Client channel drainage method based on big data recommendation algorithm

A recommendation algorithm and big data technology, applied in data processing applications, calculations, advertising, etc., can solve the problems of customers who are prone to deviation, the drainage plan is not comprehensive, rigorous, scientific, and unable to tap the potential of drainage, so as to achieve less deviation, The comprehensive effect of the drainage plan

Pending Publication Date: 2020-05-08
HUANGYANG ELECTRIC POWER
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Problems solved by technology

The existing channel drainage methods mainly rely on experience and experience, and cannot accurately screen target customers, and cannot tap customers with drainage potential. The drainage plan is not comprehensive, rigorous, and scientific, and is prone to deviation

Method used

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  • Client channel drainage method based on big data recommendation algorithm
  • Client channel drainage method based on big data recommendation algorithm
  • Client channel drainage method based on big data recommendation algorithm

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specific Embodiment

[0101] At present, State Grid Corporation’s related business payment includes 7 channels including the online State Grid APP, Alipay, WeChat, Dian Ebao, self-service terminals, business halls, and banks. The distribution of customers’ household age, age, urban and rural categories, etc. under each channel The situation, the frequency of payment behaviors under each channel in the past 6 months, and the proportion of customers in each channel are analyzed in three aspects.

[0102] Using RFM model and entropy value method (determining the weight of each index) to construct payment channel preference model. According to the time interval information (R) from the customer's latest payment to the present, the total payment frequency (F) of using a certain channel within 6 months, and the average payment amount (M) of a certain channel within 6 months, output each customer's pair The usage evaluation index of each channel. The entropy method is used to optimize the weight, highlig...

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Abstract

The invention discloses a client channel drainage method based on a big data recommendation algorithm, and belongs to the technical field of power operation. An existing channel drainage method mainlydepends on experience, cannot accurately screen target customers, and cannot mine customers with drainage potential. According to the invention, a client channel drainage model is established by taking a client as a center, and the tendency of the client to handle business by means of terminal equipment is analyzed from service and product requirements triggered by the client; meanwhile, the customer use information of each electronic channel is effectively fused, the customer group is subdivided, the internal characteristics and rules of using various electronic channels by customers are deeply explored, the purpose of using the electronic channels by the customers is more comprehensively understood, and guidance is provided for development and marketing of the electronic channels; and thus, the client channel can be guided. The drainage scheme is comprehensive, rigorous and scientific, and deviation is not prone to occurring.

Description

technical field [0001] The invention relates to a customer channel drainage method based on a big data recommendation algorithm, and belongs to the technical field of electric power operation. Background technique [0002] With the increasingly fierce competition in the power market, the role of channels is no longer limited to the sales of a single business and related services, but plays a decisive role in market competition. The existing channel drainage methods mainly rely on experience and experience, and cannot accurately screen target customers, and cannot tap customers with drainage potential. The drainage plan is not comprehensive, rigorous, and scientific, and is prone to deviation. Contents of the invention [0003] Aiming at the defects of the prior art, the purpose of the present invention is to provide an in-depth analysis of the customer behavior characteristics of the online State Grid APP, combined with the results of channel customer behavior preference a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q50/06
CPCG06Q30/0255G06Q30/0254G06Q30/0271G06Q50/06
Inventor 金媛媛李鹏鹏娄伟明王庆娟蒋颖沈皓张维潘喆琼陶崇冯龙汪璐杨威陈宇渊郑则诚柯方圆毛倩倩李莉孔旭锋
Owner HUANGYANG ELECTRIC POWER
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