KR101739018B1 - Apparatus and method for target marketing - Google Patents

Abstract

The present invention relates to a profile information generation module for receiving customer information and merchant information from a database constructed by a customer selection device and generating profile information; A target merchant selection module for generating marketing target merchant information; A potential customer information generation module for generating potential purchasing customer information corresponding to the marketing target merchant information based on the generated profile information; A target customer selection module that generates sales contribution information based on the generated potential purchase customer information; .

Description

[0001] APPARATUS AND METHOD FOR TARGET MARKETING [0002]

The present invention relates to a technique for ranking a customer selected through a marketing target customer selection.

In the past, marketing customer selection systems rarely existed. Even if there are some marketing customer selection systems, customers were randomly selected without any classification criteria. In addition, the marketing contents were delivered to the randomly selected customers and the customers were influenced by the influx of the marketing expenses.

The present invention relates to a customer selecting apparatus, a method, and a storage medium storing a program for selecting a customer to solve the above-mentioned problems.

The customer selection device according to the present invention includes a profile information generation module for receiving customer information and merchant information from a pre-established database and generating profile information; A target merchant selection module for generating marketing target merchant information; A potential customer information generation module for generating potential purchasing customer information corresponding to the marketing target merchant information based on the generated profile information; A target customer selection module that generates sales contribution information based on the generated potential purchase customer information; .

The present invention also provides a method of selecting a customer, comprising: generating profile information by receiving customer information and merchant information from a pre-established database; The target merchant selection module generating marketing target merchant information;

Generating a potential customer information module corresponding to the marketing target merchant information based on the generated profile information; And the target customer selection module generates sales contribution information based on the generated potential purchase customer information.

In addition, the storage medium storing the program for selecting a customer according to the present invention is configured to receive customer information and merchant information from a pre-configured database to generate profile information, generate marketing target merchant information, Generating potential purchase customer information corresponding to marketing target merchant information, and selecting a customer to generate sales contribution information based on the generated potential purchase customer information.

According to the present invention, customers who are highly related to the content of a marketing event can be selected as a customer target.

Also, according to the present invention, first, a target person who is selected as a customer can be promoted to promote marketing, thereby enhancing marketing efficiency.

In addition, according to the present invention, it is possible to reduce unnecessary cost by promoting marketing to a target person who is selected as a customer first.

1 is a diagram for explaining an embodiment of a first customer selection system.
2 is a diagram for explaining an embodiment of customer rank information generation.
3 is a diagram for explaining an embodiment of a second customer selection system.
4 is a view for explaining an embodiment of a customer selecting apparatus.
5 is a diagram for explaining an embodiment of a customer selection method.

One embodiment of the present invention will be described in detail with reference to the accompanying drawings. In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

1 is a diagram for explaining an embodiment of a first customer selection system.

1, the first customer selection system includes a customer profile information generation unit 100, a target merchant store selection unit 110, a payment customer target analysis unit 120, a customer ranking unit 130, (140). The first customer selection system may further include a customer profile database.

The customer profile information generation unit 100, the target merchant selection unit 110, the payment customer analysis unit 120, the customer ranking unit 130, or the marketing event execution unit 140 are implemented by respective hardware processors Or may be implemented as a single integrated processor.

The customer profile information generation unit 100 may collect customer information stored in the card company database, sales transaction information by customer stored in the card company database, information related to a specific merchant shop collected from the online medium, and generate customer profile information based on the collected customer information . The generated customer profile information described above may be stored in the customer profile database 150. [

When the customer profile information generation unit 100 collects customer information stored in the card company database, the customer profile information generation unit 100 collects the above-mentioned customer information in a format having a predetermined field value as shown in Table 1 below . The field value may include at least one of a customer identifier (ID), age, sex, work (home) address, work (home) coordinates, The above format format and field value are not limited to those described above because they can be changed by a designer.

customer
ID age gender rectal
address rectal
location Home
address Home
location Use
Amount of earnings 569 553 600 600

In addition, when the customer profile information generation unit 100 collects the sales transaction information for each customer stored in the card company database, the customer profile information generation unit 100 generates the sales information in the form of a format having a pre- Information can be collected. The field value may include at least one of a customer identifier (ID), a merchant identifier (ID), a position coordinate, a transaction date, or a sales amount. However, the field values and the format of the above-described fields are not limited to those described above because they can be changed by the designer.

Customer ID Merchant ID Position coordinates Date of transaction Sales amount 569 553 600 600

In addition, when the customer profile information generation unit 100 collects information related to a specific affiliate shop collected from an online medium, the customer profile information generation unit 100 generates the customer profile information in the form of a format having a predetermined field value as shown in Table 3 below It is possible to collect information related to merchants. The field value may include at least one of a customer cluster identifier (ID), a merchant identifier (ID), a keyword of interest, an industry category, an object classification, or a document count. However, the field values and the format of the above-described fields are not limited to those described above because they can be changed by the designer. The above-mentioned online media may include social network services, blogs, community bulletin boards, and the like.

customer
Cluster ID Merchant ID Interesting keywords Sectors individual
Classification Number of documents One flavor 2 menu 3 franchisee

Also, when the customer profile information generation unit 100 collects information related to a specific affiliate shop collected from an online medium, the customer profile information generation unit 100 may extract text information and generate related keyword list information. Also, the customer profile information generation unit 100 may cluster keyword information having a high frequency of the generated keyword list information as interest keyword information or generate separate list information.

Specifically, when the customer profile information generating unit 100 collects information related to the 'A duck merchant shop' as a specific merchant from the online medium, if the text information including the bacon, fondue, smoked cheese, (100) can generate the above-described text information as keyword list information. In addition, when the frequency of smearing and smearing is high in the text information, the customer profile information generating unit 100 may generate smear or white smoke as clustering of interest keyword information or as separate list information.

Also, the customer profile information generation unit 100 may generate the customer classification information based on the generated customer profile information. Also, the customer profile information generation unit 100 can link the generated customer profile information with the generated customer classification information. In addition, the customer profile information generation unit 100 may link the clustered information with the related keyword list or the interest keyword with the customer profile information or the customer classification information.

The target merchant selection unit 110 may receive information on the marketing target merchant from the user and extract information on the marketing target merchant. Also, the target merchant store selection unit 110 may receive information on the merchant store in the customer profile information from the above-described customer profile information generator 100 or the customer profile database 150 to extract information on the marketing target merchant store.

The settlement customer target analyzing unit 120 analyzes the potential customer information that is expected to be settled at the marketing target merchant store based on the information about the marketing target merchant store extracted by the target merchant store selecting unit 110, Lt; / RTI >

In addition, the billing customer analysis unit 120 may be configured to determine, based on at least one of the customer information stored in the card company database, the sales transaction information per customer stored in the card company database, or the information related to a specific merchant shop collected from the online medium, You can generate audience information. In addition, the above-described potential customer information may include information on a customer's preference to a marketing target merchant or information on availability to a marketing target merchant.

In order to generate the prospect information, the settlement customer target analyzing unit 120 stores the information (first information) about the distance between the marketing target merchant and the potential customer, the merchant preference index that measures the interest of the prospective customer to the marketing target merchant Information (third information) about a business preference index that calculates a purchase proportion of a potential customer to a marketing target merchant business, information (fourth information) about a compensation preference for a marketing target cost, information (second information) Or information on an average sales unit price of the potential customer group for the marketing target merchant (fifth information). Hereinafter, a method for the settlement customer analysis unit 120 to generate the above-described information will be described later.

In addition, the billing customer analysis unit 120 may generate information (first information) about the distance between the marketing target merchant and the potential customer in order to generate the potential customer information based on the customer profile information.

In addition, the settlement customer analysis unit 120 may extract field value information on the customer coordinates in the customer information stored in the card company database and field value information on the merchant's point coordinates in the customer's sales transaction information stored in the card company database. Further, the settlement customer analysis unit 120 calculates the information on the angle difference between latitude and longitude based on the extracted field value information of the customer and the merchant coordinates on the basis of Equation 1 below, Can be generated.

Specifically, the billing customer analysis unit 120 converts the extracted latitude and longitude information into a value corresponding to the radian, inserts it into the right side of Equation 1 below, calculates and stores information about the above-described angle difference corresponding to the left side, Can be generated as the above-described first information.

Specifically, when the calculated angle corresponding to the left side in Equation (1) is 60, the first information can be generated by multiplying 60 * 1.1515 by a value of 1.609344 for mile conversion in mile.

In addition, the billing customer analysis unit 120 may generate information (second information) about an affiliated store preference index that measures the interest of the potential customer for the marketing target merchant based on the customer profile information.

In addition, the settlement customer analysis unit 120 may extract the field value information about the interest keyword among the information related to the specific merchant shop collected from the above-described online media. In addition, the billing customer analysis unit 120 may generate information (second information) about the merchant store preference index that measures the interest of the potential customer with respect to the marketing target merchant store using the field value information about the extracted interest keyword have.

Specifically, the billing customer analysis unit 120 receives information on interest keywords for each business category in a specific age range from at least one of an external database, customer information stored in the card company database, and sales transaction information for each customer stored in the card company database can do.

In addition, the settlement customer analysis unit 120 calculates similarity information with the field value information on the above-described interest keyword based on the received information (cosine coefficient, product of inner product, euclidean distance) (Second information) about the merchant preference index that measures the interest of the potential customer to the merchant preference index. Information on interest keywords by industry in the above-mentioned specific age range can include information on interest keywords (ducksuk, fondue, smoked, cheese nurongji, parking lot) in the twenties. In addition, the information on the field values related to the above-described interest keywords may include information on the above-mentioned keywords, such as information on sake, grocery, smoked, handmade, parking lot, and the like. Each of the above-described examples of the keyword information can be changed in accordance with the intention of the designer, so the above description is not limited.

In addition, the billing customer analysis unit 120 may generate information (third information) on the business preference index that calculates the purchase proportion of the potential customers for the marketing target merchant business based on the customer profile information. The third information may include information on the degree of preference of the marketing target merchant to the payment customer, that is, information on the preference of the specific customer for the business category of the specific region.

Also, the settlement customer analysis unit 120 may calculate information on the business preference index using the information on the payment amount of the card company's sales data among the generated customer profile information, as shown in Equation (2) below.

The left side of Equation (2) is information on the business type preference index, which indicates that the specific customer has the information on the purchase proportion for the marketing target merchant and the average purchase proportion information value of the customer group (customer cluster, customer cluster) As shown in FIG. The above-mentioned customer group means information grouped into attributes similar to a specific customer, and this can be extracted based on the customer profile information by the billing customer analysis unit 120.

Also, the merchant sales information in Equation (2) is information on the total purchase sum amount when a particular customer visited at least one specific franchise shop, and the business type sales information is the information on the average sales of the specific customer in the above-mentioned specific customer.

Also, the merchant block sales information in Equation (2) is information on the settlement amount of the customer group (customer cluster, customer cluster) of the same business type franchisees in the block including the merchant, and the average sales amount information in the region is the arithmetic average value information or region It is the information about the value which divides the total payment amount information by the value which is located in the median value after calculating for all the customer groups for the specific business type and the administrative business type. Further, the information on the above-mentioned blocks can be calculated based on the customer location information or the merchant location information in the customer profile information.

에 대한 정보는 정규화 함수 값 정보로 매출의 편차가 발생하거나 선호도 정보 편차가 발생하는 것을 방지하기 위한 기설정된 상한값에 대한 정보 또는 기설정된 하한값에 대한 정보 중 적어도 하나 이상 포함할 수 있다.Further, in the above-mentioned expression (2)

May include at least one of information on a preset upper limit value or information on a predetermined lower limit value to prevent deviation of sales or occurrence of a preference information deviation from the normalization function value information.

In addition, the billing customer analysis unit 120 may generate information (fourth information, a marketing compensation preference index) about the compensation preference for the marketing target cost based on the customer profile information. In addition, the settlement customer analysis unit 120 may generate the fourth information by calculating the information on the merchant's preference index, the information on the preference index, and the predetermined compensation information according to Equation 3 below .

In addition, the information on the predetermined compensation value may be set by the subject who performs marketing with weight information in consideration of information per customer, information on each region, information on each type of business, and the like. Specifically, for example, coffee coupons and grocery coupons are issued as marketing means, and information about the preference index of a particular customer is 0.5 (coffee shop), 0.3 (grocery shop), and information about the preference index Information about the compensation preference (fourth information) for the coffee coupon to the specific customer is 0.5 X 0.9 X predetermined first compensation information = 0.45 X (X industry), and 0.0 And the information on the compensation preference for the coupon may be 0.3 X X X predetermined second compensation information = 0. This means that if the coupon is provided to a specific customer who does not pay for the service, the information about the compensation preference for the target price for marketing is lower than that of the customer who uses the service.

In addition, the billing customer analysis unit 120 can generate information (fifth information) on the average selling unit price of the potential customer group for the marketing target merchant based on the customer profile information.

Also, the customer ranking unit 130 may generate sales contribution information or customer ranking information based on the customer profile information. Specific details will be described later with reference to FIG. Alternatively, the marketing event performing unit 140 may set a marketing target range based on the above-described customer ranking information. In addition, the marketing event performing unit 140 may perform marketing to a specific customer corresponding to the set target range. Also, the marketing event performing unit 140 may update the customer profile information using the marketing execution result information.

2 is a diagram for explaining an embodiment of customer rank information generation.

Referring to FIG. 2, the customer ranking unit 130 described in FIG. 1 may generate information 200 on sales contribution. Also, the customer ranking unit 130 can generate the customer ranking information by classifying the generated sales contribution information in descending order or ascending order. 2, the merchant unit price 210 corresponds to the fifth information, the merchant shop preference index 230 to the second information, the business preference index 240 to the third information, and the marketing compensation index 250 to the fourth information have.

Specifically, the customer ranking unit 130 receives the first information (information on the distance between the marketing target merchant and the potential customer in order to generate the potential customer information), the second information (the information about the potential customers for the marketing target merchant (Information on the preference index of the merchant that measures the degree of interest), the third information (information on the preference index of the business that calculates the proportion of potential customers to the marketing target merchant business), or the fourth information (Sales contribution information) on the basis of at least one of the sales information of the potential customer group (information on the average sales unit price of the potential customer group), or the fifth information (information on the average sales unit price of the potential customer group to the marketing target merchant).

The settlement customer analysis unit 120 or the customer ranking unit 130 may generate the information 220 about the distance weights in Equation (4) through Equation (4) below.

In addition, the billing customer analysis unit 120 or the customer ranking unit 130 may collect information on the current location distance, information on the target merchant store and the work distance, or information on the target merchant store and the home distance on the basis of the customer profile information May be extracted to generate information on the distance weight. The above-described information on the target franchise point and the current position distance may correspond to the above-described first information.

3 is a diagram for explaining an embodiment of a second customer selection system.

3, at least one of the merchant information calculation module 330, the merchant store characteristics index calculation module 340, the potential customer selection module 380, and the customer ranking module 398 may be included. The merchant information calculation module 330, the merchant store characteristics index calculation module 340, the potential customer selection module 380, and the customer ranking module 398 may be implemented by respective hardware processors or by a single integrated processor .

The merchant store information calculation module 330 or the merchant store characteristics index calculation module 340 may correspond to the customer profile information generation module 100 described above with reference to FIG. The merchant information calculation module 330 collects the customer information 350 stored in the card company database, the sales transaction information 360 for each customer stored in the card company database, and the information 370 related to a specific merchant shop collected from the online medium, To generate customer profile information.

The merchant shop information calculation module 330 may generate at least one of the neighborhood customer index information 300, the regular customer index information 310 or the social customer index information 320 based on the generated customer profile information. The neighborhood customer index information 300 includes customer profile information, customer ratio information about a specific merchant utilizing positional information on the home or work of the middle customers, and the common customer index information 310 described above, And may include information on the frequency of use of a specific customer.

In addition, the above-described social customer index information 320 may include activity information of a specific merchant through an online medium (cafe, blog, Instagram, Facebook, etc.). The above-described merchant information calculation module 330 can generate the activity information of the above-described merchant through the following equation (5).

Also, the social customer index information 320 may include information obtained by digitizing on-line / off-line response information for one or more attributes such as a menu, a taste, an atmosphere, and a service for a merchant or a business type at a specific point in time.

The merchant point characteristic index calculating module 340 may generate merchant point characteristic index information based on at least one of the neighborhood customer index information 300, the regular customer index information 310 or the social customer index information 320. The merchant attribute index information may include attribute information including at least one of neighborhood customer information, regular customer information, and social customer information for a specific merchant.

Specifically, when the neighborhood customer index information of the specific merchant shop is 0.1, the customer index information is 0.5, and the social customer index information is 0, the sales information of the specific merchant shop does not receive the influence of the social customers at all, Can be considered to be influential.

The potential customer selection module 380 includes customer information 350 stored in the card company database, customer sales transaction information 360 stored in the card company database, information 370 related to a specific affiliate shop collected from the online media, And generate potential customer information based on the collected information. Specifically, the potential customer selection module 380 may generate the prospect information by extracting the prospect customer information in the adjacent distance unit of the marketing target merchant within the marketing event period. The potential customer selection module 380 may correspond to the settlement customer analysis unit 120 described above with reference to FIG. A detailed description thereof has been given above with reference to FIG.

The customer ranking module 398 may generate customer ranking information based on at least one of the merchant preference index information 385, the business preference index information 390, or the marketing compensation index information 395. The customer ranking module 398 may correspond to the customer ranking unit 130 described above with reference to FIG. A detailed description thereof has been given above with reference to FIG.

1, the merchandise preference index information 385 corresponds to the above-described second information, the business preference index information 390 corresponds to the above-described third information, and the marketing compensation index information 395 corresponds to the above- Respectively.

The merchant shop preference index information 385 may include information on the combination of the neighborhood customer index information 300, the regular customer index information 310, or the social customer index information 320. A detailed description thereof is shown in Equation (6) below. W1, w2, and w3 described later may include predetermined weight information for each index information.

4 is a view for explaining an embodiment of a customer selecting apparatus.

4, the customer selection device includes at least one of a profile information generation module 400, a target merchant selection module 410, a potential customer information generation module 420, or a target customer selection module 430 . The profile information generation module 400, the target merchant selection module 410, the potential customer information generation module 420, or the target customer selection module 430 may be implemented by respective hardware processors or may be implemented by one integrated processor have.

The profile information generation module 400 may correspond to the customer profile information generation unit 100 in FIG. The target merchant selection module 410 may correspond to the target merchant selection section 110 described above with reference to FIG. The potential customer information generation module 420 may correspond to the settlement customer analysis unit 120 described above with reference to FIG. The target customer selection module 430 may correspond to the customer ranking unit 130 described above with reference to FIG.

The profile information generation module 400 can generate profile information by receiving customer information and merchant information from a pre-built database. The target merchant selection module 410 may generate marketing target merchant information.

The potential customer information generation module 420 may generate potential purchasing customer information corresponding to the marketing target merchant information based on the generated profile information. The target customer selection module 430 may generate sales contribution information based on the generated potential purchasing customer information.

The potential customer information generation module may generate potential purchasing customer information based on the angle difference between latitude and longitude included in individual potential purchasing customer coordinate information and marketing target merchant coordinate information among the generated profile information.

Also, the potential customer information generating module can generate potential purchasing customer information based on the merchant characteristic index information. Further, the merchant point characteristic index information may be based on at least one of the neighborhood customer index information, the regular customer index information, or the social customer index information based on the generated profile information.

The sales contribution information may include at least one of average purchase sales information of all the potential purchasing customers to the marketing target merchant, distance information between the marketing target merchant and the individual potential purchaser, merchant preference index information, industry preference index information, or compensation preference information Or more.

The merchant preference index information is information on the individual potential purchasing customer's interest for the marketing target merchant, the business preference index information is information on the purchase proportion of individual potential purchasers for the business type corresponding to the marketing target merchant, And may include utility information on marketing costs.

In addition, the distance information between the marketing target merchant and the individual potential purchasing customer may include information on the distance between the marketing target merchant location and the current potential location of the individual purchasing customer based on the generated customer profile information, the marketing target merchant location, Information about the distance between locations, or information on the distance between the marketing target merchant location and the individual potential purchasing customer home location.

Further, the merchant store preference index information may be based on a keyword for the marketing target merchant and a keyword corresponding to the individual potential purchaser customer. The sector preference index information may be based on the information on the purchase proportion of individual potential purchasing customers to marketing target merchants and on the average purchase proportion of all customers in the region such as individual potential purchasing customers.

The neighborhood customer index information is information on the ratio of customers near a specific merchant utilizing the location information of the customers' home or work in the generated profile information. The regular customer index information includes information on the frequency of use of a specific customer for a particular merchant Information, and the above-described social customer index information may include reaction information for at least one of a menu, a taste, an atmosphere, and a service for a specific merchant at a specific time point.

5 is a diagram for explaining an embodiment of a customer selection method.

Referring to FIG. 5, the customer selection method includes a step S500 of receiving profile information by receiving customer information and merchant information from a database (S500), generating marketing target merchant information (S510) (S520) generating potential purchasing customer information corresponding to the target merchant information, and generating sales contribution information based on the generated potential purchasing customer information (S530).

The profile information generation module 400 may perform the step of receiving the customer information and the merchant information from the pre-built database to generate the profile information. A detailed description thereof has been given above with reference to FIG. 1 to FIG. The target merchant selection module 410 may perform the step of generating marketing target merchant information. A detailed description thereof has been given above with reference to FIG. 1 to FIG. The potential customer information generation module 420 can generate the potential purchasing customer information corresponding to the marketing target merchant information based on the generated profile information. A detailed description thereof has been given above with reference to FIG. 1 to FIG. The target customer selection module 430 may generate sales contribution information based on the generated potential purchasing customer information. A detailed description thereof has been given above with reference to FIG. 1 to FIG.

The embodiments disclosed in the specification of the present invention do not limit the present invention. The scope of the present invention should be construed according to the following claims, and all the techniques within the scope of equivalents should be construed as being included in the scope of the present invention.

400: profile information generation module
410: Target merchant selection module
420: an audience information generation module
430: Target Customer Selection Module

Claims (17)

A profile information generation module for receiving customer information and merchant store information from an established database and generating profile information;
A target merchant selection module for generating marketing target merchant information;
A potential customer information generation module for generating potential purchasing customer information corresponding to the marketing target merchant information based on the generated profile information;
A target customer selection module that generates sales contribution information based on the generated potential purchase customer information; And
The target customer selection module may be configured to calculate the sales contribution information based on merchandise preference index information that is information on the interest of the individual potential purchasing customer for the marketing target merchant and information on the purchase proportion of the individual potential purchasers for the business type corresponding to the marketing target merchant And the reward preference information, which is utility information on the marketing cost,
Wherein the potential customer information generation module generates the compensation preference information using the merchant preference index information and the business preference index information. 2. The method of claim 1, wherein the potential purchasing customer information includes distance information between the marketing target merchant and each potential purchasing customer, and the distance information between the marketing target merchant and the individual potential purchasing customer is based on the generated customer profile information Information on a distance between the marketing target merchant location and the individual potential purchasing customer location, information on a distance between the marketing target merchant location and the individual potential purchasing customer business location, information on the distance between the marketing target merchant location and the individual potential purchasing customer's home And a sum of inverse squared information for each of the information about the distance between the locations. The apparatus of claim 2, wherein the merchant preference index information is based on a keyword for the marketing target merchant and a keyword corresponding to the individual potential purchaser. 4. The method according to claim 3, wherein the business preference index information includes at least one of a customer preference index information based on the purchase proportion information for the marketing target merchant and the average purchase proportion information of all the customers in the area such as the individual potential purchasing customer, . The method according to claim 1, wherein the potential customer information generation module generates the potential purchase information based on the angle difference between latitude and longitude included in the individual potential purchasing customer coordinate information and the marketing target merchant point information, A customer selection device that generates customer information. The system according to claim 1, wherein the potential customer information generation module generates potential purchasing customer information based on the merchant point characteristic index information, and the merchant point characteristic index information includes neighborhood customer index information, Information or social customer index information,
Wherein the neighborhood customer index information is information on a customer ratio near a specific merchant utilizing the location information of the customers' home or work in the generated profile information, and the regular customer index information includes information on a frequency of use of a specific customer Information on the at least one of the menu, the taste, the atmosphere, and the service for the specific merchant at a specific point in time. Generating profile information by receiving customer information and merchant information from a pre-established database;
The target merchant selection module generating marketing target merchant information;
Generating a potential customer information module corresponding to the marketing target merchant information based on the generated profile information;
And the target customer selection module generates sales contribution information based on the generated potential purchase customer information
The target customer selection module may be configured to calculate the sales contribution information based on merchandise preference index information that is information on the interest of the individual potential purchasing customer for the marketing target merchant and information on the purchase proportion of the individual potential purchasers for the business type corresponding to the marketing target merchant And the reward preference information, which is utility information on the marketing cost,
Wherein the potential customer information generation module generates the compensation preference information using the merchant's preference index information and the business preference index information. 8. The method of claim 7, wherein the potential purchase customer information includes distance information between the marketing target merchant and the individual potential purchasing customer, and the distance information between the marketing target merchant and the individual potential purchasing customer is based on the generated customer profile information Information on a distance between the marketing target merchant location and the individual potential purchasing customer location, information on a distance between the marketing target merchant location and the individual potential purchasing customer location, or information on a distance between the marketing target merchant location and the individual potential purchasing customer's home And a sum of inverse squared information for each of information about the distance between the locations. The method of claim 8, wherein the merchant preference index information is based on a keyword for the marketing target merchant and a keyword corresponding to the individual potential purchaser. The method according to claim 9, wherein the business preference index information includes at least one of a customer selection ratio based on the purchase proportion information of the individual potential purchasing customer to the marketing target merchant and an average purchase proportion information of all the customers in the area such as the individual potential purchasing customer . The method according to claim 7, wherein the potential customer information generation module generates the potential customer information based on the angle difference between latitude and longitude included in the individual potential purchasing customer coordinate information and the marketing target merchant point coordinate information among the generated profile information, A customer selection method that generates customer information. The system according to claim 7, wherein the potential customer information generation module generates potential purchasing customer information based on the merchant point characteristic index information, and the merchant point characteristic index information includes neighborhood customer index information, Information or social customer index information,
Wherein the neighborhood customer index information is information on a customer ratio near a specific merchant utilizing the location information of the customers' home or work in the generated profile information, and the regular customer index information includes information on a frequency of use of a specific customer Information on the at least one of the menu, the taste, the atmosphere, and the service for the specific merchant at a specific point in time. Generates customer information and merchant information from the established database to generate profile information, generates marketing target merchant information, generates potential purchase customer information corresponding to the marketing target merchant information based on the generated profile information And generating sales contribution information based on the generated potential purchasing customer information, wherein the sales contribution information is information on a sales target of the individual potential purchasing customer to the marketing target merchant, Preference index information, industry preference index information which is information on the purchase proportion of the individual potential purchasing customers to the business type corresponding to the marketing target merchant, and compensation preference information which is utility information on the marketing expense, The above- And stores the program for selecting a customer to be generated by utilizing the information on the number of customers and the information on the preference index of the business type. delete delete delete delete

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