JP5313091B2 - System and method for creating information available for marketing - Google Patents

Description

  The present invention relates to a technique for creating information that can be used for marketing using a computer.

  It is common to perform marketing using some information. For example, in Patent Document 1, passengers staying at a station are estimated by reading a commuter pass section and passenger attribute information from a commuter pass read by a ticket gate at a station, estimating a train on which the passenger would have been riding. It is described that an advertisement corresponding to the attribute estimation result is displayed on the advertisement display of the station.

JP 2004-220498 A

  In general, there are many people who go out in the daytime, and the behavior during the time of going out varies. For example, there may be a long time traveling by means of transportation other than a train, and a long time using a store.

  Accordingly, an object of the present invention is to make it possible to create information that can be used for marketing not only to passengers on trains but also to persons other than passengers on trains.

  The information creation system includes a specifying unit and a creation unit. The identification means identifies each consumer located in the target area based on the target area information including the location information of the area that constitutes the target area based on the position of the target object and the current location information of each consumer. To do. The creation means refers to information representing a cluster pre-assigned to a consumer's residence area among a plurality of clusters that are a plurality of categories according to the attribute of the area, and a cluster of the consumer's residence area (residential cluster) And the target area cluster information representing the residence cluster of each consumer identified as being located in the target area is created. For example, the creation means can calculate a ratio for each residential cluster of consumers located in the target area, and can create information representing the ratio for each residential cluster as the target area cluster information.

FIG. 1 shows a computer system including an information creation server 300 to which an information creation system according to an embodiment of the present invention is applied. FIG. 2 shows an example of a relationship between a location and a neighborhood of the location. FIG. 3 shows the functions of the information creation server 300 and the flow of creating the location-specific cluster ratio information 270. FIG. 4 shows an example of the object information 220. FIG. 5 shows an example of the location neighborhood information 230. FIG. 6 shows an example of the mobile phone usage record information 210. FIG. 7 shows an example of the consumer information 240 by location. FIG. 8 shows an example of the consumer information 250. FIG. 9 shows an example of the neighborhood consumer information 260. FIG. 10 shows an example of the cluster ratio information 270 by location. FIG. 11 shows a modification of the cluster ratio information 270 by location. FIG. 12 shows an example of information representing the consumer ratio for each time zone.

  The purpose of marketing is to attract consumers to objects. In this embodiment, marketing support information for attracting a consumer who has moved within the vicinity of the position of the object to the object is created.

  The marketing support information in the present embodiment is information based on the characteristics of consumers located in the vicinity of the object, and for the creation of the information, the current location information of consumers and the attribute information of consumers are Necessary.

  As the current location information of the consumer, for example, information representing the location of the consumer's mobile phone can be employed.

  The consumer attribute information can be specified from, for example, detailed information on the user of the mobile phone (for example, information including the gender, age, mobile phone history, etc. of the user of the mobile phone).

  However, in the present embodiment, as consumer attribute information, data such as a national census or individual questionnaire is not used as consumer attribute information, but individual consumer attributes (such as gender and age) found in mobile phone user attribute information. Based on the above, information representing clusters of residential areas classified by characteristic attribute information relating to consumer's consumption preference and economic activity, which is separately analyzed and prepared in advance, is used. A “cluster” is a category of regional attributes (for example, what characteristics are there as a consumer or typical characteristics of the group). Each area is pre-assigned with a cluster of characteristic residents.

  That is, in this embodiment, based on the consumer's current location information, a consumer who has moved within the vicinity of the position of the object is identified, and the consumer's attribute is a cluster (hereinafter, The residential cluster) is applied. As a result, it is possible to specify the ratio of each consumer's residential cluster that has moved to the vicinity of the target object, and use information representing the ratio of each residential cluster to be used for marketing the target object. Specifically, for example, the largest proportion of residential clusters are regarded as clusters in the vicinity of the target object, and contents (for example, e-mail, flyers) corresponding to the cluster are given to consumers in the vicinity of the target object. Marketing can be done to provide for.

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

  FIG. 1 shows a computer system including an information creation server 300 to which an information creation system according to an embodiment of the present invention is applied.

  A display device 100 is provided on an object used by a consumer. Examples of the object include various points such as a boarding point for public transportation (for example, a station or taxi stop), a vehicle (for example, a train or taxi), a store, a vending machine, or an unmanned terminal (for example, MMS (Multimedia Station)). There are types. The display device 100 displays the distributed digital content. As will be described later, the distribution and display of digital content is a marketing method using the cluster ratio information 270 by location, and the method of using the information 270 is not limited to the distribution and display of digital content. . For example, marketing such as distributing a paper flyer or installing a billboard for advertising an object can be performed.

  The content distribution server 400 distributes digital content to the display device 100. The server 400 determines the digital content to be distributed and the display device 100 that is the distribution destination based on the content management information 510, the display device management information 520, and the location-specific cluster ratio information 270. The server 400 distributes the determined digital content to the determined display device 100 via the communication network 150.

  The information creation server 300 creates the cluster ratio information 270 by location. The location-specific cluster ratio information 270 is an example of the marketing support information described above. In this embodiment, the information 270 is used for distribution of digital content. The server 300 uses the information 200, 210, 220, 230, 240, and 250 shown in the figure to create neighborhood consumer information 260 that represents consumers near the location of the object, and based on the information 260, the location 300 Another cluster ratio information 270 is created.

  Servers 300 and 400 may be separate computers or the same computer. One server 300 or 400 may be realized by one computer, or may be realized by a plurality of distributed computers. The computer has a CPU and storage resources. The servers 300 and 400 can be realized by executing the computer program read from the storage resource by the CPU.

  The aforementioned information 200, 210, 220, 230, 240, 250, 260, 270, 510 and 520 are stored in one or more storage resources. The one or more storage resources may exist in one or more computers in which the servers 300 and / or 400 are realized, or may be an external storage device that can communicate with the one or more computers.

  The location-specific cluster ratio information 270 is used for digital content distribution (for example, a so-called digital signage system), but can also be used for other types of marketing instead of or in addition. For example, the consumer and information for promoting the use of the object (for example, e-mail) are determined based on the location-specific cluster ratio information 270, and the determined information is stored in the mobile phone possessed by the consumer. May be sent.

In order to create the cluster ratio information 270 by location, as will be described in detail later, the following information:
(A) Information representing the location,
(B) Information representing the neighborhood of the location,
(C) information representing the location of the consumer, and
(D) information representing the consumer's residence cluster;
is necessary.

  Here, “location” in the present embodiment refers to the position of an object.

  The “residential cluster” is a cluster that is assigned in advance to an area (residential area) including the residential area of the consumer. A cluster can be specified using cluster identification information (hereinafter referred to as cluster ID).

  “Region” is defined based on an address, for example. In the present embodiment, the area is a chome unit, but is not limited thereto, and may be another unit larger than the chome, such as a town unit or a city unit. Moreover, not all areas need be the same unit. Further, the area may be defined based on latitude and longitude instead of the address.

  Hereinafter, this embodiment will be described in more detail.

  FIG. 2 shows an example of a relationship between a location and a neighborhood of the location.

Based on information representing the location L (for example, an address and / or latitude / longitude), a neighborhood _{VL of} the location is defined. In the present embodiment, the neighborhood V _L is an information creation server based on information representing the location L and a predetermined rule (for example, a rule belonging to a range of radius X kilometers (X> 0) from the location L). 300, but instead or in addition, it may be manually defined by the operator.

The neighborhood _VL is composed of a plurality of regions 20A to 20J. The plurality of regions 20A to 20J include the region 20B including the location L, but the neighborhood V _L does not necessarily include the location L. Further, at least one of the plurality of regions 20A to 20J constituting the neighboring _VL may be a neighboring component of another location in addition to the neighboring _VL component. Further, the shape of the neighborhood _VL may not depend on the shape of the region. For example, a part of the area 20A may not be included in the neighborhood _VL .

  A cluster corresponding to an attribute (feature) of the region is assigned to each of the regions 20A to 20J.

In the present embodiment, as described above, but by location cluster ratio information 270 is created, the information 270 is information representative of the location proportion of each consumer residence clusters exist close V _L of L . In order to create this information 270, as described above, the consumer's current location information (specifically, the location information of the consumer's mobile phone) and the consumer's residence cluster ID are required.

  Hereinafter, functions of the information creation server 300 will be described, and then a flow of creating the location-specific cluster ratio information 270 will be described.

  FIG. 3 shows the functions of the information creation server 300 and the flow of creating the location-specific cluster ratio information 270.

  The server 300 has a location neighborhood information creation unit 301, a location neighborhood narrowing unit 302, a cluster ID addition unit 303, and a cluster ratio calculation unit 304.

  The location neighborhood information creation unit 301 creates location neighborhood information 230 based on the map address information 200 and the object information 220 including information representing the location, and stores the information 230 in a storage resource.

  Location neighborhood narrowing section 302 creates location-specific consumer information 240 based on location neighborhood information 230 and mobile phone usage record information 210 including information representing the position of the mobile phone, and stores that information 240 as a storage resource. To store.

  The cluster ID adding unit 303 creates the neighboring consumer information 260 based on the location-specific consumer information 240 and the consumer information 250 including the consumer residence cluster ID, and uses the information 260 as a storage resource. Store.

  The cluster ratio calculation unit 304 creates location-specific cluster ratio information 270 based on the neighboring consumer information 260 and stores the information 270 in a storage resource.

  Hereinafter, the various information 200, 210, 220, 230, 240, 250, 260, and 270 will be described, and then the flow until the location-specific cluster ratio information 270 is created will be described in detail.

  The map address information 200 is prepared in advance, for example. This information 200 is information relating to the map, for example, information indicating the address of each region, mutual positional relationship, scale, and the like. As this information 200, general map information can be adopted.

  The object information 220 is information regarding the object and includes information indicating the location. Specifically, for example, as shown in FIG. 4, the object information 220 includes, for each object, a location ID (LID), an object type / name, an address of the location, and a latitude / longitude of the location. Including. The address and the latitude / longitude correspond to information representing the location.

  The location neighborhood information 230 is information including information representing the neighborhood of the location. Specifically, for example, as shown in FIG. 5, the location neighborhood information 230 includes, for each location, a location ID, an object type / name, a location address, and one or more regions constituting the neighborhood. Address (which may or may not include the region containing the location).

  The mobile phone usage record information 210 is prepared in advance, for example. This information 210 is information related to the usage record of the mobile phone and includes information indicating the position of the mobile phone. Specifically, for example, as shown in FIG. 6, the mobile phone usage record information includes, for each consumer, consumer identification information, an address of a region (location) including the location of the mobile phone, and a location Date and time (from, hereinafter, intime) and date and time (to, hereinafter, outtime) when leaving the location. For example, IMSI (International Mobile Subscriber Identity) can be adopted as the consumer identification information. The date and time in FIG. 6 is a 10-digit number. The first two digits are the year, the second two digits are the month, the third two digits are the day, the fourth two digits are the hour, and the last two Digits represent minutes. Thus, for example, “0907210850” means 8:50 on July 21, 2009. From FIG. 6, it can be seen that the consumer “abcdefg” has moved from the area “CC town DD town, BB city, Chiba prefecture” to “EE town area, CC town, BB city, Chiba prefecture”.

  Note that the location information of the mobile phone may be detected periodically, for example, and the mobile phone usage record information 210 may be updated. The position information of the mobile phone may be detected by a method such as using a GPS (Global Positioning System) signal.

  The location-specific consumer information 240 is information indicating the location where the region where the consumer is located is included in the neighborhood of the location. Specifically, for example, as shown in FIG. 7, the location-specific consumer information 240 includes, for each consumer, a location that includes in-time, out-time, a street address, and the location of the consumer as neighbors. ID.

  The consumer information 250 is information about consumers, for example, information about users of mobile phones. Specifically, for example, the consumer information 250 includes, for each consumer, consumer identification information, an address representing a place of residence, and an ID of a cluster of the place of residence. This information 250 is prepared in advance, for example. Of the consumer information 250, the consumer identification information and the address are information managed by the mobile phone company, and the residence cluster ID is not included in the information managed by the mobile phone company, so it is given separately. It is. In this embodiment, consumer information 250 to which a residence cluster ID corresponding to a consumer's residence is assigned in advance is prepared, but the present invention is not limited to this. For example, regional information representing an address for each region and a residence cluster ID (cluster ID assigned according to the region attribute) is prepared separately, and the neighborhood consumer information 260 described later is created. The residence cluster ID corresponding to the consumer's residence address may be obtained from the regional information.

  The neighborhood consumer information 260 is information (for example, a database) related to consumers in the neighborhood of the location, and is information created for each location. FIG. 9 shows neighboring consumer information 260 corresponding to a certain location (location of location ID: 001-111). The neighborhood consumer information 260 includes, for example, consumer identification information, in-time, out-time, a residence address, and a residence cluster ID for each consumer.

  The location-specific cluster ratio information 270 is also information (for example, a database) created for each location. FIG. 10 shows cluster ratio information 270 corresponding to a certain location (location ID “001-111”). The cluster ratio information 270 includes, for example, the type and name of the object and the ratio for each residential cluster ID of the consumer who is in the vicinity of the location. For example, if there are 100 consumers in the vicinity and 20 of them are consumers of the residence cluster ID “C02”, the ratio of the residence cluster ID “002” is 20/100 = 0. 2.

  In addition, it replaces with the information 270 being created for every location, and the information 270 may have the ratio for every residence cluster ID about all the locations.

  Hereinafter, with reference to FIG. 3 to FIG. 10, the flow until the location-specific cluster ratio information 270 is created will be described in detail.

  First, as shown in FIG. 3, location neighborhood information 230 is created. Specifically, for example, the following steps (1-1) to (1-5) are performed for each location.

  (1-1) The location neighborhood information creation unit 301 receives a location specification (for example, receives a specification from an operator). The information input to specify the location may be any information as long as the information can identify the location. For example, as the information, a location address, a type / name of an object, or a detailed address including an address and a number can be considered.

  (1-2) The creation unit 301 acquires the specified location ID, type / name, and address (for example, the information group 401 shown in FIG. 4) from the object information 220, and uses them as the location neighborhood information 230. (See FIG. 5).

  (1-3) The creation unit 301 determines a plurality of areas that constitute the neighborhood of the location based on the acquired address of the location and a predetermined rule (hereinafter, neighborhood determination rule).

  (1-4) The creation unit 301 acquires each address of the determined plurality of areas from the map address information 200.

  (1-5) The creation unit 301 sets the step (in the row having the location ID, the type / name, and the address (information group 401) added in step (1-2) in the location neighborhood information 230 (see FIG. 5). Each address acquired in 1-4) (the address of each area constituting the neighborhood) is added.

  The neighborhood determination rule may be common to all locations or may be different depending on the attributes (eg, address and / or type) of the object. For example, a neighborhood determination rule for an object included in an area group with a small population (for example, a prefecture) is a rule that makes a wide neighborhood, and an object included in an area group with a large population The neighborhood determination rule may be a rule that makes a narrow neighborhood.

  Now, as shown in FIG. 3, the location-specific consumer information 240 is created. Specifically, for example, the following (2-1) to (2-3) are performed for each consumer.

  (2-1) The location neighborhood narrowing-down unit 302 acquires an information group (for example, an information group 601) in a certain line from the mobile phone performance information 210 (see FIG. 6), and stores them in the consumer information 240 by location. It adds (refer FIG. 7).

  (2-2) The narrowing-down section 302 refers to the location neighborhood information 230 (see FIG. 5) by using the location address added to the information 240 (see FIG. 7) in step (2-1) as a key, and the location The location ID corresponding to the address is specified from the location neighborhood information 230. Specifically, for example, as shown by a solid line frame in FIG. 7, when the location address that is a key is “BB city CC town DD chome” in the information group 601, the address is shown in FIG. As indicated by the solid line frame, since it is included in the first line of the information 230, the location ID “001-111” (see the broken line frame) in that line is specified.

  (2-3) The narrowing-down unit 302 uses the location ID (see the broken line frame) identified from the information 230 in FIG. 5 in step (2-2) as the key location address (solid line) in the information 240 in FIG. Is added to the line including the frame reference (see the broken line frame in FIG. 7).

  Next, as shown in FIG. 3, neighborhood consumer information 260 is created for each location. Specifically, for example, the following (3-1) to (3-3) are performed for each location.

  (3-1) The cluster ID adding unit 303 selects an unselected location ID (for example, “001-111”) from among a plurality of types of location IDs included in the location-specific consumer information 240 (see FIG. 7). , Hereinafter, blank neighborhood consumer information 260 having no detailed information is prepared for the target location ID).

  (3-2) The adding unit 303 includes consumer identification information corresponding to the target location ID, in-time, and out-time in the location-specific consumer information 240 (see FIG. 7) (see the dashed line frame in FIG. 7). Is added to the neighboring consumer information 260 prepared in step (3-1) (see the one-dot chain line in FIG. 9). Step (3-2) is performed for each consumer corresponding to the target location ID.

  (3-3) The adding unit 303 sets the residence address and residence cluster ID corresponding to the consumer identification information added to the neighboring consumer information 260 (see FIG. 9), and the consumer information 250 (see FIG. 8). And the acquired residence address and residence cluster ID are added to the neighborhood consumer information 260. For example, when the consumer identification information is “abcdefg” in the one-dot chain line frame in FIG. 9, “YT-machi RE chome, HU City, Yamanashi Prefecture” and “C08” in the two-dot chain line frame from the information 250 in FIG. 8. Are added to the neighboring consumer information 260 (see the two-dot chain line in FIG. 9). Step (3-3) is performed for each consumer added to the neighborhood consumer information 260.

  The location-specific cluster ratio information 270 is created using the neighborhood consumer information 260 for each location created in this way. Specifically, for example, the following (4-1) and (4-2) are performed for each neighborhood consumer information 260.

  (4-1) The cluster ratio calculation unit 304 refers to the neighboring consumer information 260 and counts the number of consumers for each residence cluster ID included in the information 260.

  (4-2) The calculation unit 304 totals the number of consumers (count value) for each residence cluster ID, and for each residence cluster ID, based on the total and the number of consumers for each residence cluster ID. And the location-specific cluster ratio information 270 representing the result is created.

  Based on the location-specific cluster ratio information 270, the ranks of the cluster IDs in the vicinity of the location corresponding to the information 270 can be set in descending order of the ratio of the residence cluster ID. For example, the ratio of the residential cluster ID “C08” is “0.3”, the ratio of the residential cluster ID “C10” is “0.5”, and the ratio of the residential cluster ID “02” is “0.2”. In this case, the order of the cluster ID is C10, C08, C02 in descending order.

  Based on the cluster ID order determined in this way, digital content can be distributed.

  For example, it is assumed that the content management information 510 illustrated in FIG. 1 includes a content ID and a cluster ID for each digital content. Further, for example, it is assumed that the display device management information 520 illustrated in FIG. 1 includes an address and a location ID for each display device 100. Then, for example, the first-ranked cluster ID identified from the location-specific cluster ratio information 270 corresponding to the location L shown in FIG. 2 is “C10”.

  In this case, the content distribution server 400 refers to the location-specific cluster ratio information 270 corresponding to the location L and identifies the first-ranked cluster ID “C10”. Further, the server 400 identifies the display device address corresponding to the location ID of the location L from the display device management information 520 and identifies the content ID corresponding to the first cluster ID “C10” from the content management information 510. To do. Then, the server 400 distributes the digital content identified from the identified content ID to the display device 100 having the identified address.

  In this embodiment, for the sake of easy understanding, only the first cluster ID of the plurality of cluster IDs for the neighborhood of the location is considered. However, instead of or in addition to the first cluster ID, other May be considered.

  As described above, according to the above-described embodiment, each consumer located in the neighborhood of the location and the residence cluster ID of each consumer are specified, and the neighborhood of the location is assigned in advance to the area constituting the neighborhood. A residence cluster ID different from the residence cluster ID is obtained. As a result, information representing the ID of another residence cluster (a cluster different from the neighboring cluster of the location) ID, specifically, the cluster ratio information by location 270 is created as information usable for marketing. be able to.

  The embodiment of the present invention described above is an example for explaining the present invention, and is not intended to limit the scope of the present invention only to the embodiment. The present invention can be implemented in various other modes without departing from the gist thereof.

  For example, as described above, distribution of digital content is only one example of use of the cluster ratio information 270 by location, and the information 270 can be used for other purposes.

  Further, for example, the order of the residential cluster IDs for the neighborhood may be determined by another method in addition to or instead of the above method. For example, based on location information (for example, an address) of a mobile phone, a ratio (rank) for each residence cluster ID may be calculated for each region that constitutes a neighborhood. And the number which became the 1st place may be calculated for every residence cluster ID, and the order with the largest number may be made into the order of residence cluster ID about a neighborhood.

  Further, the cluster ratio information 270 by location is calculated based on the neighboring consumer information 260. However, since the ratio for each residence cluster ID can be calculated using the neighboring consumer information 260, the cluster ratio information 270 by location is used instead. Thus, the neighborhood consumer information 260 can be used for marketing. For example, the ratio for each residence cluster ID may be included in the neighborhood consumer information 260.

  In addition, based on the in-time and out-time for each consumer, it is grasped what percentage the location was in a certain period, and the weight of the consumer's residence cluster ID is set based on the grasp result May be. And when calculating the ratio for each residence cluster ID, the set weight may be taken into consideration.

  Further, for example, based on the in-time and out-time for each consumer included in the mobile phone usage record information 210, as illustrated in FIG. 11, for a certain period (for example, one day or one week) for each location. The ratio for each residence cluster ID may be calculated for each time zone.

  Furthermore, for example, as illustrated in FIG. 12, the consumer ratio for each time zone may be calculated. For example, the number of consumers is calculated for each time period, the total number of consumers for a certain period is calculated based on the number of consumers for each time period, and the total number of consumers and the number of consumers for each time period are calculated. In addition, the consumer ratio for each time zone may be calculated.

300 ... Information creation server

Claims (7)

A consumer that identifies each consumer located in the target area based on the target area information including the location information of the area constituting the target area based on the position of the object and the current location information of each consumer Specific means,
The residence of each consumer identified as being located in the target area with reference to information representing a cluster assigned to the consumer's residence area among a plurality of clusters that are a plurality of categories according to the attribute of the area An information creation system comprising: cluster information creation means for identifying a cluster in a region and creating target area cluster information representing the identified cluster of each consumer identified as being located in the target area. The information creation system according to claim 1,
The target area information includes position information of regions constituting the target area for a plurality of target areas respectively corresponding to a plurality of objects,
The consumer specifying means specifies which consumer is located in which target area based on the target area information and the current location information of each consumer,
The cluster information creation means identifies, for each object, a cluster of each consumer identified as being located in the target area, and the identification of each consumer identified as located in the target area Create target area cluster information representing the created cluster,
Information creation system. An information creation system according to claim 2,
The target area of the target is determined based on the position of the specified target and the target area determination rule corresponding to the attribute of the specified target among a plurality of target area determination rules, and the specified Further comprising area information creating means for creating the target area information representing the determined target area for the determined object.
Information creation system. The information creation system according to any one of claims 1 to 3,
The cluster information creation means calculates a ratio of consumers located in the target area for each cluster and / or a ratio of consumers located in the area for each area constituting the target area. And
The target area cluster information includes information indicating the calculated ratio for each cluster,
Information creation system. An information creation system according to claim 4,
The cluster information creating means calculates the ratio of each cluster for each time zone based on the date and time information for each consumer's current location,
The target area cluster information includes information representing the ratio of each cluster for each time zone,
Information creation system. The computer identifies each consumer located in the target area based on the target area information including the location information of the area that constitutes the target area based on the position of the object and the current location information of each consumer. And steps to
Computer, by referring to the information indicating the cluster assigned to the area of residence of the consumers of the plurality of clusters is a plurality of categories according to the attributes of the region, each consumer identified as located in the target area And creating target area cluster information representing the identified cluster of each consumer identified as being located within the target area. Identifying each consumer located in the target area based on target area information including location information of a region constituting the target area based on the position of the target object and current location information of each consumer; ,
The residence of each consumer identified as being located in the target area with reference to information representing a cluster assigned to the consumer's residence area among a plurality of clusters that are a plurality of categories according to the attribute of the area A computer program for identifying a regional cluster and causing the computer to execute target area cluster information representing the identified cluster of each consumer identified as being located within the target area.

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