CN113988934A - Method and device for marketing large-volume deposit receipt product - Google Patents

Method and device for marketing large-volume deposit receipt product Download PDF

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Publication number
CN113988934A
CN113988934A CN202111274708.2A CN202111274708A CN113988934A CN 113988934 A CN113988934 A CN 113988934A CN 202111274708 A CN202111274708 A CN 202111274708A CN 113988934 A CN113988934 A CN 113988934A
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data
user data
users
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product
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郭军材
邹雷登
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Bank of China Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0202—Market predictions or forecasting for commercial activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

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Abstract

The invention discloses a method and a device for marketing a large-volume deposit receipt product, which relate to the technical field of big data, wherein the method comprises the following steps: acquiring first user data of users in the bank, wherein the first user data comprises user data of users not using the large-volume deposit receipt product and user data of users using the large-volume deposit receipt product; preprocessing the first user data to obtain second user data; data mining is carried out on the second user data to obtain specific user attributes of the large-volume deposit receipt product; and screening target marketing users from the unused large deposit receipt product users according to the specific user attributes, and recommending the large deposit receipt product to the target marketing users. The invention can improve the identification efficiency and marketing promotion efficiency of the target client and reduce the marketing cost.

Description

Method and device for marketing large-volume deposit receipt product
Technical Field
The invention relates to the technical field of big data, in particular to a method and a device for marketing a large-volume deposit receipt product.
Background
This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
With the development of society and the continuous improvement of social economy, the personal income and assets of people are increased. More and more people choose to deposit funds into banks to obtain certain interest. Nowadays, the supervision cancels the prior file collection and interest counting, so that the liquidity demand of customers on deposit products such as the large deposit receipt is stronger, and the transferable large deposit receipt products are timely and timely. However, due to the newly-released products, the number of customers is small, and the popularization mode is very limited.
The existing bank promotion marketing mode mainly depends on the modes of marketing under a network point line or putting advertisements on line and the like. The main disadvantages faced by these marketing approaches are:
(1) the misjudgment rate of the customer identification and analysis is high
The offline website popularization mainly adopts questionnaire investigation or popularization when handling similar business, depends on business quality of marketing personnel, has strong subjectivity and no scientificity, and does not have a large amount of data support, thereby causing the problem of high misjudgment rate of client identification and analysis. The online advertisement delivery mode, such as the advertisement in the WeChat friend circle, may apply certain data mining or other technologies, and also have data support. However, most of the supporting data is customer data of the advertising platform, and the customer data cannot be leaked by the bank. Therefore, the problem of high misjudgment rate of the customer identification analysis is caused.
(2) Marketing promotion cost is high
Whether the marketing is promoted online or offline, because of the high misjudgment rate, the marketing promotion cost is high, and even customers feel dislike and lose bank base customers.
(3) The marketing and promotion efficiency is low
The marketing popularization mode is unscientific, has no data support, and has high limitation and misjudgment rate on potential customer identification, thereby resulting in low marketing popularization efficiency and low effect.
Disclosure of Invention
The embodiment of the invention provides a large-volume deposit list business marketing method, which is used for improving the identification efficiency and marketing promotion efficiency of target customers and reducing the marketing cost and comprises the following steps:
acquiring first user data of users in the bank, wherein the first user data comprises user data of users not using the large-volume deposit receipt product and user data of users using the large-volume deposit receipt product;
preprocessing the first user data to obtain second user data;
data mining is carried out on the second user data to obtain specific user attributes of the large-volume deposit receipt product;
and screening target marketing users from the unused large deposit receipt product users according to the specific user attributes, and recommending the large deposit receipt product to the target marketing users.
The embodiment of the invention also provides a large-volume deposit receipt product marketing device, which is used for improving the identification efficiency and marketing promotion efficiency of target customers and reducing the marketing cost, and comprises the following components:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring first user data of bank stock users, and the first user data comprises user data of users not using the large-volume deposit list products and user data of users using the large-volume deposit list products;
the preprocessing module is used for preprocessing the first user data to obtain second user data;
the data mining module is used for carrying out data mining on the second user data to obtain the specific user attribute of the large-volume deposit receipt product;
and the screening module is used for screening target marketing users from unused large deposit receipt product users according to the specific user attributes and recommending the large deposit receipt product to the target marketing users.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the large deposit receipt service marketing method.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program for executing the above-mentioned marketing method of the large deposit list service is stored in the computer-readable storage medium.
In the embodiment of the invention, a large amount of actual data support is provided during data mining by directly acquiring the first user data of the user storing in the bank; and then, preprocessing the first user data, mining the preprocessed second user data to obtain a specific user attribute of the user using the large deposit receipt product, and deducing and positioning potential users which are not used as the large deposit receipt product users through the specific user attribute. The data mining method is scientific, low in subjective judgment, strong in pertinence, capable of realizing accurate positioning of potential customers, high in marketing popularization efficiency and low in cost; in addition, a large data platform applying the data mining technology can be independently developed and built, and the labor cost is low. In addition, the incremental user data can be used for expanding the data mining algorithm bottom database subsequently, so that the data characteristics or attributes are perfected, the data mining model is remodeled, and the deduction prediction result is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a method for marketing a large inventory product according to an embodiment of the present invention;
FIG. 2 is another flow chart of a method for marketing a large inventory product according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a method for performing step 103 according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a mass inventory product marketing device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The embodiment of the invention provides a marketing method for a large-volume deposit receipt product, which comprises the following steps 101 to 104:
step 101, obtaining first user data of users in the bank.
Wherein the first user data comprises user data of users not using the large deposit receipt product and users using the large deposit receipt product.
The user data comprises basic data such as gender and age of the user, and user behavior data such as deposit number, daily transaction flow, daily transaction times, daily transaction amount, whether a financial product is purchased or not, and the type of the purchased financial product.
Step 102, preprocessing the first user data to obtain second user data.
Specifically, as shown in fig. 2, step 102 may be executed as the following step 1021:
and step 1021, performing data integration, data cleaning and data conversion on the first user data to obtain second user data.
Data pre-processing is the most complex and quite important. The quality and accuracy of data mining results are easily affected by the quality of the data. Therefore, preprocessing is necessary for collected data, which is helpful for improving the efficiency and quality of data mining, so that the mining result is more accurate. The data preprocessing refers to reprocessing of source data, smoothing data which are easily interfered by noise, filling up blank values, eliminating dirty data and the like.
In the preprocessing process, the steps of data integration, data cleaning and data conversion are sequentially carried out.
Data integration refers to the physical or logical organic integration of data with different formats from multiple data sources into one effective and consistent data capable of being mined. During specific execution, the acquired data collected by the bank outlets of the bank stock users and the data of the mobile phone banks and the like are integrated, and the data are converted into a preset general format.
The data cleaning means that the problem of data inconsistency is solved by filling in missing values, smoothing noise data, and identifying and deleting outsiders. Illustratively, in the process of data cleaning, if missing data is filled as much as possible, otherwise, deleting is carried out; if the repeated data exist, deleting the repeated data; other special data can be deleted, such as user data of a malicious registered user, a user who never transacts, or other special users.
Data transformation, which refers to converting collected data into a form suitable for data mining. Discretizing the first user data after data integration and data cleaning. For example, a client 18-30 years old is classified as young, a client 30-50 as middle-aged in an age attribute; the customer is classified as an inactive, normal, active user, etc. by record size on the transaction record.
And 103, performing data mining on the second user data to obtain the specific user attribute of the large-volume deposit receipt product.
Specifically, as shown in fig. 3, step 103 performs data mining on the second user data to obtain the user attribute of using the large-volume deposit receipt product, and may be performed as following step 1031 and step 1032:
step 1031, performing entity relationship mapping on the second user data, building a data set, and extracting user attributes of users using the large-volume deposit receipt product in the data set;
and step 1032, based on the set minimum support degree and minimum confidence degree, performing data mining on the second user data by using an association rule algorithm to obtain the specific user attribute of the use large deposit receipt product meeting the minimum support degree and the minimum confidence degree.
The user attributes of the users using the large deposit receipt product in the data set are extracted, the attributes related to the expected effect of data mining are extracted, and the specific user attributes with high relevance to the large deposit receipt product are determined from the related attributes.
The association rule algorithm is proposed earlier than 1994, is firstly applied to the commodity transaction industry, is used for discovering the association between commodities purchased by supermarket customers, constructs a customer consumption model, belongs to the data mining technology, and is widely applied to the fields of various industries.
Association rule algorithms can efficiently mine intrinsic and important associations between sets of items from large amounts of data, one of the important components of data mining. In the embodiment of the present invention, a classical Apriori algorithm in an association rule algorithm may be used, and other improved algorithms in the prior art may also be used. The type of association rule algorithm used in detail is not limited herein.
The minimum support and the minimum confidence are parameters commonly used in association rule algorithms.
By setting the minimum support, the result of data mining is a frequent set of terms like { AB }. In an embodiment of the invention, the minimum support is used to define a minimum probability of simultaneous occurrence of the use of a large inventory product (event a) and a specific user attribute (event B).
By setting a minimum confidence, a strong association rule of a → B is obtained, which means IF a occurs and THEN B occurs. In an embodiment of the invention, the minimum confidence is used to define the minimum probability of occurrence of a particular user attribute (event B) among users using a large inventory product (event a).
The minimum support degree and the minimum confidence degree are flexibly configured by service personnel according to actual requirements, when the configured minimum support degree and the configured minimum confidence degree are higher, the obtained specific user attribute is more strongly associated with the event of using the large-volume deposit receipt product, and the target marketing user obtained by screening according to the specific user attribute has higher probability to become a large-volume deposit receipt product user.
And 104, screening target marketing users from the unused large deposit receipt products according to the specific user attributes, and recommending the large deposit receipt products to the target marketing users.
The screened target marketing users have specific user attributes, are user groups which are more likely to use the large-volume deposit receipt products, recommend the large-volume deposit receipt products to the target marketing users, and are higher in marketing success probability and higher in efficiency.
In the embodiment of the invention, the large deposit receipt product can be recommended to the target marketing user through short messages, mobile banking APP messages, telephone marketing, or the like, or by the staff of a bank outlet recommending the user during business handling. The recommended method is not limited herein.
In the embodiment of the invention, a large amount of actual data support is provided during data mining by directly acquiring the first user data of the user storing in the bank; and then, preprocessing the first user data, mining the preprocessed second user data to obtain a specific user attribute of the user using the large deposit receipt product, and deducing and positioning potential users which are not used as the large deposit receipt product users through the specific user attribute. The data mining method is scientific, low in subjective judgment, strong in pertinence, capable of realizing accurate positioning of potential customers, high in marketing popularization efficiency and low in cost; in addition, a large data platform applying the data mining technology can be independently developed and built, and the labor cost is low. In addition, the incremental user data can be used for expanding the data mining algorithm bottom database subsequently, so that the data characteristics or attributes are perfected, the data mining model is remodeled, and the deduction prediction result is more accurate.
The embodiment of the invention also provides a marketing device for the large-volume deposit receipt product, which is described in the following embodiment. Because the principle of solving the problems of the device is similar to the marketing method of the large-volume deposit receipt product, the implementation of the device can be referred to the implementation of the marketing method of the large-volume deposit receipt product, and repeated parts are not described again.
As shown in fig. 4, the apparatus 400 includes an acquisition module 401, a preprocessing module 402, a data mining module 403, and a filtering module 404.
The acquiring module 401 is configured to acquire first user data of a user in a bank, where the first user data includes user data of a user who does not use a large-volume deposit receipt product and user data of a user who uses the large-volume deposit receipt product;
a preprocessing module 402, configured to preprocess the first user data to obtain second user data;
the data mining module 403 is configured to perform data mining on the second user data to obtain a specific user attribute of the large-volume deposit receipt product;
and the screening module 404 is used for screening target marketing users from unused large deposit receipt products according to the specific user attributes and recommending the large deposit receipt products to the target marketing users.
In an implementation manner of the embodiment of the present invention, the preprocessing module 402 is configured to:
and performing data integration, data cleaning and data conversion on the first user data to obtain second user data.
In an implementation manner of the embodiment of the present invention, the preprocessing module 402 is configured to:
discretizing the first user data.
In an implementation manner of the embodiment of the present invention, the data mining module 403 is configured to:
entity relation mapping is carried out on the second user data, a data set is built, and user attributes of users using the large-volume deposit receipt product in the data set are extracted;
based on the set minimum support degree and minimum confidence degree, carrying out data mining on the second user data by using an association rule algorithm to obtain a specific user attribute which meets the minimum support degree and the minimum confidence degree and uses a large deposit receipt product;
wherein the minimum support is used to define a minimum probability of simultaneous occurrence of using the large inventory product and the specific user attribute; the minimum confidence is used to define the minimum probability of a particular user attribute occurring among users using the large inventory product.
In the embodiment of the invention, a large amount of actual data support is provided during data mining by directly acquiring the first user data of the user storing in the bank; and then, preprocessing the first user data, mining the preprocessed second user data to obtain a specific user attribute of the user using the large deposit receipt product, and deducing and positioning potential users which are not used as the large deposit receipt product users through the specific user attribute. The data mining method is scientific, low in subjective judgment, strong in pertinence, capable of realizing accurate positioning of potential customers, high in marketing popularization efficiency and low in cost; in addition, a large data platform applying the data mining technology can be independently developed and built, and the labor cost is low. In addition, the incremental user data can be used for expanding the data mining algorithm bottom database subsequently, so that the data characteristics or attributes are perfected, the data mining model is remodeled, and the deduction prediction result is more accurate.
An embodiment of the present invention further provides a computer device, and fig. 5 is a schematic diagram of the computer device in the embodiment of the present invention, where the computer device is capable of implementing all steps in the marketing method for a large-volume deposit receipt product in the embodiment of the present invention, and the computer device specifically includes the following contents:
a processor (processor)501, a memory (memory)502, a communication Interface (Communications Interface)503, and a communication bus 504;
the processor 501, the memory 502 and the communication interface 503 complete mutual communication through the communication bus 504; the communication interface 503 is used for implementing information transmission between related devices;
the processor 501 is used to call the computer program in the memory 502, and when the processor executes the computer program, the processor implements the large deposit receipt product marketing method in the above embodiments.
An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program for executing the marketing method of the large deposit receipt product.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A method of marketing a large inventory product, the method comprising:
acquiring first user data of users in the bank, wherein the first user data comprises user data of users not using the large-volume deposit receipt product and user data of users using the large-volume deposit receipt product;
preprocessing the first user data to obtain second user data;
data mining is carried out on the second user data to obtain specific user attributes of the large-volume deposit receipt product;
and screening target marketing users from the unused large deposit receipt product users according to the specific user attributes, and recommending the large deposit receipt product to the target marketing users.
2. The method of claim 1, wherein pre-processing the first user data to obtain second user data comprises:
and performing data integration, data cleaning and data conversion on the first user data to obtain second user data.
3. The method of claim 2, wherein the data translating the first user data comprises:
discretizing the first user data.
4. The method of any of claims 1 to 3, wherein data mining the second user data for specific user attributes using the large inventory product comprises:
entity relation mapping is carried out on the second user data, a data set is built, and user attributes of users using the large-volume deposit receipt product in the data set are extracted;
based on the set minimum support degree and minimum confidence degree, carrying out data mining on the second user data by using an association rule algorithm to obtain a specific user attribute which meets the minimum support degree and the minimum confidence degree and uses a large deposit receipt product;
wherein the minimum support is used to define a minimum probability of simultaneous occurrence of using the large inventory product and the specific user attribute; the minimum confidence is used to define the minimum probability of a particular user attribute occurring among users using the large inventory product.
5. A mass-deposit-list product marketing device, the device comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring first user data of bank stock users, and the first user data comprises user data of users not using the large-volume deposit list products and user data of users using the large-volume deposit list products;
the preprocessing module is used for preprocessing the first user data to obtain second user data;
the data mining module is used for carrying out data mining on the second user data to obtain the specific user attribute of the large-volume deposit receipt product;
and the screening module is used for screening target marketing users from unused large deposit receipt product users according to the specific user attributes and recommending the large deposit receipt product to the target marketing users.
6. The apparatus of claim 5, wherein the pre-processing module is configured to:
and performing data integration, data cleaning and data conversion on the first user data to obtain second user data.
7. The apparatus of claim 6, wherein the pre-processing module is configured to:
discretizing the first user data.
8. The apparatus of any of claims 5 to 7, wherein the data mining module is configured to:
entity relation mapping is carried out on the second user data, a data set is built, and user attributes of users using the large-volume deposit receipt product in the data set are extracted;
based on the set minimum support degree and minimum confidence degree, carrying out data mining on the second user data by using an association rule algorithm to obtain a specific user attribute which meets the minimum support degree and the minimum confidence degree and uses a large deposit receipt product;
wherein the minimum support is used to define a minimum probability of simultaneous occurrence of using the large inventory product and the specific user attribute; the minimum confidence is used to define the minimum probability of a particular user attribute occurring among users using the large inventory product.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 4.
CN202111274708.2A 2021-10-29 2021-10-29 Method and device for marketing large-volume deposit receipt product Pending CN113988934A (en)

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