CN114741598A - Marketing big data informatization management cloud platform - Google Patents
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Abstract
The invention discloses a marketing big data informatization management cloud platform, which belongs to the technical field of commodity marketing and comprises a data source module, a data acquisition module, a data preprocessing module, a big data processing module, a big data analysis module and a data information visualization module, wherein the big data analysis module is used for carrying out integrated modeling analysis on effective data and carrying out data analysis on the effective data based on a data model. This marketing big data information management cloud platform, relevant data through to the whole network is gathered, wash and extraction processing, get rid of complete wrong interference data and the not invalid data of concern, extract the relevant valid data of marketing, and through built-in field and user label, analyze out audience crowd, and then carry out data analysis based on the model to marketing effect and the fluctuation of commodity pricing that the advertisement brought, obtain the reasonable interval of commodity pricing, and optimize the advertisement to the marketing effect of advertisement, improve the precision of marketing.
Description
Technical Field
The invention belongs to the technical field of commodity marketing, and particularly relates to a marketing big data informatization management cloud platform.
Background
With the rapid development of internet technology, the internet has become an important channel for people to quickly acquire, publish and transmit information, electronic commerce has also been developed rapidly, domestic enterprises are experiencing unprecedented marketing environment changes, big data applications are more and more extensive, marketing data management based on big data is an important field of big data applications, marketing based on big data needs analysis and processing of big data of massive clients, and a marketing process is to screen target clients based on tags and then send specified contents to the target clients in a proper manner.
In the prior art, when a target customer is screened and an advertisement is put in through a user tag, big data information usually only concerns the purchasing power problem of audience crowds, the marketing effect brought by the advertisement and the fluctuation of commodity pricing are not analyzed, and only the commodity price is fixed in a certain reasonable range and is continuously optimized according to the marketing effect of the advertisement, so that the marketing accuracy is improved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a marketing big data informatization management cloud platform to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a marketing big data informatization management cloud platform comprises a data source module, a data acquisition module, a data preprocessing module, a big data processing module, a big data analysis module and a data information visualization module;
the data source module is used for aggregating data terminals related to the whole network marketing data, and the data terminals comprise an e-commerce WEB or APP, a third-party e-commerce WEB or APP, a store customer service system and a service management system;
the data acquisition module is used for acquiring marketing-related big data information from each data source, accessing the marketing-related big data information into the cloud platform, establishing a database to store the data information, and transmitting the accessed big data information to the subsequent data preprocessing module;
the data preprocessing module is used for preprocessing the acquired big data information and transmitting the preprocessed data to the subsequent big data processing module;
the big data processing module is used for cleaning, fusing and extracting big data, and is internally provided with preset field information and a user tag so as to extract effective data related to marketing;
the big data analysis module is used for performing integrated modeling analysis on the effective data, performing data analysis on the effective data based on a data model, and improving the marketing accuracy by pricing commodities and numerical analysis of advertisements;
the data information visualization module is used for carrying out panoramic exhibition on the analyzed data result and outputting an image reporting marketing analysis report;
the output end signal connection of the data source module is at the input end of the data acquisition module, the output end signal connection of the data acquisition module is at the input end of the data preprocessing module, the output end signal connection of the data preprocessing module is at the input end of the big data processing module, the output end signal connection of the big data processing module is at the input end of the big data analysis module, and the output end signal connection of the big data analysis module is at the input end of the data information visualization module.
Further optimizing the technical scheme, the data acquisition module is based on a data sensing system, a network communication system and an intelligent identification system and accesses the system through software and hardware resources to acquire massive big data information.
Further optimizing the technical scheme, the big data information collected by the data collection module comprises commodity sales data, after-sales data, interaction data, advertisement data and member registration data.
The technical scheme is further optimized, the data preprocessing module carries out preprocessing processes of tracking, accessing, transmitting, signal converting and monitoring on massive big data information, and the big data information types comprise structured, semi-structured and unstructured data types.
Further optimizing the technical scheme, the field in the big data processing module is used for representing variables associated with objects or classes, and the user tag is used for representing the organization mode of data content, describing and classifying data so as to facilitate screening, analysis and identification; the big data processing module is internally provided with a feature recognizer and a data washing engine, the feature recognizer is used for accurately recognizing features and identifying fuzzy features based on fields or user labels, and the data washing engine is used for filtering, washing, debugging, removing duplicate and combining data based on the fields or the user labels.
Further optimizing the technical scheme, a commodity price evaluation model and an advertisement marketing effect calculation model are arranged in the big data analysis module, the commodity price evaluation model evaluates the marketing pricing of commodities based on the price fluctuation degree, and the advertisement marketing effect calculation model analyzes the marketing results of advertisements based on an index evaluation technology.
Further optimizing the technical scheme, the commodity price evaluation model comprises a price fluctuation variance model, a price fluctuation standard deviation model and a price pricing model, and the advertisement marketing effect calculation model comprises an advertisement factor score model and an advertisement effect score model.
Further optimizing the technical solution, the price fluctuation variance model is shown as the following formula (1), the price fluctuation standard deviation model is shown as the following formula (2), and the price pricing model is shown as the following formula (3):
wherein, sigma is the variance of price fluctuation, s is the standard deviation of the variance of price fluctuation, PiFor each price value, n is the price fluctuation times, and A is the average number of the price values; and evaluating the stability of the commodity price according to the model.
Further optimizing the technical scheme, the advertisement factor score model is as follows:
wherein P is a numerical value of the ratio of advertisement factors, A is the number of people who have viewed the advertisement and purchased the commodity, B is the number of people who have not viewed the advertisement and purchased the commodity, C is the number of people who have viewed the advertisement and have not purchased the commodity, and D is the number of people who have not viewed the advertisement and have not purchased the commodity; and the numerical value based on the P is used for analyzing the advertising marketing effect of the commodity.
Further optimizing the technical scheme, the advertisement effect score model is as follows:
wherein Q is a numerical value of the advertisement effect value, A is the number of people who have viewed the advertisement and purchased the commodity, B is the number of people who have not viewed the advertisement and purchased the commodity, C is the number of people who have viewed the advertisement and have not purchased the commodity, and D is the number of people who have not viewed the advertisement and have not purchased the commodity; and analyzing the advertisement stimulation purchase effect of the commodity based on the value of Q.
Compared with the prior art, the invention provides a marketing big data informatization management cloud platform, which has the following beneficial effects:
this marketing big data information management cloud platform, through gathering the relevant data to the whole network, wash and extraction processing, get rid of complete wrong interference data and careless invalid data, extract the relevant effective data of marketing, and through built-in field and user label, analyze out audience crowd, and then carry out data analysis based on the model to marketing effect and the fluctuation of commodity pricing that the advertisement brought, obtain the reasonable interval of commodity pricing, and optimize the advertisement to the marketing effect of advertisement, improve the precision of marketing.
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Fig. 1 is a schematic structural diagram of a marketing big data informatization management cloud platform provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
referring to fig. 1, a marketing big data informatization management cloud platform comprises a data source module, a data acquisition module, a data preprocessing module, a big data processing module, a big data analysis module and a data information visualization module;
the data source module is used for aggregating data terminals related to the whole network marketing data, and the data terminals comprise an e-commerce WEB or APP, a third-party e-commerce WEB or APP, a store customer service system and a service management system;
the data acquisition module is used for acquiring marketing-related big data information from each data source, accessing the marketing-related big data information into the cloud platform, establishing a database to store the data information, and transmitting the accessed big data information to the subsequent data preprocessing module;
the data preprocessing module is used for preprocessing the acquired big data information and transmitting the preprocessed data to a subsequent big data processing module;
the big data processing module is used for cleaning, fusing and extracting big data, and is internally provided with preset field information and a user tag so as to extract effective data related to marketing;
the big data analysis module is used for performing integrated modeling analysis on the effective data, performing data analysis on the effective data based on a data model, and improving the marketing accuracy by pricing commodities and numerical analysis of advertisements;
the data information visualization module is used for carrying out panoramic exhibition on the analyzed data result and outputting an image reporting marketing analysis report;
the output end signal connection of the data source module is at the input end of the data acquisition module, the output end signal connection of the data acquisition module is at the input end of the data preprocessing module, the output end signal connection of the data preprocessing module is at the input end of the big data processing module, the output end signal connection of the big data processing module is at the input end of the big data analysis module, and the output end signal connection of the big data analysis module is at the input end of the data information visualization module.
Specifically, the data acquisition module is based on a data sensing system, a network communication system and an intelligent identification system and is accessed to the system through software and hardware resources, so that massive big data information is acquired.
Specifically, the big data information collected by the data collection module includes commodity sales data, after-sales data, interaction data, advertisement data and member registration data.
Further, the commodity sales data includes commodity price adjustment data and adjustment times, the after-sales data includes information of a purchaser and characteristic parameters of after-sales service formation of the commodity, the interaction data includes customer service interaction and commodity behavior interaction data, the advertisement data includes advertisement browsing amount, browsing number, purchasing number and the like, and the member registration data includes registration information of the purchaser.
Specifically, the data preprocessing module performs preprocessing processes of tracking, accessing, transmitting, signal converting and monitoring on massive big data information, and the big data information types include structured, semi-structured and unstructured data types.
Specifically, the fields in the big data processing module are used for representing variables associated with objects or classes, and the user tags are used for representing the organization mode of data content, describing and classifying data so as to facilitate screening, analysis and identification; the big data processing module is internally provided with a feature recognizer and a data washing engine, the feature recognizer is used for accurately recognizing features and identifying fuzzy features based on fields or user labels, and the data washing engine is used for filtering, washing, debugging, removing duplicate and combining data based on the fields or the user labels. And through the built-in fields and the user tags, the audience population is analyzed, and the follow-up further big data analysis is facilitated.
Specifically, a commodity price evaluation model and an advertisement marketing effect calculation model are arranged in the big data analysis module, the commodity price evaluation model evaluates the marketing pricing of commodities based on the price fluctuation degree, and the advertisement marketing effect calculation model analyzes the marketing result of the advertisement based on an exponential evaluation technology.
Specifically, the commodity price evaluation model comprises a price fluctuation variance model, a price fluctuation standard deviation model and a price pricing model, and the advertisement marketing effect calculation model comprises an advertisement factor score model and an advertisement effect score model.
Specifically, the price fluctuation variance model is shown in the following formula (1), the price fluctuation standard deviation model is shown in the following formula (2), and the price pricing model is shown in the following formula (3):
wherein, sigma is the variance of price fluctuation, s is the standard deviation of the variance of price fluctuation, PiFor each price value, n is the price fluctuation times, and A is the average of the price values; and evaluating the stability of the commodity price according to the model.
Specifically, the advertisement factor score model is as follows:
wherein P is a numerical value of the ratio of advertisement factors, A is the number of people who have viewed the advertisement and purchased the commodity, B is the number of people who have not viewed the advertisement and purchased the commodity, C is the number of people who have viewed the advertisement and have not purchased the commodity, and D is the number of people who have not viewed the advertisement and have not purchased the commodity; and the numerical value based on the P is used for analyzing the advertising marketing effect of the commodity.
Based on the above model, the percentage of advertisers who see no purchase action is regarded as the specific weight of advertisers who see "not purchasing due to advertisement incentive", and therefore, the percentage of advertisers who see no purchase action is subtracted from the purchasers who see advertisements, leaving a pure advertisement sales effect.
Specifically, the advertisement effectiveness score model is as follows:
wherein Q is a numerical value of the advertisement effect value, A is the number of people who have viewed the advertisement and purchased the commodity, B is the number of people who have not viewed the advertisement and purchased the commodity, C is the number of people who have viewed the advertisement and have not purchased the commodity, and D is the number of people who have not viewed the advertisement and have not purchased the commodity; and analyzing the advertisement stimulation purchase effect of the commodity based on the value of Q.
Based on the above model, it can be considered that a certain percentage of people who have purchased an advertised product among consumers who have not viewed the advertisement purchase the product regardless of whether there is an advertising incentive, and then a certain percentage of people who have viewed the advertisement and purchased the product do not purchase the product due to the advertising incentive. The remaining people are actually evoking the effect of the purchase due to the advertisement.
In the marketing big data information management cloud platform, the big data analysis module may further have a data analysis model related to the advertisement, for example, the average browsing time of the advertisement may be analyzed, and the analysis model of the average browsing time of the advertisement is shown as the following formula:
wherein t is the average browsing time of the advertisement, and the unit is second; t is a unit ofiThe browsing time of the ith browser is shown, and n is the total number of the browsed people.
Through carrying out average statistics on the browsing time of the browser, the marketing effect brought by the analyzed advertisement is coached, so that the marketing accuracy of the marketing big data information management cloud platform can be embodied.
The invention has the beneficial effects that:
this marketing big data information management cloud platform, relevant data through to the whole network is gathered, wash and extraction processing, get rid of complete wrong interference data and the not invalid data of concern, extract the relevant valid data of marketing, and through built-in field and user label, analyze out audience crowd, and then carry out data analysis based on the model to marketing effect and the fluctuation of commodity pricing that the advertisement brought, obtain the reasonable interval of commodity pricing, and optimize the advertisement to the marketing effect of advertisement, improve the precision of marketing.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A marketing big data informatization management cloud platform is characterized by comprising a data source module, a data acquisition module, a data preprocessing module, a big data processing module, a big data analysis module and a data information visualization module;
the data source module is used for aggregating data terminals related to the whole network marketing data, and the data terminals comprise an e-commerce WEB or APP, a third-party e-commerce WEB or APP, a store customer service system and a service management system;
the data acquisition module is used for acquiring marketing-related big data information from each data source, accessing the marketing-related big data information into the cloud platform, establishing a database to store the data information, and transmitting the accessed big data information to the subsequent data preprocessing module;
the data preprocessing module is used for preprocessing the acquired big data information and transmitting the preprocessed data to a subsequent big data processing module;
the big data processing module is used for cleaning, fusing and extracting big data, and is internally provided with preset field information and a user tag so as to extract effective data related to marketing;
the big data analysis module is used for performing integrated modeling analysis on the effective data, performing data analysis on the effective data based on a data model, and providing pricing for commodities and numerical analysis of advertisements to improve marketing accuracy;
the data information visualization module is used for carrying out panoramic exhibition on the analyzed data result and outputting an image reporting marketing analysis report;
the output end signal connection of the data source module is at the input end of the data acquisition module, the output end signal connection of the data acquisition module is at the input end of the data preprocessing module, the output end signal connection of the data preprocessing module is at the input end of the big data processing module, the output end signal connection of the big data processing module is at the input end of the big data analysis module, and the output end signal connection of the big data analysis module is at the input end of the data information visualization module.
2. The marketing big data informatization management cloud platform according to claim 1, wherein the data acquisition module is based on a data sensing system, a network communication system and an intelligent recognition system and realizes acquisition of massive big data information through a software and hardware resource access system.
3. The marketing big data informatization management cloud platform according to claim 1, wherein the big data information collected by the data collection module comprises commodity sales data, after-sales data, interaction data, advertisement data and member registration data.
4. The marketing big data informatization management cloud platform according to claim 1, wherein the data preprocessing module performs preprocessing processes of tracking, accessing, transmitting, signal converting and monitoring on massive big data information, and the big data information types comprise structured, semi-structured and unstructured data types.
5. The marketing big data informatization management cloud platform according to claim 1, wherein fields in the big data processing module are used for representing variables associated with objects or classes, user tags are used for representing organization modes of data contents, description and classification data, so as to facilitate screening, analysis and identification; the big data processing module is internally provided with a feature recognizer and a data washing engine, the feature recognizer is used for accurately recognizing features and identifying fuzzy features based on fields or user labels, and the data washing engine is used for filtering, washing, debugging, removing duplicate and combining data based on the fields or the user labels.
6. The marketing big data informatization management cloud platform according to claim 1, characterized in that a commodity price evaluation model and an advertisement marketing effect calculation model are built in the big data analysis module, the commodity price evaluation model evaluates marketing pricing of commodities based on price fluctuation degree, and the advertisement marketing effect calculation model analyzes marketing results of advertisements based on an exponential evaluation technology.
7. The marketing big data informatization management cloud platform according to claim 6, wherein the commodity price evaluation model comprises a price fluctuation variance model, a price fluctuation standard deviation model and a price pricing model, and the advertisement marketing effect calculation model comprises an advertisement factor score model and an advertisement effect score model.
8. The marketing big data informatization management cloud platform according to claim 7, wherein the price fluctuation variance model is shown in the following formula (1), the price fluctuation standard deviation model is shown in the following formula (2), and the price pricing model is shown in the following formula (3):
wherein, sigma is the variance of price fluctuation, s is the standard deviation of the variance of price fluctuation, PiFor each price value, n is the price fluctuation times, and A is the average of the price values; and evaluating the stability of the commodity price according to the model.
9. The marketing big data informatization management cloud platform according to claim 7, wherein the advertisement factor score model is as follows:
wherein P is a numerical value of the ratio of advertisement factors, A is the number of people who have viewed the advertisement and purchased the commodity, B is the number of people who have not viewed the advertisement and purchased the commodity, C is the number of people who have viewed the advertisement and have not purchased the commodity, and D is the number of people who have not viewed the advertisement and have not purchased the commodity; and the numerical value based on the P is used for analyzing the advertising marketing effect of the commodity.
10. The marketing big data informatization management cloud platform according to claim 7, wherein the advertisement effect score model is as follows:
wherein Q is a numerical value of the advertisement effect value, A is the number of people who have viewed the advertisement and purchased the commodity, B is the number of people who have not viewed the advertisement and purchased the commodity, C is the number of people who have viewed the advertisement and have not purchased the commodity, and D is the number of people who have not viewed the advertisement and have not purchased the commodity; and analyzing the advertisement stimulation purchase effect of the commodity based on the value of Q.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115687472A (en) * | 2022-09-30 | 2023-02-03 | 中国电建集团国际工程有限公司 | Data storage management system based on cloud platform |
| CN116862578A (en) * | 2023-09-05 | 2023-10-10 | 销生客(北京)数字科技有限公司 | Internet marketing management system and method based on blockchain technology |
| CN117035874A (en) * | 2023-10-10 | 2023-11-10 | 南京莫愁智慧信息科技有限公司 | Digital human advertisement data processing method |
-
2022
- 2022-04-19 CN CN202210408452.8A patent/CN114741598A/en not_active Withdrawn
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115687472A (en) * | 2022-09-30 | 2023-02-03 | 中国电建集团国际工程有限公司 | Data storage management system based on cloud platform |
| CN116862578A (en) * | 2023-09-05 | 2023-10-10 | 销生客(北京)数字科技有限公司 | Internet marketing management system and method based on blockchain technology |
| CN116862578B (en) * | 2023-09-05 | 2024-02-02 | 销生客(北京)数字科技有限公司 | Internet marketing management system and method based on blockchain technology |
| CN117035874A (en) * | 2023-10-10 | 2023-11-10 | 南京莫愁智慧信息科技有限公司 | Digital human advertisement data processing method |
| CN117035874B (en) * | 2023-10-10 | 2023-12-12 | 南京莫愁智慧信息科技有限公司 | Digital human advertisement data processing method |
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