Method for segmenting metered industry customers on basis of CRFM (customer recency, frequency and monetary) models

A customer and model technology, applied in the direction of calculation, computer parts, characters and pattern recognition, etc., can solve the problems of unable to subdivide customer behavior characteristics, RFM model can not meet customer relationship management, etc., to simplify the process of customer segmentation, improve profit effect

Pending Publication Date: 2018-05-04
FUJIAN METROLOGY INST
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

A single RFM model cannot satisfy the management of each type of customer relationship, nor can it comprehensively subdivide the behavioral characteristics of customers. In view

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for segmenting metered industry customers on basis of CRFM (customer recency, frequency and monetary) models
  • Method for segmenting metered industry customers on basis of CRFM (customer recency, frequency and monetary) models
  • Method for segmenting metered industry customers on basis of CRFM (customer recency, frequency and monetary) models

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] Such as figure 1 As shown, a kind of measurement industry customer subdivision method based on CRFM model of the present invention comprises the following steps:

[0029] Step S1, extracting historical sample data of metering customers;

[0030] Step S2, preprocessing the extracted sample data;

[0031] Step S3, define and calculate the index values ​​in the CRFM model, and normalize these index values, the index values ​​include the latest inspection time R, inspection frequency F, detection amount M and average inspection period C;

[0032] Step S4, based on the index value of the CRFM model, use the K-Means algorithm to cluster the customers for measurement and inspection;

[0033] Step S5, calculate the average value of each index of different customer groups after clustering, compare with the average value of each index corresponding to the sample data before clustering, and create a customer classification matrix according to the changes of these index values, ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method for segmenting metered industry customers on the basis of CRFM (customer recency, frequency and monetary) models. The method includes extracting historical sample dataof the metered customers; preprocessing the extracted sample data; defining and computing index values in the CRFM models and carrying out normalization processing on the index values; clustering themetered inspected customers on the basis of the index values of the CRFM models by the aid of K-Means algorithms; computing average values of various indexes of different clustered customer groups, comparing the average values of the various indexes of the different clustered customer groups to average values of various indexes corresponding to the sample data before the sample data are clustered,creating customer classification matrixes according to change of index values and classifying values of the customer groups. The index values in the CRFM models include recent inspection time R, inspection frequencies F, detection money amounts M and average inspection periods C. The method for segmenting the customers has the advantages that the method is combined with actual business requirements of metered industries, accordingly, the customers can be segmented, bases can be provided for customizing personalized service, and the ultimate purpose of maximizing profits of the metered industries can be achieved.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a method for subdividing customers in the metering industry based on a CRFM model. Background technique [0002] Using data mining technology to extract customer transaction behavior characteristics has gradually become an important strategic means for various industries to formulate differentiated marketing strategies, improve customer loyalty, and maximize customer value. In order to understand the consumption behavior of different customer groups, techniques such as customer segmentation are widely used. At present, domestic metrology institutions do not have a relatively complete customer segmentation system to unify and integrate metrology customer resources. [0003] Among the many customer relationship management (CRM) analysis models, the RFM model is widely mentioned. The RFM model is an important tool and means to measure customer value and customer profitability. It is base...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/62
CPCG06F18/23213
Inventor 郑培强林景星江乃深庄慧强张丽贞
Owner FUJIAN METROLOGY INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products