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Resident customer value grading model construction method based on analytic hierarchy process

An analytic hierarchy process and customer value technology, applied in the power field, can solve problems such as inability to accurately distinguish customers, inability to identify and evaluate influencing factors, and inability to realize lean transformation of power supply services, so as to improve users' social credit and evaluate grading schemes Science, improve the effect of electricity consumption behavior

Inactive Publication Date: 2020-05-08
STATE GRID ZHEJIANG ELECTRIC POWER CO MARKETING SERVICE CENT
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Problems solved by technology

[0003] However, the above-mentioned scheme directly applies the formula to carry out the credit evaluation calculation, and cannot carry out deeper identification and evaluation of influencing factors according to the actual situation. Realize lean transformation of power supply services

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  • Resident customer value grading model construction method based on analytic hierarchy process
  • Resident customer value grading model construction method based on analytic hierarchy process
  • Resident customer value grading model construction method based on analytic hierarchy process

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specific Embodiment

[0076] Establish a customer value classification model, and decompose the relevant index factors into several levels from top to bottom according to different attributes; when there are too many criteria (more than 9), it should be further decomposed into sub-criteria layers; For pairwise comparison, according to their relative importance, use the Star relative importance scale to assign values, and form a pairwise comparison judgment matrix: A=(X ij ) n*n .

[0077] Incorporate the comprehensive score of resident customers into the target layer as a decision-making target;

[0078] Incorporate information, payment, electricity consumption, interaction, and growth into the standard layer;

[0079] Incorporate each sub-item into its corresponding program layer to form a hierarchical analysis structure;

[0080] Construct a paired comparison array, starting from the second layer of the hierarchical structure model, and use the paired comparison method to construct a paired co...

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Abstract

The invention discloses a resident customer value grading model construction method based on an analytic hierarchy process, and belongs to the technical field of electric power. An existing evaluationscheme directly uses a formula to carry out credit evaluation calculation, deeper influence factor identification and evaluation cannot be carried out according to actual conditions, and an evaluation grading scheme is not scientific and reasonable enough. According to the invention, the AHP analytic hierarchy process is adopted to calculate the comprehensive rating score of the customer, and qualitative and quantitative analysis is carried out on the value of the customer in a multi-objective and hierarchical manner; customer value characteristics can be fully mined, and an evaluation grading scheme is more scientific and reasonable. In combination with customer marketing service guidance at the present stage and based on customer power consumption historical data such as information conditions, payment conditions, power consumption conditions, interaction conditions and growth conditions, customer model scores are comprehensively evaluated from five dimensions such as the customer information conditions, the payment conditions, the power consumption conditions, the interaction conditions and the growth conditions through research methods such as business research, expert interview and mining modeling.

Description

technical field [0001] The invention relates to a method for constructing a residential customer value classification model based on analytic hierarchy process, which belongs to the field of electric power technology. Background technique [0002] Chinese patent (application publication number CN 106780140 A) discloses a big data-based electric power credit evaluation method, which systematically cleans and compares a large amount of historical data such as customer basic information, payment behavior, electricity consumption behavior, and social credit information. Analysis, using mathematical statistics methods and BP neural network model improved by genetic algorithm to mine the behavior patterns and credit characteristics contained in the data, capture the relationship between historical information and credit performance, comprehensively evaluate credit performance with credit ratings, and promote power customers Classified credit management supports the research on dif...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/06393G06Q10/067G06Q50/06
Inventor 金良峰郑斌王正国侯素颖洪健山裘炜浩丁麒沈皓许小卉叶盛张维沈然陈海娜陈雨佳项秋涛张爽吕诗宁汪一帆朱凯熙吴冰洁左玉朱亚雯
Owner STATE GRID ZHEJIANG ELECTRIC POWER CO MARKETING SERVICE CENT
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