Customer service strategy making method and device based on random forest and decision-making tree

A random forest and customer service technology, applied in the field of machine learning to achieve precise positioning, maintain long-term sustainable development, and enhance competitiveness

Inactive Publication Date: 2018-07-13
STATE GRID SHANDONG ELECTRIC POWER
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In order to overcome the deficiencies of the above-mentioned existing technologies and solve the existing problems in the existing technologies of how to realize the precise identification and positioning of high-quality customers based on big data, and how to formulate personalized and value-added service strategies based on the identified high-quality customers, this paper The invention provides a method and device for formulating customer service strategies based on random forests and decision trees on the electricity sales side. Dimensional customer evaluation index

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  • Customer service strategy making method and device based on random forest and decision-making tree
  • Customer service strategy making method and device based on random forest and decision-making tree
  • Customer service strategy making method and device based on random forest and decision-making tree

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Embodiment 1

[0071] This embodiment discloses a method for formulating customer service strategies based on random forests and decision trees, as shown in Figure 1, including the following steps:

[0072] Step (1): Obtain the value characteristics of sample customers, and judge the quality of sample customers;

[0073] Step (2): Use sample customer data, train based on random forest and decision tree algorithms, and build a high-quality customer identification model;

[0074] Step (3): Analyzing the validity of the judgment results of the high-quality customer identification model based on the expert supervision method, and training the high-quality customer optimization identification model based on the analysis results;

[0075] Step (4): Using the value characteristics of the customers to be identified as input, based on the high-quality customer optimization identification model, the high-quality customer identification results of different interpretations are obtained;

[0076] Step ...

Embodiment 2

[0178] The purpose of this embodiment is to provide a device for formulating customer service strategies based on random forests and decision trees.

[0179] A client service strategy formulation device based on random forest and decision tree, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, the processor implements the following steps when executing the program, including :

[0180] Step (1): Obtain the value characteristics of sample customers, and judge the quality of sample customers;

[0181] Step (2): Use sample customer data, train based on random forest and decision tree algorithms, and build a high-quality customer identification model;

[0182] Step (3): Analyzing the validity of the judgment results of the high-quality customer identification model based on the expert supervision method, and training the high-quality customer optimization identification model based on the analysis results;

[0183] Step ...

Embodiment 3

[0188] The purpose of this embodiment is to provide a computer-readable storage medium.

[0189] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are performed:

[0190] Step (1): Obtain the value characteristics of sample customers, and judge the quality of sample customers;

[0191] Step (2): Use sample customer data, train based on random forest and decision tree algorithms, and build a high-quality customer identification model;

[0192] Step (3): Analyzing the validity of the judgment results of the high-quality customer identification model based on the expert supervision method, and training the high-quality customer optimization identification model based on the analysis results;

[0193] Step (4): Using the value characteristics of the customers to be identified as input, based on the high-quality customer optimization identification model, the high-quality customer identif...

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Abstract

The invention discloses a customer service strategy making method and device based on a random forest and decision-making tree. The method includes: acquiring the value features of a sample customer,performing quality discrimination, and the using the sample customer data to build a high-quality customer identification model on the basis of a random forest and decision-making tree algorithm; inputting the value features of a to-be-identified customer into the high-quality customer identification model to obtain high-quality customer identification results of different definitions; acquiring the service requirements of the sample customer, and performing standardized classification analysis to build a service requirement library; matching the service requirements in the service requirementlibrary with service content, matching the service content with the high-quality customers of different definitions, and building a service strategy library; searching the service strategy library according to the high-quality customer identification results to obtain the service strategy matched with a current customer. The customer service strategy making method has the advantages that high-quality customers can be precisely positioned on the basis of big data, and the analysis results of user power use service requirement analysis are used to make personalized and value-added service products and service strategies.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and relates to a method and device for formulating customer service strategies based on random forests and decision trees, in particular to a method and device for formulating high-quality customer service strategies based on random forests and decision trees. Background technique [0002] With the deepening of electric power reform and the full liberalization of the electricity sales side market, power supply companies at all levels of the State Grid Corporation of China are facing pressure from market competition. In order to improve the profitability and competitiveness of power grid enterprises, increase the loyalty, satisfaction and customer Stickiness, on the basis of doing a good job in the general service of the whole society, providing high-quality services to high-quality customers will be the main means and strategies for various electricity sales entities to compete for high-q...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q30/02G06Q50/06
CPCG06Q10/04G06Q10/0639G06Q30/0201G06Q50/06
Inventor 张洪利李云亭荣以平朱伟义刘霄慧尹明立乔学明王伟姜云刘昳娟王鑫
Owner STATE GRID SHANDONG ELECTRIC POWER
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