CN105701691A - Client-feature-database-based real-time recommendation system - Google Patents
Client-feature-database-based real-time recommendation system Download PDFInfo
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- CN105701691A CN105701691A CN201610158976.0A CN201610158976A CN105701691A CN 105701691 A CN105701691 A CN 105701691A CN 201610158976 A CN201610158976 A CN 201610158976A CN 105701691 A CN105701691 A CN 105701691A
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Abstract
The invention provides a client-feature-based-based real-time recommendation system comprising a name calling machine, a queuing machine, a client feature database management platform, a mobile device, a plurality of calling machines and a plurality of window display screens. The client feature database management platform is used for constructing a client service type tag system. When a client queues and obtains a waiting number, the queuing machine transmits client identification information to the client feature database management platform in real time; after processing by the client feature database management platform, a corresponding recommended service content is returned to the mobile device in real time; and the service staff carries out differentiated services on the client by using the name calling machines, calling machines, and the window display screens according to the client identification information and the recommended service content. According to the system, the invented achievement is applied to the practical queuing system of a business hall on the unified and efficient client feature database management platform, so that the client type can be identified and the client experience can be improved.
Description
Technical field
The invention belongs to data analysis excavation applications, be specifically related to the real-time intelligent commending system of a kind of client feature library based on machine learning。
Background technology
At present in customer analysis manages, it is common to there is the problems such as qualitative analysis is many, quantitative analysis is few, decision-making subjectivity strong, decision science has much room for improvement, be unfavorable for improving enterprise management。Along with the practical level of information system improves, a large amount of data reflecting client characteristics are have accumulated at present, carry out the desk study of data analysis Added Management decision-making in fields such as client's accurate marketing, customer demand prediction, customer service quality, achieve certain achievement。Carry out client's multi dimensional analysis, explore the facilitation that client's multi dimensional analysis manages for customer life cycle, improve customer life cycle management quantization level and decision science。
Machine learning and data mining are increasingly becoming excavation, utilize the topmost technical force of magnanimity business data assets。Sorting technique is at machine learning and Data Mining all in occupation of extremely important status, and its main task is under previously given category label set, judges its classification according to its attribute candidates。Foreign study mechanism manages for client characteristics, generally forms complete closed loop management theory from client's lifecycle management angle, a complete closed loop procedure is built up in customer account management。Adopt the strategy that client's base attribute, behavior characteristics, social network relationships combine, in conjunction with customer status analysis, accumulate a large amount of customer information, dynamically adjust client's marketing program, service program, client is carried out quantitative evaluation and decision, thus improve efficiency and the accuracy of customer account management flow process。
Domestic research is also in the starting stage, and current emphasis focuses in the research of the aspects such as customer status assay。Multiple industries successively build client's lifecycle management evaluation index system。By overall merit with analyze Customer Acquisition cost, loss loss, promote service quality, income, the balance of cost three and organic unity, enterprise customer account management level in corporate client management, reduce client's lifecycle management cost。
The queuing machine system of current each business hall big multi-functional simply, it is impossible to Real time identification high-end customer and potentiality client, thus good service cannot be provided for it；Also the integrated information of client cannot be obtained, it is impossible to it is carried out precision marketing。
Summary of the invention
For solving the technical problem existing for prior art, the present invention proposes based on the real-time intelligent commending system of client feature library, and this system is unifying, in efficient client characteristics management platform, by application of result in actual business hall queuing system, can recognize that the classification of client, promote customer experience。
The present invention realizes by the following technical solutions: based on the real-time intelligent commending system of client feature library, including device of calling out the numbers, queue machine, client feature library management platform, mobile equipment, multiple calling set and multiple window display screen, device, queue machine, the client feature library management platform of wherein calling out the numbers is sequentially connected with, mobile equipment is connected with client feature library management platform, multiple calling sets are connected with client feature library management platform respectively, and multiple window display screens are connected with client feature library management platform respectively；
Described client feature library management platform is used for building customer service class label system；
Subscriber identity information, when the custom queueing number of taking, is transferred to client feature library management platform by described queue machine in real time；After client feature library management platform processes, return corresponding recommendation service content in real time to mobile equipment, then service personal's service content according to subscriber identity information and recommendation, carries out the service of differentiation by device of calling out the numbers, calling set, window display screen to client。
Preferably, described client feature library management platform structure customer service class label system is as follows:
(1) identify the inherent nature of client, and be refined into customer basis class label；
(2) utilize data mining technology, based on client's expense record, subscriber identity information, customer action assessment customer value, evaluation customer value " height, potentiality, in, low " grade, composition customer value class label；
(3) according to customer action, client's potentiality, in conjunction with operation flow and present situation, formulate customer service measure, refine and form customer service class label；
(4) for each specific customer service class label client, corresponding service measures are set。
Further, after completing customer service, the service content recommended is fed back to client feature library management platform by described mobile equipment, and client feature library management platform is according to feedback information, real-time intelligent commending system and label system are continued to optimize, transformed, promotes the service content quality recommended。
By above technical scheme it can be seen that the present invention deepens the understanding to client, improve the effective means of marketing work ability and level of customer service。Data multi-level for the multi-angles such as marketing data, Customer Service Information, distribution data, weather information, social networks are carried out organic combination, carry out big data analysis to excavate, form with " label ", build at many levels, from various visual angles, the client feature library of three-dimensional, realize comprehensively portraying client characteristics, so that business personnel can quick obtaining client's essential information, individual's fine-feature such as preference, credit risk, behavioral trait, improve the becoming more meticulous of customer service, differentiation degree, improve specific aim and the effectiveness of marketing program design。Compared with prior art, the invention have the advantages that and beneficial effect:
1, system is when custom queueing is called out the numbers, in real time customer ID code is transferred to client characteristics management platform, on the one hand, the service plan back pass of corresponding for client feature and recommendation is passed on display interface or the mobile equipment of business hall personnel according to customer ID code by platform in real time, on the other hand, the result that platform returns as the tactful index assigned of attending a banquet, can assign business hall service personal in real time。
2, in each enterprise business hall, queue machine is as first equipment of contact client, and the impact of customer experience degree is extremely important。The present invention is based on client feature library, real-time Intelligent Service is provided to recommend for business hall personnel, in time client can be provided for each enterprise business hall personnel the service of differentiation, particularly promote the Experience Degree of high-end customer and potentiality client, effectively promote the market competitiveness。
Accompanying drawing explanation
Fig. 1 is the structural representation of the present invention；
Fig. 2 is the flow process that the present invention designs client's label system。
Detailed description of the invention
Below in conjunction with embodiment and accompanying drawing the present invention done in real-time intelligent exemplary application and describe more specifically, but embodiments of the present invention are not limited to this。
Embodiment:
Client feature library is to deepen the understanding to client, improves the effective means of marketing work ability and level of customer service。Data multi-level for the multi-angles such as marketing data, Customer Service Information, distribution data, weather information, social networks are carried out organic combination, carry out big data analysis to excavate, form with " label ", build at many levels, from various visual angles, the client feature library of three-dimensional, realize comprehensively portraying client characteristics, so that business personnel can quick obtaining client's essential information, individual's fine-feature such as preference, credit risk, behavioral trait, improve the becoming more meticulous of customer service, differentiation degree, improve specific aim and the effectiveness of marketing program design。
Referring to Fig. 1, real-time intelligent commending system of the present invention includes call out the numbers device, queue machine, client feature library management platform, mobile equipment, multiple calling set and multiple window display screen, device, queue machine, the client feature library management platform of wherein calling out the numbers is sequentially connected with, mobile equipment is connected with client feature library management platform, multiple calling sets are connected with client feature library management platform respectively, and multiple window display screens are connected with client feature library management platform respectively。
The present invention is when realizing customer information intelligent recommendation, and flow process is as follows:
One, customer service class label system is built based on client feature library management platform。
(1) identify the inherent nature of client, and be refined into customer basis class label, for instance the attribute tags such as booming income client, corporate client, frequent complaint。
(2) utilize the technological means such as data mining, based on the assessment customer value such as client's expense record, subscriber identity information, customer action, evaluation customer value " height, potentiality, in, low " grade, composition customer value class label。
In the process utilizing data mining technology tag design, implement Data Mining, the data status such as analytical data distribution characteristics, missing values, outlier, find data problem, and feed back to intelligent recommendation system, promote the inspection of data problem, revise data, improve the quality of data。
(3) according to customer action, client's potentiality, in conjunction with operation flow and present situation, formulate customer service measure, refine and form customer service class label。
(4) for each specific customer service class label client, corresponding service measures are set, as: for high value label client, the system of setting to return subscriber identity information and individual's preference and the high-end business product recommending enterprise currently mainly to promote。
Two, exploitation real-time intelligent recommends interface, returns corresponding recommendation service content according to client。
The interface using queue machine to provide, when the custom queueing number of taking, recommends interface by the identification information of client by real-time informing in real time, is transferred to client feature library management platform；After client feature library management platform processes, return corresponding recommendation service content in real time to go to the mobile equipment of service personal, then service personal can according to the service content of subscriber identity information and recommendation, by device of calling out the numbers, calling set, window display screen, client is carried out the service of differentiation, promotes customer experience degree。
Three, feedback recommendation service, to recommending to be optimized。
After service personal completes customer service, can use mobile equipment that the service recommended is fed back, client feature library management platform is returned to by intelligent recommendation interface, client feature library management platform is according to feedack, commending system and label system are continued to optimize, transformed, promotes the service content quality recommended。
As in figure 2 it is shown, in the present invention, adopt " design of client's label finds that data problem promotes to revise data " and the application closed loop procedure of " label application application staining effect optimizes label ", design client's label system。Client's label system follows the design principle of " MECE " (separate, fully exhaustive, MutuallyExclusiveCollectivelyExhaustive), realizes according to the process step of " find feature, refine label, build catalogue ":
(1) induction and conclusion, analysis mining data record, it has been found that the service features such as customer basis behavior, channel preference。
(2) refine service feature, or combine multiple service feature, express in succinct accurate mode, form client's label。
(3) from multiple dimension tissues such as industry characteristic, operation flow, professional field theory, management label, client feature library is built。
Above-described embodiment is one embodiment of the present invention; but embodiments of the present invention do not limit and this; be engaged in these those skilled in the art without departing from the present invention spirit and principle under make any amendment, replacement, improvement, be all contained in protection scope of the present invention。
Claims (3)
1. based on the real-time intelligent commending system of client feature library, it is characterized in that, including device of calling out the numbers, queue machine, client feature library management platform, mobile equipment, multiple calling set and multiple window display screen, device, queue machine, the client feature library management platform of wherein calling out the numbers is sequentially connected with, mobile equipment is connected with client feature library management platform, multiple calling sets are connected with client feature library management platform respectively, and multiple window display screens are connected with client feature library management platform respectively；
Described client feature library management platform is used for building customer service class label system；
Subscriber identity information, when the custom queueing number of taking, is transferred to client feature library management platform by described queue machine in real time；After client feature library management platform processes, return corresponding recommendation service content in real time to mobile equipment, then service personal's service content according to subscriber identity information and recommendation, carries out the service of differentiation by device of calling out the numbers, calling set, window display screen to client。
2. the real-time intelligent commending system based on client feature library according to claim 1, it is characterised in that it is as follows that described client feature library management platform builds customer service class label system:
(1) identify the inherent nature of client, and be refined into customer basis class label；
(2) utilize data mining technology, based on client's expense record, subscriber identity information, customer action assessment customer value, evaluation customer value " height, potentiality, in, low " grade, composition customer value class label；
(3) according to customer action, client's potentiality, in conjunction with operation flow and present situation, formulate customer service measure, refine and form customer service class label；
(4) for each specific customer service class label client, corresponding service measures are set。
3. the real-time intelligent commending system based on client feature library according to claim 1, it is characterized in that, after completing customer service, the service content recommended is fed back to client feature library management platform by described mobile equipment, client feature library management platform is according to feedback information, real-time intelligent commending system and label system are continued to optimize, transformed, promotes the service content quality recommended。
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| CN201610158976.0A CN105701691A (en) | 2016-03-18 | 2016-03-18 | Client-feature-database-based real-time recommendation system |
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| CN201610158976.0A CN105701691A (en) | 2016-03-18 | 2016-03-18 | Client-feature-database-based real-time recommendation system |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106845747A (en) * | 2016-06-29 | 2017-06-13 | 国网浙江省电力公司宁波供电公司 | Electricity charge risk prevention system application process based on power customer label |
| CN107067289A (en) * | 2016-10-28 | 2017-08-18 | 广东亿迅科技有限公司 | A kind of personal marketing commending system |
| CN108776910A (en) * | 2018-06-15 | 2018-11-09 | 北京盛宴联盟科技有限公司 | A kind of customer service management method and device |
| CN109872083A (en) * | 2019-03-15 | 2019-06-11 | 江苏海事职业技术学院 | A kind of harbour production information on services integration management system based on technology of Internet of things |
| CN110462610A (en) * | 2017-08-05 | 2019-11-15 | 辟博股份有限公司 | The system and method for being used to form the network with integrated management position and task arrangement |
| CN110992167A (en) * | 2019-11-28 | 2020-04-10 | 中国银行股份有限公司 | Bank client business intention identification method and device |
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| CN101216962A (en) * | 2008-01-04 | 2008-07-09 | 深圳市奥拓电子有限公司 | Queuing information managing system and its managing method |
| CN103377432A (en) * | 2012-04-16 | 2013-10-30 | 殷程 | Intelligent customer service marketing analysis system |
| CN104616116A (en) * | 2015-02-13 | 2015-05-13 | 武汉金锐达科技有限公司 | Bank client service system and method |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101216962A (en) * | 2008-01-04 | 2008-07-09 | 深圳市奥拓电子有限公司 | Queuing information managing system and its managing method |
| CN103377432A (en) * | 2012-04-16 | 2013-10-30 | 殷程 | Intelligent customer service marketing analysis system |
| CN104616116A (en) * | 2015-02-13 | 2015-05-13 | 武汉金锐达科技有限公司 | Bank client service system and method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106845747A (en) * | 2016-06-29 | 2017-06-13 | 国网浙江省电力公司宁波供电公司 | Electricity charge risk prevention system application process based on power customer label |
| CN106845747B (en) * | 2016-06-29 | 2020-12-04 | 国网浙江省电力公司宁波供电公司 | Electricity charge risk prevention and control application method based on electric power customer label |
| CN107067289A (en) * | 2016-10-28 | 2017-08-18 | 广东亿迅科技有限公司 | A kind of personal marketing commending system |
| CN110462610A (en) * | 2017-08-05 | 2019-11-15 | 辟博股份有限公司 | The system and method for being used to form the network with integrated management position and task arrangement |
| CN110462610B (en) * | 2017-08-05 | 2022-12-27 | 辟博股份有限公司 | Professional service recommendation system |
| CN108776910A (en) * | 2018-06-15 | 2018-11-09 | 北京盛宴联盟科技有限公司 | A kind of customer service management method and device |
| CN109872083A (en) * | 2019-03-15 | 2019-06-11 | 江苏海事职业技术学院 | A kind of harbour production information on services integration management system based on technology of Internet of things |
| CN110992167A (en) * | 2019-11-28 | 2020-04-10 | 中国银行股份有限公司 | Bank client business intention identification method and device |
| CN110992167B (en) * | 2019-11-28 | 2023-09-22 | 中国银行股份有限公司 | Bank customer business intention recognition method and device |
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