CN116883117A - Intelligent customer service platform driven by predictive analysis - Google Patents
Intelligent customer service platform driven by predictive analysis Download PDFInfo
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- CN116883117A CN116883117A CN202310922810.1A CN202310922810A CN116883117A CN 116883117 A CN116883117 A CN 116883117A CN 202310922810 A CN202310922810 A CN 202310922810A CN 116883117 A CN116883117 A CN 116883117A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Recommending goods or services
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- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a predictive analysis driven intelligent customer service platform, which comprises: the client side is used for acquiring historical behavior records of browsing and purchasing commodities of any registered client on the intelligent client service platform and attribute characteristics of the registered client, and constructing a buyer database; the data acquisition module is used for acquiring periodic characteristic data of different commodities on the intelligent customer service platform; the prediction analysis module is used for analyzing the historical behavior records of the browsed and purchased commodities according to a preset analysis prediction model and outputting consumption indexes of registered clients on different commodities; and the data processing module is used for pushing corresponding commodity information to the client when detecting that the client triggers the recommendation instruction according to the consumption index and the period characteristic data. According to the method, the periodic characteristic data of different commodities and the predicted customer consumption index are combined, the commodities recommended to the customer side are determined, and the phenomenon that the purchased commodities are repeatedly pushed to the customer in a short time is avoided.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a prediction analysis driven intelligent customer service platform
Background
At present, electronic commerce develops rapidly, more and more consumers select online shopping, each large electronic commerce competes fiercely, a recommendation system of an electronic commerce platform is an important means for improving commodity sales at present, and the electronic commerce automatically pushes personalized products to clients by analyzing the behaviors of the clients and outputting the interests of the clients, so that the shopping efficiency of the clients is improved.
The conventional shopping platforms develop commodity pushing services, but in practice, the commodity pushing services generally repeatedly push purchased commodities or similar commodities to customers, and in a short period of time, the customers are very likely not to consider purchasing recommended similar commodities again, so that the platform does not push commodity information effectively.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a predictive analysis-driven intelligent customer service platform, which solves the technical problem that in the prior art, in a period with a short interval, commodity pushing service generally repeatedly pushes purchased commodities or similar commodities to customers, and the customers are not likely to consider purchasing the recommended similar commodities again, so that the recommended commodities are not effective.
The technical scheme adopted for solving the technical problems is as follows: a predictive analysis driven smart customer service platform comprising:
the client side is used for acquiring historical behavior records of browsing and purchasing commodities of any registered client on the intelligent client service platform and attribute characteristics of the registered client, and constructing a buyer database;
the data acquisition module is used for acquiring periodic characteristic data of different commodities on the intelligent customer service platform;
the prediction analysis module is used for analyzing the historical behavior records of the browsed and purchased commodities according to a preset analysis prediction model and outputting consumption indexes of registered clients for different types of commodities, wherein the consumption indexes comprise consumption capacity level of the registered clients, probability of initiating service requests, repurchase period and consumption intention;
and the data processing module is used for pushing corresponding commodity information to the client when detecting that the client triggers the recommendation instruction according to the consumption index and the period characteristic data.
As a further improvement of the invention: the attribute characteristics of the registered clients comprise client identities, member grades and client contact ways, and the clients are further used for carrying out labeled management on the registered clients and constructing a buyer database according to the consumption indexes and the attribute characteristics.
As a further improvement of the invention: the period characteristic data comprises commodity consumption period information uploaded by a seller and commodity re-purchase period information uploaded by a buyer, and the prediction analysis module is further used for determining period coefficients of different commodities according to the period characteristic data and establishing a commodity database according to the period coefficients.
As a further improvement of the invention: and pushing corresponding commodity information to the client when the client triggering recommendation instruction is detected according to the consumption index and the period characteristic data specifically comprises the following steps:
the data processing module comprehensively analyzes the consumption index and the cycle coefficient of the corresponding commodity to determine a commodity list to be recommended;
the weight ratio of the repurchase period is 5 according to the consumption capability level, the probability of initiating the service request: 2: sorting the commodities in the commodity list to be recommended, and determining the recommendation levels of different commodities in the commodity list to be recommended;
and recommending corresponding commodity information to the client according to the recommendation level.
As a further improvement of the invention: the recommendation instructions comprise registered clients searching commodity keywords, browsing commodity purchase records, logging requests and browsing merchant information.
As a further improvement of the invention: the client is also used for registering a client to initiate a service request on the intelligent client service platform, and the data processing module is also used for determining a plurality of target service providers and corresponding target commodities according to the service request and the consumption capability level of the registered client.
As a further improvement of the invention: further comprises: the service provider is used for enabling a plurality of target service providers to respond to the service based on the service request information uploaded by the client, generating service list information and sending the service list information to the intelligent client service platform.
As a further improvement of the invention: the data acquisition module is further used for acquiring commodity browsing times of registered users exceeding a preset time threshold and generating a commodity gray list according to the fact that the commodity browsing times of the registered users exceed a preset time threshold, and the data processing module is further used for reducing the recommendation frequency of commodities in the commodity gray list when a client triggering recommendation instruction is detected.
As a further improvement of the invention: the data processing module is also used for analyzing related commodities with association relation with the target commodity according to the service request, sorting the related commodities according to the association relation strength between the related commodities and the target commodity, and merging the related commodities with the sorting order lower than a preset level threshold into the commodity list to be recommended.
Compared with the prior art, the invention has the beneficial effects that:
according to the method and the system, according to the historical behavior records of browsing and purchasing commodities of the registered clients and the attribute characteristics of the registered clients, the consumption index of the registered clients for different commodities is predicted and analyzed, the corresponding commodity information is comprehensively determined and pushed to the clients by combining the cycle characteristic data of the different commodities, the phenomenon that the purchased commodities or similar commodities are repeatedly pushed to the clients by the platform in a short purchasing cycle in the prior art is avoided, the function of effectively recommending commodity information by the platform is improved, and meanwhile the use experience of the clients is improved.
Drawings
FIG. 1 is a schematic diagram of a predictive analysis driven intelligent customer service platform according to the present invention.
Fig. 2 is a schematic flow chart of a predictive analysis driven intelligent customer service platform according to the present invention.
Fig. 3 is a schematic flow chart of an embodiment 2 of a predictive analysis driven intelligent customer service platform according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to specific embodiments of the present invention and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the technical problems in the prior art, the present invention will be further described with reference to the accompanying drawings and examples:
example 1
As shown in fig. 1-2, this embodiment discloses a predictive analysis driven intelligent customer service platform, which includes:
the client side is used for acquiring historical behavior records of browsing and purchasing commodities of any registered client on the intelligent client service platform and attribute characteristics of the registered client, and constructing a buyer database;
the data acquisition module is used for acquiring periodic characteristic data of different commodities on the intelligent customer service platform;
the periodic characteristic data of different commodities are generally related to the capacity, the use area, the use frequency and the like of the commodities, and the periodic characteristic data is judged by a platform based on the re-purchase time of a purchasing client of any commodity and the use period time of a merchant corresponding to the commodity.
The prediction analysis module is used for analyzing the historical behavior records of the browsed and purchased commodities according to a preset analysis prediction model and outputting consumption indexes of registered clients for different types of commodities, wherein the consumption indexes comprise consumption capacity level of the registered clients, probability of initiating service requests, repurchase period and consumption intention;
and the data processing module is used for pushing corresponding commodity information to the client when detecting that the client triggers the recommendation instruction according to the consumption index and the period characteristic data.
As a preferred embodiment of the invention, the attribute characteristics of the registered clients comprise client identity, member level and client contact mode, and the client is further used for carrying out label management on the registered clients and constructing a buyer database according to the consumption index and the attribute characteristics.
The membership grade of the registered client and the identity of the registered client have a certain influence on the consumption index, the identity of the registered client is generally marked as students, payroll classes and the like by the platform, and the membership grade of the registered client can be rated according to the consumption amount of the client every year or every quarter. Besides pushing commodity information to registered clients through clients, the platform can also push commodity information through client contact ways in a targeted manner, for example, part of high-value and high-potential clients can push commodity information together through clients and client contact ways.
As a preferred embodiment of the present invention, the cycle characteristic data includes commodity consumption cycle information uploaded by a seller and commodity repurchase cycle information uploaded by a buyer, and the prediction analysis module is further configured to determine cycle coefficients of different commodities according to the cycle characteristic data, and establish a commodity database according to the cycle coefficients.
As a preferred embodiment of the present invention, when detecting that the client triggers the recommendation command according to the consumption index and the period feature data, pushing corresponding commodity information to the client specifically includes:
the data processing module comprehensively analyzes the consumption index and the cycle coefficient of the corresponding commodity to determine a commodity list to be recommended;
the weight ratio of the repurchase period is 5 according to the consumption capability level, the probability of initiating the service request: 2: sorting the commodities in the commodity list to be recommended, and determining the recommendation levels of different commodities in the commodity list to be recommended;
and recommending corresponding commodity information to the client according to the recommendation level.
Example 2
As shown in fig. 2-3, this embodiment discloses a predictive analysis driven intelligent customer service platform, which includes:
the client side is used for acquiring historical behavior records of browsing and purchasing commodities of any registered client on the intelligent client service platform and attribute characteristics of the registered client, and constructing a buyer database;
the data acquisition module is used for acquiring periodic characteristic data of different commodities on the intelligent customer service platform;
the prediction analysis module is used for analyzing the historical behavior records of the browsed and purchased commodities according to a preset analysis prediction model and outputting consumption indexes of registered clients for different types of commodities, wherein the consumption indexes comprise consumption capacity level of the registered clients, probability of initiating service requests, repurchase period and consumption intention;
and the data processing module is used for pushing corresponding commodity information to the client when detecting that the client triggers the recommendation instruction according to the consumption index and the period characteristic data.
As a preferred embodiment of the present invention, the cycle characteristic data includes commodity consumption cycle information uploaded by a seller and commodity repurchase cycle information uploaded by a buyer, and the prediction analysis module is further configured to determine cycle coefficients of different commodities according to the cycle characteristic data, and establish a commodity database according to the cycle coefficients.
As a preferred embodiment of the present invention, when detecting that the client triggers the recommendation command according to the consumption index and the period feature data, pushing corresponding commodity information to the client specifically includes:
the data processing module comprehensively analyzes the consumption index and the cycle coefficient of the corresponding commodity to determine a commodity list to be recommended;
the weight ratio of the repurchase period is 5 according to the consumption capability level, the probability of initiating the service request: 2: sorting the commodities in the commodity list to be recommended, and determining the recommendation levels of different commodities in the commodity list to be recommended;
and recommending corresponding commodity information to the client according to the recommendation level.
As a preferred embodiment of the invention, the attribute characteristics of the registered clients comprise client identity, member level and client contact mode, and the client is further used for carrying out label management on the registered clients and constructing a buyer database according to the consumption index and the attribute characteristics.
This embodiment differs from embodiment 1 in that:
as a preferred embodiment of the invention, the client is further used for registering a client to initiate a service request on the intelligent client service platform, and the data processing module is further used for determining a plurality of target service providers and corresponding target commodities according to the service request and the consumption capability level of the registered client.
As a preferred embodiment of the present invention, further comprising: the service provider is used for enabling a plurality of target service providers to respond to the service based on the service request information uploaded by the client, generating service list information and sending the service list information to the intelligent client service platform.
The data acquisition module is further used for acquiring commodity browsing times of registered users exceeding a preset time threshold and generating a commodity gray list according to the fact that the commodity browsing times of the registered users exceed a preset time threshold, and the data processing module is further used for reducing the recommendation frequency of commodities in the commodity gray list when a client triggering recommendation instruction is detected.
Example 3
The embodiment discloses a predictive analysis driven intelligent customer service platform, comprising:
the client side is used for acquiring historical behavior records of browsing and purchasing commodities of any registered client on the intelligent client service platform and attribute characteristics of the registered client, and constructing a buyer database;
the data acquisition module is used for acquiring periodic characteristic data of different commodities on the intelligent customer service platform;
the prediction analysis module is used for analyzing the historical behavior records of the browsed and purchased commodities according to a preset analysis prediction model and outputting consumption indexes of registered clients for different types of commodities, wherein the consumption indexes comprise consumption capacity level of the registered clients, probability of initiating service requests, repurchase period and consumption intention;
and the data processing module is used for pushing corresponding commodity information to the client when detecting that the client triggers the recommendation instruction according to the consumption index and the period characteristic data.
As a preferred embodiment of the invention, the client is further used for registering a client to initiate a service request on the intelligent client service platform, and the data processing module is further used for determining a plurality of target service providers and corresponding target commodities according to the service request and the consumption capability level of the registered client.
As a preferred embodiment of the present invention, further comprising: the service provider is used for enabling a plurality of target service providers to respond to the service based on the service request information uploaded by the client, generating service list information and sending the service list information to the intelligent client service platform.
The data acquisition module is further used for acquiring commodity browsing times of registered users exceeding a preset time threshold and generating a commodity gray list according to the fact that the commodity browsing times of the registered users exceed a preset time threshold, and the data processing module is further used for reducing the recommendation frequency of commodities in the commodity gray list when a client triggering recommendation instruction is detected.
As a preferred embodiment of the present invention, the data processing module is further configured to analyze, according to the service request, related products having an association relationship with the target product, sort the related products according to the strength of the association relationship between the related products and the target product, and integrate the related products with the sorting order lower than a preset level threshold into the to-be-recommended product list.
The main functions of the invention are as follows: according to the method and the system, according to the historical behavior records of browsing and purchasing commodities of the registered clients and the attribute characteristics of the registered clients, the consumption index of the registered clients for different commodities is predicted and analyzed, the corresponding commodity information is comprehensively determined and pushed to the clients by combining the cycle characteristic data of the different commodities, the phenomenon that the purchased commodities or similar commodities are repeatedly pushed to the clients by the platform in a short purchasing cycle in the prior art is avoided, the function of effectively recommending commodity information by the platform is improved, and meanwhile the use experience of the clients is improved.
As a preferred embodiment of the present invention, the recommendation instructions include registering a customer search for merchandise keywords, browsing merchandise purchase records, logging in requests, and browsing merchant information.
The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software that is executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope and spirit of the invention and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwired, or a combination of any of these. In addition, each functional unit may be integrated in one processing unit, each unit may exist alone physically, or two or more units may be integrated in one unit.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A predictive analysis driven intelligent customer service platform, comprising:
the client side is used for acquiring historical behavior records of browsing and purchasing commodities of any registered client on the intelligent client service platform and attribute characteristics of the registered client, and constructing a buyer database;
the data acquisition module is used for acquiring periodic characteristic data of different commodities on the intelligent customer service platform;
the prediction analysis module is used for analyzing the historical behavior records of the browsed and purchased commodities according to a preset analysis prediction model and outputting consumption indexes of registered clients for different types of commodities, wherein the consumption indexes comprise consumption capacity level of the registered clients, probability of initiating service requests, repurchase period and consumption intention;
and the data processing module is used for pushing corresponding commodity information to the client when detecting that the client triggers the recommendation instruction according to the consumption index and the period characteristic data.
2. The predictive analysis driven intelligent customer service platform according to claim 1, wherein the registered customer's attribute characteristics include customer identity, membership grade and customer contact details, the client being further configured to label the registered customer and build a buyer database based on the consumption index and attribute characteristics.
3. The predictive analysis driven intelligent customer service platform according to claim 1, wherein the periodic characteristic data comprises commodity consumption periodic information uploaded by a seller and commodity repurchase periodic information uploaded by a buyer, and wherein the predictive analysis module is further configured to determine periodic coefficients of different commodities according to the periodic characteristic data, and to build a commodity database according to the periodic coefficients.
4. The intelligent customer service platform driven by predictive analysis according to claim 3, wherein pushing corresponding commodity information to the client when the client triggering recommendation command is detected according to the consumption index and the period characteristic data specifically comprises:
the data processing module comprehensively analyzes the consumption index and the cycle coefficient of the corresponding commodity to determine a commodity list to be recommended;
the weight ratio of the repurchase period is 5 according to the consumption capability level, the probability of initiating the service request: 2: sorting the commodities in the commodity list to be recommended, and determining the recommendation levels of different commodities in the commodity list to be recommended;
and recommending corresponding commodity information to the client according to the recommendation level.
5. The predictive analysis driven intelligent customer service platform according to claim 1, wherein the recommendation instructions include registered customer search product keywords, browse product purchase records, login requests, and browse merchant information.
6. The predictive analysis driven intelligent customer service platform according to claim 4, wherein said client is further configured to register a customer to initiate a service request on the intelligent customer service platform, and said data processing module is further configured to determine a plurality of target service providers and corresponding target commodities based on said service request and a level of consumption capabilities of the registered customer.
7. The predictive analysis driven intelligent customer service platform according to claim 6, further comprising: the service provider is used for enabling a plurality of target service providers to respond to the service based on the service request information uploaded by the client, generating service list information and sending the service list information to the intelligent client service platform.
8. The predictive analysis driven intelligent customer service platform according to claim 1, wherein the data acquisition module is further configured to obtain that the number of times the registered user browses the commodity exceeds a preset number of times threshold, and the number of times the registered user does not have a purchased commodity record, and generate a commodity gray list, and the data processing module is further configured to reduce the recommendation frequency of the commodity in the commodity gray list when the client trigger recommendation command is detected.
9. The predictive analysis driven intelligent customer service platform according to claim 6, wherein the data processing module is further configured to analyze related commodities having an association relationship with the target commodity according to the service request, order the related commodities according to the strength of the association relationship between the related commodities and the target commodity, and incorporate the related commodities having an order of order lower than a preset level threshold into the commodity list to be recommended.
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| CN202310922810.1A CN116883117A (en) | 2023-07-26 | 2023-07-26 | Intelligent customer service platform driven by predictive analysis |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117835170A (en) * | 2023-10-16 | 2024-04-05 | 深圳市天一泓科技有限公司 | Intelligent short message sending method and system based on short message template |
| CN118657555A (en) * | 2024-08-20 | 2024-09-17 | 新立讯科技集团股份有限公司 | Intention prediction method and system based on AI machine learning |
-
2023
- 2023-07-26 CN CN202310922810.1A patent/CN116883117A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117835170A (en) * | 2023-10-16 | 2024-04-05 | 深圳市天一泓科技有限公司 | Intelligent short message sending method and system based on short message template |
| CN118657555A (en) * | 2024-08-20 | 2024-09-17 | 新立讯科技集团股份有限公司 | Intention prediction method and system based on AI machine learning |
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