CN114049225A - Method and system for intelligently recommending insurance products and electronic equipment - Google Patents
Method and system for intelligently recommending insurance products and electronic equipment Download PDFInfo
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Abstract
The invention relates to a method, a system and an electronic device for intelligently recommending insurance products, wherein the method comprises the following steps: obtaining interest points of a pre-designated client according to historical internet surfing data of the pre-designated client; and acquiring the insurance product corresponding to the interest point of the pre-designated customer so that an insurance salesman recommends specific information of the insurance product to the pre-designated customer. Then, firstly, according to the historical internet surfing data of the pre-designated client, the interest point of the pre-designated client is determined, then the insurance product corresponding to the interest point of the pre-designated client is obtained, the insurance product can meet the requirements of the pre-designated client to the maximum extent, at the moment, the insurance salesman can recommend the insurance product to the pre-designated client more pertinently, and the probability of talking into a service is greatly improved.
Description
Technical Field
The invention relates to the technical field of natural language processing, in particular to a method, a system and electronic equipment for intelligently recommending insurance products.
Background
At present, when an insurance salesperson recommends an insurance product to a client, the insurance salesperson generally recommends based on experience according to personal information provided by the client, or recommends blindly, resulting in the problem of low unit rate.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art and provides a method, a system and electronic equipment for intelligently recommending insurance products.
The technical scheme of the method for intelligently recommending the insurance product is as follows:
obtaining interest points of a pre-designated client according to historical internet surfing data of the pre-designated client;
and acquiring the insurance product corresponding to the interest point of the pre-designated customer so that an insurance salesman recommends specific information of the insurance product to the pre-designated customer.
The method for intelligently recommending the insurance products has the following beneficial effects:
firstly, according to historical internet surfing data of a pre-designated client, an interest point of the pre-designated client is determined, then an insurance product corresponding to the interest point of the pre-designated client is obtained, the insurance product can meet the requirements of the pre-designated client to the maximum extent, at the moment, an insurance operator can recommend the insurance product to the pre-designated client more pertinently, and the probability of talking into a service is greatly improved.
On the basis of the scheme, the method for intelligently recommending the insurance products can be further improved as follows.
Further, still include:
obtaining the answering content of each question asked by the pre-specified client to form question and answer information;
generating information pointing to the insurance product and a two-dimensional code of the question and answer information, and sending the two-dimensional code to the intelligent terminal of the pre-designated customer;
and when the intelligent terminal of the pre-designated customer identifies the received two-dimensional code, turning to the information of the insurance product and the question and answer information.
The beneficial effect of adopting the further scheme is that: on one hand, the insurance businessman recommends the specific information of the insurance product to the pre-designated client through the telephone, after the call is finished, the pre-designated client easily forgets the specific information of the insurance product, and at the moment, the specific information of the insurance product and the question and answer information are sent to the intelligent terminal of the pre-designated client, so that the preset user can conveniently check the information repeatedly, the user experience is improved, and the probability of talking into the service is further improved; on the other hand, if the specific information and the question and answer information of the recommended insurance product are directly sent to the intelligent terminal of the pre-designated client in a text form, the pre-designated client is often disliked due to too many texts, and the specific information and the question and answer information of the insurance product are recommended in a two-dimensional code mode to the intelligent terminal of the pre-designated client, so that the user experience degree is further improved, and the probability of talking into a service is further improved.
Further, still include:
obtaining all associated clients of the pre-designated client according to the social network data of the pre-designated client;
obtaining a target associated client set according to the social network data of each associated client, wherein a social relationship exists between every two target associated clients in the target associated client set;
and sending the two-dimensional code to the intelligent terminal of each associated client except the target associated client set.
The beneficial effect of adopting the further scheme is that: on one hand, social relations exist between every two target associated clients in the target associated client set, which shows that all the target associated clients in the target associated client set and pre-designated clients are in tight contact, at the moment, only the two-dimensional code is sent to the intelligent terminal of the pre-designated client, the two-dimensional code can be diffused to the intelligent terminals of all the target associated clients at the maximum probability, the probability of talking into a service is further improved, on the other hand, the two-dimensional code is sent to the intelligent terminals of all the associated clients except the target associated client set, the two-dimensional code is not sent to the intelligent terminals of all the target associated clients, the two-dimensional code can be diffused to the intelligent terminals of all the associated clients at the maximum probability, and network resources are saved.
Further, still include:
and establishing a forwarding relation graph, wherein nodes in the forwarding relation graph represent target associated clients, and when any target associated client forwards the two-dimensional code to any remaining target associated client, a connecting line with a forwarding mark is added between the nodes respectively corresponding to the two target associated clients.
The beneficial effect of adopting the further scheme is that: the insurance businessman can visually determine the target associated client which does not receive the two-dimensional code through the forwarding relation graph so as to facilitate the businessman to carry out reissue.
Further, still include:
acquiring a target associated client with the most times of forwarding the two-dimensional code from the latest forwarding relation graph as a target associated client to be recommended;
and after the two-dimension code is updated, sending the updated two-dimension code to the intelligent terminal of the target associated client to be recommended.
The beneficial effect of adopting the further scheme is that: the time consumed by the two-dimensional code to spread to all intelligent terminals of target associated customers is reduced.
Further, obtaining interest points of each target associated client according to the historical internet surfing data of each target associated client;
calculating the similarity between the interest points of the pre-designated clients and the interest points of each target associated client, and determining the target associated client corresponding to the similarity larger than the similarity threshold as a target client;
sending the two-dimensional code to an intelligent terminal of each target customer;
the beneficial effect of adopting the further scheme is that: because the similarity between the interest point of each target client and the interest point of the pre-designated client is greater than the similarity threshold value, the requirement of each target client for insurance is the same as that of the pre-designated client for insurance to the greatest extent, and the two-dimensional code is sent to the intelligent terminal of each target client to recommend the same insurance product, so that the number of clients is further expanded in a targeted manner, and the probability of talking into a service is further improved.
The technical scheme of the system for intelligently recommending the insurance products is as follows:
the device comprises a determining module and an obtaining module;
the determining module is used for obtaining interest points of the pre-designated clients according to historical internet surfing data of the pre-designated clients;
the acquisition module is used for acquiring the insurance products corresponding to the interest points of the pre-designated customers so that insurance businessmen recommend specific information of the insurance products to the pre-designated customers.
The system for intelligently recommending the insurance products has the following beneficial effects:
firstly, according to historical internet surfing data of a pre-designated client, an interest point of the pre-designated client is determined, then an insurance product corresponding to the interest point of the pre-designated client is obtained, the insurance product can meet the requirements of the pre-designated client to the maximum extent, at the moment, an insurance operator can recommend the insurance product to the pre-designated client more pertinently, and the probability of talking into a service is greatly improved.
On the basis of the scheme, the system for intelligently recommending the insurance products can be further improved as follows.
Further, the system also comprises a recommending module, wherein the recommending module is used for:
obtaining the answering content of each question asked by the pre-specified client to form question and answer information;
generating information pointing to the insurance product and a two-dimensional code of the question and answer information, and sending the two-dimensional code to the intelligent terminal of the pre-designated customer;
and when the intelligent terminal of the pre-designated customer identifies the received two-dimensional code, turning to the information of the insurance product and the question and answer information.
The beneficial effect of adopting the further scheme is that: on one hand, the insurance businessman recommends the specific information of the insurance product to the pre-designated client through the telephone, after the call is finished, the pre-designated client easily forgets the specific information of the insurance product, and at the moment, the specific information of the insurance product and the question and answer information are sent to the intelligent terminal of the pre-designated client, so that the preset user can conveniently check the information repeatedly, the user experience is improved, and the probability of talking into the service is further improved; on the other hand, if the specific information and the question and answer information of the recommended insurance product are directly sent to the intelligent terminal of the pre-designated client in a text form, the pre-designated client is often disliked due to too many texts, and the specific information and the question and answer information of the insurance product are recommended in a two-dimensional code mode to the intelligent terminal of the pre-designated client, so that the user experience degree is further improved, and the probability of talking into a service is further improved.
Further, the recommendation module is further configured to:
obtaining all associated clients of the pre-designated client according to the social network data of the pre-designated client;
obtaining a target associated client set according to the social network data of each associated client, wherein a social relationship exists between every two target associated clients in the target associated client set;
and sending the two-dimensional code to the intelligent terminal of each associated client except the target associated client set.
The beneficial effect of adopting the further scheme is that: on one hand, social relations exist between every two target associated clients in the target associated client set, which shows that all the target associated clients in the target associated client set and pre-designated clients are in tight contact, at the moment, only the two-dimensional code is sent to the intelligent terminal of the pre-designated client, the two-dimensional code can be diffused to the intelligent terminals of all the target associated clients at the maximum probability, the probability of talking into a service is further improved, on the other hand, the two-dimensional code is sent to the intelligent terminals of all the associated clients except the target associated client set, the two-dimensional code is not sent to the intelligent terminals of all the target associated clients, the two-dimensional code can be diffused to the intelligent terminals of all the associated clients at the maximum probability, and network resources are saved.
Further, the system comprises a construction module, wherein the construction module is used for:
and establishing a forwarding relation graph, wherein nodes in the forwarding relation graph represent target associated clients, and when any target associated client forwards the two-dimensional code to any remaining target associated client, a connecting line with a forwarding mark is added between the nodes respectively corresponding to the two target associated clients.
The beneficial effect of adopting the further scheme is that: the insurance businessman can visually determine the target associated client which does not receive the two-dimensional code through the forwarding relation graph so as to facilitate the businessman to carry out reissue.
Further, the recommendation module is further configured to:
acquiring a target associated client with the most times of forwarding the two-dimensional code from the latest forwarding relation graph as a target associated client to be recommended;
and after the two-dimension code is updated, sending the updated two-dimension code to the intelligent terminal of the target associated client to be recommended.
The beneficial effect of adopting the further scheme is that: the time consumed by the two-dimensional code to spread to all intelligent terminals of target associated customers is reduced.
Further, the recommendation module is further configured to:
obtaining interest points of each target associated client according to the historical internet surfing data of each target associated client;
calculating the similarity between the interest points of the pre-designated clients and the interest points of each target associated client, and determining the target associated client corresponding to the similarity larger than the similarity threshold as a target client;
sending the two-dimensional code to an intelligent terminal of each target customer;
the beneficial effect of adopting the further scheme is that: because the similarity between the interest point of each target client and the interest point of the pre-designated client is greater than the similarity threshold value, the requirement of each target client for insurance is the same as that of the pre-designated client for insurance to the greatest extent, and the two-dimensional code is sent to the intelligent terminal of each target client to recommend the same insurance product, so that the number of clients is further expanded in a targeted manner, and the probability of talking into a service is further improved.
The technical scheme of the electronic equipment is as follows:
comprising a memory, a processor and a program stored on the memory and executed on the processor, the processor implementing the steps of a method of intelligently recommending insurance products, as claimed in any of the above.
Drawings
FIG. 1 is a schematic flow chart of a method for intelligently recommending insurance products according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a forwarding relationship graph;
fig. 3 is a schematic structural diagram of a system for intelligently recommending insurance products according to an embodiment of the present invention.
Detailed Description
As shown in fig. 1, a method for intelligently recommending insurance products according to an embodiment of the present invention includes the following steps:
s1, obtaining interest points of the pre-designated clients according to historical internet surfing data of the pre-designated clients; specifically, the method comprises the following steps:
1) the historical internet data comprises published information, collected information, forwarded information and comment information, browsed webpages and the like, at least one of the published information, the collected information, the forwarded information and the comment information, the browsed webpages and the like is subjected to word segmentation and stop word removal respectively, the obtained words are subjected to semantic clustering, and the interest points of the target users are determined by utilizing clustering results.
2) The history surfing data comprises tags marked in social media, and interest points of the customer are determined by using the tags marked in the social media by the pre-designated customer;
s2, acquiring the insurance product corresponding to the interest point of the pre-designated customer, so that the insurance salesman can recommend the specific information of the insurance product to the pre-designated customer. Specifically, the method comprises the following steps:
for example, when the point of interest of the user is "endowment", the corresponding insurance product is an insurance product in the aspect of endowment, and when the point of interest of the user is "medical", the corresponding insurance product is an insurance product in the aspect of medical, and the point of interest may also be: safety, disease types, property, lost business, industrial injury, birth, accident and the like, and it can be understood that the number of the interest points of the preset user can be multiple, and then the insurance product corresponding to each interest point is obtained, so that the insurance businessman can recommend the specific information of each insurance product to the pre-specified client.
The specific information of the insurance product represents a plurality of risk categories included in the insurance product, the price of each risk category, the specific claim settlement mode and the like.
Firstly, according to historical internet surfing data of a pre-designated client, an interest point of the pre-designated client is determined, then an insurance product corresponding to the interest point of the pre-designated client is obtained, the insurance product can meet the requirements of the pre-designated client to the maximum extent, at the moment, an insurance operator can recommend the insurance product to the pre-designated client more pertinently, and the probability of talking into a service is greatly improved.
In another embodiment, the preset user input interest point may be specifically input by text, or input by voice through a voice interaction software or device, and the preset user input interest point is explained by taking the interest point as disease information as an example, specifically:
s200, establishing a disease knowledge base, an insurance knowledge base and a recommendation knowledge base, wherein the disease knowledge base comprises disease knowledge, and the insurance knowledge base comprises insurance knowledge; the recommendation knowledge base comprises: recommending knowledge, wherein based on the recommending knowledge, insurance products suitable for certain disease knowledge can be determined.
S201, acquiring disease information input by a preset user, and finding out target disease knowledge from a disease knowledge base according to the disease information, wherein the target disease knowledge is the disease knowledge about the disease information;
the disease information may be input by the client, or may be summarized from the interaction process of the client with the voice interaction software, for example: a customer has recently viewed an article about a disease, a customer has recently searched for a disease, etc.
It will be appreciated that the description of the acquired disease information may not be accurate, and that a more accurate description, i.e., knowledge of the target disease, needs to be found from a disease knowledge base.
S202, judging whether recommended knowledge corresponding to target disease knowledge exists in a recommended knowledge base or not, if so, sending the recommended knowledge to an insurance businessman, so that the insurance businessman recommends an insurance product to a client according to the recommended knowledge, and if not, executing S203;
s203, determining the correlation between the target disease knowledge and each insurance knowledge in an insurance knowledge base, wherein the correlation can be realized through a certain algorithm such as a neural network model or a TF-IDF algorithm and can be measured through a numerical value;
and S204, determining the target insurance knowledge, wherein the target insurance knowledge is the insurance knowledge with the highest correlation.
S205, determining a target insurance product according to the target insurance knowledge, wherein the target insurance product is an insurance product suitable for the target disease knowledge. The relevance of the target insurance knowledge and the insurance products can be determined through a neural network model or a TF-IDF algorithm and the like, and the insurance product with the highest relevance is used as the target insurance product;
s206, the target insurance product is sent to an insurance clerk, so that the insurance clerk recommends the insurance product to the client.
S207, knowledge mining is conducted on the target disease knowledge and the target insurance product through technologies such as a crawler and the like, a piece of recommended knowledge is generated, and based on the piece of recommended knowledge, an insurance product suitable for the target disease knowledge can be determined to be the target insurance product.
And S208, updating the recommendation knowledge generated in the S207 into a recommendation knowledge base.
Since the insurance products are updated along with the development of insurance companies, the recommendation knowledge base also needs to be updated in the above way, so as to ensure that the recommendation contents received by insurance businessmen are accurate.
Preferably, in the above technical solution, the method further comprises:
s3, when the insurance salesman recommends the concrete information of the insurance product to the pre-designated customer through the telephone, making a telephone recording;
s4, carrying out voice recognition on the content of the telephone recording to obtain the question asked by the pre-designated customer; specifically, the method comprises the following steps: carrying out voice recognition on the content of the telephone recording to obtain the text content of the telephone recording, and then carrying out semantic analysis on the text content of the telephone recording to obtain the question asked by the pre-specified client;
s5, obtaining the answer content of each question to form question and answer information, specifically:
1) taking the answer of the insurance salesman to each question as the answer content of each question: directly acquiring answer content from the text content of the telephone recording, for example, the questions are: how to buy the insurance product, obtaining the answering content of the question from the text content of the telephone recording until the answering content of each question is obtained to form question and answer information;
2) as the answer content of each question, a more accurate answer is made according to each question, for example: the problems are as follows: how to buy the insurance product, sometimes an insurance businessman can temporarily forget some detailed contents due to tension or other reasons, so that the answer of the insurance businessman to the question is obtained from the text contents recorded by the telephone, the forgotten detailed contents are supplemented according to the actual situation, the answering contents of the question are obtained, and the answering contents of each question are obtained to form question and answer information;
in another embodiment, the questions asked by the pre-designated user and the answering contents given by the insurance businessman are directly obtained according to the text conversation information between the insurance businessman and the pre-designated client.
S6, generating two-dimensional codes pointing to the information of the insurance products and the question and answer information, and sending the two-dimensional codes to the intelligent terminal of the pre-designated customer;
and S7, when the intelligent terminal of the pre-designated customer identifies the received two-dimensional code, turning to the information of the insurance product and the question and answer information.
On one hand, the insurance businessman recommends the specific information of the insurance product to the pre-designated client through the telephone, after the call is finished, the pre-designated client easily forgets the specific information of the insurance product, and at the moment, the specific information of the insurance product and the question and answer information are sent to the intelligent terminal of the pre-designated client, so that the preset user can conveniently check the information repeatedly, the user experience is improved, and the probability of talking into the service is further improved; on the other hand, if the specific information and the question and answer information of the recommended insurance product are directly sent to the intelligent terminal of the pre-designated client in a text form, the pre-designated client is often disliked due to too many texts, and the specific information and the question and answer information of the insurance product are recommended in a two-dimensional code mode to the intelligent terminal of the pre-designated client, so that the user experience degree is further improved, and the probability of talking into a service is further improved.
Preferably, in the above technical solution, the method further comprises:
s8, obtaining all associated clients of the pre-designated clients according to the social network data of the pre-designated clients; wherein, social network data includes phone communication record data, little communication record data etc. then:
1) determining all telephone numbers and all mobile phone numbers which are in contact with a pre-designated client from the telephone communication record data, and determining each telephone number and each client corresponding to each mobile phone number which are in contact with the pre-designated client as an associated client;
2) determining all micro signals which are in contact with a pre-designated client through the micro messages from the micro message communication record data, and determining the client corresponding to each micro signal as a related client;
the social network data also comprises mailbox communication record data, QQ communication record data and the like, and all the associated clients are determined;
s9, obtaining a target associated client set according to the social network data of each associated client, where two target associated clients in the target associated client set have social relationships, specifically:
for example, it is known from the social network data of each associated client that there are 10 associated clients, and each two associated clients are connected by at least one of telephone, WeChat, mailbox, and QQ, which indicates that there is a social relationship between each two associated clients in the 10 associated clients, and then the 10 associated clients are all target associated clients, and are divided into a target associated client set;
among these, it is understood that: all associated clients of any one target associated client in the set of target associated clients include all target associated clients remaining in the set of target associated clients.
And S10, sending the two-dimensional code to the intelligent terminal of each associated client except the target associated client set. Then:
1) because social relations exist between every two target associated clients in the target associated client set, it is shown that all target associated clients in the target associated client set and pre-designated clients are in close contact, at this time, only the two-dimensional code is sent to the intelligent terminal of the pre-designated client, the two-dimensional code can be diffused to the intelligent terminals of all target associated clients on the maximum probability, and the probability of talking into a service is further improved;
2) and the two-dimension code is sent to the intelligent terminal of each associated client except the target associated client set, and the two-dimension code is not sent to the intelligent terminal of each target associated client, so that the two-dimension code can be diffused to the intelligent terminals of all associated clients at the maximum probability, and network resources can be saved.
Preferably, in the above technical solution, the method further comprises:
and S11, establishing a forwarding relation graph, wherein the nodes in the forwarding relation graph represent target associated clients, and when any target associated client forwards the two-dimensional code to any remaining target associated client, a connecting line with a forwarding mark is added between the nodes respectively corresponding to the two target associated clients. The following description will be given by taking a target associated client set including 4 target associated clients as an example:
s110, drawing a node, specifically: respectively marking 4 target associated customers as a first target associated customer, a second target associated customer, a third target associated customer and a fourth target associated customer, wherein because the total number of the 4 target associated customers is 4, each target associated customer corresponds to one node, four nodes are drawn, namely a first node 101, a second node 102, a third node 103 and a fourth node 104, wherein the first node 101 represents the first target associated customer, the second node 102 represents the second target associated customer, the third node 103 represents the third target associated customer, and the fourth node 104 represents the fourth target associated customer;
s111, drawing a connecting line with a forwarding mark, specifically: when it is detected that the two-dimensional code is forwarded to the second target associated client by the first target associated client, specifically, when the two-dimensional code is forwarded to the intelligent terminal of the second target associated client by the first target associated client through the intelligent terminal, a connection line with a forwarding mark is added between the first node 101 and the second node 102, where the forwarding mark may be a text mark, a shape mark, and the like, and in fig. 2, a connection line with a forwarding mark is adopted, where an arrow points from the first node 101 to the second node 102, indicating that the first target associated client forwards the two-dimensional code to the second target associated client, and so on, the forwarding relation graph shown in fig. 2 is obtained within a preset time duration; the preset time can be 1 day or 2 days and the like, and can be adjusted according to the actual situation; wherein, the tracking of forwarding two-dimensional codes can be realized through technologies such as a crawler and the like.
The insurance businessman can visually determine the target associated client which does not receive the two-dimensional code through the forwarding relation graph so as to facilitate the businessman to carry out reissue, and specifically:
for example, within a preset time period, if it is found that each connection line with the forwarding mark points to the second node 102, which indicates that the intelligent terminal of the second target-associated client has not received the two-dimensional code, the insurance clerk can timely reissue the intelligent terminal of the second target-associated client.
Preferably, in the above technical solution, the method further comprises:
s12, obtaining the target associated client with the most number of times of forwarding the two-dimensional code from the latest forwarding relation graph as a target associated client to be recommended, specifically:
taking the forwarding relation graph shown in fig. 2 as a latest forwarding relation graph, it is obvious that the number of times that the two-dimensional code is forwarded by the first target associated client corresponding to the first node 101 is 4, the number of times that the two-dimensional code is forwarded by the second target associated client corresponding to the second node 102 is 1, the number of times that the two-dimensional code is forwarded by the third target associated client corresponding to the third node 103 is 0, the number of times that the two-dimensional code is forwarded by the fourth target associated client corresponding to the fourth node 104 is 1, and since the number of times that the two-dimensional code is forwarded by the first target associated client is the largest, the first target associated client is determined as the target associated client to be recommended;
and S13, after the two-dimensional code is updated, sending the updated two-dimensional code to the intelligent terminal of the target associated client to be recommended. Due to the fact that the number of times of forwarding the two-dimensional code by the target associated client to be recommended is the largest, time consumed by the fact that the two-dimensional code is spread to intelligent terminals of all target associated clients is reduced to the greatest extent.
Preferably, in the above technical solution, the method further comprises:
s16, obtaining interest points of each target associated client according to the historical internet surfing data of each target associated client; with particular reference to the description of S1 above;
s17, calculating similarities between the interest points of the pre-designated clients and the interest points of each target associated client, and determining the target associated client corresponding to the similarity greater than the similarity threshold as the target client, specifically by comparing all the interest points of the pre-designated clients with all the interest points of each target associated client, specifically:
for example, the number of the interest points of the pre-designated client is 10, the number of the interest points of the first target associated client is 15, wherein the number of the same interest points is 5, then the similarity between the interest points of the pre-designated client and the interest points of the first target associated client is 5/(10+15-5) ═ 20%, and so on, the similarity between the interest points of the pre-designated client and the interest points of each target associated client is obtained;
then, determining the target associated client corresponding to the similarity greater than the similarity threshold as a target client, wherein the similarity threshold can be set to 80%, 85%, 90% or the like, or can be set according to actual conditions, if the similarity threshold is set to 80%, the first target associated client is not the target client because the similarity between the interest point of the first target associated client and the interest point of the pre-designated client is 20%, and if the similarity between the interest point of the second target associated client and the interest point of the pre-designated client is 92%, the second target associated client is the target client;
s18, sending the two-dimensional code to an intelligent terminal of each target customer;
because the similarity between the interest point of each target client and the interest point of the pre-designated client is greater than the similarity threshold value, the requirement of each target client for insurance is the same as that of the pre-designated client for insurance to the greatest extent, and the two-dimensional code is sent to the intelligent terminal of each target client to recommend the same insurance product, so that the number of clients is further expanded in a targeted manner, and the probability of talking into a service is further improved.
In the above embodiments, although the steps are numbered as S1, S2, etc., but only the specific embodiments are given in this application, and those skilled in the art may adjust the execution sequence of S1, S2, etc. according to the actual situation, which is also within the protection scope of the present invention, it is understood that some embodiments may include some or all of the above embodiments.
As shown in fig. 3, a system 200 for intelligently recommending insurance products according to an embodiment of the present invention includes a determining module 210 and an obtaining module 220;
the determining module 210 is configured to obtain an interest point of a pre-designated client according to historical internet surfing data of the pre-designated client;
the obtaining module 220 is configured to obtain an insurance product corresponding to the interest point of the pre-designated customer, so that an insurance clerk recommends specific information of the insurance product to the pre-designated customer.
Firstly, according to historical internet surfing data of a pre-designated client, an interest point of the pre-designated client is determined, then an insurance product corresponding to the interest point of the pre-designated client is obtained, the insurance product can meet the requirements of the pre-designated client to the maximum extent, at the moment, an insurance operator can recommend the insurance product to the pre-designated client more pertinently, and the probability of talking into a service is greatly improved.
Preferably, in the above technical solution, the apparatus further includes a recommending module, and the recommending module is configured to:
obtaining the answering content of each question asked by the pre-specified client to form question and answer information;
generating information pointing to the insurance product and a two-dimensional code of the question and answer information, and sending the two-dimensional code to the intelligent terminal of the pre-designated customer;
and when the intelligent terminal of the pre-designated customer identifies the received two-dimensional code, turning to the information of the insurance product and the question and answer information.
On one hand, the insurance businessman recommends the specific information of the insurance product to the pre-designated client through the telephone, after the call is finished, the pre-designated client easily forgets the specific information of the insurance product, and at the moment, the specific information of the insurance product and the question and answer information are sent to the intelligent terminal of the pre-designated client, so that the preset user can conveniently check the information repeatedly, the user experience is improved, and the probability of talking into the service is further improved; on the other hand, if the specific information and the question and answer information of the recommended insurance product are directly sent to the intelligent terminal of the pre-designated client in a text form, the pre-designated client is often disliked due to too many texts, and the specific information and the question and answer information of the insurance product are recommended in a two-dimensional code mode to the intelligent terminal of the pre-designated client, so that the user experience degree is further improved, and the probability of talking into a service is further improved.
Preferably, in the above technical solution, the recommending module is further configured to:
obtaining all associated clients of the pre-designated client according to the social network data of the pre-designated client;
obtaining a target associated client set according to the social network data of each associated client, wherein a social relationship exists between every two target associated clients in the target associated client set;
and sending the two-dimensional code to the intelligent terminal of each associated client except the target associated client set.
On one hand, social relations exist between every two target associated clients in the target associated client set, which shows that all the target associated clients in the target associated client set and pre-designated clients are in tight contact, at the moment, only the two-dimensional code is sent to the intelligent terminal of the pre-designated client, the two-dimensional code can be diffused to the intelligent terminals of all the target associated clients at the maximum probability, the probability of talking into a service is further improved, on the other hand, the two-dimensional code is sent to the intelligent terminals of all the associated clients except the target associated client set, the two-dimensional code is not sent to the intelligent terminals of all the target associated clients, the two-dimensional code can be diffused to the intelligent terminals of all the associated clients at the maximum probability, and network resources are saved.
Preferably, in the above technical solution, the system further comprises a construction module, wherein the construction module is configured to:
and establishing a forwarding relation graph, wherein nodes in the forwarding relation graph represent target associated clients, and when any target associated client forwards the two-dimensional code to any remaining target associated client, a connecting line with a forwarding mark is added between the nodes respectively corresponding to the two target associated clients.
The insurance businessman can visually determine the target associated client which does not receive the two-dimensional code through the forwarding relation graph so as to facilitate the businessman to carry out reissue.
Preferably, in the above technical solution, the recommending module is further configured to:
acquiring a target associated client with the most times of forwarding the two-dimensional code from the latest forwarding relation graph as a target associated client to be recommended;
and after the two-dimension code is updated, sending the updated two-dimension code to the intelligent terminal of the target associated client to be recommended.
The time consumed by the two-dimensional code to spread to all intelligent terminals of target associated customers is reduced.
Preferably, in the above technical solution, the recommending module is further configured to:
obtaining interest points of each target associated client according to the historical internet surfing data of each target associated client;
calculating the similarity between the interest points of the pre-designated clients and the interest points of each target associated client, and determining the target associated client corresponding to the similarity larger than the similarity threshold as a target client;
sending the two-dimensional code to an intelligent terminal of each target customer;
because the similarity between the interest point of each target client and the interest point of the pre-designated client is greater than the similarity threshold value, the requirement of each target client for insurance is the same as that of the pre-designated client for insurance to the greatest extent, and the two-dimensional code is sent to the intelligent terminal of each target client to recommend the same insurance product, so that the number of clients is further expanded in a targeted manner, and the probability of talking into a service is further improved.
The above steps for implementing the corresponding functions of the parameters and the unit modules in the system 200 for intelligently recommending insurance products according to the present invention can refer to the above parameters and steps in the embodiment of the method for intelligently recommending insurance products, which are not described herein again.
The electronic equipment comprises a memory, a processor and a program which is stored on the memory and runs on the processor, wherein the processor executes the program to realize any one of the steps of the method for intelligently recommending insurance products.
The electronic device may be a computer, a mobile phone, or the like, and the program of the electronic device is computer software or a mobile phone APP, and the parameters and the steps in the electronic device of the present invention may refer to the parameters and the steps in the above embodiment of the method for intelligently recommending an insurance product, which are not described herein again.
As will be appreciated by one skilled in the art, the present invention may be embodied as a system, method or computer program product.
Accordingly, the present disclosure may be embodied in the form of: may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software, and may be referred to herein generally as a "circuit," module "or" system. Furthermore, in some embodiments, the invention may also be embodied in the form of a computer program product in one or more computer-readable media having computer-readable program code embodied in the medium.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A method for intelligently recommending insurance products, comprising:
obtaining interest points of a pre-designated client according to historical internet surfing data of the pre-designated client;
and acquiring the insurance product corresponding to the interest point of the pre-designated customer so that an insurance salesman recommends specific information of the insurance product to the pre-designated customer.
2. The method of claim 1, further comprising:
obtaining the answering content of each question asked by the pre-specified client to form question and answer information;
generating information pointing to the insurance product and a two-dimensional code of the question and answer information, and sending the two-dimensional code to the intelligent terminal of the pre-designated customer;
and when the intelligent terminal of the pre-designated customer identifies the received two-dimensional code, turning to the information of the insurance product and the question and answer information.
3. The method of claim 2, further comprising:
obtaining all associated clients of the pre-designated client according to the social network data of the pre-designated client;
obtaining a target associated client set according to the social network data of each associated client, wherein a social relationship exists between every two target associated clients in the target associated client set;
and sending the two-dimensional code to the intelligent terminal of each associated client except the target associated client set.
4. The method of claim 3, further comprising:
and establishing a forwarding relation graph, wherein nodes in the forwarding relation graph represent target associated clients, and when any target associated client forwards the two-dimensional code to any remaining target associated client, a connecting line with a forwarding mark is added between the nodes respectively corresponding to the two target associated clients.
5. The method of claim 4, further comprising:
acquiring a target associated client with the most times of forwarding the two-dimensional code from the latest forwarding relation graph as a target associated client to be recommended;
and after the two-dimension code is updated, sending the updated two-dimension code to the intelligent terminal of the target associated client to be recommended.
6. The system for intelligently recommending the insurance products is characterized by comprising a determining module and an acquiring module;
the determining module is used for obtaining interest points of the pre-designated clients according to historical internet surfing data of the pre-designated clients;
the acquisition module is used for acquiring the insurance products corresponding to the interest points of the pre-designated customers so that insurance businessmen recommend specific information of the insurance products to the pre-designated customers.
7. The system of claim 6, further comprising a recommendation module configured to:
obtaining the answering content of each question asked by the pre-specified client to form question and answer information;
generating information pointing to the insurance product and a two-dimensional code of the question and answer information, and sending the two-dimensional code to the intelligent terminal of the pre-designated customer;
and when the intelligent terminal of the pre-designated customer identifies the received two-dimensional code, turning to the information of the insurance product and the question and answer information.
8. The system of claim 7, wherein the recommendation module is further configured to:
obtaining all associated clients of the pre-designated client according to the social network data of the pre-designated client;
obtaining a target associated client set according to the social network data of each associated client, wherein a social relationship exists between every two target associated clients in the target associated client set;
and sending the two-dimensional code to the intelligent terminal of each associated client except the target associated client set.
9. The system of claim 8, further comprising a build module configured to:
and establishing a forwarding relation graph, wherein nodes in the forwarding relation graph represent target associated clients, and when any target associated client forwards the two-dimensional code to any remaining target associated client, a connecting line with a forwarding mark is added between the nodes respectively corresponding to the two target associated clients.
10. An electronic device comprising a memory, a processor and a program stored on the memory and executed on the processor, wherein the processor when executing the program performs the steps of a method of intelligently recommending insurance products according to any of claims 1-5.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011159146A (en) * | 2010-02-02 | 2011-08-18 | Dainippon Printing Co Ltd | Method, system, device and program for managing advertising research |
| US20120245963A1 (en) * | 2011-03-23 | 2012-09-27 | Peak David F | System and method for distributing insurance social media related information |
| CN107730389A (en) * | 2017-09-30 | 2018-02-23 | 平安科技（深圳）有限公司 | Electronic installation, insurance products recommend method and computer-readable recording medium |
| CN109544266A (en) * | 2018-10-19 | 2019-03-29 | 中国平安人寿保险股份有限公司 | Product data method for pushing, device and computer readable storage medium |
| WO2019104876A1 (en) * | 2017-11-30 | 2019-06-06 | 平安科技（深圳）有限公司 | Insurance product pushing method and system, terminal, client terminal, and storage medium |
| CN111224886A (en) * | 2020-01-17 | 2020-06-02 | 中国平安人寿保险股份有限公司 | Network traffic control method and system |
| CN111859020A (en) * | 2019-04-26 | 2020-10-30 | 北京达佳互联信息技术有限公司 | Recommendation method and device, electronic equipment and computer-readable storage medium |
| TWM605342U (en) * | 2020-09-09 | 2020-12-11 | 玉山商業銀行股份有限公司 | Intelligent recommendation system for financial product |
| CN112464110A (en) * | 2020-12-15 | 2021-03-09 | 上海云鱼智能科技有限公司 | Method, device, server, client, terminal and storage medium for promoting interpersonal activities in application with social function |
| CN113486237A (en) * | 2021-06-07 | 2021-10-08 | 海南太美航空股份有限公司 | Flight information recommendation method and system, storage medium and electronic equipment |
-
2021
- 2021-10-13 CN CN202111191416.2A patent/CN114049225B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011159146A (en) * | 2010-02-02 | 2011-08-18 | Dainippon Printing Co Ltd | Method, system, device and program for managing advertising research |
| US20120245963A1 (en) * | 2011-03-23 | 2012-09-27 | Peak David F | System and method for distributing insurance social media related information |
| CN107730389A (en) * | 2017-09-30 | 2018-02-23 | 平安科技（深圳）有限公司 | Electronic installation, insurance products recommend method and computer-readable recording medium |
| WO2019104876A1 (en) * | 2017-11-30 | 2019-06-06 | 平安科技（深圳）有限公司 | Insurance product pushing method and system, terminal, client terminal, and storage medium |
| CN109544266A (en) * | 2018-10-19 | 2019-03-29 | 中国平安人寿保险股份有限公司 | Product data method for pushing, device and computer readable storage medium |
| CN111859020A (en) * | 2019-04-26 | 2020-10-30 | 北京达佳互联信息技术有限公司 | Recommendation method and device, electronic equipment and computer-readable storage medium |
| CN111224886A (en) * | 2020-01-17 | 2020-06-02 | 中国平安人寿保险股份有限公司 | Network traffic control method and system |
| TWM605342U (en) * | 2020-09-09 | 2020-12-11 | 玉山商業銀行股份有限公司 | Intelligent recommendation system for financial product |
| CN112464110A (en) * | 2020-12-15 | 2021-03-09 | 上海云鱼智能科技有限公司 | Method, device, server, client, terminal and storage medium for promoting interpersonal activities in application with social function |
| CN113486237A (en) * | 2021-06-07 | 2021-10-08 | 海南太美航空股份有限公司 | Flight information recommendation method and system, storage medium and electronic equipment |
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| Publication number | Publication date |
|---|---|
| CN114049225B (en) | 2023-02-21 |
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