Method for establishing panoramic view of power customer

Abstract

The invention relates to a method for establishing a panoramic view of a power customer, which comprises the following steps of: carding a panoramic view standard of the power customer, collecting and integrating power customer data of multiple data sources inside and outside a state grid system, carrying out data analysis mining by virtue of a big data analysis technology, perfecting a multi-layer, multi-view and three-dimensional customer panoramic view in a label form, and establishing a panoramic view of the power customer. And an accurate and comprehensive customer portrait is described.

Description

Technical Field

[0001] The present invention relates to a method for establishing a panoramic view of power customers, sorting out the standards for the panoramic view of power customers, collecting and integrating power customer data from multiple data sources inside and outside the system, relying on big data analysis technology, conducting data analysis and mining, and improving the multi-level, multi-perspective, three-dimensional customer panoramic view in the form of tags to depict an accurate and comprehensive customer portrait. Technical Background

[0002] At present, power companies have a large number of customer groups and data resources, but the update and improvement of customer file information are relatively lagging behind. There is no perfect data mining and analysis platform for customer credit information, and it is impossible to effectively use fragmented information data such as customer files, customer credit investigation data, electricity consumption behavior, and payment behavior to depict an accurate and comprehensive credit customer portrait. Based on the long-term development strategy of the enterprise to achieve precise marketing, cost reduction and efficiency improvement, by refining the basic power data of existing customers, integrating external credit investigation data, relying on big data analysis technology, establishing and improving multi-dimensional and three-dimensional customer tags and customer portraits, mining customer credit characteristics, and realizing the efficient aggregation of customer credit data and business service data. Summary of the Invention

[0003] The technical problem to be solved by the present invention is a method for establishing a panoramic view of power users, sorting out the standards for the panoramic view of power customers, collecting and integrating power customer data from multiple data sources inside and outside the system, relying on big data analysis technology, conducting data analysis and mining, and improving the multi-level, multi-perspective, three-dimensional customer panoramic view in the form of tags to depict an accurate and comprehensive customer portrait.

[0004] The present invention relates to a method, which at least includes the following steps:

[0005] Step 1: Design of tag library management function

[0006] Based on customer interaction information data, combined with typical business applications of customer service big data, customer basic information, customer industry information, and third-party customer data are used to extract customer tags by means of statistics, data mining, etc., to enrich the existing customer tag library and assist in supporting innovative interactive service applications.

[0007] Step 2: Design of tag management function

[0008] In order to more effectively manage, use, and optimize tags, a set of tag lifecycle management processes is established to implement the lifecycle of tags from creation, update, approval, release, evaluation, to decommissioning, forming a benign closed-loop management for tags and guiding requirements analysis. Additionally, since tags and strategies are the basis for subsequent marketing-related mining and analysis functions, the storage of tags needs to meet performance requirements such as being shareable, easily expandable, and having efficient storage and query capabilities.

[0009] Step 3: Design of Customer View Function

[0010] Based on internal business data collection, external data collection, on-site tag data collection, and data dynamic maintenance and supplementation, the collected tag data is summarized. Using big data visualization technology, a comprehensive data view of major customers is constructed to provide services such as data query and retrieval for relevant personnel.

[0011] Step 4: Design of Customer Analysis Function

[0012] Customer group analysis helps business personnel conduct two-way screening of customer demand characteristics and customer tag attributes, and further carry out customer segmentation. For the selected customer groups with specific needs, business personnel can understand the characteristics of these customers in different dimensions, such as age distribution and occupation distribution. After importing or screening customers through customer group analysis, multi-dimensional analysis of these customers is carried out. In terms of the implementation method of the customer group analysis function, it is required to select dimensions of customer attributes on the customer demand attribute view in a graphical drag-and-drop manner, and display the analysis results by selecting appropriate graphics (pie chart, line chart, bar chart).

[0013] Utilize customer tags and customer attributes to provide a simple and direct drag-and-drop target customer screening function. Users only need to select the corresponding customer tags and customer attributes (including judgment conditions greater than, less than, equal to) and the combination relationship between them (AND / OR) to quickly screen target customers through the customer tag application system.

[0014] For the customer list screened out based on customer tags, customer needs, and characteristic attributes, it is pushed to relevant business systems through an interface method to achieve a fine description of the characteristics of major power customers, provide a support basis for business operations, enable employees to quickly and comprehensively identify major customer characteristics, and conduct customer service strategy analysis based on this. For traditional business work such as power consumption inspections and orderly power consumption plans for users with default electricity theft, customers who often generate late fees, and black and white lists, corresponding service strategies are formulated, and at the same time, differentiated service strategies are formulated for specific customers. Specific Implementation Manner

[0015] Step 1: Design of Tag Library Management Function

[0016] Based on customer interaction information data, combined with typical business applications of customer service big data, for customers' basic information, customer industry information, and third-party customer data, statistical and data mining methods are used to extract customer tags, enrich the existing customer tag library, and assist in supporting innovative interactive service applications.

[0017] Construct a customer interaction information model: Based on the marketing basic data platform, combined with the theory of customer full life cycle management, comprehensively analyze customer basic information, customer behavior traces, etc. in internal related business systems such as marketing, 95598, distribution network, bank credit investigation, Alipay, and mobile positioning. Conduct research on the customer information interaction requirements between internal and external systems, and establish a customer information interaction model. The customer interaction information model mainly includes customer basic information, customer contact point information, power outage information, meter reading, billing and collection information, customer relationship information, business handling information, power consumption inspection information, substation-line-transformer-customer information, etc., which is used to support customer demand analysis.

[0018] (1) Customer basic information: Customer basic information mainly includes account information, contact information, address information, customer manager information, etc.

[0019] (2) Customer contact point information: Customer contact point information mainly includes consultation and inquiry information, fault repair information, complaints and reports, praise and suggestions, information subscription, return visit information, payment information, etc.

[0020] (3) Power outage information: Power outage information mainly includes the work orders of customers' previous power outage records.

[0021] (4) Meter reading, billing and collection information: Meter reading, billing and collection information mainly includes meter reading lists, basic information, indication number information, calculation lists, electricity charge information, bill lists, payment details, etc.

[0022] (5) Customer relationship information: Customer relationship information mainly includes customer relationship diagrams, customer relationship lists, etc.

[0023] (6) Business handling information: Business handling information mainly includes business handling records, detailed business handling situations, etc.

[0024] (7) Power consumption inspection information: Power consumption inspection information mainly includes power consumption inspection lists, detailed power consumption inspection situations, etc.

[0025] (8) Contract information: Contract information mainly includes basic information, relocation information, financial information, etc.

[0026] (9) Substation-line-transformer-customer information: Substation-line-transformer-customer information mainly includes user information, substation-line-transformer-customer diagrams, etc.

[0027] Step 2: Design of label management function

[0028] In order to more effectively manage, use, and optimize tags, a set of tag lifecycle management processes is established to implement the lifecycle of tags from creation, update, approval, release, evaluation to decommissioning, forming a virtuous closed-loop management for tags and guiding requirements analysis. Additionally, since tags and strategies are the basis for subsequent marketing-related mining and analysis functions, the storage of tags needs to meet performance requirements such as being shareable, easily extensible, and efficient in storage and query.

[0029] Tag category management: Tag category management mainly realizes the creation and definition of the tag structure tree, and the hierarchy of the tag tree supports multi-level customization functions.

[0030] Tag generation management: Tag generation management realizes the task management of tagging customers for the published tags in manual or automatic ways. The manual way means manually triggering the tagging task, and the automatic way means that through the timing configuration of task execution, the computer automatically executes the tagging task according to the task requirements.

[0031] Tag analysis management: Configure and define the generation of large customer demand analysis models and model-related information. The information maintained mainly includes 1) Maintenance of model basic information: model definition, model evaluation cycle, model trigger time; 2) Maintenance of model evaluation indicators: indicator definition, indicator data fetching rules, indicator weights; 3) Maintenance of model output results: comprehensive evaluation criteria (such as high-quality customer level, potential high-quality customers, high-quality customers, etc.).

[0032] Step 3: Design of customer view functions

[0033] Based on internal business data collection, external data collection, on-site tag data collection, data dynamic maintenance and supplement, summarize the collected tag data. Using big data visualization technology, construct a comprehensive data view of large customers to provide services such as data query and retrieval for relevant personnel.

[0034] Customer portrait view: Based on external data, use big data visualization technology to display information such as the customer's industry, legal person, geographical location, legal affairs, taxation, bank, etc., and portrait the customer.

[0035] Power data view: Based on the data in the power marketing system, display specific services such as customer fault repair, consultation business, business demands, business complaints, electricity consumption statistics, payment risks, and illegal electricity use in the form of a data view.

[0036] (1) Summary and analysis of fault repair

[0037] Based on the historical fault repair data of large customers, summarize information such as the number of fault repairs of large customers, processed data, pending data, average service evaluation, and average processing duration, and display it using visualization technology

[0038] (2) Aggregate Analysis of Consulting Services

[0039] Based on the historical electricity consumption consulting data of large customers, aggregate information such as the number of consultations of large customers, analysis of consultation hotspots, and average service evaluation, and display it using visualization technology.

[0040] (3) Aggregate Analysis of Business Demands

[0041] Based on the historical electricity consumption data of large customers, aggregate information such as the number of demand feedbacks of large customers, processed data, analysis of demand feedback business hotspots, and average service evaluation, and display it using visualization technology.

[0042] (4) Aggregate Analysis of Complaint Services

[0043] Based on the historical electricity consumption complaint data of large customers, aggregate information such as the number of complaints of large customers, processed data, analysis of complaint business hotspots, and average service evaluation, and display it using visualization technology.

[0044] (5) Aggregate Analysis of Electricity Consumption Statistics

[0045] Based on the historical electricity consumption data of large customers, aggregate the electricity consumption of large customers annually and monthly, and display information such as the peak and valley periods of large customers' electricity consumption, peak electricity consumption statistics, peak electricity consumption payment statistics, valley electricity consumption statistics, and electricity consumption growth rate analysis, and display it using visualization technology.

[0046] (6) Aggregate Analysis of Payment Risk Indicators

[0047] Based on the historical payment situation of large customers, aggregate the situations of large customers' arrears, overdue payments, and penalty payments, establish a risk assessment index system, and comprehensively analyze the electricity bill risks of customers. Display it using visualization technology

[0048] Panoramic Data View: Based on external data and data from the power marketing system, conduct penetrative management of power customers from the natural attributes, management attributes, and behavioral attributes of customers, display the customer panorama in the form of a data view, and enable three-level penetration. Achieve a multi-level, multi-perspective, and three-dimensional customer panorama view, and depict an accurate and comprehensive customer portrait.

[0049] Step 4: Design of Customer Analysis Function

[0050] Customer group analysis helps business personnel to conduct two-way screening of customer demand characteristics and customer label attributes, and further carry out customer segmentation. For the selected customer groups with specific needs, business personnel can understand the characteristics of these customers in different dimensions, such as: distribution in terms of age, distribution in terms of occupation. Through customer group analysis, after importing customer groups or screening out customers, multi-dimensional analysis can be carried out on these customers. In terms of the implementation method of the customer group analysis function, it is required to select dimensions of customer attributes on the customer demand attribute view in a graphical drag-and-drop manner, and display the analysis results by selecting appropriate graphics (pie chart, line chart, bar chart).

[0051] Utilize customer labels and customer attributes to provide a simple and direct drag-and-drop target customer screening function. Users only need to select the corresponding customer labels and customer attributes (including judgment conditions greater than, less than, equal to) and the combination relationship (AND / OR) between them, and they can quickly screen target customers through the customer label application system.

[0052] For the customer list screened out based on customer labels, customer needs, and characteristic attributes, it is pushed to the relevant business systems through an interface method to achieve a fine description of the characteristics of large power customers, provide a support basis for business operations, enable employees to quickly and comprehensively identify the characteristics of large customers, and conduct customer service strategy analysis based on this. For traditional business work such as electricity consumption inspections and orderly electricity use plans for users with default electricity theft, customers who often generate late fees, and black and white lists, corresponding service strategies are formulated, and at the same time, differentiated service strategies are formulated for specific customers.

[0053] When implementing the above technical solution, a method for establishing a panoramic customer view is provided. The standards for the panoramic view of power customers are sorted out, and the power customer data from multiple data sources inside and outside the system are collected and integrated. Relying on big data analysis technology, data analysis and mining are carried out to improve the multi-level, multi-perspective, and three-dimensional panoramic customer view in the form of labels, and an accurate and comprehensive customer portrait is depicted.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate rather than limit the technical solutions described in the present invention; therefore, although this specification has described the present invention in detail with reference to the above embodiments, those of ordinary skill in the art should understand that the present invention can still be modified or equivalently replaced; and all technical solutions and their improvements that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A method for establishing a panoramic view of power customers, characterized in that: The method comprises at least the following steps: Step 1: Design of tag library management function Based on customer interaction information data and combined with typical business applications of customer service big data, we use statistics, data mining and other methods to refine customer tags for customer basic information, customer industry information and third-party customer data, enrich the existing customer tag library, and assist in supporting innovative interactive service applications. Step 2: Design of tag management function In order to more effectively master, use and optimize labels, a label lifecycle management process is established to implement the label lifecycle from creation, update, approval, release, evaluation, and offline, form a benign closed-loop management of labels, and guide demand analysis; in addition, because labels and strategies are the basis of subsequent marketing-related mining and analysis functions, the storage of labels needs to meet performance requirements such as shareability, easy scalability, and efficient storage and query. Step 3: Customer view function design Based on internal business data collection, external data collection, on-site label data collection, dynamic data maintenance and supplementary recording, the collected label data is summarized. Using big data visualization technology, a comprehensive data view of key customers is constructed to provide data query, retrieval and other services for relevant personnel. Step 4: Design customer analysis functions Customer group analysis is to help business personnel conduct two-way screening of customer demand characteristics and customer label attributes, and further develop customer segmentation. For the selected customer groups with specific needs, business personnel can understand the characteristics of this group of customers in different dimensions, such as: age distribution, occupational distribution, and through customer group analysis, after importing customer groups or screening out customers, conduct multi-dimensional analysis on this group of customers. The implementation method of customer group analysis requires the dimension selection of customer attributes on the customer demand attribute view by dragging and dropping graphics, and the analysis results are displayed by selecting appropriate graphics (pie charts, line charts, bar charts). The customer tags and customer attributes provide a simple and direct drag-and-drop target customer screening function. Users only need to select the corresponding customer tags and customer attributes (including the judgment conditions of greater than, less than, and equal to) and the combination relationship (AND / OR) between them to quickly screen target customers through the customer tag application system. The customer list screened out based on customer tags, customer needs and characteristic attributes is pushed to the relevant business system through the interface, which enables a detailed characterization of the characteristics of large power customers, provides support for business operations, and enables employees to quickly and comprehensively identify the characteristics of large customers, and use this to analyze customer service strategies, formulate corresponding service strategies for traditional business tasks such as defaulting on electricity theft users, lists of customers who frequently incur late payment fees, electricity usage inspections based on black and white lists, orderly electricity usage plans, etc., and at the same time formulate differentiated service strategies for specific customers.