Multi-source data processing system for advertisement marketing
By designing a multi-source data processing system, collecting and analyzing advertising marketing data in real time, and calculating volatility index and marketing index, the problem of traditional systems lacking real-time feedback is solved, and efficient advertising marketing strategy optimization and product reputation maintenance are achieved.
Patent Information
- Application Number
- CN202411250807.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-06
- Publication Date
- 2024-12-27
AI Technical Summary
The multi-source data processing system used in traditional advertising marketing lacks real-time feedback mechanisms, cannot adjust marketing strategies in a timely manner, and ignores the quality of product after-sales service, resulting in waste of resources and product reputation maintenance problems.
A multi-source data processing system for advertising marketing is designed, including data collection module, processing and analysis module and marketing management module. It connects the big data platform to obtain marketing, marketing and after-sales service data through the network, calculates volatility index, marketing index and scores. Data, set monitoring cycles and thresholds, provide real-time feedback on advertising marketing conversion efficiency and stability, and timely optimize marketing strategies.
Real-time feedback, high conversion efficiency of advertising marketing, improve the accuracy and conversion rate of advertising marketing, promptly solve after-sales problems, effectively maintain product reputation, and improve the flexibility of marketing strategies and user satisfaction.
Smart Images
Figure CN119205217A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of advertising and marketing, and in particular to a multi-source data processing system for advertising and marketing. Background Art
[0002] In modern digital marketing, advertising business is a data-driven industry. From advertising delivery to broadcasting, and then to effect tracking, every link relies heavily on data support. The amount of data that the advertising platform needs to process is huge, and it comes from different systems and scenarios. The huge data processing needs put forward extremely high requirements on the efficiency, stability and security of the system. In the data cleaning and stratification stage, the multi-source data processing system needs to uniformly process and process the collected raw data to ensure the consistency and accuracy of the data. This process involves operations such as removing useless fields, unifying data formats, and verifying data integrity, providing a reliable data foundation for subsequent data analysis and application. In the data processing stage, the multi-source data processing system needs to use a powerful computing framework to process large amounts of data. For example, using frameworks such as Spark streaming for efficient data processing and aggregation calculations not only improves the efficiency of data processing, but also ensures the flexibility and scalability of data processing. In the data application stage, the multi-source data processing system needs to provide data support for multiple links such as advertising delivery, effect analysis, and strategy optimization. The system needs to generate various reports and indicators based on the processed data to help advertisers and operators make more accurate decisions. In addition, the system also needs to provide real-time data services to support business scenarios with high timeliness requirements, such as real-time bidding and advertising optimization.
[0003] At present, the multi-source data processing system used in traditional advertising marketing lacks a real-time feedback mechanism. It is often necessary to evaluate the marketing effect after the advertising campaign ends. It is impossible to adjust the marketing strategy in time according to the changing market demand, which leads to a large waste of resources. In addition, it is easy to ignore the quality score of product after-sales service and fail to maintain the product reputation in time according to user experience. 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 a multi-source data processing system for advertising and marketing, which has the advantages of high conversion efficiency of real-time feedback advertising and marketing, and better marketing effect by focusing on after-sales ratings. It solves the problem that traditional multi-source data processing systems for advertising and marketing lack a real-time feedback mechanism and ignore the importance of product after-sales ratings to product reputation.
[0006] (II) Technical solution
[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a multi-source data processing system for advertising and marketing, comprising a data acquisition module, a processing and analysis module and a marketing management module;
[0008] The data acquisition module is composed of a market situation unit, a marketing feedback unit and an after-sales service unit. The market situation unit collects a market data set through a network connection to a big data platform. The market data set includes market transaction volume data of commodities at all time points. The marketing feedback unit collects a marketing data set through a network connection to a big data platform. The marketing data set includes advertising and marketing conversion data of commodities at all time points. The after-sales service unit collects an after-sales data set through a network connection to a big data platform. The after-sales data set includes after-sales service data of commodities at all time points. The data acquisition module transmits the market data set, the marketing data set and the after-sales data set to the processing and analysis module through the network.
[0009] The processing and analysis module is composed of a market analysis unit, a marketing analysis unit and an after-sales analysis unit. The market analysis unit generates a fluctuation index Bdzs based on the market data set through analysis. The marketing analysis unit generates a marketing index Yxzs based on the marketing data set through analysis. The after-sales analysis unit generates a scoring data group Pfsj based on the after-sales data set through analysis. The processing and analysis module transmits the fluctuation index Bdzs, the marketing index Yxzs and the scoring data group Pfsj to the marketing management module through the network.
[0010] The marketing management module is provided with a fixed-duration monitoring cycle ZQ and an index threshold YZ, and combines the fluctuation index Bdzs and the marketing index Yxzs to judge the effectiveness of marketing conversion and the stability of advertising marketing, and then outputs a marketing report.
[0011] Preferably, the expression of the market data set is {S1 d 、S2 d 、S3 d 、...、Sn d},S1 d To Sn d It corresponds to the daily transaction volume of the commodity at each time point in turn, d represents the time point when the market transaction volume data is collected, and 1 to n represent that there are n groups of market transaction volume data collected.
[0012] Preferably, the expression of the marketing data set is {Y1 t 、Y2 t 、Y3 t ,...,Yx t}, Y1 t To Yx tThe number of daily ad clicks corresponding to each time point in turn, t represents the time point for collecting advertising marketing conversion data, and 1 to x represents that there are x groups of advertising marketing conversion data collected.
[0013] Preferably, the expression of the after-sales data set is {F1 m 、F2 m 、F3 m , ..., Fw m}, F1 m To Fw m The after-sales ratings of the products at each time point correspond in sequence, m represents the time point when the after-sales service data is collected, and 1 to w represent that there are w groups of after-sales service data collected.
[0014] Preferably, the calculation formula of the volatility index Bdzs is as follows:
[0015]
[0016] In the formula, Bdzs represents the volatility index, Si d represents the commodity transaction volume on the i-th day in the market data set, Si+1 d represents the commodity transaction volume on the i+1th day in the market data set, Si+1 d -Si d It represents the difference in commodity trading volume between two consecutive days, which is the volatility index of the i+1th day. It means calculating the volatility index of n groups of market transaction volume data in chronological order from early to late.
[0017] Preferably, the marketing index Yxzs is calculated as follows:
[0018]
[0019] In the formula, Yxzs represents the marketing index, The average number of clicks is the sum of the number of ad clicks in x days divided by the number of marketing days. Yi t represents the number of daily clicks on the advertisement on the i-th day in the marketing dataset, It means that the variance value of x groups of advertising marketing conversion data and average click volume is calculated by the variance formula, which is the marketing index.
[0020] Preferably, the calculation formula of the scoring data set Pfsj is as follows:
[0021]
[0022] In the formula, Pfsj represents the scoring data group, represents the after-sales service data with the highest score in the after-sales data set. It represents the average after-sales rating obtained by dividing the sum of the after-sales ratings of group w by the total number. Represents the after-sales service data with the lowest score in the after-sales data set.
[0023] Preferably, within a single monitoring period ZQ, if the daily fluctuation index Bdzs is a positive number, it indicates that the effectiveness of the marketing conversion is high; if the daily fluctuation index Bdzs is negative more than three times, it indicates that the effectiveness of the marketing conversion is low.
[0024] Preferably, the marketing management module is provided with an index threshold YZ. If the marketing index Yxzs is lower than or included in the index threshold YZ within a single monitoring period ZQ, it indicates that the stability of the advertising marketing is high. If the marketing index Yxzs exceeds the index threshold YZ within a single monitoring period ZQ, it indicates that the stability of the advertising marketing is low.
[0025] Preferably, the marketing report includes a fluctuation index Bdzs, a marketing index Yxzs, a scoring data group Pfsj, a judgment result of the effectiveness of marketing conversion, and a judgment result of the stability of advertising marketing.
[0026] Compared with the prior art, the present invention provides a multi-source data processing system for advertising and marketing, which has the following beneficial effects:
[0027] 1. The present invention obtains the market transaction volume data, advertising marketing conversion data and after-sales service data of commodities at all time points through a data acquisition module network connection big data platform, and classifies them into market data sets, marketing data sets and after-sales data sets. The processing and analysis module is composed of a market analysis unit, a marketing analysis unit and an after-sales analysis unit. The market analysis unit analyzes and generates a fluctuation index Bdzs according to the market data set. Each group of market transaction volume data corresponds to a fluctuation index of one day, which can intuitively feedback the conversion trend before and after advertising marketing. The marketing analysis unit analyzes and generates a marketing index Yxzs according to the marketing data set. The smaller the marketing index, the more stable the daily click volume of the advertisement and the higher the authenticity of the traffic. The after-sales analysis unit analyzes and generates a scoring data set Pfsj according to the after-sales data set, ensuring that subsequent advertising marketing strategies can be efficiently and professionally optimized following consumer feedback, and real-time feedback advertising marketing conversion efficiency is high.
[0028] 2. The present invention sets a monitoring cycle ZQ and an index threshold YZ with a fixed duration through the marketing management module, and combines the fluctuation index Bdzs and the marketing index Yxzs to judge the effectiveness of marketing conversion and the stability of advertising marketing. Within a single monitoring cycle ZQ, if the daily fluctuation index Bdzs is a positive number, it indicates that the effectiveness of marketing conversion is high. If the marketing index Yxzs is lower than or included in the index threshold YZ within a single monitoring cycle ZQ, it indicates that the stability of advertising marketing is high. The marketing management module composes a marketing report with the fluctuation index Bdzs, the marketing index Yxzs, the scoring data group Pfsj, the judgment result of the effectiveness of marketing conversion and the judgment result of the stability of advertising marketing, and outputs it to the advertiser, which can help the advertiser improve the accuracy and conversion rate of advertising marketing, solve after-sales problems in a timely manner and effectively maintain the reputation of the product, and pay attention to after-sales scoring for better marketing effect. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION
[0030] 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.
[0031] Since the multi-source data processing system used in traditional advertising marketing lacks a real-time feedback mechanism, it is often necessary to evaluate the marketing effect after the advertising campaign ends, and it is impossible to adjust the marketing strategy in time according to the changing market demand, resulting in a large waste of resources. In addition, it is easy to ignore the quality rating of product after-sales service, and it is impossible to maintain the product reputation in time according to the user experience. Therefore, a multi-source data processing system for advertising marketing is provided. Please refer to Figure 1 ,The system includes a data acquisition module, a processing and analysis module, and a marketing management module;
[0032] The data collection module consists of a market situation unit, a marketing feedback unit, and an after-sales service unit. The market situation unit collects market data sets through a network connection to the big data platform. The market data set includes the market transaction volume data of commodities at all time points. The expression of the market data set is {S1 d 、S2 d 、S3 d 、...、Sn d},S1 d To Sn dThe daily transaction volume of commodities at each time point corresponds to the time point of collecting market transaction volume data, 1 to n means that there are n groups of collected market transaction volume data. Real-time collection of daily transaction volume of commodities can instantly capture the sales dynamics in the market and quickly respond to market changes.
[0033] The marketing feedback unit collects marketing data sets through the network connection to the big data platform. The marketing data sets include the advertising and marketing conversion data of the products at all time points. The expression of the marketing data set is {Y1 t 、Y2 t 、Y3 t ,...,Yx t}, Y1 t To Yx t The number of daily clicks on ads at each time point in turn. t represents the time point at which the ad marketing conversion data is collected. 1 to x represent the number of x sets of ad marketing conversion data collected. Real-time collection of daily clicks on ads can instantly evaluate the effect of ad placement, optimize ad budget allocation, accurately identify false traffic, and avoid cost waste caused by false clicks.
[0034] The after-sales service unit collects after-sales data sets through the network connection to the big data platform. The after-sales data set includes the after-sales service data of the products at all time points. The expression of the after-sales data set is {F1 m 、F2 m 、F3 m , ..., Fw m}, F1 m To Fw m The after-sales ratings of the products at each time point correspond in sequence. m represents the time point when the after-sales service data is collected. 1 to w represent the number of w groups of after-sales service data collected. After-sales service and customer satisfaction are key factors for the continuous competition and development of products. Timely solving of customer problems and targeted optimization of product functions and marketing activities can better maintain the reputation of products.
[0035] The data collection module transmits the market data set, marketing data set and after-sales data set to the processing and analysis module through the network, providing data support for subsequent effect analysis and strategy optimization;
[0036] The processing and analysis module consists of a market analysis unit, a marketing analysis unit, and an after-sales analysis unit. The market analysis unit generates a volatility index Bdzs based on the market data set. The calculation formula is as follows:
[0037]
[0038] In the formula, Bdzs represents the volatility index, Si d represents the commodity transaction volume on the i-th day in the market data set, Si+1 drepresents the commodity transaction volume on the i+1th day in the market data set, Si+1 d -Si d It represents the difference in commodity trading volume between two consecutive days, which is the volatility index of the i+1th day. It means calculating the volatility index of n groups of market transaction volume data in chronological order from morning to night. Each group of market transaction volume data corresponds to a volatility index of one day, which can directly reflect the conversion trend before and after advertising marketing.
[0039] The marketing analysis unit analyzes and generates the marketing index Yxzs based on the marketing data set. The calculation formula is as follows:
[0040]
[0041] In the formula, Yxzs represents the marketing index, The average number of clicks is the sum of the number of ad clicks in x days divided by the number of marketing days. Yi t represents the number of daily clicks on the advertisement on the i-th day in the marketing dataset, The variance formula is used to calculate the variance between the x-group advertising marketing conversion data and the average click volume, which is the marketing index. The smaller the marketing index, the more stable the daily click volume of the advertisement, and the higher the authenticity of the traffic.
[0042] The after-sales analysis unit analyzes and generates a scoring data group Pfsj based on the after-sales data set. The calculation formula is as follows:
[0043]
[0044] In the formula, Pfsj represents the scoring data group, represents the after-sales service data with the highest score in the after-sales data set. It represents the average after-sales rating obtained by dividing the sum of the after-sales ratings of group w by the total number. Indicates the after-sales service data with the lowest score in the after-sales data set, ensuring that subsequent advertising and marketing strategies can be optimized efficiently and professionally based on consumer feedback, and real-time feedback advertising and marketing conversion efficiency is high;
[0045] The processing and analysis module transmits the fluctuation index Bdzs, the marketing index Yxzs and the scoring data group Pfsj to the marketing management module through the network;
[0046] The marketing management module is set with a fixed-duration monitoring cycle ZQ and index threshold YZ, and combines the fluctuation index Bdzs and the marketing index Yxzs to judge the effectiveness of marketing conversion and the stability of advertising marketing. Within a single monitoring cycle ZQ, if the daily fluctuation index Bdzs is positive, it means that the effectiveness of marketing conversion is high. If the daily fluctuation index Bdzs is negative more than three times, it means that the effectiveness of marketing conversion is low. The marketing management module is set with an index threshold YZ. If the marketing index Yxzs is lower than or included in the index within a single monitoring cycle ZQ, When the marketing index Yxzs exceeds the index threshold YZ, it indicates that the stability of advertising marketing is high. If within a single monitoring period ZQ, the marketing index Yxzs exceeds the index threshold YZ, it indicates that the stability of advertising marketing is low. The marketing management module will form a marketing report with the fluctuation index Bdzs, marketing index Yxzs, scoring data group Pfsj, the judgment results of the effectiveness of marketing conversion and the judgment results of the stability of advertising marketing, and output it to advertisers. It can help advertisers improve the accuracy and conversion rate of advertising marketing, solve after-sales problems in a timely manner and effectively maintain the reputation of products. Paying attention to after-sales scoring will have better marketing effects.
[0047] Example 1: In this experiment, the market data set contains two days of commodity transaction volume, the commodity transaction volume at the current time point is set to 854 pieces, and the commodity transaction volume one day before the current time point is set to 723 pieces. The volatility index Bdzs at the current time point is calculated, and the calculation formula is as follows:
[0048]
[0049] In the formula, Bdzs represents the volatility index, Si d represents the commodity transaction volume on the i-th day in the market data set, which is 723, Si+1 d represents the commodity transaction volume on the i+1th day in the market data set, which is 854, Si+1 d -Si d It represents the difference in commodity transaction volume between two consecutive days. 131 is the volatility index at the current time point.
[0050] Example 2: In this experiment, the number of marketing days is set to 10 days, and the marketing data set contains the daily click volume of advertisements for 10 days. The daily click volume of advertisements in the 10 days is 132, 201, 391, 492, 549, 611, 750, 778, 812 and 822. The marketing index Yxzs is calculated as follows:
[0051]
[0052]
[0053] In the formula, Yxzs represents the marketing index, The average number of clicks is the sum of the number of ad clicks in x days divided by the number of marketing days. That is 966.6, It means that the variance value of x groups of advertising marketing conversion data and average click volume is calculated through the variance formula, and 50498.66 is the marketing index.
[0054] 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. A multi-source data processing system for advertising and marketing, characterized in that: It includes data collection module, processing and analysis module and marketing management module; The data acquisition module is composed of a market situation unit, a marketing feedback unit and an after-sales service unit. The market situation unit collects a market data set through a network connection to a big data platform. The market data set includes market transaction volume data of commodities at all time points. The marketing feedback unit collects a marketing data set through a network connection to a big data platform. The marketing data set includes advertising and marketing conversion data of commodities at all time points. The after-sales service unit collects an after-sales data set through a network connection to a big data platform. The after-sales data set includes after-sales service data of commodities at all time points. The data acquisition module transmits the market data set, the marketing data set and the after-sales data set to the processing and analysis module through the network. The processing and analysis module is composed of a market analysis unit, a marketing analysis unit and an after-sales analysis unit. The market analysis unit generates a fluctuation index Bdzs based on the market data set through analysis. The marketing analysis unit generates a marketing index Yxzs based on the marketing data set through analysis. The after-sales analysis unit generates a scoring data group Pfsj based on the after-sales data set through analysis. The processing and analysis module transmits the fluctuation index Bdzs, the marketing index Yxzs and the scoring data group Pfsj to the marketing management module through the network. The marketing management module is provided with a fixed-duration monitoring cycle ZQ and an index threshold YZ, and combines the fluctuation index Bdzs and the marketing index Yxzs to judge the effectiveness of marketing conversion and the stability of advertising marketing, and then outputs a marketing report.
2. The multi-source data processing system for advertising and marketing according to claim 1, characterized in that: The expression of the market data set is {S1 d 、S2 d 、S3 d 、...、Sn d },S1 d To Sn d It corresponds to the daily transaction volume of the commodity at each time point in turn, d represents the time point when the market transaction volume data is collected, and 1 to n represent that there are n groups of market transaction volume data collected.
3. The multi-source data processing system for advertising and marketing according to claim 2, characterized in that: The expression of the marketing data set is {Y1 t 、Y2 t 、Y3 t ,...,Yx t }, Y1 t To Yx t The number of daily ad clicks corresponding to each time point in turn, t represents the time point for collecting advertising marketing conversion data, and 1 to x represents that there are x groups of advertising marketing conversion data collected.
4. The multi-source data processing system for advertising and marketing according to claim 3, characterized in that: The expression of the after-sales data set is {F1 m 、F2 m 、F3 m , ..., Fw m }, F1 m To Fw m The after-sales ratings of the products at each time point correspond in sequence, m represents the time point when the after-sales service data is collected, and 1 to w represent that there are w groups of after-sales service data collected.
5. The multi-source data processing system for advertising and marketing according to claim 4, characterized in that: The calculation formula of the volatility index Bdzs is as follows: In the formula, Bdzs represents the volatility index, Si d represents the commodity transaction volume on the i-th day in the market data set, Si+1 d represents the commodity transaction volume on the i+1th day in the market data set, Si+1 d -Si d It represents the difference in commodity trading volume between two consecutive days, which is the volatility index of the i+1th day. It means calculating the volatility index of n groups of market transaction volume data in chronological order from early to late.
6. The multi-source data processing system for advertising and marketing according to claim 5, characterized in that: The marketing index Yxzs is calculated as follows: In the formula, yxzs represents the marketing index, The average number of clicks is the sum of the number of ad clicks in x days divided by the number of marketing days. Yi t represents the number of daily clicks on the advertisement on the i-th day in the marketing dataset, It means that the variance value of x groups of advertising marketing conversion data and the average click volume is calculated through the variance formula, which is the marketing index.
7. The multi-source data processing system for advertising and marketing according to claim 6, characterized in that: The calculation formula of the scoring data set Pfsj is as follows: In the formula, Pfsj represents the scoring data group, represents the after-sales service data with the highest score in the after-sales data set. It represents the average after-sales rating obtained by dividing the sum of the after-sales ratings of group w by the total number. Represents the after-sales service data with the lowest score in the after-sales data set.
8. The multi-source data processing system for advertising and marketing according to claim 7, characterized in that: Within a single monitoring period ZQ, if the daily fluctuation index Bdzs is a positive number, it indicates that the effectiveness of the marketing conversion is high. If the daily fluctuation index Bdzs is negative more than three times, it indicates that the effectiveness of the marketing conversion is low.
9. The multi-source data processing system for advertising and marketing according to claim 8, characterized in that: The marketing management module is provided with an index threshold YZ. If the marketing index Yxzs is lower than or included in the index threshold YZ within a single monitoring cycle ZQ, it indicates that the stability of the advertising marketing is high. If the marketing index Yxzs exceeds the index threshold YZ within a single monitoring cycle ZQ, it indicates that the stability of the advertising marketing is low.
10. The multi-source data processing system for advertising and marketing according to claim 9, characterized in that: The marketing report includes the fluctuation index Bdzs, the marketing index Yxzs, the scoring data group Pfsj, the judgment result of the effectiveness of marketing conversion and the judgment result of the stability of advertising marketing.