Power supply customer value evaluation method based on customer portrait technology and big data platform

Abstract

The invention discloses a power supply customer value evaluation method based on a customer portrait technology, and the method comprises the steps: extracting user features through the analysis of the internal data of an enterprise and the external data of an Internet transaction platform in an informatization system such as a power customer service system, and formulating a power customer labelset based on business demands, so as to make customer value evaluation. The method comprises a step of data acquisition and a step of data analysis and mining. The step of data acquisition comprises substeps of acquiring data from each business system and an external environment. The data comprises enterprise internal data such as a user standing book, power consumption data, payment information and GIS data and external data such as an internet transaction platform, and the data is analyzed and mined so as to extract customer characteristics from the data and formulate a power customer labelset based on business requirements.

Description

technical field [0001] The invention relates to a value evaluation method for power supply customers, more specifically, a power supply customer value evaluation method and a big data platform based on customer portrait technology. Background technique [0002] In recent years, the reform of the power system and the liberalization of the power sales side have put forward new requirements for customer service of power companies. How to make full use of various power customer data, gain insights into customer needs, formulate precise marketing strategies and provide differentiated services based on this, It has become the key for power supply enterprises to improve customer experience and expand market share, and customer portrait is an effective technical means to realize the explicitness of customer hidden characteristics and assist in in-depth insight into customer needs. [0003] At present, there are many types of power marketing customer data, and the data information is...

AI Technical Summary

Problems solved by technology

[0003] At present, there are many types of power marketing customer data, and the data information is fragmented and distributed in multiple information systems. Marketing business personnel need to filter effective information from the complex business systems, with a heavy workload and high requirements on the business level of business personnel; and due to Lacking theoretical guidance on classification methods, customer label categories are extensively expanded according to business needs, which brings more and more problems to the establishment of subsequent label models, label calculation efficiency, label management and use

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