JP5702821B2 - Purpose store commercial area determination device, method and program - Google Patents

Description

  The present invention relates to a target store commercial area determination apparatus, method, and program, and in particular, the range of residence of a target visitor who visits (visit) with interest in the facility (for example, a store) and the possibility of developing into a target store. The present invention relates to a destination store trade area determination apparatus, method, and program for determining the range of residence of an impulse visitor as a target store trade area.

  A service for grasping a user's location information using a GPS function of a cellular phone and providing information according to the location is spreading. For users, it is possible to obtain information suitable for their own situation, and for information providers, it can be expected that their services can be provided to effective users.

  In order to perform such a service, the first necessary information is the trade area of what kind of area people are coming to each facility. In particular, various applications can be considered by seeking a “target visit commercial area” that is a range of residence of a visitor who is likely to visit the facility with a purpose.

  For example, a user who has selected a certain region can obtain facility information that people frequently visit from the vicinity. In addition to the recommended facilities at the current location and the planned location, you can also learn about other people's trends, such as information about the facilities that people in a certain area visit. .

  In addition, an information provider who operates each facility can use the obtained trade area for marketing. For example, it can be used as a reference for an advertisement distribution / distribution area. If you can find out more detailed business areas that are closer to the actual situation, you can expect to be able to narrow down the range of residents and effective targets that you couldn't understand with conventional methods. It can also be used for forecasting sales. In addition, if the trade areas of each facility in the town are superimposed on the map, a wide trade area such as the town can be grasped. And, for example, in Kyoto, which is famous for tourism, measure the attractiveness of a town that attracts people according to the size of the trade area, so that people come from geographically distant areas, and how it depends on the shape of the trade area. You can also expect to know the characteristics of the town whether you are coming from that area. Such information is expected to be useful information for those who are considering moving, opening new stores, etc., as well as for the administrative side of city reform.

  In this way, various applications are conceivable. Conventionally, the destination store trade area is often set approximately according to the travel time from the facility. In addition, in order to find the actual destination store trade area, it was necessary to conduct a questionnaire survey asking the reason for the store visitor. Therefore, a technique for automatically determining the target store trade area of each facility is desired.

  As a conventional trade area determination method, there is a technique in which a map is divided into a mesh shape, the number of customer residents is calculated for each area, and an area with many residents is set as a trade area range (see, for example, Patent Document 1).

  In addition, as a method that does not require the acquisition of customer information through questionnaires, etc., a technology that calculates the geographical range of each keyword by overlaying place names that co-occur with the keyword in the blog (for example, see Non-Patent Document 1) is applied. It is possible to obtain the trade area of each facility automatically from web information by obtaining the residence of the person who writes the article that visited the place in the blog with reference to the profile etc. .

Japanese Patent No. 3393461

Naoki Fujita, Yoshihiko Nuwara, Ryoji Kataoka, "Search service for smartphones that leads to discovery of local topics: Discovery Map Area Das", DEIM Forum 2012 F8-2.

  However, if an attempt is made to find the destination store trade area using the technology of the above-mentioned Patent Document 1, for example, if there is an attractive facility nearby where people from other prefectures gather, the target store trade area of a minor facility is large. This leads to the problem of being overestimated.

  In the technology to which Non-Patent Document 1 is applied, the same problem as described above occurs.

  The present invention has been made in view of the above points, without being affected by attractive facilities in the surroundings, without performing a questionnaire survey or the like on an appropriate trade area that visits the facility itself for the purpose, It is an object of the present invention to provide an object store trade area determination apparatus, method and program that can be automatically determined.

In order to solve the above problems, the present invention (Claim 1) is a trade area determination device for judging a target visit trade area from a residence area of a purpose visit customer who visits a certain facility with a purpose and an impulse visitor who visits impulse. There,
Facility name storage means storing facility name and location information including abbreviations,
User residence storage means for storing user residence information;
Facility name storage means for storing the name of each facility,
When the facility name is input, the facility name storage means is referred to based on the facility name, the facility name or abbreviation is obtained, and the facility is actually identified from the Web document by context determination processing based on the facility name or the abbreviation. Search means to extract the contributors who visited,
Referring to the user residence storage means based on the extracted poster, a residence allocation means for obtaining the residence of each poster;
Based on the name of the facility, the name of the facility is acquired from the facility name degree storage means, a threshold value that increases as the degree of name recognition increases, a distance between the place of residence and the facility is obtained, and a place where the distance is shorter than the threshold value And a purpose-of-sales business area calculation means that uses only the business area as a business area.

Further, the present invention (Claim 2) is a trade area determination device for judging a target visit trade area from a residence range of a purpose visit customer who visits a certain facility with a purpose and an impulse visit customer who visits impulsively,
Facility name storage means storing facility name and location information including abbreviations,
User residence storage means for storing user residence information;
Facility name storage means for storing the name of each facility,
When the facility name is input, the facility name storage means is referred to based on the facility name, the facility name or abbreviation is obtained, and the facility is actually identified from the Web document by context determination processing based on the facility name or the abbreviation. Search means to extract the contributors who visited,
Referring to the user residence storage means based on the extracted poster, obtaining the residence of each poster, and residence allocation means for counting the number of posters in a predetermined group unit;
Based on the facility name, the facility name is acquired from the facility name recognition means, a threshold value that increases as the name recognition value increases, and when the groups are arranged in descending order of the number of contributors, the cumulative composition ratio is the threshold value And a destination store trade area calculation means for setting the area corresponding to the top N groups exceeding the trade area as a trade area.

  As described above, according to the present invention, even if there is an attractive facility where people from other prefectures gather nearby, the facility itself is visited with a purpose without being predicted too much in a large area. It is possible to automatically calculate a residential area where many people and people who will visit in the future gather as the target visit commercial area.

  In addition, since the information of people who actually went to the place is used, it is possible to know the actual situation of a complex trade area that takes into account ease of travel and attractiveness. For example, it is a conventional method in a certain area. It can be expected to discover the range of residence of customers who could not be understood.

  Also, by using Web information such as Twitter (registered trademark), a lot of information can be easily obtained, so it can save a lot of money and trouble compared to the conventional method of taking a questionnaire. Information can be updated in real time.

It is a block diagram of the trade area determination apparatus in the 1st Embodiment of this invention. It is an example of the facility name database in the 1st Embodiment of this invention. It is an example of the user residence database in the 1st Embodiment of this invention. It is an example of the facility visibility database in the 1st Embodiment of this invention. It is a flowchart of the facility well-known database creation process in the 1st Embodiment of this invention. It is a flowchart of a process of the trade area determination apparatus in the 1st Embodiment of this invention. It is an example of the point data used when acquiring the residence in the 1st Embodiment of this invention. It is an example of the mapping of the residence of the visitor in the 1st Embodiment of this invention. It is an example of the residence data in the 100 km range in the 1st Embodiment of this invention. It is an example of the trade area display in the 1st Embodiment of this invention. It is an example of the trade area display of the convenience store in the 1st Embodiment of this invention. It is a block diagram of the trade area determination apparatus in the 2nd Embodiment of this invention. It is a flowchart of a process of the trade area determination apparatus in the 2nd Embodiment of this invention. It is a Pareto chart for Shinjuku coffee shops in the second embodiment of the present invention. It is a Pareto diagram of "Mummy ranch" in the second embodiment of the present invention. It is an example of the trade area display in the 2nd Embodiment of this invention.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  Hereinafter, “store” will be described as an example of the facility, but it may be a leisure facility, a restaurant, a hotel, etc. in addition to the store, and is not limited to the store. In the following, “store” is used as an example to describe “store visit” and “customer”, but in the case of other facilities, it means “visitor” and “visitor”.

  In the following description, the “target visitor” is a visitor who has purposely visited the store with a purpose, and the “impulse visitor” is a visitor who has another purpose and then visits the store. In the present invention, the range of residence of the target visitor and the range of residence of the impulse visitor who may develop into the target visit are defined as the “target visit commercial area”.

  In the present invention, even if there is an attractive store where people gather from other prefectures nearby, the purpose of visiting the minor store is not expected to be too large, and it will bother to visit the store The range of residence where many customers who are likely to develop into the target store customers and who are likely to develop into the target store visits is calculated as the target store trade area.

  If it is a famous store, an impulse visitor who happens to visit the store from a distance may develop into a purpose store, but if it is an unknown store, the purpose is to bother to visit the store from a distance. There is no possibility of developing into a store. Therefore, as shown in Table 1, the six items {[2], [6], [8]} and {[1], [5], [7]} is there.

[第1の実施の形態]
本実施の形態では、知名度に比例した店舗からの距離によって、商圏の絞り込みを行う場合を説明する。居住地のマッピングに用いるデータとしては、点データを用いている。

[First embodiment]
In the present embodiment, a case will be described in which a trade area is narrowed down by a distance from a store that is proportional to the degree of recognition. Point data is used as data used for mapping the residence.

  In this embodiment, a method using one of microblogs called Twitter (registered trademark) will be described, but the same method can be applied to other Web documents.

  FIG. 1 shows a configuration of a trade area determination apparatus according to the first embodiment of the present invention.

  The trade area determination device 100 includes a facility name database 110, a search unit 120, a user residence database 130, a residence assignment unit 140, a facility visibility database 150, a destination visit trade area calculation unit 160, a facility visibility calculation unit 170, and a display unit 180. .

  The Web document 101 may be acquired directly from the outside of the trade area determination device 100, or may be held inside as a Web document file after acquisition.

  In the present embodiment, description will be made assuming that a Web document file is stored after the Web document is acquired.

  The facility name database 110 is a database in which information on each facility (store) is recorded, and the facility name, abbreviation, telephone number, address, etc. of each facility are recorded as shown in FIG.

The user residence database 130 is a database that records the residences of Twitter (registered trademark) users. The user's residence is estimated from past posts and profiles, and recorded as shown in FIG. For example, Non-Patent Document 2 (Zhiyuan cheng, James Caverlee, Kyumin Lee, “You are where you tweet: a content-based approach to geo-locating twitter users”, Proceedings of the 19 ^th ACM international conference on Information and knowledge management, pp. 759-768 (2010)) can be used to estimate the residence from past posts.

  The facility visibility database 150 is a database that stores the facility visibility generated by the facility visibility calculator 170.

  The facility visibility calculation unit 170 calculates the facility visibility as shown in Table 2 using, for example, the number of users who tweeted store names in all Twitter (registered trademark), and stores them in the facility visibility database 150. . The facility visibility calculation unit 170 sets the visibility according to the number of murmured users. In the example of Table 2, the degree of popularity has ranks from 1 to 5, and the greater the number of murmured users, the higher the degree of familiarity.

図５に施設知名度計算部１７０の処理を示す。

FIG. 5 shows the processing of the facility visibility calculation unit 170.

  A store name is extracted from the facility name database 110 (step 501), and the Web document 101 is searched based on the store name (step 502). The number of contributors who tweeted the store information is determined (step 503), and the number of contributors is counted (step 504). The obtained number of contributors is converted into facility visibility using logarithmic conversion or the like (step 505) and registered in the facility visibility database 150 (step 506).

  In addition, it is not limited to said example, In addition to this, it is also conceivable that the name recognition is calculated from the sales scale of the store and the number of visitors.

  The search unit 120 searches the Web document 101 for the input store name, and searches for and acquires a poster who has actually visited the store. Whether or not the store is actually visited is analyzed by morphological analysis of the document. Specifically, the store name is included, and words indicating experience (for example, “I went to ○○”, “I went to ○○”, “When I went to ○○”, “○○ The contributor who posted the sentence including “

  The residence allocation unit 140 acquires the poster's residence from the user residence database 130 based on each poster acquired from the search unit 120, calculates the distance between the residence and the store, It passes to the calculation unit 160.

  The destination store trade area calculation unit 160 acquires the name recognition from the facility name database 150 based on the store name, determines the market area based on the distance between the residence and the store and the name recognition, and stores it in the destination store trade area database 170.

  The display unit 180 displays on the display means based on the trade area data input from the destination store trade area calculation unit 160.

  The operation in the above configuration will be described below.

  FIG. 6 is a flowchart of processing of the trade area determination device according to the first embodiment of the present invention.

  Step 510) The search unit 120 receives a store name from the operator.

  Step 520) The search unit 120 determines whether the input store name is in the facility name database 110, and if there is, searches the Web document 101 based on the store name.

  Step 530) In the search unit 120, the context of the article obtained from the Web document 101 is determined, the contributor who actually goes to the store is determined, and the contributor of the article is determined. As a method for determining whether or not the user actually went to the store, for example, it may be possible to extract expressions such as “I went to XX” and “XX Now”.

  Step 535) The residence allocation unit 140 extracts only a poster who has a residence in the user residence database 130 based on the user name of the poster acquired from the Web document 101.

  Step 540) Obtain the residence of each poster from the user residence database 130. As the residence, point data such as an address of the residence may be used as shown in FIG. 7, or a living area having a certain size such as a municipality name may be used.

  Step 550) The residence allocation unit 140 calculates the distance from each residence to the store.

  Step 560) The destination store trade area calculation unit 160 acquires the store's name recognition from the facility name recognition database 150.

  Step 570) The destination store trade area calculation unit 160 narrows the range of residence, and based on the name recognition, the distance between the store and the resident shown in Table 3 stored in the memory within the target visit store area calculation unit 160 The distance threshold value is acquired by referring to the well-known table.

ステップ５８０） 目的来店商圏計算部１６０は、所定の閾値よりも距離が短い居住地のみを居住地データとして残す。

Step 580) The destination store trade area calculation unit 160 leaves only the residences whose distance is shorter than the predetermined threshold value as the residence data.

  Step 590) The destination store trade area calculation unit 160 sets the remaining residence address data as a trade area and outputs the data to the display unit 180. As a method of drawing the trade area by the display unit 180, the map may be divided into meshes or regions, and the area where the data exists may be adopted as the trade area, or the total number of residence data may be taken for each area and color-coded. Thus, it can be output to a display means such as a display. In addition to outputting the trade area to the display means, it may be stored in the storage means.

  Hereinafter, the above series of processes will be specifically described.

An example of mapping by the residence allocation unit 140 is shown in FIG. When the number of users who tweet the noun “Mummy Farm” in the Web document 101 is “4188” in the Web document 101, the destination store trade area calculation unit 160 has a name recognition level “4” from the name recognition table (number of users) in Table 2. Become. In this case, since the distance from the facility is within 100 km from the well-known table (distance) in Table 3, the residence data within 100 km is adopted as shown in FIG. By outputting the residence data to the display unit 180, the display unit 180 can draw a trade area as shown in FIG. As a display method of the trade area in the display unit 180, in addition to the method of surrounding the trade area with a frame line as shown in FIG. 10, it is displayed in a color-coded manner like a heat map according to the number of residents, or is not graphic It is also possible to display it as a character string. For example,
“Purpose of visits: Chiba, Tokyo, Kanagawa, Saitama, Ibaraki, Shizuoka, Yamanashi”
Outputs such as are also possible.

  On the other hand, if you consider a convenience store in Tokyo, if you adopt a range within 100 km as in “Mummy Ranch,” you will include people who happen to visit. If the range within 10 km calculated according to the name recognition is adopted, only the vicinity of Shinjuku is calculated as a trade area as shown in FIG.

[Second Embodiment]
In the present embodiment, as in the first embodiment, a method using one of microblogs called Twitter (registered trademark) will be described, but the same method can be applied to other Web documents.

  FIG. 12 is a configuration diagram of a trade area determination device according to the second embodiment of the present invention.

  The business area determination apparatus 1000 includes a facility name database 1110, a search unit 1120, a user residence database 1130, a residence allocation unit 1140, a facility visibility database 1150, a destination visit trade area calculation unit 1160, a facility visibility calculation unit 1170, a display unit 1180, A diagram creation unit 1190 is included.

  The Web document 101 may be acquired directly from the outside of the trade area determination apparatus 1000, or may be held inside as a Web document file after acquisition.

  Also in this embodiment, a description will be given assuming that a Web document file is held after the Web document is acquired.

  The facility name database 1110 is a database in which information of each facility is recorded and is the same as that in FIG.

  Since the user residence database 1130 has the same configuration as that of FIG. 3 of the first embodiment, the description thereof is omitted.

  The facility visibility database 1150 is generated by the facility visibility calculation unit 1170, and the configuration thereof is the same as that of FIG. 4 of the first embodiment, and thus the description thereof is omitted.

  The search unit 1120 searches the Web document 101 (Twitter (registered trademark)) for the input facility name, and searches for and acquires a poster who has actually visited the facility.

  The residence allocation unit 1140 acquires the residence of each poster acquired by the search unit 1120.

  The Pareto chart creation unit 1190 groups for each area of residence and creates a Pareto chart.

  The destination store trade area calculation unit 1160 narrows down the residence data acquired by the residence assignment unit 1140 according to the degree of recognition, and obtains a trade area.

  The facility visibility calculation unit 1170 generates the facility visibility database 1150 by the same method as in the first embodiment.

  The Pareto chart creation unit 1190 groups the areas of residences acquired from the residence assignment unit 1140 and creates a Pareto chart.

  Hereinafter, processing in the above configuration will be described.

  FIG. 13 is a flowchart of the process of the trade area determination device according to the second embodiment of the present invention.

  Step 1310) The search unit 1120 receives the store name.

  Step 1320) The search unit 1120 determines whether the input store name is in the facility name database 1110. If there is, the search unit 1120 searches the Web document 101 based on the store name.

  Step 1330) In the search unit 1120, the context of the article obtained from the Web document is determined, the poster who actually goes to the store is determined, and the poster of the article is determined. Since the determination method is the same as that of the first embodiment, the description thereof is omitted.

  Step 1335) The residence allocation unit 1140 extracts only a poster who has a residence in the user residence database 1130.

  Step 1340) The residence allocation unit 1140 acquires each poster's residence in units of prefectures based on information in the user residence database 1130. It should be noted that the unit of width can be arbitrarily set, for example, by dividing into a unit of a municipality or a mesh of a predetermined size.

  Step 1350) The Pareto chart creation unit 1190 creates a Pareto chart of residence data for each prefecture.

  Step 1360) The destination store trade area calculation unit 1160 refers to the facility visibility database 1150 on the basis of the store name, and acquires the visibility of the store.

  Step 1370) The destination store trade area calculation unit 1160 sets the threshold α of the cumulative composition ratio according to the name of the store in order to narrow down the residence range, as shown in Expression (1). The formula for calculating the threshold value of the cumulative composition ratio is not limited to the formula (1). If the degree of recognition is large, it is considered that there are many people who go for the place. Therefore, the value of α is increased and convenience is conversely established. If the degree of publicity is low, such as a store, the calculation method should be such that the number of people who come to the purpose is considered to be a small number of neighbors and the value of α is reduced.

α [%] = 40 + popularity x 10 formula (1)
The values of “40” and “10” above are values that are appropriately determined so that the value of the threshold α corresponding to the degree of familiarity from 1 to 5 is in the range of 50% to 90%, and is arbitrarily set Is possible.

  Step 1380) The destination store trade area calculation unit 1160 employs the data up to the area where the cumulative composition ratio exceeds the threshold value α as the residence data.

  Step 1390) The destination store trade area calculation unit 1160 determines a trade area based on the adopted residence data and outputs it to the display unit 1180. As a display method of the trade area, the adopted prefecture may be displayed as a trade area as it is, or may be color-coded according to the cumulative value of the number of contributors in each adopted prefecture.

  FIG. 14 is a Pareto diagram created for the coffee shop in Shinjuku in the second embodiment of the present invention. Since the number of users who hit two nouns of the place name “Shinjuku” and the store name “stub” is “104” per store, the name recognition is “1” from the name table (number of users) in Table 2. Since α can be calculated as 50%, in the case of FIG. 14, only Tokyo that exceeds the cumulative composition ratio of 50% is adopted as data used for the trade area, and “Tokyo” is determined as the trade area.

  Further, if the “Mummy ranch” shown in the first embodiment is used, the above Pareto chart can be created as shown in FIG. Since the degree of recognition can be calculated as 80% from "4", in the case of Fig. 15, the data of the four prefectures of Chiba, Tokyo, Kanagawa and Saitama that exceed the cumulative composition ratio of 80% Adopted as data to be used. Then, the display unit 1180 can display the four prefectures as a trade area as it is, or a color-coded method such as a heat map according to the cumulative value of each prefecture, or a corresponding trade area as shown in FIG. Can also be expressed by a frame line.

  In addition, the operation | movement of the component of the trade area determination apparatus shown in FIG. 1, FIG. 12 in said 1st, 2nd embodiment is constructed | assembled as a program, and it installs and runs on the computer utilized as a trade area determination apparatus, Alternatively, it can be distributed via a network.

  The present invention is not limited to the above-described embodiments, and various modifications and applications are possible within the scope of the claims.

100, 1000 Trade area determination device 101 Web document 110, 1110 Facility name database 120, 1120 Search unit 130, 1130 User residence database 140, 1140 Residence location assignment unit 150, 1150 Facility name database 160, 1160 Destination store trade area calculation unit 170, 1170 Facility visibility calculator 180, 1180 Display 1190 Pareto chart generator

Claims (8)

A business area determination device for determining a target visit commercial area from a residence area of a purpose visit customer who visits a certain facility with a purpose and an impulse visitor who visits impulsively,
Facility name storage means storing facility name and location information including abbreviations,
User residence storage means for storing user residence information;
Facility name storage means for storing the name of each facility,
When the facility name is input, the facility name storage means is referred to based on the facility name, the facility name or abbreviation is obtained, and the facility is actually identified from the Web document by context determination processing based on the facility name or the abbreviation. Search means to extract the contributors who visited,
Referring to the user residence storage means based on the extracted poster, a residence allocation means for obtaining the residence of each poster;
Based on the name of the facility, the name of the facility is obtained from the facility name degree storage means, a threshold value that increases as the degree of name recognition increases, the distance between the place of residence and the facility is obtained, and only a place of residence where the distance is shorter than the threshold value The purpose store visit area calculation means with
A trade area determination device characterized by comprising: A business area determination device for determining a target visit commercial area from a residence area of a purpose visit customer who visits a certain facility with a purpose and an impulse visitor who visits impulsively,
Facility name storage means storing facility name and location information including abbreviations,
User residence storage means for storing user residence information;
Facility name storage means for storing the name of each facility,
When the facility name is input, the facility name storage means is referred to based on the facility name, the facility name or abbreviation is obtained, and the facility is actually identified from the Web document by context determination processing based on the facility name or the abbreviation. Search means to extract the contributors who visited,
Referring to the user residence storage means based on the extracted poster, obtaining the residence of each poster, and residence allocation means for counting the number of posters in a predetermined group unit;
Based on the facility name, the facility name is acquired from the facility name recognition means, a threshold value that increases as the name recognition value increases, and when the groups are arranged in descending order of the number of contributors, the cumulative composition ratio is the threshold value Purpose store trade area calculation means with the area corresponding to the top N groups exceeding
A trade area determination device characterized by comprising: The residence allocation means is
3. The trade area determination device according to claim 2, wherein the group unit is a prefecture unit, a municipality, or a mesh unit obtained by dividing an area with a predetermined size. 3. The trade area determination device according to claim 2, further comprising a Pareto chart creation means for converting the trade area obtained by the target store trade area calculation means into a Pareto chart. 3. The trade area determination device according to claim 1, further comprising display means for mapping and displaying the trade area obtained by the target store trade area calculation means on a map. A trade area determination method for determining a destination visit trade area from a residential area of a purpose visit customer who visits a certain facility with a purpose and an impulse visitor who visits impulsively,
Facility name storage means storing facility name and location information including abbreviations,
User residence storage means for storing user residence information;
Facility name storage means for storing the name of each facility,
In an apparatus having search means, residence allocation means, and destination store trade area calculation means,
When the facility name is input, the search unit refers to the facility name storage unit based on the facility name, acquires the facility name or abbreviation, and performs context determination processing from the Web document based on the facility name or the abbreviation A search step for extracting contributors who actually visited the facility,
The residence allocation step for obtaining the residence of each poster by referring to the user residence storage unit based on the extracted poster,
The destination store trade area calculation means obtains the name of the facility from the facility name storage means based on the name of the facility, obtains a threshold value that increases as the degree of name recognition increases, obtains the distance between the residence and the facility, A destination visit trade area calculation step in which only a residence whose distance is shorter than the threshold is a trade area;
A trade area determination method characterized by: A trade area determination method for determining a destination visit trade area from a residential area of a purpose visit customer who visits a certain facility with a purpose and an impulse visitor who visits impulsively,
Facility name storage means storing facility name and location information including abbreviations,
User residence storage means for storing user residence information;
Facility name storage means for storing the name of each facility,
In an apparatus having search means, residence allocation means, and destination store trade area calculation means,
When the facility name is input, the search unit refers to the facility name storage unit based on the facility name, acquires the facility name or abbreviation, and performs context determination processing from the Web document based on the facility name or the abbreviation A search step for extracting contributors who actually visited the facility,
The residence allocation means refers to the user residence storage means based on the extracted poster, obtains the residence of each poster, and counts the number of posters in a predetermined group unit An assignment step;
When the destination store trade area calculation means obtains the name of the facility from the facility name storage means based on the name of the facility, obtains a threshold that increases as the name increases, and arranges the groups in descending order of the number of contributors And a destination visit trade area calculation step in which the area corresponding to the top N groups whose cumulative composition ratio exceeds the threshold is the trade area,
A trade area determination method characterized by: Computer
A business area determination program for causing each of the means of the business area determination apparatus according to any one of claims 1 to 5 to function.

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