Customer screening method based on big data

A screening method and big data technology, applied in the field of big data, can solve problems such as inability to mine potential customers, low customer screening accuracy, and small reference range, so as to ensure sales and profits, reduce maintenance time, and screen accuracy high effect

Pending Publication Date: 2021-12-21
深圳市我们在线教育有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a customer screening method based on big data, which aims to solve the problem that the prior art cannot mine potential customers, the conv

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0030] Example 1

[0031] This specific embodiment is a client screening method based on big data, which steps are as follows:

[0032] S1: Crawling data from the website, App, and stores data:

[0033] S11: Define the goal of crawling requirements and describes the initial URL;

[0034]S12: Depending on the initial URL crawling page, obtain the new URL, filter out the link with the climb target from the new URL, put the filtered link to the URL queue;

[0035] S13: From the URL queue, according to the depth preferred crawling strategy, determine the priority of the URL and determine the URL address to climb next step;

[0036] S14: Repeat S12-S13 until the preset stop condition is satisfied, or when the new URL address is not acquired;

[0037] S2: According to the data climbed, the user's basic information is analyzed from the user's static attributes and performs user static attribute level division: basic information includes gender, age, degree, income, geographical, marriage...

Example Embodiment

[0043] Example 2

[0044] This specific embodiment is a client screening method based on big data, which steps are as follows:

[0045] S1: Crawling data from the website, App, and stores data:

[0046] S11: Define the goal of crawling requirements and describes the initial URL;

[0047] S12: Depending on the initial URL crawling page, obtain the new URL, filter out the link with the climb target from the new URL, put the filtered link to the URL queue;

[0048] S13: From the URL queue, according to the depth preferred crawling strategy, determine the priority of the URL and determine the URL address to climb next step;

[0049] S14: Repeat S12-S13 until the preset stop condition is satisfied, or when the new URL address is not acquired;

[0050] S2: According to the data climbed, the user's basic information is analyzed from the user's static attributes and performs user static attribute level division: basic information includes gender, age, degree, income, geographical, marriag...

Example Embodiment

[0056] Example 3

[0057] This specific embodiment is a client screening method based on big data, which steps are as follows:

[0058] S1: Crawling data from the website, App, and stores data:

[0059] S11: Define the goal of crawling requirements and describes the initial URL;

[0060] S12: Depending on the initial URL crawling page, obtain the new URL, filter out the link with the climb target from the new URL, put the filtered link to the URL queue;

[0061] S13: From the URL queue, according to the depth preferred crawling strategy, determine the priority of the URL and determine the URL address to climb next step;

[0062] S14: Repeat S12-S13 until the preset stop condition is satisfied, or when the new URL address is not acquired;

[0063] S2: According to the data climbed, the user's basic information is analyzed from the user's static attributes and performs user static attribute level division: basic information includes gender, age, degree, income, geographical, marriag...

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PUM

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Abstract

The invention discloses a customer screening method based on big data, and aims to solve the technical problems that in the prior art, potential customers cannot be mined, the conversion rate of the customers is low, data is not crawled from a network, the data volume is relatively small, and the referable range is relatively small, so that the customer screening precision is not low during decision making or marketing. The method comprises the following steps: S1, crawling data from a website and an APP, and storing the data; S2, according to the crawled data, analyzing user basic information from the aspect of user static attributes, and performing user static attribute grade division. Data is crawled from the network, the cardinal number of the data size is larger, the screening precision of clients is higher, potential clients with low conversion rate are effectively deleted, the advertisement putting cost is reduced, higher profits are achieved, meanwhile, old clients are screened, and the quality of the old clients is graded, so that the advertisement putting efficiency is improved in a targeted manner. And a corresponding marketing strategy is made.

Description

technical field [0001] The invention belongs to the technical field of big data, and in particular relates to a method for screening customers based on big data. Background technique [0002] With the advent of the cloud era, big data has also attracted more and more attention. Based on big data, companies can conduct precise marketing to consumers. By understanding the gap between raw data and data analysis, companies can eliminate low-quality data and Get better decisions with BI. [0003] At present, the invention patent with the patent number CN201810546593.X discloses a customer screening method, which specifically includes the following steps: S1, enter customer information and upload to the database; S2, call out customer-related information from the database and download it, and download the downloaded customer information Upload to the big data insurance analysis system; S3, the big data insurance analysis system calculates and analyzes the proposed insurance type ...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q30/02G06F16/951G06F16/955
CPCG06Q10/06393G06Q30/0201G06Q30/0271G06Q30/0273G06Q30/0277G06F16/951G06F16/955Y02D10/00
Inventor 刘祥
Owner 深圳市我们在线教育有限公司
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