A method for generating personalized marketing strategies based on customer portraits

Abstract

The present invention relates to the technical field of generating personalized marketing strategies for customer portraits, and discloses a method for generating personalized marketing strategies based on customer portraits. By obtaining the age, gender and loan amount information of all historical credit users, the users are grouped according to age groups, from 18 to 36 years old and above, and refined into multiple age groups. The loan amounts of men and women in each age group are obtained respectively, and divided, and the age group, gender and loan amount are associated and analyzed to form multiple historical loan association groups. This method of grouping and association analysis can not only help identify the consumption behavior and credit demand characteristics of different age groups, but also capture the needs and behavioral differences of users of different age groups at different stages of life. Through these data, enterprises can build more targeted customer groups, thereby optimizing customer portraits and personalized marketing strategies, and improving the accuracy and effectiveness of marketing.

Description

Technical Field

[0001] The present invention relates to the technical field of generating personalized marketing strategies based on customer portraits, and in particular to a method for generating personalized marketing strategies based on customer portraits. Background Art

[0002] With the development of information technology and the maturity of big data analysis technology, personalized marketing strategies based on customer portraits have been widely used in the financial field. Customer portraits are a comprehensive description of users constructed by analyzing and mining historical behavior data, demographic information, consumption habits, preferences, and other relevant information. This description can help companies better understand user needs and develop more accurate marketing strategies, thereby improving the effectiveness of marketing activities and customer satisfaction.

[0003] In the financial field, especially in the credit business, basic information such as the customer's age, gender, loan amount, etc. is important data for analyzing customer behavior and needs. Through the analysis of this data, the differences in credit needs and consumption habits among customers of different age groups and genders can be identified. For example, young users may be more inclined to apply for short-term small loans, while older users may be more concerned with long-term and stable credit products. Gender differences may also affect users' choice of loan products. For example, female users may be more inclined to choose products with greater repayment flexibility. Therefore, through the detailed analysis of this information, it can help companies better formulate products and services that meet customer needs. This case intends to propose a method for generating personalized marketing strategies based on customer portraits to push different loan information on different platforms for different age groups and genders. Summary of the invention

[0004] The present invention provides a method for generating personalized marketing strategies based on customer portraits, which helps solve the problems mentioned in the above background technology.

[0005] The present invention provides the following technical solution: a method for generating a personalized marketing strategy based on customer portraits, comprising:

[0006] Get all credit user information in history;

[0007] The credit user information includes: age, gender and loan amount;

[0008] The credit users are grouped according to their age, specifically:

[0009] 18 years old is the first age group;

[0010] 19 to 23 years old is the second age group;

[0011] 24 to 28 years old is the third age group;

[0012] 29 to 35 years old is the fourth age group;

[0013] Starting from the age of 36, each additional 10 years is divided into an age group, which is recorded as the fifth age group until the Nth age group;

[0014] Obtain the loan amounts of men and women in each age group separately and divide the loan amounts;

[0015] Associating the gender corresponding to each age group and the loan amount corresponding to each gender to form multiple historical loan association groups;

[0016] Build a customer profile.

[0017] Optionally, the division of the loan amount specifically includes:

[0018] Get the loan amount for each age group and gender;

[0019] Arrange the obtained loan amounts in ascending order to form a loan amount range;

[0020] Set the unit for dividing the loan amount range;

[0021] Divide the loan amount range into multiple loan amount sub-ranges according to the loan amount range division unit;

[0022] Count the number of borrowers in each loan amount sub-range respectively, and record the statistical result as the total number of borrowers in the loan amount sub-range;

[0023] Set the total number of loan borrowers threshold for the loan amount sub-range;

[0024] Determine whether the total number of loanees in the loan amount sub-interval > the total number of loanees in the loan amount sub-interval threshold condition is met;

[0025] Traverse all loan amount sub-intervals, and when the loan amount sub-interval meets the conditions, record the loan amount sub-interval corresponding to the total number of loan borrowers in the loan amount sub-interval as the true sub-interval of the loan amount interval.

[0026] Optionally, the building of the customer portrait specifically includes:

[0027] Collect information submitted by customers when handling business;

[0028] The submitted information includes: age, gender, education level, place of residence, application channel and occupation type;

[0029] Analyze customer behavior data and organize the collected data;

[0030] The arrangement includes: removing noise and erroneous data, extracting key features from the data, and generating customer tags based on the extracted features;

[0031] Obtain customer preferences;

[0032] Understand customer needs and pain points;

[0033] The needs and pain points mentioned include: the level of loan interest rates, repayment flexibility and value-added services;

[0034] Combine customer information, behavior data, customer preferences, customer needs and pain points to form a customer profile;

[0035] Divide customers into different markets based on the different characteristics of their profiles, and recommend different financial products to different customer groups;

[0036] Develop personalized content and selected channels to execute targeted marketing campaigns;

[0037] Track the performance of marketing campaigns;

[0038] The marketing performance is specifically: customer response rate, conversion rate and feedback;

[0039] Adjust customer profiles based on data analysis results.

[0040] Optionally, dividing customers into different markets based on different features of customer portraits and recommending different financial products to different customer groups specifically includes:

[0041] Record all the customers who are placed as target customers;

[0042] Get the age and gender of target customers;

[0043] Get the short video types that different genders like in each age group;

[0044] Count the short video types and obtain the number of target customers in each type;

[0045] Arrange the number of target customers in descending order and obtain the top ten short video types;

[0046] Add the obtained short video type to the collection of the corresponding age group and gender.

[0047] Optionally, the types of short videos preferred by different genders in each age group specifically include:

[0048] Categorize different short videos;

[0049] Get the viewing time of different types of short videos by different genders in each age group;

[0050] The viewing time was compared, and the short video type with the longest viewing time was recorded as the short video type preferred by different genders in each age group.

[0051] Optionally, the personalized content and selected channels are formulated to execute targeted marketing activities, including:

[0052] Get target customers who have installment consumption options, and calculate the average of their most recent installment consumption records, which is recorded as the consumption value of the target customers.

[0053] Get the age and gender of the push customer;

[0054] Get the age group of the push customers;

[0055] Get the type of short videos that are pushed to customers based on their age group and gender;

[0056] Obtain the search keywords of push customers on the short video platform, and use keyword analysis strategies to obtain marketing products and prices corresponding to the keywords;

[0057] Calculate the difference between the target customer's consumption value and the price of the marketing product. The difference between the price of the marketing product and the target customer's consumption value = marketing product price - target customer's consumption value.

[0058] Optionally, the personalized content and selected channels are formulated to execute targeted marketing activities, including:

[0059] If the difference between the target customer's consumption value and the price of the marketing product is greater than the target customer's consumption value × 10%, the marketing product price is obtained in the true sub-interval of the push user's loan limit interval;

[0060] If the true sub-interval of the loan amount interval is obtained, the loan amount information consistent with the marketing product price is pushed in the short video type pushed to the user;

[0061] If the true sub-interval of the loan limit interval is not obtained, obtain the minimum value of each true sub-interval of the loan limit interval of the pushed user;

[0062] The differences between all minimum values ​​and the marketing commodity price are compared, and the loan amount interval true sub-interval corresponding to the minimum value of the loan amount interval true sub-interval with the minimum difference with the marketing commodity price is used as the pushed loan amount information.

[0063] Optionally, the personalized content and selected channels are formulated to execute targeted marketing activities, including:

[0064] Obtain the search keywords of target customers on media platforms;

[0065] Split and analyze the keywords, obtain the products corresponding to the analysis results, and record them as marketing products;

[0066] Obtain all prices of marketing products to form a marketing product price set;

[0067] Get the number of consumers and their ages in each element of the marketing product price collection;

[0068] The number of consumers is counted with age as the first factor;

[0069] Get the number of consumers of different ages at different prices for marketing products;

[0070] Obtain the highest price among consumers of different ages at different prices for marketing products and record it as the standard price;

[0071] Get the corresponding ages in different age groups;

[0072] Get the standard price for each age group, compare the number of consumers in the standard price, and record the standard price with the largest number of consumers as the general price of the marketing product in the corresponding age group.

[0073] The present invention has the following beneficial effects:

[0074] 1. Grouping credit users by age group can help identify the consumption behavior and credit demand characteristics of different age groups. Segmenting the age groups into 18, 19-23, 24-28, 29-35, and 36 and above can help capture the needs and behavioral differences of users at different stages of life. Correlation analysis of age group, gender, and loan amount can be performed to form multiple historical loan correlation groups, which will help build targeted customer groups.

[0075] 2. By setting the division unit of the loan amount range, you can group the loan data more finely according to actual needs, thereby enhancing the granularity of the analysis. By subdividing the loan amount range into multiple loan amount sub-ranges, you can more carefully analyze the distribution of customers with different loan amounts. By counting the number of loan applicants in each loan amount sub-range, you can clarify the concentration of customers in each sub-range. Setting the total number of loan applicants threshold for the loan amount sub-range is to determine which sub-ranges have sufficient market size and deserve special attention. Traversing and identifying the loan amount sub-ranges that meet the conditions and recording them as true sub-ranges of the loan amount range will help companies accurately lock in core market ranges.

[0076] 3. Collecting information submitted by customers when handling business, such as age, gender, education level, place of residence, application channel and occupation type, helps to fully understand the basic background and socioeconomic status of customers. Removing noise and erroneous data ensures the accuracy of data analysis and makes the generated customer labels more reliable. By obtaining customer preferences, companies can have a deeper understanding of customer interests and needs, thereby providing customers with more personalized products and services. Obtaining customer needs and pain points, such as the level of loan interest rates, repayment flexibility and value-added services, can help companies more accurately identify customers' core concerns. By integrating customers' basic information, behavioral data, preferences, needs and pain points, a comprehensive customer portrait is formed, which enables companies to fully understand customers' needs and behavior patterns. According to the different characteristics of customer portraits, customers are divided into different markets, and companies can achieve more accurate market segmentation. By formulating personalized content and selecting appropriate channels, companies can better attract and retain target customers in marketing activities. Tracking the performance of marketing activities, such as customer response rates, conversion rates and feedback, can help companies evaluate the effectiveness of marketing strategies in a timely manner.

[0077] 4. By obtaining the short video types that customers of different genders in each age group like, companies can gain a deeper understanding of customers' interests and content preferences. By counting the short video types and obtaining the number of customers in each type, companies can quantify the popularity of different content types, arrange the number of customers in order from large to small, and obtain the top ten short video types, which helps companies focus on the most popular content. Adding the obtained short video types to the collections of corresponding age groups and genders can help companies refine the content preferences of customer groups and achieve more accurate market segmentation.

[0078] 5. Obtaining the target customer's most recent ten consumption records and calculating the average value can help accurately grasp the customer's consumption capacity and consumption behavior. By obtaining the search keywords of the push customer on the short video platform and using the keyword analysis strategy, the company can accurately understand the customer's current interests and purchasing intentions. By calculating the price difference between the target customer's consumption value and the marketing product, the company can evaluate whether the recommended product meets the customer's payment ability. When it is found that the price of the marketing product is significantly different from the customer's consumption value, by obtaining the loan amount range true sub-interval that meets the price range, the customer can be provided with financial support options. Adding loan amount information consistent with the marketing product price to the short video type pushed to the user can make the loan option more targeted and attractive. When a completely matching loan amount range true sub-interval cannot be found, the minimum value of all loan amount ranges is obtained to ensure that the company can provide the minimum loan amount acceptable to the customer. By comparing the difference between all minimum values ​​and the marketing product price and selecting the loan amount range true sub-interval with the smallest difference, the company can provide the customer with the most suitable loan option. This precise matching strategy ensures that customers can obtain loan products that are closest to their consumption capacity and increases the possibility of purchasing goods.

[0079] 6. Obtaining the target customers' search keywords on the media platform can help companies accurately locate customers' interests and needs. Obtaining all prices of marketing products and forming a price set can help companies fully grasp the price ranges of different products on the market. By obtaining the number of consumers and age corresponding to each element in the marketing product price set, companies can refine the consumption behavior and habits of customer groups. Counting the number of consumers with age as the first factor can help companies identify the consumption trends and preferences of customers of different age groups. Obtaining the number of consumers of marketing products at different prices by customers of different age groups can help companies identify the price sensitivity and acceptance of each age group. By identifying the price with the largest number of consumers in each age group and recording it as the standard price, companies can determine the price preference of customers in that age group. By comparing the standard prices of each age group and determining the standard price with the largest number of consumers as the general price, companies can identify the most popular price range in a specific age group. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 A schematic diagram of the customer portrait generation process of the present invention. DETAILED DESCRIPTION

[0081] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0082] In an embodiment, a method for generating a personalized marketing strategy based on a customer portrait comprises:

[0083] Get all credit user information in history;

[0084] The credit user information includes: age, gender and loan amount;

[0085] The credit users are grouped according to their age, specifically:

[0086] 18 years old is the first age group;

[0087] 19 to 23 years old is the second age group;

[0088] 24 to 28 years old is the third age group;

[0089] 29 to 35 years old is the fourth age group;

[0090] Starting from the age of 36, each additional 10 years is divided into an age group, which is recorded as the fifth age group until the Nth age group;

[0091] Obtain the loan amounts of men and women in each age group separately and divide the loan amounts;

[0092] Associating the gender corresponding to each age group and the loan amount corresponding to each gender to form multiple historical loan association groups;

[0093] Build a customer profile.

[0094] Grouping credit users by age group can help identify the consumption behavior and credit demand characteristics of different age groups. Segmenting the age groups into 18, 19-23, 24-28, 29-35, and 36 and above can help capture the differences in needs and behaviors of users at different stages of life. Correlation analysis of age groups, genders, and loan amounts can be conducted to form multiple historical loan correlation groups, which will help build targeted customer groups.

[0095] The division of loan amount specifically includes:

[0096] Get the loan amount for each age group and gender;

[0097] Arrange the obtained loan amounts in ascending order to form a loan amount range;

[0098] Set the unit for dividing the loan amount range;

[0099] Divide the loan amount range into multiple loan amount sub-ranges according to the loan amount range division unit;

[0100] Count the number of borrowers in each loan amount sub-range respectively, and record the statistical result as the total number of borrowers in the loan amount sub-range;

[0101] Set a total number of loan applicants threshold for a loan amount sub-interval, where the total number of loan applicants threshold for a loan amount sub-interval represents a limit judgment on the number of people in a sub-interval. When the number of people is greater than the total number of loan applicants threshold for a loan amount sub-interval, it indicates that this sub-interval has push significance;

[0102] Determine whether the total number of loanees in the loan amount sub-interval > the total number of loanees in the loan amount sub-interval threshold condition is met;

[0103] Traverse all loan amount sub-intervals, and when the loan amount sub-interval meets the conditions, record the loan amount sub-interval corresponding to the total number of loan borrowers in the loan amount sub-interval as the true sub-interval of the loan amount interval.

[0104] By setting the division unit of the loan amount range, the loan data can be grouped more finely according to actual needs, thereby enhancing the granularity of the analysis. By subdividing the loan amount range into multiple loan amount sub-ranges, the distribution of customers with different loan amounts can be analyzed in more detail. By counting the number of loan applicants in each loan amount sub-range, the concentration of customers in each sub-range can be clarified. The total number of loan applicants in the loan amount sub-range is set to determine which sub-ranges have sufficient market size and deserve special attention. Traversing and identifying the loan amount sub-ranges that meet the conditions and recording them as true sub-ranges of the loan amount range will help companies accurately lock in core market ranges.

[0105] Reference Figure 1 , the construction of customer portraits specifically includes:

[0106] Collect information submitted by customers when handling business;

[0107] The submitted information includes: age and gender, as well as education level, place of residence, application channel and occupation type;

[0108] Analyze customer behavior data and organize the collected data;

[0109] The arrangement includes: removing noise and erroneous data, extracting key features from the data, and generating customer tags based on the extracted features;

[0110] Obtain customer preferences;

[0111] Understand customer needs and pain points;

[0112] The needs and pain points mentioned include: the level of loan interest rates, repayment flexibility and value-added services;

[0113] Combine customer information, behavior data, customer preferences, customer needs and pain points to form a customer profile;

[0114] Divide customers into different markets based on the different characteristics of their profiles, and recommend different financial products to different customer groups;

[0115] Develop personalized content and selected channels to execute targeted marketing campaigns;

[0116] Track the performance of marketing campaigns;

[0117] The marketing performance is specifically: customer response rate, conversion rate and feedback;

[0118] Adjust customer profiles based on data analysis results.

[0119] Gathering information submitted by customers when handling business, such as age, gender, education level, place of residence, application channel and occupation type, helps to fully understand the basic background and socioeconomic status of customers. Removing noise and erroneous data ensures the accuracy of data analysis and makes the generated customer labels more reliable. By obtaining customer preferences, companies can have a deeper understanding of customer interests and needs, thereby providing customers with more personalized products and services. Obtaining customer needs and pain points, such as the level of loan interest rates, repayment flexibility and value-added services, can help companies more accurately identify customers' core concerns. By integrating customers' basic information, behavioral data, preferences, needs and pain points, a comprehensive customer portrait is formed, which enables companies to fully understand customers' needs and behavior patterns. According to the different characteristics of customer portraits, customers can be divided into different markets, and companies can achieve more accurate market segmentation. By formulating personalized content and selecting appropriate channels, companies can better attract and retain target customers in marketing activities. Tracking the performance of marketing activities, such as customer response rates, conversion rates and feedback, can help companies evaluate the effectiveness of marketing strategies in a timely manner.

[0120] The customer profiles are divided into different markets based on different characteristics, and different financial products are recommended to different customer groups, including:

[0121] Record all the customers who are placed as target customers;

[0122] Get the age and gender of target customers;

[0123] Get the short video types that different genders like in each age group;

[0124] Count the short video types and obtain the number of target customers in each type;

[0125] Arrange the number of target customers in descending order and obtain the top ten short video types;

[0126] Add the obtained short video types to the collection of the corresponding age group and gender. By obtaining the short video types that customers of different genders in each age group like, companies can gain a deeper understanding of customers' interests and content preferences. By counting the short video types and obtaining the number of customers in each type, companies can quantify the popularity of different content types, sort the number of customers from large to small, and obtain the top ten short video types, which helps companies focus on the most popular content. Adding the obtained short video types to the collection of the corresponding age group and gender can help companies refine the content preferences of customer groups, thereby achieving more accurate market segmentation.

[0127] The types of short videos preferred by different genders in each age group specifically include:

[0128] Categorize different short videos;

[0129] Get the viewing time of different types of short videos by different genders in each age group;

[0130] The viewing time was compared, and the short video type with the longest viewing time was recorded as the short video type preferred by different genders in each age group.

[0131] The above mentioned personalised content and selected channels are used to execute targeted marketing activities, including:

[0132] Get target customers who have installment consumption options, and calculate the average of their most recent installment consumption records, which is recorded as the consumption value of the target customers.

[0133] Get the age and gender of the push customer;

[0134] Get the age group of the push customers;

[0135] Get the type of short videos that are pushed to customers based on their age group and gender;

[0136] Obtain the search keywords of push customers on the short video platform, and use keyword analysis strategies to obtain marketing products and prices corresponding to the keywords;

[0137] Calculate the difference between the target customer's consumption value and the price of the marketing product. The difference between the price of the marketing product and the target customer's consumption value = marketing product price - target customer's consumption value.

[0138] The above mentioned personalised content and selected channels are used to execute targeted marketing activities, including:

[0139] If the difference between the target customer's consumption value and the price of the marketing product is greater than the target customer's consumption value × 10%, the marketing product price is obtained in the true sub-interval of the push user's loan limit interval;

[0140] If the true sub-interval of the loan amount interval is obtained, the loan amount information consistent with the marketing product price is pushed in the short video type pushed to the user;

[0141] If the true sub-interval of the loan limit interval is not obtained, obtain the minimum value of each true sub-interval of the loan limit interval of the pushed user;

[0142] The differences between all minimum values ​​and the marketing commodity price are compared, and the loan amount interval true sub-interval corresponding to the minimum value of the loan amount interval true sub-interval with the minimum difference with the marketing commodity price is used as the pushed loan amount information.

[0143] Obtaining the target customer's most recent ten consumption records and calculating the average value can help accurately grasp the customer's consumption capacity and consumption behavior. By obtaining the search keywords of the push customer on the short video platform and using the keyword analysis strategy, the company can accurately understand the customer's current interests and purchasing intentions. By calculating the price difference between the target customer's consumption value and the marketing product, the company can evaluate whether the recommended product meets the customer's payment ability. When it is found that the price of the marketing product is significantly different from the customer's consumption value, by obtaining the loan amount range true sub-interval that meets the price range, the customer can be provided with financial support options. Adding loan amount information consistent with the marketing product price to the short video type pushed to the user can make the loan option more targeted and attractive. When a completely matching loan amount range true sub-interval cannot be found, the minimum value of all loan amount ranges is obtained to ensure that the company can provide the minimum loan amount acceptable to the customer. By comparing the difference between all minimum values ​​and the marketing product price and selecting the loan amount range true sub-interval with the smallest difference, the company can provide the customer with the most suitable loan option. This precise matching strategy ensures that customers can obtain loan products that are closest to their consumption capacity and increases the possibility of purchasing goods.

[0144] The above mentioned personalised content and selected channels are used to execute targeted marketing activities, including:

[0145] Obtain the search keywords of target customers on media platforms;

[0146] Split and analyze the keywords, obtain the products corresponding to the analysis results, and record them as marketing products;

[0147] Obtain all prices of marketing products to form a marketing product price set;

[0148] Get the number of consumers and their ages in each element of the marketing product price collection;

[0149] The number of consumers is counted with age as the first factor;

[0150] Get the number of consumers of different ages at different prices for marketing products;

[0151] Obtain the highest price among consumers of different ages at different prices for marketing products and record it as the standard price;

[0152] Get the corresponding ages in different age groups;

[0153] Get the standard price for each age group, compare the number of consumers in the standard price, and record the standard price with the largest number of consumers as the general price of the marketing product in the corresponding age group.

[0154] Obtaining the target customers' search keywords on the media platform can help companies accurately locate customers' interests and needs. Obtaining all prices of marketing products and forming a price set can help companies fully grasp the price ranges of different products on the market. By obtaining the number of consumers and age corresponding to each element in the marketing product price set, companies can refine the consumption behavior and habits of customer groups. Counting the number of consumers with age as the first factor can help companies identify the consumption trends and preferences of customers of different age groups. Obtaining the number of consumers of marketing products at different prices by customers of different age groups can help companies identify the price sensitivity and acceptance of each age group. By identifying the price with the largest number of consumers in each age group and recording it as the standard price, companies can determine the price preference of customers in that age group. By comparing the standard prices of each age group and determining the standard price with the largest number of consumers as the general price, companies can identify the most popular price range in a specific age group.

[0155] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0156] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for generating personalized marketing strategies based on customer portraits, characterized in that: include: Get all credit user information in history; The credit user information includes: age, gender and loan amount; The credit users are grouped according to their age, specifically: 18 years old is the first age group; 19 to 23 years old is the second age group; 24 to 28 years old is the third age group; 29-35 years old is the fourth age group; Starting from the age of 36, each additional 10 years is divided into an age group, which is recorded as the fifth age group until the Nth age group; Obtain the loan amounts of men and women in each age group separately and divide the loan amounts; The division of loan amount specifically includes: Get the loan amount for each age group and gender; Arrange the obtained loan amounts in ascending order to form a loan amount range; Set the unit for dividing the loan amount range; Divide the loan amount range into multiple loan amount sub-ranges according to the loan amount range division unit; Count the number of borrowers in each loan amount sub-range respectively, and record the statistical result as the total number of borrowers in the loan amount sub-range; Set the total number of loan borrowers threshold for the loan amount sub-range; Determine whether the total number of loanees in the loan amount sub-interval > the total number of loanees in the loan amount sub-interval threshold condition is met; Traverse all loan amount sub-intervals, and when a loan amount sub-interval meets the conditions, record the loan amount sub-interval corresponding to the total number of loanees in the loan amount sub-interval as the true sub-interval of the loan amount interval; The gender corresponding to each age group and the loan amount corresponding to each gender are associated to form multiple historical loan association groups to build customer portraits; Divide customers into different markets based on the different characteristics of customer portraits, and recommend different financial products to different customer groups. At the same time, develop personalized content and selected channels to implement targeted marketing activities; The customer profiles are divided into different markets based on different characteristics, and different financial products are recommended to different customer groups, including: Record all the customers who are placed as target customers; Get the age and gender of target customers; Get the short video types that different genders like in each age group; Count the short video types and obtain the number of target customers in each type; Arrange the number of target customers in descending order and obtain the top ten short video types; Add the obtained short video type to the collection of the corresponding age group and gender; The above mentioned personalised content and selected channels are used to execute targeted marketing activities, including: Get target customers who have installment consumption options, and calculate the average of their most recent installment consumption records, which is recorded as the consumption value of the target customers. Get the age and gender of the push customer; Get the age group of the push customers; Get the type of short videos that are pushed to customers based on their age group and gender; Obtain the search keywords of push customers on the short video platform, and use keyword analysis strategies to obtain marketing products and prices corresponding to the keywords; Calculate the difference between the target customer's consumption value and the price of the marketing product. The difference between the price of the marketing product and the target customer's consumption value = the marketing product price - the target customer's consumption value. If the difference between the target customer's consumption value and the price of the marketing product is greater than the target customer's consumption value × 10%, the marketing product price is obtained in the true sub-range of the push user's loan limit range; If the true sub-interval of the loan amount interval is obtained, the loan amount information consistent with the marketing product price is pushed in the short video type pushed to the user; If the true sub-interval of the loan limit interval is not obtained, obtain the minimum value of each true sub-interval of the loan limit interval of the pushed user; The differences between all minimum values ​​and the marketing commodity price are compared, and the loan amount interval true sub-interval corresponding to the minimum value of the loan amount interval true sub-interval with the minimum difference with the marketing commodity price is used as the pushed loan amount information.

2. The method for generating personalized marketing strategies based on customer portraits according to claim 1, characterized in that: The construction of the customer portrait specifically includes: Collect information submitted by customers when handling business; Said submitted information includes: age and gender; Analyze customer behavior data and organize the collected data; The said arranging of the collected data includes: removing noise and erroneous data, extracting key features from the data, and generating customer tags based on the extracted features; Obtain customer preferences; Understand customer needs and pain points; The needs and pain points mentioned include: the level of loan interest rates, repayment flexibility and value-added services; Combine customer information, behavior data, customer preferences, customer needs and pain points to form a customer profile; Divide customers into different markets based on the different characteristics of their profiles, and recommend different financial products to different customer groups; Develop personalized content and selected channels to execute targeted marketing campaigns; Track the performance of marketing campaigns; The performance of the marketing activities is specifically: customer response rate, conversion rate and feedback; Adjust customer profiles based on data analysis results.

3. The method for generating personalized marketing strategies based on customer portraits according to claim 1, characterized in that: The types of short videos preferred by different genders in each age group specifically include: Categorize different short videos; Get the viewing time of different types of short videos by different genders in each age group; The viewing time was compared, and the short video type with the longest viewing time was recorded as the short video type preferred by different genders in each age group.

4. The method for generating personalized marketing strategies based on customer portraits according to claim 3, characterized in that: The above mentioned personalised content and selected channels are used to execute targeted marketing activities, including: Obtain the search keywords of target customers on media platforms; Split and analyze the keywords, obtain the products corresponding to the analysis results, and record them as marketing products; Obtain all prices of marketing products to form a marketing product price set; Get the number of consumers and their ages in each element of the marketing product price collection; The number of consumers is counted with age as the first factor; Get the number of consumers of different ages at different prices for marketing products; Obtain the highest price among consumers of different ages at different prices for marketing products and record it as the standard price; Get the corresponding ages in different age groups; Obtain the standard price for each age group, compare the number of consumers in the standard prices, and record the standard price with the largest number of consumers as the marketing price of the marketing product in the corresponding age group.

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