Information management method and system for electricity marketing

Abstract

The invention relates to an information management method and system for power marketing, and the method comprises the steps: determining which power package is selected by a plurality of users under different power consumption conditions through the pre-construction of a user package model; therefore, package selection intentions of different users are determined. And then matching the current package information of the current power user with the user information and the historical power consumption data through the user package model. And if not, it is possible that the current power consumer lacks corresponding marketing information, so that the package change is not carried out. Therefore, the marketing copywriting of other matched packages is automatically matched with the current power user, so that marketing personnel can carry out directional marketing according to user requirements. The method is based on user demands, and has the advantages of being accurate in marketing content, high in success rate and capable of meeting the user demands.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to an information management method and system for power marketing. Background Art

[0002] The purpose of power marketing is to provide corresponding services according to customer needs. The essence of power marketing is to adjust the demand level and demand time of the power market, meet the users' reasonable power consumption requirements with good service quality, achieve mutual coordination between power supply and demand, establish a partnership between power companies and users, and encourage users to actively change their consumption behavior and power consumption methods, improve power consumption efficiency, and thus increase the benefits of the company. Power companies achieve their various goals by satisfying consumers' needs.

[0003] For corporate users, there are many choices of electricity packages. Therefore, it is very important to carry out appropriate electricity marketing for corporate users. The existing electricity marketing methods are relatively simple, mainly based on telephone, text messages and other means to push packages and business information. There is no information push based on user needs. Summary of the invention

[0004] In view of this, an object of the present invention is to provide an information management method and system for power marketing to solve the problem of user demand for information content in power marketing in the prior art.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for managing information for power marketing of the present invention comprises the following steps:

[0007] Obtain user information, historical electricity consumption data and current package information of current electricity users;

[0008] Determine the matching degree between the current power user and the current package information based on a pre-built user package model, user information of the current power user and historical power consumption data, wherein the user package model represents the matching degree between the user information, historical power consumption data and the package selected by the user;

[0009] When the matching degree between the current electricity user and the current package information is less than a preset threshold, a target package whose matching degree with the current electricity user is greater than or equal to the preset threshold is determined, and the marketing copy of the target package is obtained from a pre-built marketing copy library, and the marketing copy of the target package is associated with the current electricity user.

[0010] In one embodiment of the present application, the method for constructing the user package model includes:

[0011] Obtain user information and historical electricity consumption data of users corresponding to the various electricity packages, wherein the user information includes values ​​of various parameter factors, and the historical electricity consumption data includes average electricity consumption in multiple time periods;

[0012] Filter out the user set H corresponding to each electricity package, cluster the values ​​of the parameter factor n corresponding to multiple users in the user set, and obtain multiple first data clusters The average power consumption corresponding to multiple users in the user set is clustered to obtain multiple second data clusters H j , where i is the serial number of the first data cluster corresponding to the same parameter factor, and j is the serial number of the second data cluster;

[0013] From the first data cluster and the second data cluster H j The first associated data cluster associated with the corresponding electricity package is determined respectively and the second associated data cluster h j , and based on the first associated data cluster Determine the associated value range of the parameter factor n based on the second associated data cluster h j Determine the associated value range of historical electricity consumption data;

[0014] The number of data points of all first associated data clusters corresponding to each electricity package And the number of data points in the second associated data cluster N(h j ), determine the matching degree W of various parameter factors n The matching degree with the historical electricity consumption data is W0;

[0015]

[0016]

[0017] Based on the value range of various parameter factors corresponding to each electricity package, the matching degree W of various parameter factors n , the associated value range of historical electricity consumption data and the matching degree W0 of historical electricity consumption data are used to build a user package model.

[0018] In one embodiment of the present application, the matching degree between the current power user and the current package information is determined based on the pre-built user package model, the user information of the current power user and the historical power consumption data, including:

[0019] Compare the values ​​of each parameter factor of the user information of the current power user with the associated value range corresponding to the current package information, and compare the values ​​of the historical power consumption data of the current power user with the associated value range corresponding to the current package information;

[0020] When the value of each parameter factor falls within the corresponding associated value range, or the value of the historical power consumption data falls within the corresponding associated value range, a plurality of target matching degrees are obtained, wherein the target matching degree is the matching degree of the parameter factor or the matching degree of the parameter factor;

[0021] The multiple target matching degrees are summed to obtain the matching degree between the current electricity user and the current package information.

[0022] In one embodiment of the present application, from the first data cluster and the second data cluster H j The first associated data cluster associated with the corresponding electricity package is determined respectively and the second associated data cluster h j ,include:

[0023] Calculate the first data cluster Variance and the second data cluster H j The variance S j , and count the first data cluster The number of data points and the second data cluster H j The number of data points;

[0024] In Variance is less than the preset variance threshold, and the first data cluster When the number of data points in the first data cluster is greater than the preset threshold, As the first associated data cluster In the variance S j is less than the preset variance threshold, and the second data cluster H j When the number of data points of the second data cluster H is greater than a preset number threshold, j As the second associated data cluster h j .

[0025] In one embodiment of the present application, based on the first associated data cluster Determine the associated value range of the parameter factor n based on the second associated data cluster h j Determine the associated value range of historical electricity consumption data, including:

[0026] Calculate the first data cluster The average and the second data cluster H j The average value A j ;

[0027] Based on the first data cluster The average and variance Construct the associated value range of parameter factor n Based on the second data cluster H j The average value A j and variance S j Constructing the associated value range of historical electricity consumption data Among them, α is the first proportional parameter, and β is the second proportional parameter.

[0028] In an embodiment of the present application, determining a target package whose matching degree with the current power user is greater than or equal to a preset threshold includes:

[0029] The pre-built user package model, the user information of the current power user and the historical power consumption data determine the matching degree between the current power user and all power packages;

[0030] Select the target package whose matching degree is greater than or equal to the preset threshold.

[0031] In one embodiment of the present application, the process of constructing the marketing copy library includes:

[0032] Get marketing copy for a variety of electricity packages;

[0033] Build a marketing copy library based on the marketing copies of various electricity packages.

[0034] In one embodiment of the present application, it also includes:

[0035] The historical feedback channel of the current power user is used as a promotion channel for the marketing copy of the target package, and the promotion channel of the marketing copy of the target package is associated with the current power user.

[0036] In one embodiment of the present application, it also includes:

[0037] The user information of the associated electricity users, the marketing copy of the target package and the promotion channels are sent to the target objects.

[0038] The present application also provides an information management system for power marketing, including:

[0039] The acquisition module is used to obtain the user information, historical electricity consumption data and current package information of the current electricity user;

[0040] A matching module, used to determine the matching degree between the current power user and the current package information based on a pre-built user package model, the user information and the historical power consumption data of the current power user, wherein the user package model represents the matching degree between the user information, the historical power consumption data and the package selected by the user;

[0041] An association module is used to determine, from a pre-built marketing copy library, a marketing copy of a target package whose matching degree with the current power user is greater than or equal to a preset threshold when the matching degree between the current power user and the current package information is less than a preset threshold, and associate the marketing copy of the target package with the current power user.

[0042] The beneficial effects of the present invention are as follows: an information management method and system for power marketing of the present invention, by pre-building a user package model, determines which power package multiple users choose under different power usage conditions. Thereby determining the package selection intentions of different users. Then, the current package information of the current power user is matched with the user information and historical power usage data through the user package model. If there is a mismatch, it is possible that the current power user lacks the corresponding marketing information and thus has not made any package changes. Therefore, the present application automatically matches the marketing copy of other matching packages with the current power user, so that marketers can conduct targeted marketing according to user needs. The present application is based on user needs and has the advantages of accurate marketing content, high success rate, and meeting user needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0044] Figure 1 is a flow chart of a method for managing information for power marketing shown in one embodiment of the present application;

[0045] Figure 2 This is a schematic diagram of the marketing copy promotion process in one embodiment of the present application;

[0046] Figure 3 is a structural diagram of an information management system for power marketing shown in one embodiment of the present application;

[0047] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0048] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0049] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show the layers related to the present invention rather than being drawn according to the number, shape and size of the layers in actual implementation. In actual implementation, the type, quantity and proportion of each layer may be changed arbitrarily, and the layer layout may also be more complicated.

[0050] In the following description, numerous details are discussed to provide a more thorough explanation of embodiments of the present invention; however, it is apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details.

[0051] There are various electricity packages for corporate users on the market. Generally, users will choose the most suitable electricity package according to their own needs. However, some users choose packages that are not suitable for their needs due to lack of understanding of the products. Or when relevant personnel perform marketing tasks, they blindly promote marketing information from the product perspective and fail to conduct marketing activities from the user perspective. This leads to a disconnect between marketing information and user needs, which in turn leads to low efficiency of marketing activities.

[0052] In order to solve the above problems, the present application provides an information management method for power marketing, which is as follows.

[0053] Figure 1 is a flow chart of a method for managing information for power marketing shown in one embodiment of the present application. Figure 1 As shown: A power marketing information management method of this embodiment may include steps S110 to S130:

[0054] S110, obtaining user information, historical electricity consumption data and current package information of the current electricity user;

[0055] Among them, the electricity users in this application are corporate users, and the user information may include the type of enterprise, the industry to which it belongs, the scale of the enterprise (including the number of social security personnel, output value, tax amount, etc.), the location of the enterprise, etc. The above parameter factors will affect the electricity consumption of corporate users, and therefore serve as the electricity consumption characteristics of the enterprise. This application also obtains the historical electricity consumption data of corporate users, which is directly used as the electricity consumption characteristics of the enterprise.

[0056] S120, determining a matching degree between the current power user and the current package information based on a pre-built user package model, user information of the current power user, and historical power consumption data, wherein the user package model represents a matching degree between the user information, the historical power consumption data, and the package selected by the user;

[0057] Among them, the pre-built user-package model records the parameter factor value range and the historical electricity consumption data value range that may lead enterprise users to choose a certain electricity package. That is, when the value of a parameter factor of an enterprise falls into a certain range, or the historical electricity consumption data falls into a certain range, which electricity package the enterprise is likely to choose and the corresponding matching degree.

[0058] Since electricity packages are generally charged based on the user's electricity usage, this application builds a model based on the user's electricity usage characteristics and then associates it with the package selection. The model building method in this application is as follows:

[0059] (1) obtaining user information and historical electricity consumption data of users corresponding to the various electricity packages, wherein the user information includes values ​​of various parameter factors, and the historical electricity consumption data includes average electricity consumption in multiple time periods, such as average annual electricity consumption in the past five years;

[0060] Each electricity package will have multiple users to choose from. This application will first collect the user information and historical electricity usage data of the users who have chosen each electricity package as the basic data for model construction.

[0061] The following table is a schematic diagram of the basic data in this application. The basic data for model construction is shown in the following table:

[0062] Table 1. Basic data diagram

[0063]

[0064] (2) Filter out the user set H corresponding to each electricity package, cluster the values ​​of the parameter factor n corresponding to multiple users in the user set, and obtain multiple first data clusters The average power consumption corresponding to multiple users in the user set is clustered to obtain multiple second data clusters H j , where i is the serial number of the first data cluster corresponding to the same parameter factor, and j is the serial number of the second data cluster;

[0065] This application uses the user data corresponding to the electricity package as set H, which includes multiple values ​​of each parameter factor and multiple values ​​of average power consumption. This application clusters the multiple values ​​of each parameter factor and the multiple values ​​of average power consumption to obtain clustered values.

[0066] Specifically, for one-dimensional or two-dimensional numerical parameter factors, such as enterprise scale-related parameters (one-dimensional) and geographic coordinates (two-dimensional), this application adopts a density-based clustering algorithm, such as the DBSCAN algorithm. For text-based parameter factors, such as the industry and enterprise type, clustering can be performed directly through keyword screening.

[0067] After obtaining the plurality of first data clusters and the plurality of second data clusters, it is necessary to judge whether the plurality of first data clusters and the plurality of second data clusters are associated with the package selection. The specific process is as follows.

[0068] (3) From the first data cluster and the second data cluster H j The first associated data cluster associated with the corresponding electricity package is determined respectively and the second associated data cluster h j , and based on the first associated data cluster Determine the associated value range of the parameter factor n based on the second associated data cluster h j Determine the associated value range of historical electricity consumption data;

[0069] For text-type data clusters, the present application directly counts the number of data points in the data cluster. If the number exceeds a preset threshold, it means that the value of the corresponding parameter factor (including the text of the keyword) is associated with the selection of the electricity package.

[0070] For data clusters of numerical type, this application makes a comprehensive judgment by calculating the variance and the number of data points in the statistical data cluster, as follows:

[0071] (3.1) Calculate the first data cluster Variance and the second data cluster H j The variance S j , and count the first data cluster The number of data points and the second data cluster H j The number of data points;

[0072] (3.2) In the variance is less than the preset variance threshold, and the first data cluster When the number of data points in the first data cluster is greater than the preset threshold, As the first associated data cluster In the variance S j is less than the preset variance threshold, and the second data cluster H j When the number of data points of the second data cluster H is greater than a preset number threshold, j As the second associated data cluster h j .

[0073] Among them, the variance reflects the stability of the values ​​in the data cluster. Therefore, if the variance is less than the variance threshold, it means that the values ​​in the data cluster are stable and highly clustered. Combined with a large number of data points (used to exclude accidentally formed data clusters), a data cluster associated with the choice of electricity package is obtained.

[0074] In addition, since the associated data clusters are discrete, in order to facilitate subsequent matching, the corresponding value range is also constructed based on the associated data clusters, including:

[0075] (3.3) Calculate the first data cluster The average and the second data cluster H j The average value A j ;

[0076] (3.4) Based on the first data cluster The average and variance Construct the associated value range of parameter factor n Based on the second data cluster H j The average value A j and variance S j Constructing the associated value range of historical electricity consumption data Among them, α is the first proportional parameter, and β is the second proportional parameter.

[0077] This application constructs a continuous value range based on the standard deviation and the average value, and introduces a ratio parameter to adjust the size of the value range. The larger the ratio parameter, the larger the matching range, and the smaller the ratio parameter, the higher the matching accuracy, which can be adjusted according to actual needs. In this application, the values ​​of α and β are between 0.3-0.5.

[0078] (4) The number of data points in all first associated data clusters corresponding to each electricity package And the number of data points in the second associated data cluster N(h j ), determine the matching degree W of various parameter factors n The matching degree with the historical electricity consumption data is W0;

[0079]

[0080]

[0081] This application assigns weights based on the ratio of the number of data points. The more data points in the first associated data cluster or the second associated data cluster corresponding to the parameter factor or historical electricity consumption data, the greater the corresponding weight. The above formula directly normalizes the weight, so it is directly used as the matching degree. When calculating the matching degree later, the matching pairs of the matching items can be summed up.

[0082] (5) Based on the value range of various parameter factors corresponding to each electricity package and the matching degree W of various parameter factors n , the associated value range of historical electricity consumption data and the matching degree W0 of historical electricity consumption data are used to build a user package model.

[0083] After the above model is constructed, the matching degree between the current power user and the current package information is determined based on the pre-constructed user package model, the user information of the current power user and the historical power consumption data, including:

[0084] S121, comparing the values ​​of each parameter factor of the user information of the current power user with the associated value range corresponding to the current package information, and comparing the values ​​of the historical power consumption data of the current power user with the associated value range corresponding to the current package information;

[0085] S122, when the value of each parameter factor falls within the corresponding associated value range, or the value of the historical power consumption data falls within the corresponding associated value range, obtaining multiple target matching degrees, wherein the target matching degree is the matching degree of the parameter factor or the matching degree of the parameter factor;

[0086] S123, summing up multiple target matching degrees to obtain a matching degree between the current electricity user and the current package information.

[0087] When matching, the values ​​of each parameter factor of the current power user and the historical power consumption data are compared with the associated value range corresponding to the current package. For example, the scale data is compared with the scale associated value range of the current package. If it falls within the range, the corresponding matching value is obtained. Finally, all the obtained matching values ​​can be summed up.

[0088] In the present application, a parameter factor or historical electricity consumption data may have multiple associated value ranges. As long as the value of the parameter factor of the current electricity user or the value of the historical electricity consumption data falls into one of the corresponding associated value ranges, the matching value of this parameter factor can be obtained.

[0089] S130, when the matching degree between the current electricity user and the current package information is less than a preset threshold, determine a target package whose matching degree with the current electricity user is greater than or equal to the preset threshold, obtain the marketing copy of the target package from a pre-built marketing copy library, and associate the marketing copy of the target package with the current electricity user.

[0090] If the matching degree between the current electricity user and the current package information is less than the preset threshold, that is, if there is no match, this application searches for a target package matching the current electricity user from the model as a marketing target, specifically including:

[0091] S131, determining the matching degree between the current power user and all power packages using a pre-built user package model, user information of the current power user, and historical power consumption data;

[0092] S132, selecting a target package whose matching degree is greater than or equal to a preset threshold.

[0093] In this embodiment, the user information and historical electricity consumption data of the current electricity user are substituted into the model to obtain the matching degree between the current electricity user and all packages. The specific matching process is as described above, and then the target package with a matching degree greater than or equal to the preset threshold is selected. If the marketer has a marketing task for a certain package, he can also select a package with a heavy marketing task as the target package, so that the success rate of targeted marketing is higher.

[0094] In one embodiment of the present application, the process of constructing the marketing copy library includes:

[0095] Get marketing copy for a variety of electricity plans; marketing copy can be extracted from historical marketing activities or created by marketers.

[0096] A marketing copy library is constructed based on the marketing copy of various electricity packages. The marketing copy in the marketing copy library adopts a tree structure, with the electricity package as the lowest node. Higher-level nodes can also be established based on some characteristics of the electricity package. For example, dedicated electricity packages, electricity activity packages, etc.

[0097] Figure 2 Schematic diagram of the marketing copy promotion process in one embodiment of the present application. Figure 2 As shown, after obtaining the marketing copy of the target package through matching, the historical feedback channel of the current electricity user is also used as the promotion channel of the marketing copy of the target package, and the promotion channel of the marketing copy of the target package is associated with the current electricity user.

[0098] In order to improve the efficiency of marketing promotion, this application also conducts marketing copy promotion based on the historical feedback channels of current electricity users. If there is no historical feedback, promotion will be carried out through telephone, text messages, etc.

[0099] Finally, the user information of the associated power users, the marketing copy of the target package, and the promotion channels are sent to the target objects. The target objects are the staff in the marketing position, and the relevant personnel can carry out marketing promotion accurately and efficiently based on the associated information.

[0100] The present invention provides an information management method for power marketing, which determines which power package multiple users choose under different power usage conditions by pre-building a user package model. Thereby determining the package selection intentions of different users. Then, the current package information of the current power user is matched with the user information and historical power usage data through the user package model. If there is a mismatch, it is possible that the current power user lacks the corresponding marketing information and thus has not made a package change. Therefore, the present application automatically matches the marketing copy of other matching packages with the current power user, so that marketers can conduct targeted marketing according to user needs. The present application is based on user needs and has the advantages of accurate marketing content, high success rate, and meeting user needs.

[0101] like Figure 3 As shown, the present application also provides an information management system for power marketing, including:

[0102] The acquisition module is used to obtain the user information, historical electricity consumption data and current package information of the current electricity user;

[0103] A matching module, used to determine the matching degree between the current power user and the current package information based on a pre-built user package model, the user information and the historical power consumption data of the current power user, wherein the user package model represents the matching degree between the user information, the historical power consumption data and the package selected by the user;

[0104] An association module is used to determine, from a pre-built marketing copy library, a marketing copy of a target package whose matching degree with the current power user is greater than or equal to a preset threshold when the matching degree between the current power user and the current package information is less than a preset threshold, and associate the marketing copy of the target package with the current power user.

[0105] An information management system for power marketing of the present invention determines which power package multiple users choose under different power usage conditions by pre-building a user package model. Thereby determining the package selection intentions of different users. Then, the current package information of the current power user is matched with the user information and historical power usage data through the user package model. If there is a mismatch, it is possible that the current power user lacks the corresponding marketing information and thus has not made any package changes. Therefore, the present application automatically matches the marketing copy of other matching packages with the current power user, so that marketing personnel can conduct targeted marketing according to user needs. The present application is based on user needs and has the advantages of accurate marketing content, high success rate, and meeting user needs.

[0106] Figure 4 The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Figure 4The computer system of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0107] like Figure 4 As shown, the computer system includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method in the above embodiment. In RAM 403, various programs and data required for system operation are also stored. CPU 401, ROM 402 and RAM 403 are connected to each other through bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0108] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0109] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 409, and / or installed from a removable medium 411. When the computer program is executed by a central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0110] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0111] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the above-mentioned module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0112] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0113] Another aspect of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor of a computer, the computer executes the above method. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0114] Another aspect of the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method provided in each of the above embodiments.

[0115] The above embodiments are only preferred embodiments for fully illustrating the present application, and the protection scope of the present application is not limited thereto. Any equivalent substitution or change made by a person skilled in the art based on the present application is within the protection scope of the present application.

Claims

1. A method for managing information for power marketing, characterized in that: Includes steps: Obtain user information, historical electricity consumption data and current package information of current electricity users; Determine the matching degree between the current power user and the current package information based on a pre-built user package model, user information of the current power user and historical power consumption data, wherein the user package model represents the matching degree between the user information, historical power consumption data and the package selected by the user; When the matching degree between the current electricity user and the current package information is less than a preset threshold, a target package whose matching degree with the current electricity user is greater than or equal to the preset threshold is determined, and the marketing copy of the target package is obtained from a pre-built marketing copy library, and the marketing copy of the target package is associated with the current electricity user.

2. The method for managing information for power marketing according to claim 1, characterized in that: The method for constructing the user package model includes: Obtain user information and historical electricity consumption data of users corresponding to the various electricity packages, wherein the user information includes values ​​of various parameter factors, and the historical electricity consumption data includes average electricity consumption in multiple time periods; Filter out the user set H corresponding to each electricity package, cluster the values ​​of the parameter factor n corresponding to multiple users in the user set, and obtain multiple first data clusters The average power consumption corresponding to multiple users in the user set is clustered to obtain multiple second data clusters H j , where i is the serial number of the first data cluster corresponding to the same parameter factor, and j is the serial number of the second data cluster; From the first data cluster and the second data cluster H j The first associated data cluster associated with the corresponding electricity package is determined respectively and the second associated data cluster h j , and based on the first associated data cluster Determine the associated value range of the parameter factor n based on the second associated data cluster h j Determine the associated value range of historical electricity consumption data; The number of data points of all first associated data clusters corresponding to each electricity package And the number of data points in the second associated data cluster N(h j ), determine the matching degree W of various parameter factors n The matching degree with the historical electricity consumption data is W0; Based on the value range of various parameter factors corresponding to each electricity package, the matching degree W of various parameter factors n , the associated value range of historical electricity consumption data and the matching degree W0 of historical electricity consumption data are used to build a user package model.

3. The method for managing information for power marketing according to claim 2, characterized in that: Determining the matching degree between the current power user and the current package information based on the pre-built user package model, the user information of the current power user and the historical power consumption data includes: Compare the values ​​of each parameter factor of the user information of the current power user with the associated value range corresponding to the current package information, and compare the values ​​of the historical power consumption data of the current power user with the associated value range corresponding to the current package information; When the value of each parameter factor falls within the corresponding associated value range, or the value of the historical power consumption data falls within the corresponding associated value range, a plurality of target matching degrees are obtained, wherein the target matching degree is the matching degree of the parameter factor or the matching degree of the parameter factor; The multiple target matching degrees are summed to obtain the matching degree between the current electricity user and the current package information.

4. The method for managing information for power marketing according to claim 2, characterized in that: From the first data cluster and the second data cluster H j The first associated data cluster associated with the corresponding electricity package is determined respectively and the second associated data cluster h j ,include: Calculate the first data cluster Variance and the second data cluster H j The variance S j , and count the first data cluster The number of data points and the second data cluster H j The number of data points; In Variance is less than the preset variance threshold, and the first data cluster When the number of data points in the first data cluster is greater than the preset threshold, As the first associated data cluster In the variance S j is less than the preset variance threshold, and the second data cluster H j When the number of data points of the second data cluster H is greater than a preset number threshold, j As the second associated data cluster h j .

5. The method for managing information for power marketing according to claim 4, characterized in that: Based on the first associated data cluster Determine the associated value range of the parameter factor n based on the second associated data cluster h j Determine the associated value range of historical electricity consumption data, including: Calculate the first data cluster The average and the second data cluster H j The average value A j ; Based on the first data cluster The average and variance Construct the associated value range of parameter factor n Based on the second data cluster H j The average value A j and variance S j Constructing the associated value range of historical electricity consumption data Among them, α is the first proportional parameter, and β is the second proportional parameter.

6. The method for managing information for power marketing according to claim 1, characterized in that: Determining a target package whose matching degree with the current power user is greater than or equal to a preset threshold includes: The pre-built user package model, the user information of the current power user and the historical power consumption data determine the matching degree between the current power user and all power packages; Select the target package whose matching degree is greater than or equal to the preset threshold.

7. The method for managing information for power marketing according to claim 1, characterized in that: The process of constructing the marketing copy library includes: Get marketing copy for a variety of electricity packages; Build a marketing copy library based on the marketing copies of various electricity packages.

8. The method for managing information for power marketing according to claim 1, characterized in that: Also includes: The historical feedback channel of the current power user is used as a promotion channel for the marketing copy of the target package, and the promotion channel of the marketing copy of the target package is associated with the current power user.

9. The method for managing information for power marketing according to claim 8, characterized in that: Also includes: The user information of the associated electricity users, the marketing copy of the target package and the promotion channels are sent to the target objects.

10. An information management system for power marketing, characterized in that: include: The acquisition module is used to obtain the user information, historical electricity consumption data and current package information of the current electricity user; A matching module, used to determine the matching degree between the current power user and the current package information based on a pre-built user package model, the user information and the historical power consumption data of the current power user, wherein the user package model represents the matching degree between the user information, the historical power consumption data and the package selected by the user; An association module is used to determine, from a pre-built marketing copy library, a marketing copy of a target package whose matching degree with the current power user is greater than or equal to a preset threshold when the matching degree between the current power user and the current package information is less than a preset threshold, and associate the marketing copy of the target package with the current power user.

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