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E-commerce platform customer behavior analytical method based on big data

An e-commerce platform and behavior analysis technology, applied in marketing and other directions, can solve problems such as business entry difficulties, inability to obtain, and inability to understand the status quo of the industry, and achieve the effect of promoting enterprise development

Inactive Publication Date: 2015-06-24
INSPUR GROUP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The current customer behavior analysis is limited to the analysis of information obtained from a store, and can only be adjusted according to the operation of its own store, and it is impossible to understand the current situation of the entire industry. The existing customer behavior analysis is based on the data of a single store. , unable to understand the different price ranges of the entire industry and the preferences of consumers. For operators who are new to this industry, they cannot even obtain the data of a single store, which makes the store operation into an embarrassing situation. The operation of the industry is in trouble

Method used

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  • E-commerce platform customer behavior analytical method based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0017] The steps of this analytical method are as follows:

[0018] Step 1: Analyze the information on the transaction information page of well-known e-commerce websites on the Internet;

[0019] Step 2: Obtain the key url and set the collection rules through the analysis of the webpage to perform data capture;

[0020] Step 3: Perform data verification on the captured data;

[0021] Step 4: Classify and store the collected data according to categories;

[0022] Step 5: Carry out cluster analysis on the information under the same category to obtain the customer's price preference and purchase frequency information;

[0023] Step 6: Generate corresponding industry reports based on the analysis results.

Embodiment 2

[0025] The steps of this analytical method are as follows:

[0026] Step 1: Analyze the information on the transaction information page of well-known e-commerce websites on the Internet;

[0027] Step 2: Obtain the key url. Set the collection rules through the analysis of the webpage, and use the web crawler tool to capture the data;

[0028] Step 3: Perform data verification on the captured data;

[0029] Step 4: Store the collected data in two categories according to categories;

[0030] Step 5: Carry out cluster analysis on the information under the same category to obtain the customer's price preference and purchase frequency information;

[0031] Step 6: Generate corresponding industry reports based on the analysis results.

Embodiment 3

[0033] The steps of this analytical method are as follows:

[0034] Step 1: Analyze the information on the transaction information page of well-known e-commerce websites on the Internet;

[0035] Step 2: Obtain the key url. Set the collection rules through the analysis of the webpage, and use the web crawler tool to capture the data;

[0036] Step 3: Perform data verification on the captured data. If the data verification finds that the quality or accuracy of the collection is poor, adjust the collection rules in step 2 and collect again;

[0037] Step 4: Store the collected data in two categories according to categories;

[0038] Step 5: Carry out cluster analysis on the information under the same category to obtain key information such as customer's price preference and purchase frequency;

[0039] Step 6: Generate corresponding industry reports based on the analysis results.

[0040] Through the collection and cleaning of the public data of e-commerce websites, an...

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Abstract

The invention discloses an E-commerce platform customer behavior analytical method based on big data. The analytical method includes the following steps that first, the information of trading information pages of well-known E-commerce websites on the Internet is analyzed; second, a key url is acquired, a collecting rule is set by analyzing the web pages and data are captured; third, data verification is conducted on the captured data; fourth, the collected data are stored in a classified mode according to categories; fifth, clustering analysis is conducted on the information under the same category to obtain the preference to prices by customers and the purchase frequency information; sixth, corresponding industrial reports are generated according to analysis results. By the adoption of the method, the market segmentation and the level of competition of a certain industry in the E-commerce field can be acquired, hence, existing enterprises can be guided to adjust operating strategies, new enterprises can be guided to enter in the blue ocean industry, enterprise development is promoted, and resource matching can be guided to a certain extent.

Description

technical field [0001] The invention relates to the technical field of computer data mining, in particular to a method for analyzing customer behavior of an e-commerce platform based on big data. Background technique [0002] The vigorous development of e-commerce has injected a strong impetus into the economy of our country, and at the same time, the competition among merchants has been carried out to the point of white-hot. Subsequent operators cannot understand the form of the market, and existing businesses do not have enough information to support themselves to expand their production and operation scale. However, the current data collection has developed to a relatively mature stage, and there are already many applicable theories in marketing and customer relationship management. The combination of the two can provide some information that was not possible before. [0003] The current customer behavior analysis is limited to the analysis of information obtained fro...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
Inventor 王世创崔杰崔乐乐
Owner INSPUR GROUP CO LTD
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