Client monitoring and analyzing system based on big data

An analysis system and big data technology, applied in the field of data analysis systems, can solve problems such as low efficiency, low accuracy, low pertinence, and difficulties, and achieve the effect of improving the success rate of push

Active Publication Date: 2019-09-20
浙江华坤道威数据科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For offline shopping, its unique shopping experience and service efficiency are still a shopping method chosen by many people. There are few methods, so it is very difficult to carry out data mining for offline shopping be

Method used

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  • Client monitoring and analyzing system based on big data
  • Client monitoring and analyzing system based on big data
  • Client monitoring and analyzing system based on big data

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Embodiment Construction

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0043] see figure 1As shown, the present embodiment provides a customer monitoring and analysis system based on big data, including a storage server, and the system also includes a member login module, a promotion push module, a recording module, a checkout module and a consumption analysis module; Data can be transmitted via wifi or 4G data network.

[0044] The storage server is used to store customer account information, commodity information of each commodity ...

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Abstract

The invention discloses a client monitoring analysis system based on big data. The client monitoring analysis system comprises a member login module, a promotion push module, a recording module, a checkout module and a consumption analysis module, a one-way shopping channel is formed by forming a plurality of first-level areas of first-level category commodities and second-level areas containing commodities of the same brand, and a scene used for client shopping behavior monitoring is constructed; entering and leaving time of a client in each brand and the first-level area are obtained to serve as original data for describing shopping behaviors of the client; after interference factors are removed through primary analysis of the original data, an average stay point T is obtained; therefore, the shopping behavior of the client during shopping in the offline supermarket can be monitored. Processing and analyzing the average staying score T to obtain a concerned brand and a concerned category, and optimizing a promotion pushing module according to an analysis result, so as to analyze the shopping behavior of the client during offline supermarket shopping, thereby improving the pushing success rate.

Description

technical field [0001] The invention relates to a data analysis system, in particular to a customer monitoring and analysis system based on big data. Background technique [0002] With the development of network technology, more and more people choose to shop online. For merchants, online shopping can easily obtain the data of customers when shopping, and then through mining and processing these data, the customer's Predict the shopping behavior and realize timely and accurate advertising push to increase the possibility of transaction. For offline shopping, its unique shopping experience and service efficiency are still a shopping method chosen by many people. There are few methods, so it is very difficult to carry out data mining for offline shopping behavior information. The existing method is to analyze the online shopping data and associate customers, and then realize the offline shopping of customers. Forecasting, but this method is not efficient, accurate and target...

Claims

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Application Information

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IPC IPC(8): G06Q30/00G06Q30/02
CPCG06Q30/01G06Q30/0201
Inventor 孟宪坤田文郭杨
Owner 浙江华坤道威数据科技有限公司
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