basic benefit data of advertising delivery is determined according to the advertising delivery cost data, the total customer transaction volume data and the customer conversion rate data.

[0006] Furthermore, the calculation method of the basic benefit data of advertising placement includes: , In the formula, D is the basic benefit data of advertising, G is the total transaction volume data of customers, Z is the customer conversion rate data, and C is the advertising cost data; , The first weight and the second weight are preset respectively.

[0007] Further, .

[0008] Further, the advertising delivery trend impact data within a preset time period is analyzed based on the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertising quantity ratio data and the historical customer consultation volume data, including: Suppose there are n types of advertising display formats, then the proportion of advertisements in the i-th type of advertising display format is , the historical customer consultation data of the i-th advertising display form is ; The total number of historical customer consultation data is ; The customer quantity ratio data is ; The calculation method of advertising trend impact data is: , Where Q is the impact data of advertising trend.

[0009] In a second aspect, the present application provides an intelligent marketing promotion system based on big data, the system comprising: An acquisition module is used to acquire historical advertising data; the historical advertising data includes advertising cost data of the channel party, advertising display form data, advertising quantity ratio data corresponding to each advertising display form, historical customer consultation volume data and historical customer transaction volume data; A determination module, configured to determine basic advertising benefit data within a preset time period according to the historical advertising delivery data; the basic advertising benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data; An analysis module, configured to analyze advertising delivery trend impact data within a preset time period according to the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertising quantity ratio data and the historical customer consultation volume data; A calculation module is used to calculate the comprehensive advertising revenue data of the channel party based on the basic advertising benefit data and the advertising trend impact data, and determine the priority data of each channel party based on the comprehensive advertising revenue data; the priority data represents the priority of the merchant in placing advertisements to each channel party.

[0010] Furthermore, the determination module is further configured to determine basic advertising benefit data within a preset time period based on the historical advertising delivery data; the basic advertising benefit data associated with the historical customer consultation volume data and the historical customer transaction volume data includes: Determine the total customer consultation data and the total customer transaction data within a preset time period based on the historical advertising delivery data; Calculate customer conversion rate data based on the total customer consultation volume data and the total customer transaction volume data; The basic benefit data of advertising delivery is determined according to the advertising delivery cost data, the total customer transaction volume data and the customer conversion rate data.

[0011] Furthermore, the determination module is further configured such that the calculation method of the basic benefit data of advertising delivery includes: , In the formula, D is the basic benefit data of advertising, G is the total transaction volume data of customers, Z is the customer conversion rate data, and C is the advertising cost data; , The first weight and the second weight are preset respectively.

[0012] Furthermore, the determining module is further configured to: .

[0013] Furthermore, the analysis module is further configured to analyze the advertising delivery trend impact data within a preset time period according to the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertising quantity ratio data and the historical customer consultation volume data and includes: Suppose there are n types of advertising display formats, then the proportion of advertisements in the i-th type of advertising display format is , the historical customer consultation data of the i-th advertising display form is ; The total number of historical customer consultation data is ; The customer quantity ratio data is ; The calculation method of advertising trend impact data is: , Where Q is the impact data of advertising trend.

[0014] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein: Figure 1 A flowchart of an intelligent marketing promotion method based on big data in an embodiment of the present application is shown; Figure 2 A block diagram of an intelligent marketing promotion system based on big data in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are 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.

[0017] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0018] The present application provides an intelligent marketing promotion method and system based on big data, which can improve the effectiveness of marketing promotion.

[0019] In the first aspect, the present application provides an intelligent marketing promotion method based on big data. Figure 1 The specific steps included in the method are as follows.

[0020] Step S110: Acquire historical advertising data; the historical advertising data includes the channel's advertising cost data, advertising display format data, advertising quantity ratio data corresponding to each advertising display format, historical customer consultation volume data, and historical customer transaction volume data.

[0021] In the scheme of the present application, merchants place advertisements through channels, and the channels themselves have multiple forms of advertisement display, each with its own emphasis. Therefore, after receiving the needs of merchants, an advertising plan will be formulated. For example, in a video platform, a preset number of advertisements are placed, and the user will see the video advertisement after swiping the video a preset number of times. In a channel, there must be multiple types of advertisement forms, and the proportion of each form of advertisement is different. In this scheme, the proportion data of different forms of advertisements placed by the channel is represented by the proportion data of the number of advertisements. It should be noted that in this scheme, the contact information left by different forms of advertisements from different channels is different, so the source can be monitored to obtain customer consultation data for different forms of advertisements. Similarly, customer transaction data is screened out from the consulting customers. Therefore, after the consulting customers have been labeled with the corresponding advertising form and channel, the corresponding customer transaction data can be naturally obtained.

[0022] Step S120: determining basic advertising benefit data within a preset time period based on the historical advertising data; the basic advertising benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data.

[0023] In an embodiment of the present application, determining basic advertising benefit data within a preset time period based on the historical advertising delivery data specifically includes: determining total customer consultation volume data and total customer transaction volume data within the preset time period based on the historical advertising delivery data; calculating customer conversion rate data based on the total customer consultation volume data and the total customer transaction volume data; and determining basic advertising benefit data based on the advertising delivery cost data, the total customer transaction volume data and the customer conversion rate data.

[0024] The calculation methods of basic advertising benefit data include: , In the formula, D is the basic benefit data of advertising, G is the total transaction volume data of customers, Z is the customer conversion rate data, and C is the advertising cost data; , The first weight and the second weight are preset respectively, .

[0025] It is understandable that the customer conversion rate data here is obtained by dividing the total customer transaction volume data by the total customer consultation volume data; it is understandable that both the customer transaction volume and the customer conversion rate can indicate the revenue brought by advertising.

[0026] Step S130: analyzing the advertising delivery trend impact data within a preset time period according to the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertisement quantity ratio data and the historical customer consultation quantity data.

[0027] Specifically, the advertising delivery trend impact data within a preset time period is analyzed based on the historical advertising delivery data. If there are n types of advertising display forms, the advertising quantity ratio data of the i-th advertising display form is: , the historical customer consultation data of the i-th advertising display form is ; The total number of historical customer consultation data is ; The customer quantity ratio data is ; The calculation method of advertising trend impact data is: , where Q is the impact data of advertising trend.

[0028] It can be understood that the proportion of advertising forms represents the degree of attention the channel pays to this form of advertising. The higher the proportion, the more resources the channel has invested in this form of advertising, which is reflected in this plan, that is, the more advertisements are placed. If the channel's advertising revenue is sufficient, then the customer consultation volume brought by this form of advertising should be the largest; for example, if the channel includes three advertising forms, ABC, and the customer consultation volumes corresponding to these three forms are abc, among which A is 30%, B is 60%, and C is 10%, which represents the proportion of the number of advertisements placed; and the actual customer consultation volume is a is 20%, b is 50%, and c is 30%, which means that the advertising revenue of AB forms is lower than that of C form.

[0029] Step S140: Calculate the comprehensive advertising revenue data of the channel party according to the basic advertising benefit data and the advertising trend impact data, and determine the priority data of each channel party based on the comprehensive advertising revenue data; the priority data represents the priority of the merchant in placing advertisements to each channel party.

[0030] In this solution, the calculation method of comprehensive advertising revenue data is: comprehensive advertising revenue data = basic advertising benefit data * advertising trend impact data; after obtaining the comprehensive advertising revenue data of each channel party, the priority of each channel party is confirmed from high to low based on the comprehensive advertising revenue data; after obtaining the priority of the channel party, when the merchant needs to increase the advertising cost, the merchant can choose a channel party with a high priority to increase its advertising cost; when the merchant needs to reduce the advertising cost, the merchant can choose a channel party with a low priority to reduce its advertising cost.

[0031] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0032] In the second aspect, the present application provides an intelligent marketing promotion system based on big data. Figure 2 As shown, the system includes, an acquisition module 210, which is used to acquire historical advertising delivery data; the historical advertising delivery data includes the advertising delivery cost data of the channel party, the advertising display form data, the advertising quantity ratio data corresponding to each advertising display form, the historical customer consultation volume data and the historical customer transaction volume data; a determination module 220, which is used to determine the basic advertising delivery benefit data within a preset time period according to the historical advertising delivery data; the basic advertising delivery benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data; an analysis module 230, which is used to analyze the advertising delivery trend impact data within a preset time period according to the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertising quantity ratio data and the historical customer consultation volume data; a calculation module 240, which is used to calculate the comprehensive advertising revenue data of the channel party according to the basic advertising delivery benefit data and the advertising delivery trend impact data, and determine the priority data of each channel party based on the comprehensive advertising revenue data; the priority data represents the priority of the merchant in delivering advertisements to each channel party.

[0033] Furthermore, the determination module 220 is further configured to determine basic advertising benefit data within a preset time period based on the historical advertising delivery data; the basic advertising benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data, including: determining total customer consultation volume data and total customer transaction volume data within a preset time period based on the historical advertising delivery data; calculating customer conversion rate data based on the total customer consultation volume data and the total customer transaction volume data; determining basic advertising benefit data based on the advertising delivery cost data, the total customer transaction volume data and the customer conversion rate data.

[0034] Furthermore, the determination module 220 is further configured to calculate the basic benefit data of advertising delivery in the following manner:

[0035] In the formula, D is the basic benefit data of advertising, G is the total transaction volume data of customers, Z is the customer conversion rate data, and C is the advertising cost data; , The first weight and the second weight are preset respectively, .

[0036] Furthermore, the analysis module 230 is further configured to analyze the advertising delivery trend impact data within a preset time period according to the historical advertising delivery data; the advertising delivery trend impact data is associated with the advertising quantity ratio data and the historical customer consultation volume data, including: if there are n types of advertising display forms, the advertising quantity ratio data of the i-th advertising display form is , the historical customer consultation data of the i-th advertising display form is ; The total number of historical customer consultation data is ; The customer quantity ratio data is ; The calculation method of advertising trend impact data is: , where Q is the impact data of advertising trend.

[0037] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0038] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. An intelligent marketing promotion method based on big data, characterized in that: include: Obtaining historical advertising data; the historical advertising data includes the advertising cost data of the channel party, the advertising display form data, the advertising quantity ratio data corresponding to each advertising display form, the historical customer consultation volume data and the historical customer transaction volume data; Determine basic advertising benefit data within a preset time period based on the historical advertising data; The basic advertising benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data; Analyze the advertising delivery trend impact data within a preset time period based on the historical advertising delivery data; The advertising placement trend impact data is associated with the advertisement quantity ratio data and the historical customer consultation volume data; The comprehensive advertising revenue data of the channel party is calculated according to the basic advertising benefit data and the advertising trend impact data, and the priority data of each channel party is determined based on the comprehensive advertising revenue data; the priority data represents the priority of the merchant in placing advertisements to each channel party.

2. The method according to claim 1, characterized in that The determining of basic advertising benefit data within a preset time period according to the historical advertising data; the basic advertising benefit data associated with the historical customer consultation volume data and the historical customer transaction volume data includes: Determine the total customer consultation data and the total customer transaction data within a preset time period based on the historical advertising delivery data; Calculate customer conversion rate data based on the total customer consultation volume data and the total customer transaction volume data; The basic benefit data of advertising delivery is determined according to the advertising delivery cost data, the total customer transaction volume data and the customer conversion rate data.

3. The method according to claim 2, characterized in that The calculation method of the basic benefit data of advertising placement includes: ， In the formula, D is the basic benefit data of advertising, G is the total transaction volume data of customers, Z is the customer conversion rate data, and C is the advertising cost data; , The first weight and the second weight are preset respectively.

4. The method according to claim 3, characterized in that: 。 5. The method according to claim 3, characterized in that: analyzing the advertising delivery trend impact data within a preset time period based on the historical advertising delivery data; The advertising placement trend impact data associated with the advertising quantity ratio data and the historical customer consultation volume data include: Suppose there are n types of advertising display formats, then the proportion of advertisements in the i-th type of advertising display format is , the historical customer consultation data of the i-th advertising display form is ; The total number of historical customer consultation data is ; The customer quantity ratio data is ; The calculation method of advertising trend impact data is: ， Where Q is the impact data of advertising trend.

6. An intelligent marketing promotion system based on big data, characterized in that: include: An acquisition module (210) is used to acquire historical advertising delivery data; the historical advertising delivery data includes advertising delivery cost data of the channel party, advertising display format data, advertising quantity ratio data corresponding to each advertising display format, historical customer consultation volume data and historical customer transaction volume data; A determination module (220) is used to determine basic advertising benefit data within a preset time period based on the historical advertising delivery data; the basic advertising benefit data is associated with the historical customer consultation volume data and the historical customer transaction volume data; An analysis module (230) is used to analyze the advertising delivery trend impact data within a preset time period based on the historical advertising delivery data; The advertising placement trend impact data is associated with the advertisement quantity ratio data and the historical customer consultation volume data; The calculation module (240) is used to calculate the comprehensive advertising revenue data of the channel party according to the basic advertising benefit data and the advertising trend impact data, and determine the priority data of each channel party based on the comprehensive advertising revenue data; the priority data represents the priority of the merchant in placing advertisements on each channel party.

7. The system according to claim 6, characterized in that The determination module (220) is further configured to determine basic advertising benefit data within a preset time period based on the historical advertising delivery data; the basic advertising benefit data associated with the historical customer consultation volume data and the historical customer transaction volume data includes: Determine the total customer consultation data and the total customer transaction data within a preset time period based on the historical advertising delivery data; Calculate customer conversion rate data based on the total customer consultation volume data and the total customer transaction volume data; The basic benefit data of advertising delivery is determined according to the advertising delivery cost data, the total customer transaction volume data and the customer conversion rate data.

8. The system according to claim 7, characterized in that The determination module (220) is further configured to calculate the basic benefit data of advertising delivery in the following manner: ， In the formula, D is the basic benefit data of advertising, G is the total transaction volume data of customers, Z is the customer conversion rate data, and C is the advertising cost data; , The first weight and the second weight are preset respectively.

9. The system according to claim 8, characterized in that The determination module (220) is further configured to: .

10. The system according to claim 8, characterized in that The analysis module (230) is further configured to analyze the advertising delivery trend impact data within a preset time period based on the historical advertising delivery data; The advertising placement trend impact data associated with the advertising quantity ratio data and the historical customer consultation volume data include: Suppose there are n types of advertising display formats, then the proportion of advertisements in the i-th type of advertising display format is , the historical customer consultation data of the i-th advertising display form is ; The total number of historical customer consultation data is ; The customer quantity ratio data is ; The calculation method of advertising trend impact data is: ， Where Q is the impact data of advertising trend.

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