CN115689610A - Credit card marketing customer-obtaining method and device based on big data - Google Patents
Credit card marketing customer-obtaining method and device based on big data Download PDFInfo
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Abstract
The invention provides a credit card marketing and customer-obtaining method and device based on big data, wherein the method comprises the following steps: collecting basic information of a client through an associated activity scene; white list screening is carried out on the basic information through big data, and the screened customers are layered; selecting a corresponding marketing mode to push information according to the level of the client, and acquiring a feedback result; and establishing a client label according to the feedback result to perfect the client image. The invention is a customer acquisition system integrating information acquisition, screening and layering and marketing push modules, breaks through the data isolation between banks and partners, and converts low-efficiency direct customer acquisition into high-efficiency flow-process clue marketing customer acquisition; meanwhile, through the real-time interaction among the systems, the customer experience is improved, marketing breakpoints are reduced, and the data conversion rate is improved to the maximum extent, so that high-quality credit card customers can be obtained efficiently in batches.
Description
Technical Field
The invention relates to the field of big data, in particular to a credit card marketing and customer-obtaining method and device based on big data.
Background
With the continuous development of the internet, internet users are climbing, the online transaction service is frequently seen, the technology of the big data fields such as artificial intelligence and machine learning is produced, the user data is used as the basis, the big data is used for collecting, processing and analyzing to mark the client, the client portrait is formed, and the client behavior is analyzed and predicted, however, the client acquisition is a permanent problem of enterprises, the online customer acquisition cost of the credit card market is gradually increased at present, and the online customer acquisition marketing emphasis of each bank is gradually increased. In the field of online customer acquisition, each bank has the following three problems:
1. in the traditional customer obtaining mode, customer information is collected through a long table, the customer filling content is large, visual experience is influenced, a lot of customer information is selected to be abandoned when the customer information is not completely filled, and the customer obtaining efficiency is low;
2. the traditional customer obtaining mode completely fills in a large amount of information, so that the customer has strong capital demand and high risk of customer groups, and the quality of enterprise qualification is influenced;
3. the country strengthens the protection of personal information, and as the sensitivity of customers to personal privacy gradually increases, traditional long-form customers are limited by compliance requirements and gradually quit the mainstream customer market.
Disclosure of Invention
Aiming at the technical problems, the invention provides a credit card marketing customer acquisition method and a credit card marketing customer acquisition device based on big data, which realize online and offline multi-scene intention customer data acquisition by a large data intelligent marketing customer acquisition system in a heaven-earth butt joint mode.
The technical scheme provided by the invention is as follows:
in one aspect, the invention provides a credit card marketing and customer-obtaining method based on big data, which comprises the following steps:
collecting basic information of a client through an associated activity scene;
white list screening is carried out on the basic information through big data, and the screened customers are layered;
selecting a corresponding marketing mode to push information according to the level of the client, and acquiring a feedback result;
and establishing a client label according to the feedback result, and perfecting the client image.
In some embodiments, according to the big data based credit card marketing customer obtaining method, after collecting basic information of a customer through an associated activity scenario, before white list screening the basic information through big data, the method further includes:
the basic information comprises name, mobile phone number, certificate number and contact address information, and the customer is allocated to the corresponding branch line by adopting an address selection mode according to the contact address information.
In some embodiments, the selecting a corresponding marketing mode to push information and obtain a feedback result according to the level of the customer specifically includes:
the layer includes card-held customer, APP suitable customer, SMS suitable customer and artifical marketing customer, marketing mode includes big data push, artifical marketing, robot automatic marketing and SMS marketing.
In some embodiments, according to the big data-based credit card marketing guest-obtaining method, the white list screening of the basic information by the big data specifically includes:
and calling an in-line system interface and an out-of-line system interface according to the basic information, and rejecting and screening the clients which fail to pass.
In some embodiments, the screening failed customers include customers who are blacklisted, anti-money laundering, anti-terrorism, multi-headed loan, poor credit investigation, high liability, or public security network blacklist according to the big-data based credit card marketing customer-obtaining method.
On the other hand, based on the same technical concept, the invention also provides a credit card marketing and customer-obtaining device based on big data, which is characterized by comprising the following components:
the information acquisition module is used for acquiring basic information of the client through the associated activity scene;
the screening and layering module is used for screening the white list of the basic information through big data and layering the screened customers;
the marketing pushing module is used for selecting a corresponding marketing mode to push information according to the level of the client to obtain a feedback result;
and the data precipitation module is used for establishing a client label according to the feedback result and perfecting the client image.
In some embodiments, the big-data based credit card marketing guest-obtaining device further comprises:
the data processing module is used for processing the basic information of the client; the data processing module specifically comprises:
the address specification submodule is used for normalizing the contact address in the basic information;
and the distribution submodule is used for distributing the clients to the corresponding branch lines.
In some embodiments, according to the big-data-based credit card marketing guest-obtaining device, the marketing push module specifically includes:
the big data pushing submodule is used for pushing information in a big data marketing mode;
the manual pushing submodule is used for pushing information in a manual marketing mode;
the robot automatic pushing submodule is used for pushing information in a marketing mode of the robot;
and the short message pushing submodule is used for pushing information in a short message marketing mode.
In some embodiments, according to the big-data-based credit card marketing guest-obtaining device, the screening and layering module specifically includes:
the screening submodule is used for eliminating the clients outside the white list;
and the layering submodule is used for layering the customers, and the layering comprises card-held customers, APP applicable customers, short message applicable customers and manual marketing customers.
In some embodiments, according to the big-data based credit card marketing guest-obtaining device, the data precipitation module specifically includes:
the label establishing submodule is used for establishing a client label according to the feedback result;
and the portrait perfecting submodule is used for perfecting the portrait of the client according to the feedback result.
The credit card marketing and customer-obtaining method and device based on big data provided by the invention at least have the following beneficial effects:
1. according to the credit card marketing customer acquisition method and device based on big data, the traditional mode of acquiring customers by using a long form is abandoned, the form of a short form is adopted, and four basic information of the names, mobile phone numbers, certificate numbers and contact addresses of the customers are acquired only through various channels, such as offline large business surpasses, weChat links, program interfaces and the like, so that the form filling willingness of the customers can be effectively improved, and the customer acquisition efficiency is increased.
2. According to the credit card marketing and customer-obtaining method and device based on the big data, the customers are layered through the big data, different pushing modes are adopted according to the customers of different layers, accurate marketing is achieved for the customers, marketing breakpoints are reduced, and customer experience is improved.
3. According to the credit card marketing customer-obtaining method and device based on big data, customers who do not accord with card issuing rules are eliminated by utilizing the in-line query interface and the out-of-line query interface, and high-quality credit card users are obtained in batches and efficiently.
4. The credit card marketing and customer-obtaining method and device based on the big data have a data precipitation function, can construct new customer labels according to the obtaining path of customers, the preference scene of the customers and the big data screening result of the customers, simultaneously improve the customer figures of stock customers, and provide policy support in the expansion of the new customers and the operation of the stock customers.
Drawings
The foregoing features, technical features, advantages and implementations of a big data based credit card marketing guest-acquiring method and apparatus will be further described in the following detailed description of preferred embodiments in a clearly understandable manner in conjunction with the accompanying drawings.
FIG. 1 is a schematic flow chart diagram illustrating one embodiment of a big-data based credit card marketing guest-obtaining method of the present invention;
FIG. 2 is a schematic flow chart diagram illustrating another embodiment of a big-data based credit card marketing customer acquisition method of the present invention;
FIG. 3 is a block diagram of one embodiment of a big-data based credit card marketing guest-obtaining device of the present invention;
FIG. 4 is a block diagram of another embodiment of a big-data based credit card marketing guest-obtaining apparatus of the present invention;
FIG. 5 is a block diagram of another embodiment of a big-data based credit card marketing guest-obtaining apparatus of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
In some embodiments, referring to fig. 1, the big data based marketing customer-obtaining method provided by the present invention comprises the steps of:
s100, collecting basic information of a client through a relevant activity scene;
s200, white list screening is carried out on the basic information through big data, and the screened customers are layered;
s300, selecting a corresponding marketing mode to push information according to the level of the client, and acquiring a feedback result;
and S400, establishing a client label according to the feedback result, and perfecting the client image.
Specifically, the method includes the steps that basic information of a client is obtained by enabling the client to fill in a form, during the period, the client can be touched by various channels and basic information of the client can be obtained, such as a WeChat link, a text transmission system, an API interface and a Xingshan (digital operation service platform), then the client is attracted by a welfare issuing mode, an activity scene is created, for example, full consumption and deactivation with a certain partner are carried out, the client fills in a name, a mobile phone, a certificate number and a contact address on an activity interface, full consumption 100 minus 10 yuan welfare activity can be enjoyed after completion of filling, then the system processes the obtained client information, and the obtained client is divided into different layers through big data; and finally, based on different levels of the clients, different marketing strategies are adopted, the clients are efficiently and accurately obtained and mined, then, the client labels are newly established through client feedback and experience summarization, the client images are perfected, and strategy support is provided for the subsequent pushing mode. The scenes involved in the embodiment are real consumption scenes, and low-risk consumption customers are obtained, so that high-risk capital hunger-thirst type customers are effectively prevented from entering, and the asset risk is reduced.
In some embodiments, on the basis of the above example, with reference to fig. 2, after the collecting of the basic information of the customer through the associated activity scenario and before the white list screening of the basic information through big data, further comprising,
the basic information comprises name, mobile phone number, certificate number and contact address information, and the customer is allocated to the corresponding branch line by adopting an address selection mode according to the contact address information.
Specifically, the traditional long form needs to be filled with various complicated information such as identity information including names and identity numbers, work information, income information and contact information, the willingness of customers is gradually weakened along with the filling of the information, and the customer obtaining effect is influenced. In view of the fact that various service systems in the current line cannot be automatically matched and allocated to corresponding sub-lines directly according to client address information, when the client address information is processed, a standardized address selection mode is adopted in the embodiment, meanwhile, the address is compared with the key field information and is converted into a mechanism code, the downstream can be automatically matched to the home according to the mechanism code conveniently, and then the client data in different regions are allocated to the corresponding sub-lines. For example, the contact address filled by the client is Guangdong Shenzhen, and the data is automatically allocated to the Shenzhen branch line.
In some embodiments, on the basis of the above embodiment, the selecting, according to the hierarchy of the customer, a corresponding marketing mode to push information and obtain a feedback result specifically includes:
the layer includes card-held client, APP applicable client, SMS applicable client and manual marketing client, the marketing means includes big data push, manual marketing, robot automatic marketing and SMS marketing.
Specifically, client layering is carried out according to client attributes or an inline model, for example, card-held clients, APP applicable clients, short message applicable clients, manual marketing clients and the like, and data are pushed to an accurate marketing system. The system integrates various client touch modes such as short messages, APP pushing, robot intelligent marketing, manual marketing and the like. Different customer hierarchies can be accurately marketed according to channels and activities matched with the customer attributes: screening, forming batch files for the clients who have already held the card, transmitting the batch files to the robot, the short message and APP pushing module, and pushing various market activities; if the card passes the screening and is a new customer, pushing the new customer to a manual marketing card handling; and pushing the intelligent outbound card or other services to the robot when the user is not touched by the human. Through the processing layering of big data, accurate marketing can effectively promote the work efficiency of bank like this, promotes the customer and obtains the rate, for the customer fit the marketing mode, can promote customer experience equally moreover.
In some embodiments, on the basis of the foregoing embodiment, the white list screening of the basic information through big data specifically includes:
and calling an in-line system interface and an out-of-line system interface according to the basic information, and removing the clients which do not pass the screening, wherein the clients which do not pass the screening comprise the clients belonging to the blacklist, the anti-money laundering, the anti-terrorism, the multi-head loan, the poor credit investigation, the overhigh liability or the blacklist of the public security network.
Specifically, the collected basic information of the client is transmitted to a client information processing system, a big data query function is arranged in the system, an in-line and out-line system interface can be called in real time, and clients such as blacklists, anti-money laundering, anti-terrorism, current marketing, age inconsistency, multi-head loan and the like are removed by querying an in-line system; and by inquiring an off-line system, clients with bad credit investigation, overhigh liability, black lists of a public security network and the like are removed. In the query sequence, the embodiment queries the in-line system preferentially, and if the in-line screening is not passed, the in-line system does not enter an out-of-line system query program, so that the data processing timeliness is improved; the screening result is transmitted back to the partner in real time by using the API interface, and if the screening is passed, the partner can directly issue the A-type coupons with larger face value; if the screening is not passed (i.e. the screening is not passed through the in-line system or the out-of-line system), the partner issues the B-type coupon with smaller face value for the client to immediately pick up. In addition, the returned information of the API interface can be customized according to business terms, the returned information comprises one or more states of screening passing, piece feeding, card issuing, first swiping and staging, in the subsequent marketing process, only the clients capable of card issuing are reserved for contact, the clients can be reserved to the maximum extent and can be accurately acquired, the efficiency improving data processing module and the accurate marketing module can classify the clients, and the client experience is optimized while the differentiated marketing and processing mode maximally utilizes data resources.
Based on the same technical concept, the present invention further provides a big data based credit card marketing customer-obtaining device, referring to fig. 3, including:
the information acquisition module 10 is used for acquiring basic information of the client through the associated activity scene;
a screening and layering module 20, configured to perform white list screening on the basic information through big data, and perform layering on the screened clients;
the marketing pushing module 30 is used for selecting a corresponding marketing mode to push information according to the level of the client, and obtaining a feedback result;
and the data precipitation module 40 is used for establishing a client label according to the feedback result and perfecting the client image.
The information acquisition module is used for acquiring basic information of a client through a related activity scene, in the embodiment, the basic information of the client is acquired by filling a short form in the client, the name, the mobile phone number, the certificate number and the contact address of the client are acquired, the client can be touched and the basic information of the client can be acquired through various channels in the period, the screening and layering module is used for processing the acquired basic information of the client, the client is hierarchically managed through big data, the marketing and pushing module can conveniently touch the client and mine the client through different marketing strategies, the data precipitation module is used for constructing a new client label according to an acquisition path of the client, a preference scene of the client and a big data screening result of the client, meanwhile, the client figure of the stock client is perfected, and strategy support is provided in the expansion of the new client and the management of the stock client.
In some embodiments, on the basis of the above embodiments, the big-data-based credit card marketing guest-obtaining device, with reference to fig. 4, further includes:
a data processing module 15, configured to process the basic information of the client; the data processing module specifically comprises:
an address specification submodule 16, configured to normalize the contact address in the basic information;
and the distribution submodule 17 is used for distributing the clients to the corresponding branch lines.
Specifically, the address specification submodule is used for enabling the contact address in the basic information of the client to adopt a standardized address selection mode, the allocation submodule enables the address to take the key field information to be compared with the mapping table and converted into a mechanism code, downstream is convenient to automatically match to the home according to the mechanism code, and then client data of different regions are allocated to corresponding division lines, for example, the contact address of the client is Guangdong Shenzhen, and the system automatically allocates the client to the Shenzhen division lines.
In some embodiments, on the basis of the above embodiment, with reference to fig. 5, the marketing push module specifically includes:
the big data pushing submodule 31 is used for pushing information in a big data marketing mode;
the manual pushing submodule 32 is used for pushing information in a manual marketing mode;
the robot automatic pushing submodule 33 is used for pushing information in a marketing mode of the robot;
and the short message pushing submodule 34 is used for pushing information in a short message marketing mode.
Specifically, after the clients are layered according to the client attributes or the inline model, data is pushed to the accurate marketing system, such as card-held clients, APP applicable clients, short message applicable clients, manual marketing clients and the like. The system integrates various pushing sub-modules such as a short message pushing sub-module, a robot automatic pushing sub-module, a manual pushing sub-module and a big data pushing sub-module. Channels and activities matched with the customer spread attributes are selected according to the levels of customers for accurate marketing, and batch files are formed for the customers who pass the screening and have held the card and are transmitted to the robot, the short message and APP pushing module to push various market activities; if the card passes the screening and is a new customer, pushing the new customer to a manual marketing card handling; and pushing the intelligent outbound card or other services to the robot when the user is not touched by the human. Through the processing layering of big data, accurate marketing can effectively promote the work efficiency of bank like this, promotes the customer and obtains the rate, for the customer fit the marketing mode, can promote customer experience equally moreover.
In some embodiments, based on the above embodiments, according to the big data based credit card marketing guest-obtaining device, the screening and layering module specifically includes:
the screening submodule is used for eliminating the clients outside the white list;
and the layering submodule is used for layering the customers, and the layering comprises card-held customers, APP applicable customers, short message applicable customers and manual marketing customers.
Specifically, the screening submodule is used for screening the collected basic information of the customers and eliminating the customers which do not accord with bank card issuing rules, for example, the customers such as blacklists, anti-money laundering, anti-terrorism, current marketing, age inconsistency, multi-head loan and the like are eliminated by inquiring an inline system; and by inquiring an off-line system, clients with bad credit investigation, overhigh liability, black lists of a public security network and the like are removed. In the query sequence, the in-line system is queried preferentially, and if the in-line screening is not passed, the in-line system query program is not entered, so that the data processing timeliness is improved; the screening result is transmitted back to the partner in real time by using the API interface, and if the screening is passed, the partner can directly issue the A-type coupons with larger face value; if the filtering is not passed (namely, the filtering is not passed through the in-line system or the out-of-line system), the partner issues the B-type coupon with smaller face value for the client to immediately pick up. In addition, the returned information of the API can be customized according to business terms in a personalized mode, the returned information comprises one or more states of screening passing, piece entering, card issuing, first swiping and staging, in the follow-up marketing process, only the clients capable of card issuing are reserved for contact, the clients are reserved to the maximum extent, the clients can be obtained accurately, the efficiency improving data processing module and the accurate marketing module can classify the clients, and the clients are also optimized in the mode of differentiated marketing and processing, wherein the data resources are utilized to the maximum extent.
In some embodiments, the data precipitation module specifically comprises:
the label establishing submodule is used for establishing a client label according to the feedback result;
and the portrait perfecting submodule is used for perfecting the portrait of the client according to the feedback result.
Specifically, the data precipitation module is used for building a new client label according to the acquisition path of the client, the preference scene of the client and the big data screening result of the client, perfecting the client figure of the stock client and providing strategy support in the expansion of the new client and the operation of the stock client. For example, a customer clue of entering a gas station scene can market customers by using a refueling activity, so that the marketing success rate of the customers is greatly improved; if the stock is in cross operation, stock clients with abnormal big data screening results can be brought into control in advance, so that risks are avoided; the refueling customer can push the automobile for staging, and the product dimension of the customer is increased.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or recited in detail in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
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 application 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.
It should be noted that the above embodiments can be freely combined as necessary. The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A credit card marketing and customer-obtaining method based on big data is characterized by comprising the following steps:
collecting basic information of a client through an associated activity scene;
white list screening is carried out on the basic information through big data, and the screened customers are layered;
selecting a corresponding marketing mode to push information according to the level of the client, and acquiring a feedback result;
and establishing a client label according to the feedback result to perfect the client image.
2. The big data based credit card marketing customer acquisition method according to claim 1, wherein after collecting basic information of the customer through the associated activity scene, before white list screening the basic information through big data, further comprising:
the basic information comprises name, mobile phone number, certificate number and contact address information, and the customer is allocated to the corresponding branch line by adopting an address selection mode according to the contact address information.
3. The big data-based credit card marketing and customer-obtaining method according to claim 1, wherein the selecting a corresponding marketing mode to push information and obtain a feedback result according to the level of the customer specifically comprises:
the layer includes card-held customer, APP suitable customer, SMS suitable customer and artifical marketing customer, marketing mode includes big data push, artifical marketing, robot automatic marketing and SMS marketing.
4. The big data based credit card marketing guest-obtaining method according to any one of claims 1 to 3, wherein the white list screening of the basic information through big data specifically comprises:
and calling an in-line system interface and an out-of-line system interface according to the basic information, and eliminating the clients which fail in screening.
5. The big-data based credit card marketing customer acquisition method of claim 4, wherein the screening failed customers comprise customers who belong to blacklists, anti-money laundering, anti-terrorism, multi-headed loan, poor credit investigation, high liability, or public security network blacklists.
6. A big data based credit card marketing guest-obtaining device, comprising:
the information acquisition module is used for acquiring basic information of the client through the associated activity scene;
the screening and layering module is used for screening the white list of the basic information through big data and layering the screened customers;
the marketing pushing module is used for selecting a corresponding marketing mode to push information according to the level of the client to obtain a feedback result;
and the data precipitation module is used for establishing a client label according to the feedback result and perfecting the client image.
7. The big-data based credit card marketing guest-obtaining device according to claim 6, further comprising:
the data processing module is used for processing the basic information of the client; the data processing module specifically comprises:
the address specification submodule is used for normalizing the contact address in the basic information;
and the distribution submodule is used for distributing the clients to the corresponding branch lines.
8. The big-data based credit card marketing guest-obtaining device according to claim 7, wherein the marketing push module specifically comprises:
the big data pushing submodule is used for pushing information in a big data marketing mode;
the manual pushing submodule is used for pushing information in a manual marketing mode;
the robot automatic pushing submodule is used for pushing information in a marketing mode of the robot;
and the short message pushing submodule is used for pushing information in a short message marketing mode.
9. The big-data based credit card marketing guest-obtaining device according to any one of claims 6 to 8, wherein the filtering hierarchy module specifically comprises:
the screening submodule is used for eliminating the clients outside the white list;
and the layering submodule is used for layering the customers, and the layering comprises card-held customers, APP applicable customers, short message applicable customers and manual marketing customers.
10. The big-data based credit card marketing guest-obtaining device according to claim 9, wherein the data precipitation module specifically comprises:
the label establishing submodule is used for establishing a client label according to the feedback result;
and the portrait perfecting submodule is used for perfecting the portrait of the client according to the feedback result.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116049512A (en) * | 2023-03-30 | 2023-05-02 | 紫金诚征信有限公司 | Credit body information processing method and device and electronic equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116049512A (en) * | 2023-03-30 | 2023-05-02 | 紫金诚征信有限公司 | Credit body information processing method and device and electronic equipment |
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