TWI809649B - Two-dimensional Exploration Method and System of Customer Value - Google Patents

Abstract

The invention relates to a two-dimensional exploration method and system for customer value. The customer value two-dimensional exploration method is executed by the processing device of the customer value two-dimensional exploration system, and includes the following steps: reading multiple fixed deposit data, multiple fixed deposit historical data and their total assets of multiple customers from the database data; calculate the total assets after adjustment; retrospectively calculate the actual storage months of each fixed deposit data; calculate the idle amount of certain deposit funds for each fixed deposit data; generate the total idle amount of certain deposit funds; according to the adjusted amount of all customers The total assets and the total idle amount of fixed deposit funds are divided into two-dimensional groups to generate a one-dimensional and two-dimensional group list. Because the two-dimensional grouping list can accurately analyze the total idle amount of fixed deposit funds of customers, as well as the possible relationship between supply and implicit demand with other total assets. From the perspective of customer group segmentation, it provides customers with financial products that may meet their hidden needs, guides customers to activate their idle funds, increases customers' interest in financial products, and improves the efficiency of marketing financial products.

Description

Two-dimensional Exploration Method and System of Customer Value

An exploration method and system thereof, especially a two-dimensional exploration method and system for customer value.

In the early product-oriented marketing model, when the financial industry promoted financial products to customers, it directly listed the customer list, and then contacted the customers one by one to carry out marketing for each customer. However, this method of marketing financial products is usually a needle in a haystack, and it is difficult to find suitable customers, resulting in low marketing efficiency. Today, the financial industry usually first explores the needs of each customer based on the attributes of each customer, and sells suitable financial products for specific customer groups, thereby improving the efficiency of marketing financial products.

However, the current method of exploring customers has not explored the asset management habits of customers themselves, resulting in poor results in improving the efficiency of selling financial products.

The present invention provides a method and system for two-dimensional exploration of customer value. The two-dimensional exploration system for customer value includes a database, a processing device and a display device, and the processing device is connected to the database and the display device.

The processing device reads multiple fixed deposit data, multiple fixed deposit historical data and total asset data of multiple customers from the database, and for each customer, according to all fixed deposit amounts of all fixed deposit data and the For the total asset amount of the total asset data, calculate an adjusted total asset excluding the fixed deposit amount. The processing device is further aimed at each customer, according to the certain deposit period in each fixed deposit data and the fixed deposit For the amount of deposit, the actual number of storage months for each fixed deposit data is retroactively calculated from the multiple fixed deposit historical data. And the processing device also calculates the idle amount of certain deposit funds of each fixed deposit data for each customer according to the fixed deposit amount in each fixed deposit data and the actual number of months of deposit. Finally, for each customer, the processing device sums up all the idle amount of fixed deposit funds of all its fixed deposit materials to generate the total idle amount of fixed deposit funds, and calculates the total idle amount of fixed deposit funds according to the adjusted total assets of all customers and the total idle amount of fixed deposit funds The two-dimensional grouping is carried out after sorting respectively to generate a two-dimensional grouping list, and then the two-dimensional grouping list is sent to the display device, and the two-dimensional grouping list is displayed by the display device.

The customer value two-dimensional exploration method is executed by the processing device of the customer value two-dimensional exploration system. And the customer value two-dimensional exploration method includes the following steps: read multiple fixed deposit data, multiple fixed deposit historical data and their total asset data of multiple customers from the database; All fixed deposit amounts and the total asset data of the deposit data, calculate an adjusted total asset excluding the fixed deposit amount; for each customer, according to the certain deposit period and the fixed deposit amount in each fixed deposit data, in Retroactively calculate the actual storage months of each fixed deposit data from the multiple fixed deposit historical data; for each customer, calculate each time deposit according to the fixed deposit amount and the actual storage months The idle amount of certain deposit funds of fixed deposit data; for each customer, sum up all the idle amount of fixed deposit funds of all its fixed deposit data to generate the total idle amount of fixed deposit funds; according to the adjusted total assets of all customers and the fixed deposit The total idle amount of deposit funds is sorted and then grouped into two-dimensional groups to generate a one-dimensional grouping list.

Since the two-dimensional grouping list is generated by two-dimensional grouping based on the adjusted total assets and the total idle amount of the time deposit funds, the results of the two-dimensional grouping list can accurately analyze the customer's time deposit The total idle amount of funds, and the possible relationship between supply and implicit demand with other total assets. From the perspective of customer group segmentation, it provides customers with financial products that may meet their hidden needs, guides customers to activate their idle funds, increases customers' interest in financial products, and improves the efficiency of marketing financial products.

In addition, since the total idle amount of fixed deposit funds is calculated based on the fixed deposit amount of each fixed deposit data and the actual number of months of deposit, the total idle time of the fixed deposit funds further considers the relationship between idle funds and time. This can more accurately provide the financial products that customers want, so as to achieve the purpose of precise marketing.

10: Database

20: Processing device

30: Display device

S201~S206: steps

S2031~S2032: Steps

Fig. 1 is a block diagram of a customer value two-dimensional exploration system of the present invention.

FIG. 2 is a flowchart of a two-dimensional exploration method for customer value in the present invention.

Fig. 3 is a schematic diagram of the two-dimensional clustering results of the present invention.

Fig. 4 is another flow chart of the two-dimensional customer value exploration method of the present invention.

Please refer to FIG. 1 , the present invention provides a two-dimensional customer value exploration method and its system. The customer value two-dimensional exploration system includes a database 10 , a processing device 20 and a display device 30 . And the processing device 20 is communicatively connected to the database 10 and the display device 30 .

Please also refer to FIG. 2 that the processing device 20 executes the two-dimensional customer value exploration method, and the customer value two-dimensional exploration method includes the following steps:

Step S201: read multiple fixed deposit data, multiple fixed deposit historical data and total asset data of multiple customers from the database 10 . In this embodiment, the fixed deposit data and the fixed deposit historical data are described using Taiwan dollar fixed deposit data as a preferred embodiment, but not limited thereto.

Step S202: For each customer, calculate an adjusted total asset according to all the fixed deposit amounts of all the fixed deposit data and the total asset amount of the total asset data. In this embodiment, the processing device 20 first calculates the sum of all fixed deposit amounts of all fixed deposit materials, that is, the total fixed deposit amount, and then further subtracts the total fixed deposit amount from the total asset amount to obtain the Adjusted total assets.

Step S203: For each customer, according to the fixed deposit period and the fixed deposit amount in each fixed deposit data, retroactively calculate the actual storage months of each fixed deposit data in the multiple fixed deposit historical data. In this embodiment, since each fixed deposit will be settled (ineffective) when the fixed deposit period expires, the number of months of each fixed deposit is its fixed deposit period. But if the customer transfers the expired fixed deposit to the next fixed deposit again in a short period of time, and when the fixed deposit period of the next fixed deposit is still the same as the previous time, the processing device 20 will The fixed deposit is regarded as the same fixed deposit data, and the number of fixed deposit periods of the expired fixed deposit and the fixed deposit period of the next fixed deposit are summed up as the actual storage month of the fixed deposit data number.

Step S204: For each customer, calculate the idle amount of fixed deposit funds for each fixed deposit data according to the fixed deposit amount in each fixed deposit data and the actual number of months of deposit. In this embodiment, the processing device 20 multiplies the fixed deposit amount in each fixed deposit data by the actual number of months of deposit and then divides it by 12 to calculate the idle amount of the fixed deposit funds. Since the idle amount of fixed deposit funds is calculated on an annual basis, the actual number of deposit months needs to be converted into annual units by dividing by 12.

Step S205: For each customer, add up all the idle amount of fixed deposit funds of all its fixed deposit materials to generate the total idle amount of fixed deposit funds. Since each customer may have multiple time deposit data, and the amount, period and actual storage months of each time deposit data may not be the same, so all time deposit data for each customer need to be calculated separately The respective idle amount of fixed deposit funds. For each customer, a parameter is needed to refer to the idle degree of its fixed deposit funds, so the processing device 20 will then add up all the idle amounts of fixed deposit funds of all fixed deposit materials of the same customer to obtain the corresponding The total idle amount of fixed deposit funds of each customer is used to represent the idle degree of its fixed deposit funds.

Step S206: Carry out two-dimensional grouping according to the adjusted total assets and the total idle amount of fixed deposit funds of all customers, and generate a two-dimensional grouping list. In the present embodiment, the processing device 20 uses k-means clustering to sort the adjusted total assets and the total idle amount of fixed deposit funds of all customers from small to large respectively and perform a two-dimensional grouping, to define a grouping threshold and generate the two-dimensional grouping list.

For example, please refer to FIG. 3 , where each point represents a two-dimensional grouping position of a customer. And according to the position of the two-dimensional grouping, it is divided into multiple groups. For example, group A is aimed at groups with low total idle amount of fixed deposit funds and high adjusted total assets, and dots represent each customer in this group Two-dimensional grouping position. Similarly, group B, group C, group D, and group E all represent different groups, and are represented by points of different shapes. For different groups of customers, lists can be generated separately, such as the customer list of group A, the customer list of group B, etc., so as to complete the two-dimensional group list.

In addition, after the processing device 20 generates the two-dimensional group list, the processing device 20 further transmits the two-dimensional group list to the display device 30, and the display device 30 displays the two-dimensional group list. In this way, the banking industry can use the two-dimensional grouping list to formulate marketing plans to promote and sell financial products suitable for customers of this type of grouping, thereby accurately providing the financial products that customers want to achieve the purpose of precise marketing .

Furthermore, a good marketing model is to provide competitive products to customers who are interested in the product at the right time and through channels. Therefore, the focus of the present invention is to extend the time axis, observe customers and the products they choose, and dig out meaningful information that may be hidden under their representative transaction behaviors, thereby increasing the probability of successful co-sales.

Generally speaking, customers who have a little strength and are willing to keep most of their assets in the bank will be the target customer group for important promotion and marketing in the financial industry. From the perspective of customer group segmentation, the present invention provides customers with financial products that may meet their hidden needs, guides customers to activate their idle funds, increases customers' interest in financial products, improves the efficiency of marketing financial products, and has the opportunity to help improve corporate intrinsic value.

For any product selected by the customer, in addition to confirming the current position of the product, it is also necessary to consider the actual elapsed time of the customer owning the product. For example, if the time axis is extended to observe that the product has been traded twice, that is, after the first purchase, when the original duration expires, the product will be recorded first to terminate it. If the customer purchases the same product again in a short period of time 2nd. Therefore, from a customer perspective, That is, the time point of the first purchase of the product can be regarded as the time point of real capital investment, and then the real elapsed time of the product can be calculated.

Since fixed deposit is a kind of wealth management product provided by the banking industry to customers, and many times customers will use fixed deposit as a temporary storage area for funds, so the present invention particularly focuses on the commodity of fixed deposit items. And for the banking industry, if the customer has no other investment projects and only has fixed deposit commodities, the invention can explore the asset investment ratio in the minds of this type of customer, and can correspondingly produce a group list of this type of customer for the banking industry For reference, use this to formulate exclusive marketing plans to promote products that meet the asset investment ratio in the minds of this type of customers, so as to improve the efficiency of selling financial products.

For example, please refer to Table 1. If customer A purchases 800,000 yuan of financial products at the bank, there are 5 fixed deposits, and the fixed deposit amount of each fixed deposit is 100,000 yuan. That is to say, all fixed deposits The total deposit amount is 500,000 yuan. The term of the first fixed deposit is 12 months; the term of the second fixed deposit is 18 months; the term of the third fixed deposit is 24 months; The term of the fixed deposit is 30 months; the term of the fifth fixed deposit is 36 months.

When executing step S202, the processing device 20 first calculates the total fixed deposit amount of customer A, that is, 5×10=500,000 yuan, and further calculates the adjusted total assets of customer A, that is, 80-50=30 ten thousand yuan. In this way, the adjusted total assets of customer A can be obtained as 300,000 yuan.

Next, when step S203 is executed, the processing device 20 is to retrospectively calculate the actual storage months of each fixed deposit of customer A, for example, the actual storage months of the first fixed deposit is 60 months, and the second fixed deposit The actual storage months of the third fixed deposit are 72 months, the actual storage months of the third fixed deposit are 72 months, the actual storage months of the fourth fixed deposit are 60 months, and the actual storage months of the fifth fixed deposit for 36 months.

In detail, please refer to FIG. 4 . When the processing device 20 retroactively calculates the actual storage months of the fixed deposit data, the processing device 20 judges whether there is a fixed deposit among the multiple fixed deposit historical data. The fixed deposit historical data with the same amount and fixed deposit periods and with a maturity date within the buffer period (step S2031). If so, the processing device 20 will count the fixed deposit period of the fixed deposit historical data traced back into the actual storage months of the fixed deposit data, and then calculate retrospectively based on the traced fixed deposit historical data Whether there is a previous fixed deposit historical data (step S2032). If not, the processing device 20 completes retrospective calculation of the actual storage months of the fixed deposit data. The buffer period is a buffer time earlier than the account opening date of the fixed deposit data, for example, the buffer period is within 1 month earlier than the account opening date.

For example, please refer to Table 2. Since each fixed deposit will be settled when the fixed deposit period expires, each fixed deposit is represented by a different account number. For example, account number 1001 represents the time deposit from 2017/01/03~2018/01/03, while account number 1005 represents the time deposit from 2018/01/03~2019/01/03. Among them, the data that have not yet been settled at due date are the fixed deposit data, and the data that have been settled at due date are the fixed deposit historical data. When retroactively calculating the actual storage months of the first fixed deposit, the processing device 20 will first confirm that the account number of the first fixed deposit is 1019. Next, the processing device 20 traces back the buffer time, for example, one month, according to the account opening date of the first fixed deposit data, that is, 2021/01/03, and judges the date of 2020/12/03~2021/01/03 During the buffer period, whether there are fixed deposit historical data with the same fixed deposit amount and fixed deposit period, and the maturity date is just within the buffer period. In Table 2, it can be confirmed that during the buffer period of 2020/12/03~2021/01/03, the maturity date of the account number 1014 is 2021/01/03, and the fixed deposit amount and fixed deposit period are also the same . Therefore, the processing device 20 can determine that the account number 1014 is the fixed deposit historical data traced back based on the account number 1019 . The processing device 20 will continue to use the account number 1014 as a benchmark to judge again whether there is a fixed deposit history back to the previous sum. Data, similarly, the processing device 20 will determine that the account number 1010 is the fixed deposit historical data traced back based on the account number 1014, and can sequentially determine that the account number 1005 and the account number 1001 are both traced historical fixed deposit data. However, when going backwards based on account number 1001, it was found that the expiration date of account number 998 did not fall within the buffer period from the account opening date of account number 1001, that is, 2016/12/03~2017/01/03. Therefore, the processing device 20 can determine that the account number 998 is not the fixed deposit historical data traced back based on the account number 1001, and there is no other traceable fixed deposit historical data. And the processing device 20 will calculate the actual storage months of the first fixed deposit data as the sum of the fixed deposit periods of account 1019, account 1014, account 1010, account 1005 and account 1001, that is, 12+12+12 +12+12=60 months.

In addition, when calculating the actual storage months of the third fixed deposit, please refer to Table 3. The processing device 20 will first confirm that the account number of the third fixed deposit is 1013. Next, the processing device 20 traces back the buffer time, for example, one month, according to the account opening date of the third fixed deposit data, that is, 2020/01/03, and judges the date of 2019/12/03~2020/01/03 During the buffer period, whether there are fixed deposit historical data with the same fixed deposit amount and fixed deposit period, and the maturity date is just within the buffer period. In Table 3, it can be confirmed that during the buffer period of 2019/12/03~2020/01/03, the maturity date of the account number 1009 is 2020/01/03, and the fixed deposit amount and fixed deposit period are also the same . Therefore, the processing device 20 can determine that the account number 1009 is an account number 1013 is the fixed deposit historical data back to the benchmark. The processing device 20 will continue to use the account number 1009 as the basis to judge whether there is any fixed deposit history data traced back to the previous one. Similarly, the processing device 20 will determine that the account number 1003 is the fixed deposit historical data traced back to the account number 1009. However, when the account number 1003 is traced back further, there is no other historical fixed deposit data that can be traced back. Therefore, the processing device 20 will count the actual storage months of the third fixed deposit data as the sum of the fixed deposit periods of account 1013, account 1009 and account 1003, that is, 24+24+24=72 months.

When step S204 is executed, the processing device 20 calculates the idle amount of fixed deposit funds of each fixed deposit of client A, for example, the idle amount of fixed deposit funds of the first fixed deposit is 10× ⁶⁰ / ₁₂ =50, the second The idle amount of fixed deposit funds in the first fixed deposit is 10× ⁷² / ₁₂ =60, the idle amount of fixed deposit funds in the third fixed deposit is 10× ⁷² / ₁₂ =60, and the idle amount of fixed deposit funds in the fourth fixed deposit is 10× ⁶⁰ / ₁₂ = 50, the idle amount of fixed deposit funds in the fifth fixed deposit is 10× ³⁶ / ₁₂ = 30.

Then, when step S205 is executed, the processing device 20 calculates the total idle amount of the fixed deposit funds of customer A, that is, 50+60+60+50+30=250.

Through the above steps S202~S205, the adjusted total asset of customer A is 300,000 yuan, and the total idle amount of the fixed deposit fund of customer A is 250. Finally, when step S206 is executed, the processing device 20 performs two-dimensional grouping, and marks customer A at the position of coordinates (250, 30) as shown in FIG. 3 , that is to say, according to FIG. A is a grouping of group B.

To sum up, through the present invention, the total idle amount of fixed deposit funds of customers can be analyzed, as well as the possible relationship between supply and implicit demand with other total assets, and after grouping, the Customers formulate exclusive marketing plans. And because the total idle amount of fixed deposit funds is obtained based on the real elapsed time, it is possible to observe the transaction behavior of specific commodities of customers more completely, so as to discover or estimate their real needs or their value in mind, and then improve the sales of financial products efficiency.

The above descriptions are only preferred embodiments of the present invention, and do not limit the present invention in any form. Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. Anyone familiar with this professional technology Personnel, without departing from the scope of the technical solution of the present invention, when the technical content disclosed above can be used to make some changes or be modified into equivalent embodiments with equivalent changes, but any content that does not depart from the technical solution of the present invention, according to the present invention Any simple modifications, equivalent changes and modifications made to the above embodiments by the technical essence still belong to the scope of the technical solution of the present invention.

10: Database 20: Processing device 30: Display device

Claims (8)

A two-dimensional exploration method for customer value, which is executed by a processing device, and includes the following steps: a: reading multiple fixed deposit data, multiple fixed deposit historical data and their total asset data of multiple customers from a database; b: For each customer, calculate an adjusted total asset excluding the fixed deposit amount based on all the fixed deposit amounts of all its fixed deposit data and the total asset data; c: For each customer, according to each of its fixed deposit data The number of fixed deposit periods and the fixed deposit amount in the multiple fixed deposit historical data are used to retroactively calculate the actual number of storage months for each fixed deposit data; d: For each customer, according to each fixed deposit data The time deposit amount and the actual number of months of deposit, calculate the idle amount of certain deposit funds for each piece of time deposit data; The total idle amount of funds; f: according to the adjusted total assets of all customers and the total idle amount of the fixed deposit funds, two-dimensional grouping is performed to generate a two-dimensional grouping list; wherein the step c includes the following sub-steps: judging Among the fixed deposit historical data, whether there is a fixed deposit historical data with the same fixed deposit amount and the fixed deposit period, and a maturity date within a buffer period; wherein the buffer period is earlier than the fixed deposit data a buffer time on the first account opening date; if there is, after counting the fixed deposit period of the retroactive fixed deposit historical data into the actual storage months of the fixed deposit data, the retroactive fixed deposit historical data is The basis again backtracks to calculate whether there is any previous fixed deposit historical data; if not, complete the retrospective calculation of the actual storage months of the fixed deposit. The two-dimensional exploration method for customer value as described in claim item 1, wherein the step b includes the following sub-steps: calculate the sum of all fixed deposit amounts of all fixed deposit data as the total fixed deposit amount; use a part of the total asset data The total assets amount is subtracted from the total amount of the time deposit to obtain the adjusted total assets. The two-dimensional exploration method for customer value as described in claim item 1, wherein the step d includes the following sub-steps: multiply the fixed deposit amount in each fixed deposit data by the actual number of deposit months and then divide by 12 to obtain the Idle amount of fixed deposit funds. The two-dimensional exploration method for customer value as described in claim item 1, wherein the step f is to use a k-means clustering algorithm (k-means clustering) to calculate the adjusted total assets and the total idle amount of the fixed deposit funds of all customers respectively Sorting from small to large and performing two-dimensional grouping to define the grouping threshold and generate the two-dimensional grouping list. A two-dimensional customer value exploration system includes: a database; a display device; and a processing device connected to the database and the display device, and the processing device reads multiple customer data from the database. One fixed deposit data, multiple fixed deposit historical data and their total asset data, and for each customer, calculate the amount excluding the fixed deposit amount based on all the fixed deposit amounts of all the fixed deposit data and the total asset amount of the total asset data 1. Adjusted total assets; Wherein, the processing device further calculates each fixed deposit in the historical data of multiple fixed deposits according to the fixed deposit period and the fixed deposit amount in each fixed deposit data for each customer The actual number of storage months of the deposit data; wherein, the processing device also calculates the fixed deposit funds of each fixed deposit data for each customer according to the fixed deposit amount and the actual storage months of each fixed deposit data Idle amount; Among them, for each customer, the processing device sums up all the idle amount of fixed deposit funds of all its fixed deposit materials to generate the total idle amount of fixed deposit funds, and calculates the total idle amount of fixed deposit funds according to the adjusted total assets of all customers and the total idle amount of fixed deposit funds amount, perform two-dimensional grouping, and generate a two-dimensional grouping list; wherein, the processing device transmits the two-dimensional grouping list to the display device, and the display device displays the two-dimensional grouping list; wherein the processing device calculates the two-dimensional grouping list in retrospect When the number of months is actually deposited, the processing device judges whether there is a certain deposit history with the same fixed deposit amount and fixed deposit period in the multiple fixed deposit historical data, and a due date within a buffer period data; wherein the buffer period is a buffer time earlier than the account opening date of the fixed deposit data; if there is, the processing device will include the fixed deposit period of the fixed deposit historical data traced back into the fixed deposit After the actual number of storage months of the data, based on the traced back to the fixed deposit historical data, it is calculated again whether there is a previous fixed deposit historical data; if not, the processing device completes the back calculation of the real storage months of the fixed deposit data . The customer value two-dimensional exploration system as described in claim item 5, wherein when the processing device calculates the adjusted total assets, the processing device first calculates the sum of all fixed deposit amounts of all fixed deposit data as the total fixed deposit amount, and then subtract the total fixed deposit amount from the total asset amount of the total asset data to obtain the adjusted total assets. The customer value two-dimensional exploration system as described in claim 5, wherein when the processing device calculates the idle amount of the fixed deposit funds, the processing device multiplies the fixed deposit amount in each fixed deposit data by the real deposit month Then divide by 12 to get the idle amount of the fixed deposit funds. The customer value two-dimensional exploration system as described in claim item 5, wherein the processing device uses a k-means clustering algorithm (k-means clustering) to calculate the adjusted total assets and the total idle amount of the fixed deposit funds of all customers respectively Sorting from small to large and performing two-dimensional grouping to define the grouping threshold and generate the two-dimensional grouping list.