CN113449163A - Customer mining method, device, equipment and storage medium based on artificial intelligence - Google Patents
Customer mining method, device, equipment and storage medium based on artificial intelligence Download PDFInfo
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Abstract
The invention relates to the field of artificial intelligence, and discloses a customer mining method, a device, equipment and a storage medium based on artificial intelligence, which are used for mining customer value by deeply analyzing customer behaviors through artificial intelligence, thereby providing accurate business service pushed according to the demands of customers and improving the customer satisfaction. The method comprises the following steps: a customer identity information database, a customer consumption information database and a customer picture database are constructed in a security system in advance; acquiring client identity information and client consumption information, performing client value layered identification based on a preset client identification model to obtain client value layered information, and screening out target clients reaching a preset value threshold; performing product matching based on a preset insurance product library and a preset matching rule to obtain product matching information; based on the customer representation and the insurance product representation, a matching image of the target customer and the corresponding product is determined.
Description
Technical Field
The invention relates to the field of artificial intelligence, in particular to a customer mining method, a customer mining device, customer mining equipment and a storage medium based on artificial intelligence.
Background
Due to the rapid development of information technology, the traditional commodity transaction is more colorful on line, and is not exceptional in the financial insurance industry, but is far less than the development scale and the expansion speed of fast-moving products. The current situation of selling insurance products on the internet cannot flexibly capture target customer groups; however, the general customers tend to explain through insurance businessmen, and purchase the recommended insurance products is not the insurance guarantee most suitable for the customers. In the prior art, an effective customer value mining solution for accurately pushing services according to customer requirements is not provided in the insurance financial industry.
Disclosure of Invention
The invention provides a customer mining method, a device, equipment and a storage medium based on artificial intelligence, which can mine customer value by deeply analyzing customer behaviors through artificial intelligence, thereby providing accurate business service pushed according to the self requirements of customers and improving the customer satisfaction.
In order to achieve the above object, a first aspect of the present invention provides a customer mining method based on artificial intelligence, including:
a customer identity information database, a customer consumption information database and a customer picture database are built in the security system in advance, wherein customer identity information in the customer identity information database, customer consumption information in the customer consumption information database and customer pictures in the customer picture database are associated with each other through a configured customer unique identification code;
acquiring the customer identity information and the customer consumption information, carrying out customer value layered recognition on the customer identity information and the customer consumption information based on a preset customer recognition model to obtain customer value layered information, and screening out target customers reaching a preset value threshold;
performing product matching on a target client in the client value layering information based on a preset insurance product library and a preset matching rule to obtain product matching information of the target client, wherein the preset insurance product library comprises insurance product information and an insurance product portrait;
and determining a matching image of the target customer and a corresponding product based on the customer portrait and the insurance product portrait according to the product matching information of the target customer.
Optionally, in another embodiment of the artificial intelligence based customer mining method, after determining a matching image of the target customer and a corresponding product based on the customer representation and insurance product representation according to product matching information of the target customer, the method further includes:
analyzing the client identity information and the client consumption information of the target client based on a preset client behavior analysis model, and predicting to obtain a behavior blueprint of the target client, wherein the behavior blueprint is the consumption behavior of the target client in the next stage;
and determining personalized product recommendation information of the target customer based on a preset product customization model according to the behavior blueprint.
Optionally, in another embodiment of the artificial intelligence based customer mining method, after determining a matching image of the target customer and a corresponding product based on the customer representation and insurance product representation according to product matching information of the target customer, the method further includes:
determining a target place for arousing the attention of the target client according to the client identity information and the client consumption information of the target client;
and pushing insurance product information and an insurance product portrait matched with the target customer to the target place for presentation according to a preset pushing mode and a pushing path.
Optionally, in another embodiment of the artificial intelligence based client mining method, after the insurance product information and the insurance product representation matched with the target client are pushed to the target location for presentation according to a preset pushing mode and a preset pushing path, the method further includes:
acquiring video stream information reported by camera equipment in the target place in real time, and acquiring eyeball focusing information of the target client in the target place by analyzing the video stream information;
and according to the eyeball focusing information, evaluating the focusing time of the target client on the pushed insurance product information matched with the target client and the insurance product image.
Optionally, in another embodiment of the artificial intelligence based customer mining method, after the evaluating the focus time of the target customer on the pushed insurance product information matching the target customer and the insurance product representation according to the eyeball focus information, the method further comprises:
determining a focused target insurance product according to the focusing time, wherein the focused target insurance product refers to that the focusing time of the target customer on the insurance product information is longer than the setting time relative to other insurance product information;
and increasing the exposure time of the target insurance product in the target place, and pushing the intelligent explanation voice video and the related explanation content of the target insurance product to the target place after configuring the intelligent explanation voice video and the related explanation content of the target insurance product so as to present the target insurance product to the target client.
Optionally, in another embodiment of the artificial intelligence based customer mining method, in the step of building in advance a customer identity information database, a customer consumption information database, and a customer picture database in the security system, the artificial intelligence based customer mining method further includes:
and based on a preset image simulator, simulating the portrait of the client according to the client identity information and the client consumption information in the client identity information database and the client consumption information database to obtain the client portrait database.
Optionally, in another embodiment of the artificial intelligence based customer mining method, the customer information database is used for storing identity objective element information of the customer, wherein the identity objective element information comprises three-dimensional identity data and social relations of the customer; the customer consumption information database is used for storing consumption flow data of customers, and the consumption flow data comprises all economic activity behaviors and money records of the customers; and the customer identity information database, the customer consumption information database and the customer image database are stored into the block chain nodes.
The invention provides a customer mining device based on artificial intelligence, which comprises:
the database construction module is used for constructing a customer identity information database, a customer consumption information database and a customer picture database in the security system in advance, wherein the customer identity information in the customer identity information database, the customer consumption information in the customer consumption information database and the customer picture in the customer picture database are associated by a configured customer unique identification code;
the value layering identification module is used for acquiring the customer identity information and the customer consumption information, carrying out customer value layering identification on the customer identity information and the customer consumption information based on a preset customer identification model to obtain customer value layering information, and screening out target customers reaching a preset value threshold;
the product matching module is used for carrying out product matching on a target client in the client value layering information based on a preset insurance product library and a preset matching rule to obtain product matching information of the target client, wherein the preset insurance product library comprises insurance product information and an insurance product portrait;
and the matching image acquisition module is used for determining a matching image of the target customer and a corresponding product based on the customer portrait and the insurance product portrait according to the product matching information of the target customer.
The third aspect of the present invention further provides an artificial intelligence based customer mining device, wherein the artificial intelligence based customer mining device comprises a memory and at least one processor, the memory storing instructions therein, the memory and the at least one processor being interconnected by a line; the at least one processor invokes the instructions in the memory to cause the artificial intelligence based customer mining device to perform any of the artificial intelligence based customer mining methods described above.
The fourth aspect of the present invention also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the artificial intelligence based customer mining method as described in any one of the above.
In the technical scheme provided by the invention, a customer identity information database, a customer consumption information database and a customer picture database are constructed in a security system in advance; acquiring client identity information and client consumption information, performing client value layered identification based on a preset client identification model to obtain client value layered information, and screening out target clients reaching a preset value threshold; performing product matching based on a preset insurance product library and a preset matching rule to obtain product matching information; based on the customer representation and the insurance product representation, a matching image of the target customer and the corresponding product is determined. According to the embodiment of the invention, the value of the customer is mined by deeply analyzing the behavior of the customer through artificial intelligence, so that accurate business service can be pushed according to the self requirement of the customer, and the customer satisfaction is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a process diagram of an embodiment of a customer mining method based on artificial intelligence in the embodiment of the present invention;
FIG. 2 is a schematic diagram of an embodiment of an artificial intelligence based client mining device according to an embodiment of the invention;
FIG. 3 is a schematic diagram of an embodiment of an artificial intelligence based customer mining device in an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a customer mining method, a device, equipment and a storage medium based on artificial intelligence, which are used for mining the value of a customer by deeply analyzing the behavior of the customer through artificial intelligence, thereby providing accurate business service pushed according to the self requirement of the customer and improving the satisfaction degree of the customer.
In order to make the technical field of the invention better understand the scheme of the invention, the embodiment of the invention will be described in conjunction with the attached drawings in the embodiment of the invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Due to the rapid development of information technology, the traditional commodity transaction is more colorful on line, and is not exceptional in the financial insurance industry, but is far less than the development scale and the expansion speed of fast-moving products. The current situation of selling insurance products on the internet cannot flexibly capture target customer groups; however, the general customers tend to explain through insurance businessmen, and purchase the recommended insurance products is not the insurance guarantee most suitable for the customers. In the prior art, an effective customer value mining solution for accurately pushing business according to customer requirements is not provided in the insurance financial industry, the application provides a customer mining method based on artificial intelligence, so that accurate business service pushing according to the customer requirements is realized, the customer satisfaction is improved, and detailed description is respectively provided below.
Referring to fig. 1, an embodiment of a customer mining method based on artificial intelligence in the embodiment of the present invention includes:
102, acquiring the customer identity information and the customer consumption information, performing customer value layered identification on the customer identity information and the customer consumption information based on a preset customer identification model to obtain customer value layered information, and screening out target customers reaching a preset value threshold;
103, performing product matching on a target client in the client value layering information based on a preset insurance product library and a preset matching rule to obtain product matching information of the target client, wherein the preset insurance product library comprises insurance product information and an insurance product portrait;
and step 104, determining a matching image of the target customer and a corresponding product based on the customer portrait and the insurance product portrait according to the product matching information of the target customer.
In specific implementation, a customer identity information database, a customer consumption information database and a customer picture database are pre-constructed in the security system, and the databases are obtained by classifying the service data acquired by the security system. The customer identity information in the customer identity information database, the customer consumption information in the customer consumption information database and the customer images in the customer image database are associated by the configured customer unique identification codes; in order to get through the data association in each database, the unique customer identification codes are adopted for association, so that corresponding data in each database can be obtained through the unique customer identification codes. Specifically, the client information database is used for storing identity objective element information of a client, wherein the identity objective element information comprises but is not limited to three-dimensional identity data and social relations of the client; the customer consumption information database is used for storing consumption flow data of customers, and the consumption flow data comprises but is not limited to all economic activity behaviors and money records of the customers.
Further, in another embodiment, in the step of building in advance a customer identity information database, a customer consumption information database and a customer picture database in the security system, the artificial intelligence-based customer mining method further includes: and based on a preset image simulator, simulating the portrait of the client according to the client identity information and the client consumption information in the client identity information database and the client consumption information database to obtain the client portrait database. The image simulator is pre-installed in the security system, and customer portrait simulation is performed according to the customer identity information and the customer consumption information in the customer identity information database and the customer consumption information database to obtain the portrait of each customer, so that a customer portrait database is established.
Further, the customer identity information database, the customer consumption information database and the customer picture database are stored in the block chain nodes. The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. The blockchain is essentially a decentralized database, which is a string of data blocks associated by using cryptography, each data block contains information of a batch of network transactions, and the information is used for verifying the validity of the information and generating the next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Further, the client identity information and the client consumption information are obtained, client value layered recognition is carried out on the client identity information and the client consumption information based on a preset client recognition model, client value layered information is obtained, and target clients reaching a preset value threshold value are screened out. Specifically, the client identification model is a model trained to identify and output a corresponding value hierarchy according to the input of the client behavior information, and the client identification model may refer to the obtaining manner of the client value prediction model in the prior art, such as a linear regression analysis model based on client value prediction and diagnosis and a machine learning model based on client value prediction analysis, which are not described in detail herein. The value positioning of the client of the positioning person which is matched with the insurance products of different grades can be obtained by carrying out value layering on the client through a client identification model, and the client value layering actually distinguishes different target groups, such as a silver member and a gold member for the client. If a series of client value positioning aiming at each client exists in the obtained client value layering information, the clients reaching the preset value threshold value are screened out, and the target clients meeting the preset value positioning are obtained, so that service recommendation service can be carried out in a personalized mode aiming at the group of the target clients.
Further, the target customers obtained from the customer value layering information are subjected to product matching based on a preset insurance product library and preset matching rules, wherein the insurance product library is a classification of existing insurance products in the security system, such as insurance product information and insurance product portrait; including information such as the type of each insurance product, target crowd location, detailed description, product simulation images, and the like. Through a preset matching rule, for example, a high-value customer matches a corresponding high-price product with a high added value, the customer value and an insurance product conforming to the corresponding customer value can be associated in a data table mode, so that the obtained target customer is subjected to corresponding product matching according to the matching rule, and corresponding product allocation information is obtained.
Furthermore, according to the obtained product matching information of the target client, the matching image of the target client and the corresponding product is determined based on the client portrait and the insurance product portrait, namely, the client portrait is associated with the associated insurance product portrait, and the obtained matching image can be conveniently displayed in a visual mode, so that the clients with different value levels are guided to the corresponding insurance products of the insurance company, and the client conversion rate and the assistance of the insurance company are improved so as to improve the market share of the insurance products.
Further, in another embodiment, after determining a matching image of the target customer and a corresponding product based on the customer representation and insurance product representation according to product matching information of the target customer, the method further comprises:
analyzing the client identity information and the client consumption information of the target client based on a preset client behavior analysis model, and predicting to obtain a behavior blueprint of the target client, wherein the behavior blueprint is the consumption behavior of the target client in the next stage;
and determining personalized product recommendation information of the target customer based on a preset product customization model according to the behavior blueprint.
Specifically, existing customer behavior data in the security system can be determined according to customer identity information and customer consumption information in the security system, the customer behavior data comprises information such as a real-time place of a customer in an insurance institution, a frequently visited place, a message behavior and the like, and the customer behavior analysis model is used for predicting a next consumption behavior of the customer, namely a behavior blueprint, according to the behavior data of the customer, so that the behavior blueprint of the target customer can be predicted according to the customer identity information and the customer consumption information of the target customer. The product customized model is similar to the preset matching rule and can be used for predicting to obtain an adaptive insurance product according to the client value in a layering mode. And the customer value hierarchical identification can be carried out by adopting the customer identification model through the behavior blueprint to obtain the predicted customer value, and the matched product information is predicted according to the product customization model.
Further, in another embodiment, after determining a matching image of the target customer and a corresponding product based on the customer representation and insurance product representation according to product matching information of the target customer, the method further comprises:
determining a target place for arousing the attention of the target client according to the client identity information and the client consumption information of the target client;
and pushing insurance product information and an insurance product portrait matched with the target customer to the target place for presentation according to a preset pushing mode and a pushing path.
Specifically, because the determined customer behavior data includes information such as a real-time location of a customer in an insurance organization, a frequently visited location, a message behavior and the like according to the customer identity information and customer consumption information in the security system, a target location where the attention of a target customer is focused is determined, insurance product information and an insurance product image matched with the target customer are pushed to the target location for presentation according to a preset pushing mode and a preset pushing path, for example, the target location can be a restaurant when the customer orders, the matched insurance product information and the insurance product image are displayed on a large screen of the restaurant, or the target location can be a public location, and the product information is pushed to the customer in all unconscious behaviors of the customer by displaying the matched insurance product information and the insurance product image on a rolling screen of a subway, therefore, the matched product information can be intelligently and conveniently recommended according to the customer value, and the purpose of mining the customer value of the customer in the security system is achieved.
Further, in another embodiment, after the insurance product information and the insurance product portrait matched with the target customer are pushed to the target location for presentation according to a preset pushing mode and a preset pushing path, the method further includes:
acquiring video stream information reported by camera equipment in the target place in real time, and acquiring eyeball focusing information of the target client in the target place by analyzing the video stream information;
and according to the eyeball focusing information, evaluating the focusing time of the target client on the pushed insurance product information matched with the target client and the insurance product image.
Specifically, the video stream information reported by the camera equipment of the target place can be obtained from the data reported in real time by the security system, and the eyeball focusing information of the target client in the place is obtained by analyzing the video stream information; therefore, the focus of the attention of the client is known, the focus time of the target client on the pushed insurance product information matched with the target client and the insurance product portrait is evaluated according to the eyeball focus information, for example, the attention of the client stays on certain recommended product information and the eyeball focus time on certain recommended product information, and the insurance product interested by the client can be known by obtaining the eyeball focus information of the client.
Further, in another embodiment, after said evaluating the focus time of said target customer on pushed insurance product information and insurance product representation matching said target customer based on said eye focus information, said method further comprises:
determining a focused target insurance product according to the focusing time, wherein the focused target insurance product refers to that the focusing time of the target customer on the insurance product information is longer than the setting time relative to other insurance product information;
and increasing the exposure time of the target insurance product in the target place, and pushing the intelligent explanation voice video and the related explanation content of the target insurance product to the target place after configuring the intelligent explanation voice video and the related explanation content of the target insurance product so as to present the target insurance product to the target client.
Specifically, by the above focusing time, a focused target insurance product is determined, where the focused target insurance product refers to that the focusing time of the target customer on the insurance product information is longer than that of other insurance product information by a set time period, for example, the focusing time of the customer on certain insurance product information is longer than that of other products by 2 seconds or 3 seconds, then the customer is shown to be interested in the insurance product, it is determined that the customer is willing to learn about the insurance product, the exposure time of the target insurance product is increased at the target location, such as intelligent explanation voice recordings and the content of the explanation of the product video, and the configured result is pushed to the video terminal of the target location and presented to the target customer, through carrying out the product configuration and the propelling movement of feeling at ease, make things convenient for the customer to know interesting product information fast conveniently, promoted customer's experience effect.
In summary, in the embodiment of the present invention, the customer identity information database, the customer consumption information database, and the customer image database are previously constructed in the security system; acquiring client identity information and client consumption information, performing client value layered identification based on a preset client identification model to obtain client value layered information, and screening out target clients reaching a preset value threshold; performing product matching based on a preset insurance product library and a preset matching rule to obtain product matching information; based on the customer representation and the insurance product representation, a matching image of the target customer and the corresponding product is determined. According to the embodiment of the invention, the value of the customer is mined by deeply analyzing the behavior of the customer through artificial intelligence, so that accurate business service can be pushed according to the self requirement of the customer, and the customer satisfaction is improved.
In the above description of the client mining method based on artificial intelligence in the embodiment of the present invention, referring to fig. 2, a client mining device based on artificial intelligence in the embodiment of the present invention is described below, and an embodiment of the client mining device based on artificial intelligence in the embodiment of the present invention includes:
the database construction module 11 is used for constructing a customer identity information database, a customer consumption information database and a customer picture database in the security system in advance, wherein the customer identity information in the customer identity information database, the customer consumption information in the customer consumption information database and the customer picture in the customer picture database are associated with each other by a configured customer unique identification code;
the value layering identification module 12 is used for acquiring the customer identity information and the customer consumption information, performing customer value layering identification on the customer identity information and the customer consumption information based on a preset customer identification model to obtain customer value layering information, and screening out target customers reaching a preset value threshold;
the product matching module 13 is used for performing product matching on a target customer in the customer value hierarchical information based on a preset insurance product library and a preset matching rule to obtain product matching information of the target customer, wherein the preset insurance product library comprises insurance product information and an insurance product portrait;
and the matching image acquisition module 14 is used for determining a matching image of the target customer and a corresponding product based on the customer portrait and the insurance product portrait according to the product matching information of the target customer.
Optionally, in another embodiment of the artificial intelligence based customer mining device, the device further comprises:
the behavior blueprint prediction module is used for analyzing the client identity information and the client consumption information of the target client based on a preset client behavior analysis model and predicting to obtain a behavior blueprint of the target client, wherein the behavior blueprint is the consumption behavior of the target client in the next stage;
and the recommendation information determining module is used for determining the personalized product recommendation information of the target customer based on a preset product customization model according to the behavior blueprint.
Optionally, in another embodiment of the artificial intelligence based customer mining device, the device further comprises:
the target place determining module is used for determining a target place which arouses the attention of the target client according to the client identity information and the client consumption information of the target client;
and the pushing module is used for pushing insurance product information and insurance product portrait matched with the target customer to the target place for presentation according to a preset pushing mode and a pushing path.
Optionally, in another embodiment of the artificial intelligence based customer mining device, the device further comprises:
the video stream information acquisition module is used for acquiring video stream information reported by the camera equipment of the target place in real time and acquiring eyeball focusing information of the target client in the target place by analyzing the video stream information;
and the focusing time evaluation module is used for evaluating the focusing time of the target client on the pushed insurance product information matched with the target client and the insurance product portrait according to the eyeball focusing information.
Optionally, in another embodiment of the artificial intelligence based customer mining device, the device further comprises:
the target insurance product focusing determination module is used for determining a focused target insurance product according to the focusing time, wherein the focused target insurance product refers to that the focusing time of the target customer on the insurance product information is longer than the setting time relative to other insurance product information;
and the exposure time increasing module is used for increasing the exposure time of the target insurance product in the target place, and pushing the intelligent explanation voice video and the related explanation content of the target insurance product to the target place after the intelligent explanation voice video and the related explanation content are configured so as to be presented to the target customer.
Optionally, in another embodiment of the artificial intelligence based customer mining device, the database construction module 11 is further configured to:
and based on a preset image simulator, simulating the portrait of the client according to the client identity information and the client consumption information in the client identity information database and the client consumption information database to obtain the client portrait database.
Optionally, in another embodiment of the artificial intelligence based client mining device, the client information database is used for storing identity objective element information of the client, wherein the identity objective element information comprises three-dimensional identity data and social relations of the client; the customer consumption information database is used for storing consumption flow data of customers, and the consumption flow data comprises all economic activity behaviors and money records of the customers; and the customer identity information database, the customer consumption information database and the customer image database are stored into the block chain nodes.
It should be noted that the apparatus in the embodiment of the present invention may be configured to implement all technical solutions in the foregoing method embodiments, and the functions of each functional module may be implemented specifically according to the method in the foregoing method embodiments, and the specific implementation process may refer to the relevant description in the foregoing example, which is not described herein again. Fig. 2 above describes in detail the artificial intelligence based client mining apparatus in the embodiment of the present invention from the perspective of the modular functional entity, and the artificial intelligence based client mining device in the embodiment of the present invention is described in detail in the following from the perspective of the hardware processing.
Fig. 3 is a schematic structural diagram of an artificial intelligence based client mining device 300 according to an embodiment of the present invention, where the artificial intelligence based client mining device 300 may generate relatively large differences due to different configurations or performances, and may include one or more processors (CPUs) 301 (e.g., one or more processors) and a memory 309, one or more storage media 308 (e.g., one or more mass storage devices) storing an application 307 or data 306. Memory 309 and storage media 308 may be, among other things, transient storage or persistent storage. The program stored on the storage medium 308 may include one or more modules (not shown), each of which may include a series of instruction operations in a boolean variable store computed on a graph. Still further, the processor 301 may be configured to communicate with the storage medium 308 to execute a series of instruction operations in the storage medium 308 on the artificial intelligence based customer mining device 300.
The artificial intelligence based client mining device 300 may also include one or more power supplies 302, one or more wired or wireless network interfaces 303, one or more input-output interfaces 304, and/or one or more operating systems 305, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the artificial intelligence based customer excavation equipment configuration shown in fig. 3 does not constitute a limitation of artificial intelligence based customer excavation equipment, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium, which may be non-volatile or volatile. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A customer mining method based on artificial intelligence is applied to a security system and is characterized in that the customer mining method based on artificial intelligence comprises the following steps:
a customer identity information database, a customer consumption information database and a customer picture database are built in the security system in advance, wherein customer identity information in the customer identity information database, customer consumption information in the customer consumption information database and customer pictures in the customer picture database are associated with each other through a configured customer unique identification code;
acquiring the customer identity information and the customer consumption information, carrying out customer value layered recognition on the customer identity information and the customer consumption information based on a preset customer recognition model to obtain customer value layered information, and screening out target customers reaching a preset value threshold;
performing product matching on a target client in the client value layering information based on a preset insurance product library and a preset matching rule to obtain product matching information of the target client, wherein the preset insurance product library comprises insurance product information and an insurance product portrait;
and determining a matching image of the target customer and a corresponding product based on the customer portrait and the insurance product portrait according to the product matching information of the target customer.
2. The artificial intelligence based customer mining method of claim 1, after determining the matching image of the target customer and the corresponding product based on the customer representation and insurance product representation according to the product matching information of the target customer, the method further comprises:
analyzing the client identity information and the client consumption information of the target client based on a preset client behavior analysis model, and predicting to obtain a behavior blueprint of the target client, wherein the behavior blueprint is the consumption behavior of the target client in the next stage;
and determining personalized product recommendation information of the target customer based on a preset product customization model according to the behavior blueprint.
3. The artificial intelligence based customer mining method of claim 1, after determining the matching image of the target customer and the corresponding product based on the customer representation and insurance product representation according to the product matching information of the target customer, the method further comprises:
determining a target place for arousing the attention of the target client according to the client identity information and the client consumption information of the target client;
and pushing insurance product information and an insurance product portrait matched with the target customer to the target place for presentation according to a preset pushing mode and a pushing path.
4. The artificial intelligence based customer mining method of claim 3, wherein after the insurance product information and the insurance product representation matched with the target customer are pushed to the target location for presentation according to a preset pushing mode and a pushing path, the method further comprises:
acquiring video stream information reported by camera equipment in the target place in real time, and acquiring eyeball focusing information of the target client in the target place by analyzing the video stream information;
and according to the eyeball focusing information, evaluating the focusing time of the target client on the pushed insurance product information matched with the target client and the insurance product image.
5. The artificial intelligence based customer mining method of claim 4, wherein after assessing the target customer's focus time for pushed insurance product information matching the target customer and insurance product representation based on the eye focus information, the method further comprises:
determining a focused target insurance product according to the focusing time, wherein the focused target insurance product refers to that the focusing time of the target customer on the insurance product information is longer than the setting time relative to other insurance product information;
and increasing the exposure time of the target insurance product in the target place, and pushing the intelligent explanation voice video and the related explanation content of the target insurance product to the target place after configuring the intelligent explanation voice video and the related explanation content of the target insurance product so as to present the target insurance product to the target client.
6. The artificial intelligence based customer mining method according to claim 5, wherein in the step of constructing in advance a customer identity information database, a customer consumption information database, and a customer picture database in the security system, the artificial intelligence based customer mining method further comprises:
and based on a preset image simulator, simulating the portrait of the client according to the client identity information and the client consumption information in the client identity information database and the client consumption information database to obtain the client portrait database.
7. The artificial intelligence based customer mining method of claim 5, wherein the customer information database is used for storing identity objective factor information of the customer, the identity objective factor information comprising three-dimensional identity data and social relations of the customer; the customer consumption information database is used for storing consumption flow data of customers, and the consumption flow data comprises all economic activity behaviors and money records of the customers; and the customer identity information database, the customer consumption information database and the customer image database are stored into the block chain nodes.
8. A customer digging device based on artificial intelligence is applied to a security system and is characterized in that the device comprises:
the database construction module is used for constructing a customer identity information database, a customer consumption information database and a customer picture database in the security system in advance, wherein the customer identity information in the customer identity information database, the customer consumption information in the customer consumption information database and the customer picture in the customer picture database are associated by a configured customer unique identification code;
the value layering identification module is used for acquiring the customer identity information and the customer consumption information, carrying out customer value layering identification on the customer identity information and the customer consumption information based on a preset customer identification model to obtain customer value layering information, and screening out target customers reaching a preset value threshold;
the product matching module is used for carrying out product matching on a target client in the client value layering information based on a preset insurance product library and a preset matching rule to obtain product matching information of the target client, wherein the preset insurance product library comprises insurance product information and an insurance product portrait;
and the matching image acquisition module is used for determining a matching image of the target customer and a corresponding product based on the customer portrait and the insurance product portrait according to the product matching information of the target customer.
9. An artificial intelligence based customer mining device, comprising a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line; the at least one processor invokes the instructions in the memory to cause the artificial intelligence based customer mining device to perform the artificial intelligence based customer mining method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the artificial intelligence based client mining method according to any one of claims 1-7.
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