JP5466097B2 - Consumer attribute information acquisition system and consumer attribute information acquisition method - Google Patents

Description

  The present invention relates to a consumer attribute information acquisition system that associates consumer attribute information obtained from questionnaires from consumers and public information on the Internet web with sales information of vending machines, and realizes a highly accurate marketing measure, and Concerning consumer attribute information acquisition.

  In general, for vending machine product sales, obtain consumer attribute information including consumer profile such as gender, age, purchase time, etc. of consumers who purchase the product, and consumer preferences and motivation items for product purchase. In addition, it is desired to realize a highly accurate marketing measure in which selection of sales products, product quantity, product replenishment cycle, and advertisement target products are selected based on the consumer attribute information. For this reason, in the prior art, marketing activities using various analysis methods are widely performed. For example, a consumer questionnaire is analyzed by data mining to classify consumers into similar segments. In the case of consumer segmentation, for example, “I like actor A” “Drink canned coffee in the morning” “Buy tea with plastic bottles” “I like blue” “Watch movies” "Watch TV well", "Hobby", "Favorite color", "Favorite fragrance", "Purchase motivation", "Where to buy well", "Favorite brand", etc. Measures are being taken, such as “broadcasting canned commercials in the early morning”.

  On the other hand, in the prior art, sales information of vending machines is analyzed, and vending machines are classified into similar segments. For example, in the case of vending machine segmentation, “canned coffee sells well in the morning” “tea bottles in tea” Are sold well on holidays, etc., and by segment analysis, such as "Vending machines that can sell canned coffee well in the morning, replenish a sufficient number of canned coffee by the previous night to prevent loss of sales opportunities." Measures are being taken.

  However, in the conventional technology, the results obtained from the consumer questionnaire processing (consumer segmentation) and the results obtained from the vending machine sales information (vending machine segmentation) are compared. A system that can obtain consumer attribute information that cannot be obtained is not considered.

  In addition, a vending machine operating system that provides consumer questionnaire counting means in a vending machine and sells products according to consumer preference according to the questionnaire results tabulated using premiums is disclosed in Patent Document 1 below. Have been described.

JP 2002-251666 A

  Although the technology described in Patent Document 1 described above can aggregate consumer preferences using a touch panel attached to a vending machine and provide products according to the results of the aggregation, the consumer can There is a problem that it is necessary to answer a questionnaire, and further, it is necessary to prepare a questionnaire collecting means for collecting the questionnaire and a gift for the consumer.

  In recent years, marketing support software that implements various statistical methods has been sold. For example, a consumer questionnaire is conducted, and the results of the questionnaire are analyzed using the marketing support software. It can be used to create a large-scale data warehouse, analyze sales results, and use them in sales strategies. However, there has been a problem that the result obtained from the processing of the consumer questionnaire cannot be combined with the result obtained from the sales information of the vending machine. These problems are the same in a small-scale store where a POS (Point Of Sales) system is not introduced. In particular, stores that cannot introduce POS systems with attributes such as IC cards and point cards have this problem.

  The object of the present invention is to solve the above-mentioned problems of the prior art, and obtained from other methods such as questionnaires even for small stores and vending machines that can only obtain sales data without consumer attributes. It is to provide a consumer attribute information acquisition system and a consumer attribute information acquisition method capable of providing a manager with vending machine strategy information of a store or a vending machine by associating consumer attributes.

In order to achieve the above object, the present invention according to claim 1 includes consumer attribute information including consumer preference product ranking, purchase location ranking, and consumer profile, sales ranking by location of the vending machine, and location ranking. A consumer attribute information acquisition system comprising an information association server and an information association database for outputting sales strategy information of products in a specific vending machine based on vending machine sales information including information,
The information association database is
A consumer classification procedure repository unit storing a procedure for classifying the consumer attribute information combining consumer preference product ranking and purchase place ranking based on questionnaire information from consumers for each consumer segment category; ,
Stores the procedure for classifying the vending machine sales information into the vending machine segment classification, which combines the sales ranking and location ranking of the vending machine by product based on the sales results and location information from the vending machine by product. Vending machine classification procedure repository part,
A consumer classification table unit for storing the consumer attribute information;
A vending machine classification table section that stores the vending machine sales information; a coefficient calculation procedure repository section that stores a procedure for calculating a correlation coefficient for each combination of the consumer segment classification and the vending machine segment classification;
An inter-segment correlation coefficient result storage unit for storing a correlation coefficient for each combination of the segment classifications calculated by the coefficient calculation procedure repository unit;
Classification processing master table storing a procedure for outputting vending machine strategy information including a correlation coefficient for each combination of the consumer segment classification and the vending machine segment classification stored in the inter-segment correlation coefficient result storage section And
The information association server calculates a correlation coefficient for each combination of the consumer segment category and the vending machine segment category with reference to the procedure stored in the classification processing master table unit, and between the calculated segment category combinations The first feature is to output vending machine strategy information including a correlation coefficient for each vending machine.

  The invention according to claim 2 is a system log in which, in the consumer attribute information acquisition system having the features described above, the consumer attribute information records public information published on the Internet web and trends in consumer purchases. The consumer classification procedure repository unit includes a procedure for storing consumer attribute information based on the questionnaire information from the consumer, the public information, and the system log information in the consumer classification table unit. It is characterized by.

  The invention according to claim 3 is the consumer attribute information acquisition system according to any one of the above features, wherein the questionnaire information and the public information include feature information of consumer sex, age and preference information, and the information association server includes: Vending machine strategy information including the correlation coefficient between the calculated combinations of segment categories and the feature information is output.

  According to a fourth aspect of the present invention, in the consumer attribute information acquisition system according to any one of the above features, the consumer associated with a correlation coefficient between the segment category combinations calculated by the information association server is larger than a predetermined value. A combination of the segment category and the vending machine segment category is stored.

According to a fifth aspect of the present invention, in the consumer attribute information acquisition system according to any one of the above features, the consumer attribute information includes purchase timing information for purchasing a consumer product, and the vending machine sales information is an automatic sale. including the time zone information that goods have been sold of the machine, in that the information associated with the server, to select a segment Classification set only combination of time zone information of the purchase timing information and the vending machine sales information of the consumer attribute information Features.

The invention described in claim 6 includes consumer attribute information including consumer preference product ranking, purchase place ranking, consumer profile, vending machine sales information including information on sales ranking and location ranking of vending machines by product, The consumer attribute that combines the information association server that outputs the sales strategy information of the product in a specific vending machine, and the consumer's favorite product ranking and purchase place ranking based on the questionnaire information from the consumer The consumer classification procedure repository section that stores the procedure for classifying information for each consumer segment category, the sales ranking by product and the location ranking of the vending machine based on the sales results and location information by product from the vending machine Stored procedures to classify the combined vending machine sales information into vending machine segment categories Vending machine classification procedure repository section, consumer classification table section for storing the consumer attribute information, vending machine classification table section for storing the vending machine sales information, the consumer segment classification and the vending machine segment classification Coefficient calculation procedure repository unit storing a procedure for calculating a correlation coefficient for each combination of segments, inter-segment correlation coefficient result storing a correlation coefficient for each combination of the segment classifications calculated by the coefficient calculation procedure repository unit A classification storing a procedure for outputting vending machine strategy information including a correlation coefficient for each combination of the consumer segment classification and the vending machine segment classification stored in the storage section, the inter-segment correlation coefficient result storage section A consumer attribute information acquisition system comprising an information association database having a processing master table section A user attribute information acquisition method,
A step of calculating a correlation coefficient for each combination of the consumer segment category and the vending machine segment category with reference to the procedure of the classification processing master table unit in the information association server, and the segment category calculated by the step And a step of outputting vending machine strategy information including a correlation coefficient for each vending machine between the combinations.

  The invention according to claim 6 is the system log information in which, in the consumer attribute information acquisition method having the characteristics described above, the consumer attribute information is public information published on the Internet web and the consumer's purchase trends are recorded. And storing the consumer attribute information based on the questionnaire information from the consumer, the public information, and the system log information in the consumer classification table part in the consumer classification procedure repository part. It is made to perform.

  The invention according to claim 7 is the consumer attribute information acquisition method according to any one of the features, wherein the questionnaire information and the public information include feature information of a consumer's sex, age, and preference talent, and the information association database includes: A step of outputting a correlation coefficient between the calculated combinations of segment categories and vending machine strategy information including the feature information is executed.

  The invention according to claim 8 is the consumer attribute information acquisition method according to any one of the above characteristics, wherein the information association server causes the consumer to have a correlation coefficient between the calculated combinations of segment classifications larger than a predetermined value. A step of storing a combination of the segment category and the vending machine segment category is executed.

The invention according to claim 10 is the consumer attribute information acquisition method according to any one of the above features, wherein the consumer attribute information includes purchase timing information for purchasing a consumer product, and the vending machine sales information is an automatic sale. including the time zone information that goods have been sold of the machine, to the information associated with the server, the step of selecting a segment Classification set only combination of time zone information of the purchase timing information and the vending machine sales information of the consumer attribute information It is characterized by performing .

  In the consumer attribute information acquisition system and the consumer attribute information acquisition method according to the present invention, the information association database refers to the procedure of the classification processing master table unit, and the correlation for each combination of the consumer segment classification and the vending machine segment classification The vending machine administrator outputs the vending machine strategy information including the correlation coefficient for each vending machine between the calculated combinations of segment classifications. Vending machine sales strategies can be easily constructed based on large consumer attribute information.

The figure which shows the structure of the consumer attribute information acquisition system by embodiment of this invention. The figure which shows the consumer attribute information classification | category whole process by embodiment of this invention. The figure which shows the consumer classification table part 121 by embodiment of this invention. The figure which shows the consumer information collection process by the questionnaire by embodiment of this invention The figure which shows the classification process master table part 122 by embodiment of this invention. The figure which shows the consumer classification procedure repository part 123 by embodiment of this invention. The figure which shows the consumer classification questionnaire process by embodiment of this invention The figure which shows the consumer classification procedure process by embodiment of this invention The figure which shows the vending machine attribute information classification | category whole process by embodiment of this invention. The figure which shows the vending machine classification | category table part 124 by embodiment of this invention. The figure which shows the vending machine classification | category procedure repository part 126 by embodiment of this invention. The figure which shows the vending machine classification | category process by embodiment of this invention. The figure which shows the vending machine classification | category procedure process by embodiment of this invention. The figure which shows the correlation coefficient calculation process between the segments by embodiment of this invention. The figure which shows the tied process between segments by embodiment of this invention The figure which shows an example of the correlation coefficient result storage part 127 between segments by embodiment of this invention. The figure which shows the correlation coefficient calculation procedure repository part 128 between the segments by embodiment of this invention. The figure which shows the matching process combination selection process by embodiment of this invention The figure which shows the correlation coefficient calculation process between segments by embodiment of this invention. The figure which shows the segment division | segmentation link | linking process by embodiment of this invention The figure which shows the other example of the correlation coefficient result storage part 127 between segments by embodiment of this invention. The figure which shows the correlation coefficient preservation | save procedure repository part 129 by embodiment of this invention. The figure which shows the selection process of the correlation coefficient calculation between segments by embodiment of this invention. The figure which shows the flow of the consumer attribute information acquisition process by embodiment of this invention The figure which shows the vending machine strategy information by embodiment of this invention.

Hereinafter, the consumer attribute information acquisition system and the consumer attribute information acquisition method according to the present invention will be described in detail. First, the principle of the present invention will be described.
[principle]
First, in the prior art, when a product is sold in a vending machine, although it is possible to obtain sales information such as the quantity, date time, and installation location of the product sold, the gender of the consumer who purchased this product, Consumer attribute information of consumers such as age and hobby preferences could not be obtained, and it was difficult to select a product to be put into a vending machine and to perform marketing activities such as a product quantity and a time zone. On the other hand, from consumer questionnaire information, public information obtained from websites (blogs) on the Internet in recent years, and system log information obtained from human body sensors installed on product display shelves, etc., consumer gender, age, and hobby preferences It is known that other consumer attribute information can be obtained.

  The present invention pays attention to the sales information from the vending machine and the consumer attribute information from the questionnaire, etc., and the sales information and the consumer attribute information are viewed from a plurality of viewpoints (in the case of beverages, for example, “drinking timing”, “ In this application, this viewpoint is referred to as a segment.) Based on this, this segmentation process divides consumers into multiple segments that have similar needs and preferences. And comparing the sales information segment based on the sales information and the consumer attribute information segment based on the consumer attribute information in order to determine which segment is important in marketing strategy. Calculating the correlation coefficient of the system, and providing the administrator with vending machine strategy information as to whether a combination between segments having a large correlation coefficient is good. It by, to do things to support a valid vending machine strategy to the vending machine and the basic principles of treatment.

  In the consumer segmentation process and the vending machine segmentation process described above, the segmentation method can assume several patterns (segments). For example, in the vending machine segmentation process, “coffee” and “fruit juice” Classification (segmentation) by “beverage type”, etc., classification (segmentation) by “container type” such as “500 ml PET bottle” and “350 ml can”, “Cola”, “green tea”, etc. It is conceivable to classify (segmentation) by “common name”. Similarly, in the consumer segmentation process, classification (segmentation) by “time to drink” such as “before commuting” and “after meal” or “everyone drinks” "Who drinks alone" such as "Drink alone" Therefore, it is conceivable to classification (segmentation).

  In the present invention, as the vending machine strategy information, for example, the correlation coefficient between the consumer segmentation segment “purchase timing” “full after meal” and the optional vending machine segment category “selling time zone” If larger than other categories, it can be assumed that many of the consumers of any of the vending machines are “full after meal” consumers, and this “full after meal” consumer segment category When consumer attribute information such as “Actress A likes” and “Coffee C (black)” is registered as consumer characteristics, “Poster of actress A is heavily used” “Kohi” Vending machine strategy information such as setting a larger quantity of “C (black)” can be provided to the administrator. The system log information refers to information such as trends in consumer product purchases by electronic devices such as human body sensors and RFID (Radio Frequency IDentification) tags attached to products.

  Specifically, if a consumer survey reveals that a consumer buying a tea plastic bottle A product is likely to be "a female office worker and spend a day buying before going to work in the morning" Among vending machines belonging to the vending machine segment that sells well in the morning work hours, measures such as “place more products A in vending machines near stations and office buildings” can be taken. If consumers found that there is a strong tendency to “like Actor D,” consumers who purchase the plastic bottle B product in the vending machine segment belonging to the vending machine segment where product B sells well, It is possible to take measures such as “aim to further increase sales through frequent use”. Details of the embodiment of the present invention will be described below.

[Constitution]
As shown in FIG. 1, the overall configuration of the consumer attribute information acquisition system according to the present embodiment includes questionnaire information 101 collected from consumers, public information 102 published on the Internet web, and system logs collected by human body sensors and the like. A control unit that receives information 103, calculates a correlation between sales information from the vending machine and consumer attribute information from a questionnaire or the like as a correlation coefficient, and provides vending machine strategy information to an administrator; And an information association database 120 that stores various information for providing the vending machine strategy information. The information association database 120 is a group of consumer groups with similar purchasing behavior. A consumer classification table that stores information such as preference products and purchase locations corresponding to the contents of the classified consumer segments. , A consumer classification procedure repository unit 123 storing a procedure for classifying consumers for each combination of segment classification contents described later based on questionnaire information from consumers, etc., and a consumer by a vending machine Vending machine corresponding to the product purchase pattern (coffee-centric type, fruit-centric type, capacity type, morning type, night type, etc.) Automatic sales storing sales rankings and location rankings corresponding to the segment segment contents Vending machine classification table section 124, vending machine classification procedure repository section 126 storing a procedure for classifying each segment classification based on sales information from vending machines, consumer segment classification contents and vending machines Inter-segment correlation coefficient result storage unit 127 that stores correlation coefficient calculation results for combinations of segment classification contents , A coefficient calculation procedure repository unit 128 that stores a procedure for calculating the correlation coefficient between the segment classification contents, and a correlation coefficient storage procedure repository that stores a procedure for storing the correlation coefficient between the segment classification contents And a classification processing master table unit 122 that stores procedure information for calculating the correlation with reference to the information of each table unit and providing the vending machine strategy information to the administrator. In the present embodiment, the configurations of the information association server 110 and the information association database 120 are configured by hardware such as a computer memory and software that executes predetermined processing.

  In addition, the segment described in this application is a group of consumers who have common needs in the market and are similar in purchasing behaviors such as how to recognize products, value them, and processes leading to purchasing. Segmentation refers to dividing an unspecified number of people into groups (segments) having the same needs and properties based on the results of marketing environment analysis.

  The consumer classification table unit 121 stores consumer attribute information in which segment classifications for a plurality of consumer segmentation names, preference product rankings, purchase place rankings, and features are associated with each other based on the result of marketing environment analysis. As shown in FIG. 3, the segment classification is “Purchase Timing” and the Favorite Product Ranking is “No. 1 Tea A” and “No. 2 Coffee B” against the consumer segmentation name “Purchase Before Commuting”. "..., where the purchase place ranking is" No. 1 in front of the station "," No. 2 in the building ", and the features are" 1 Female "," 2 Young ", etc. More specifically, the consumer classification table unit 121 purchases the product “tea A” at a place “Ekimae” in the case of a “purchase before commuting” consumer based on the result of the marketing environment analysis. Consumer attribute information such as “young” and “female” is stored.

  The consumer classification procedure repository unit 123 stores a procedure for classifying consumers for each segment classification based on information from a questionnaire from consumers. As shown in FIG. ”Is input data, the parameter is“ Para1.txt ”, the process“ 1 ”is executed, the procedure“ 1 ”using“ questionnaire total.txt ”as output data,“ questionnaire total.txt ”is input data, and the parameters are The process “2” is executed as “Para2.txt”, and the procedure “2” using “consumer segment.db” as output data is sequentially executed.

  The vending machine classification table unit 124 includes a segment classification, a sales performance (product) ranking, a location ranking, and a feature for a plurality of vending machine segmentation names based on a result of analysis of sales performance of the vending machine. Corresponding information is stored, and as shown in FIG. 10, the segment classification is “1 type” and the sales performance ranking is “1st coffee B” and “2” for the vending machine segmentation name “Coffee-centric”. Corresponding information such as “Coffee C”, etc., and the location ranking “No. 1 in front of the station” and “No. 2 in the building” are stored. More specifically, the vending machine classification table unit 124 is based on the results of sales by the vending machine. For example, in the case of a “Kohi-centric” vending machine, the product “Kohi B” is located in the “Ekimae” location. In the case of a “fruit juice centered” vending machine, sales information is stored indicating that the product “Lemon M” is sold in the “building” location.

  The vending machine classification procedure repository unit 126 stores a procedure for classifying vending machines into segments based on sales information from vending machines. As shown in FIG. Process “1” is executed with “Vending machine information” as input data and parameters as “Para3.txt”, and “POS total.txt” is output data “Procedure“ 1 ”and“ POS total.txt ”. Another procedure is executed in which the process “2” is executed with the input data and parameters set to “Para4.txt”, and the procedure “2” using “vending machine segment.db” as output data is sequentially executed.

  The inter-segment correlation coefficient calculation result storage unit 127 stores correlation coefficients for all combinations among segment segments of a plurality of vending machine segmentations for a specific consumer segmentation. For example, FIG. As shown, the correlation coefficient between the vending machine segment category “Selling time” is stored for the consumer segment category “Purchase timing”, and in this example, the vending machine segment “Purchase timing” is automatically sold. 21 shows that the correlation coefficient between the machine segment classification “morning type” and “day type” is high, and the correlation coefficient for all combinations between the consumer segment classification and the vending machine segment classification is shown in FIG. As shown, multiple segments of vending machine segmentation for the consumer segment category “purchase timing” Storing a correlation coefficient of cement segment. Note that the procedure information of the plurality of procedure repository units may be stored in one procedure repository unit.

[Operation]
[Overall operation]
Next, the overall operation of the consumer attribute information acquisition system according to this embodiment will be described. In the consumer attribute information acquisition system according to the present embodiment, the control unit of the information association server 110 acquires vending machine information (sales information) as shown in FIG. 24, and the segmentation process of this vending machine information Step S502, step S503 in which the vending machine segmentation information segmented in step S502 is aggregated and stored in the vending machine classification table unit 124 (FIG. 10) as sales information, a questionnaire from the consumer, etc. Step S504 for acquiring consumer information, Step S505 for performing segmentation processing of this consumer information, and the consumer segmentation information segmented by this step S505 as consumer attribute information in the consumer classification table unit 121 ( Step S506 that is aggregated and stored in 2), step S507 that calculates the correlation coefficient between the aggregated vending machine segment and the consumer segment, and the correlation coefficient based on the correlation coefficient calculated in Step S507 Step S508 for selecting a combination for associating a vending machine and a consumer segment classification with a value greater than a predetermined value, and comparing and selecting the vending machine segment assigned to the vending machine classification table unit 124 and the consumer segment. Step S509, step S510 for extracting by referring to the consumer characteristics and features assigned to the consumer classification table unit 121, and the extracted consumer features for each vending machine by the product sales strategy information for each vending machine By executing step S511 that is output as (FIG. 25), it is effective for the vending machine. It is possible to support the vending machine strategy. Next, the details of the above steps will be described.

[Consumer segmentation process]
As shown in FIG. 2, the consumer segmentation process in step S505 includes a step 014 in which the control unit of the information association server 110 stores the questionnaire information 101, the public information 102, and the system log information 103 in the information disclosure database 120; A plurality of consumer segmentations by performing step 015 for performing segmentation processing by a technique such as cluster analysis (dividing a set to be classified into subsets that achieve internal coupling and external separation) Are classified into consumer segment categories 016 to 018 and stored in the consumer classification table unit 121 as consumer attribute information.

  As shown in FIG. 7, a specific example of the consumer segmentation process in step 015 is as follows. The control unit of the information association server 110 receives the questionnaire information 601 from the consumer according to the process procedure registered in the classification process master table part 122. Input according to the procedure stored in the classification procedure repository unit 123 (FIG. 6), classify the input information by a technique such as cluster analysis, and classify the classified information into the consumer segment. This is done by outputting as db.

  As shown in FIG. 4, the consumer attribute information stored in the consumer classification table unit 121 includes step S301 for collecting consumer information such as a questionnaire, and the segmentation processing is performed on the collected consumer information. Step S302 to be performed and step S303 in which the information on which the segmentation processing has been performed are updated to the consumer classification table unit 121. This processing procedure is performed by the control unit of the information association server 110 by the classification shown in FIG. Refer to “Order”, “Input Data”, “Processing (Processing Number in FIG. 5)”, “Output Data”, and “Processing Parameters” registered in the consumer classification procedure repository unit 123 in accordance with the procedures registered in the processing master table unit 122. While done.

[Vending machine segmentation processing]
As shown in FIG. 9, the vending machine segmentation process in step S502 stores vending machine location information 081, vending machine attribute information 082, and vending machine sales information 083 in the information association database 120; Vending machine segmentation is performed by performing step 085 for performing segmentation processing by a technique such as cluster analysis (dividing the set to be classified into subsets in which internal combination and external separation are achieved). This is done by dividing into a plurality of consumer segment categories 086 to 088 and storing them in the vending machine classification table unit 124. The vending machine segmentation in step 085 is similar to, for example, “coffee-centered type”, “fruit-centered type”, etc., in which the vending machine is divided into several similar segments, for example, beverage types. The segmentation information of the classified vending machines is stored in the vending machine classification table unit 124 shown in FIG.

  A specific example of this vending machine segmentation process is shown in FIG. 12, in which the control unit of the information association server 110 converts the vending machine information 12 into the vending machine classification procedure repository according to the processing procedure registered in the classification process master table unit 122. The input information is classified according to the procedure stored in the section 125, the input information is classified by a technique such as cluster analysis, and the classified information is classified into a vending machine segment. Output as db.

[Comparison of segmentation information]
Here, as a premise for explaining the subsequent processing, a comparative example will be described using the above-described consumer segmentation information (FIG. 3) and segment classification in the vending machine segmentation information (FIG. 10). For example, “tea A”, which has a large sales volume in the segment classification “morning type” of the vending machine segmentation information, is a favorite product in the segment classification “purchase before commuting” in the consumer segmentation information, and these segments are similar. When the segment segment has a tendency, it is understood that the customer group is “female” and “young” as the characteristics of the vending machine, and the favorite entertainer is “actor A” as preference information. In the present embodiment, the above-mentioned consumers having similar tendencies and vending machine segment categories are compared and linked, and the vending machine sales strategy is provided to the administrator. As a method for selecting a combination of segment categories, a correlation coefficient between a plurality of segment categories is calculated. The correlation coefficient calculation process will be described next.

[Correlation coefficient calculation process]
First, a correlation coefficient calculation process based on a combination of an arbitrary consumer segment category and vending machine segment category will be described with reference to FIG. For example, in the case of a combination of the consumer segment category “purchase timing” 131 and the vending machine segment category “sellable time zone” 132, the correlation coefficient calculation processing is performed based on the contents of the consumer segment category “purchase timing” 131. There are other contents such as “Purchase type before commuting”, “Full meal type after meal”, and “Morning type” and “Day type” etc. in the contents of the vending machine segment “Selling time zone” 132. The correlation coefficient is calculated for each combination. The correlation coefficient calculation process includes a similar correlation as a typical calculation method. Here, an example of the calculation of the correlation coefficient is shown. In the case of “Purchase type before commuting” and “Morning type”, “Brown A” is the first in sales, “Ekimae” and “In the building” are the same in the first place and second place, so the points are (1 + 1 + 1) / 4 = 0.75 points are calculated as a correlation coefficient. In the case of “Purchase type before commuting” and “Day type”, “Kohi B” is close to 1st place and 2nd place, and “In-building” is 1st place and 2nd place. As a correlation coefficient, (0.5 + 0.5) /4=0.25 points are calculated as points, and in the case of “full-after-meal” and “morning”, “inside the building” and “in front of the station” Is close to 1st place and 2nd place, and (0.5 + 0.5) /4=0.25 points is calculated as the correlation coefficient. ”Is the first place and the score is 1/4 = 0.25 as the correlation coefficient. The consumer segment category“ full after meal ”and the vending machine segment category“ It can calculate the correlation coefficients of a plurality of combinations of types ".

  In step S507, the correlation coefficient is calculated for the combination of the consumer segment category content and the vending machine category content. For example, as shown in FIG. 19, a plurality of segment segments 181 of the consumer segmentation category are provided. The correlation coefficient calculation 183 between the contents of the plurality of segment sections 182 of the vending machine segmentation section is performed, and the calculation result is calculated according to the storage procedure of the correlation coefficient storage procedure repository unit 129 shown in FIG. This is done by performing the update 184 stored in the relation number calculation result storage unit 127.

  As shown in FIG. 15, the correlation coefficient calculation process between the consumer and vending machine segment classification contents is performed by the control unit of the information association server 110 stored in the inter-segment correlation coefficient calculation result storage unit 127. Step S151 for referring to the number of relations and inputting a classification processing procedure to the classification processing master table unit 122; Step S152 for setting information registered in the vending machine classification table unit 124 and the consumer classification table unit 121 as input data; Step S153 for selecting a classification process procedure process from the classification process master table unit 122, and Step S154 for designating a meta output destination (inter-segment correlation coefficient calculation result storage unit 127) for registering information of the calculated correlation coefficient Correlation between consumer segment category content and vending machine segment category content according to the procedure repository It is performed by executing the steps S155 to calculate the number.

  As described above, when a highly correlated segmentation is linked between the contents of the consumer segment and the contents of the vending machine segment, related consumer segmentation is identified in a certain vending machine segmentation, and the characteristics of the consumer segmentation are identified. (Consumer characteristics and profiles related to the vending machine segmentation, such as “gender”, “age”, “favorite talent [preference information]” etc. of the consumer who seems to be efficient in selling products on the vending machine, etc. Information) can be extracted.

[Selection processing-Output processing of strategy information by vending machine]
In the process of selecting a combination of segment segment contents to be linked in step S508 (FIG. 24), the correlation coefficient for the combination for each segment segment content stored in the inter-segment correlation coefficient calculation result storage unit 127 (FIG. 16) is calculated. By extracting, determining a combination for each segment category content whose extracted correlation coefficient is a predetermined value (for example, “0.8”) or more, and presenting the determined combination to the administrator, It is possible to present strategy information for product sales in a vending machine. The selection of the combination of the segment classification contents may be determined by an administrator in consideration of specific installation area, traffic volume, and installation peripheral information such as a station in the vending machine. Further, a combination of the contents of the consumer segment category and the contents of the vending machine segment category is stored, and this combination can be processed in preference to the subsequent selection process or used in other systems.

  As shown in FIG. 25, the merchandise sales strategy information for each vending machine includes, for each vending machine number, the segmentation name, popular product, consumer segmentation name, consumer characteristics, and strategy information of the vending machine. For example, the vending machine with the number “1” is the “morning type” segmentation, the “tea A” is a popular product, and the consumer segmentation before “commuting”. The characteristics of the consumer who purchases “Gender” are “female”, the age is “young”, the taste is “Actor A”, and the strategy information is “Use a lot of actor A's posters and supplement tea A more”.

  As described above, the consumer attribute information acquisition system and method according to the present embodiment provide the correlation between the consumer attribute information obtained by the questionnaire from the consumer and the product sales information obtained from the vending machine for each segment division content. A vending machine that is effective for the vending machine by calculating the relationship as a coefficient and presenting product sales strategy information for each vending machine to the administrator based on the combination of segment classifications with a high correlation coefficient. Can support strategy.

110 information association server, 120 information association database,
121 consumer classification table section, 122 classification processing master table section,
123 Consumer classification procedure repository part, 124 Vending machine classification table part,
126 Vending machine classification procedure repository part,
127 inter-segment correlation coefficient calculation result storage unit,
127 inter-segment correlation coefficient result storage unit,
127 inter-segment correlation coefficient calculation result storage unit,
128 coefficient calculation procedure repository part, 128 correlation coefficient calculation procedure repository part,
129 Correlation coefficient storage procedure repository

Claims (10)

Based on consumer attribute information including consumer preference product ranking, purchase place ranking and consumer profile, and vending machine sales information including vending machine sales ranking and location ranking information, specific automatic A consumer attribute information acquisition system comprising an information association server and an information association database for outputting sales strategy information of products in a vending machine,
A consumption storing a procedure for classifying the consumer attribute information, which is a combination of the consumer's favorite product ranking and purchase place ranking based on questionnaire information from consumers, for each consumer segment category Classification procedure repository part,
Stores the procedure for classifying the vending machine sales information into the vending machine segment classification, which combines the sales ranking and location ranking of the vending machine based on the sales results and location information by product from the vending machine. Vending machine classification procedure repository part,
A consumer classification table unit for storing the consumer attribute information;
A vending machine classification table section for storing the vending machine sales information;
A coefficient calculation procedure repository unit storing a procedure for calculating a correlation coefficient for each combination of the consumer segment classification and the vending machine segment classification;
An inter-segment correlation coefficient result storage unit for storing a correlation coefficient for each combination of the segment classifications calculated by the coefficient calculation procedure repository unit;
Classification processing master table storing a procedure for outputting vending machine strategy information including a correlation coefficient for each combination of the consumer segment classification and the vending machine segment classification stored in the inter-segment correlation coefficient result storage section And
The information association server calculates a correlation coefficient for each combination of the consumer segment category and the vending machine segment category with reference to the procedure stored in the classification processing master table unit, and between the calculated segment category combinations A consumer attribute information acquisition system which outputs vending machine strategy information including a correlation coefficient for each vending machine. The consumer attribute information includes public information published on the Internet web and system log information recording the consumer's product purchase trends, and the consumer classification procedure repository unit is a questionnaire from the consumer The consumer attribute information acquisition system according to claim 1, further comprising a procedure for storing consumer attribute information based on the information, the public information, and the system log information in a consumer classification table unit. Vending machine strategy in which the questionnaire information and public information include feature information of consumer sex, age, and preference information, and the information association server includes a correlation coefficient between the calculated combinations of segment categories and the feature information 3. The consumer attribute information acquisition system according to claim 1 , wherein information is output. The association information server, claim 1, the correlation coefficient between a combination of the calculated segment indicator and to store the combination of the consumer segment configuration and the vending machine business segments larger than a predetermined value 3. The consumer attribute information acquisition system according to any one of 3. Includes the purchase timing information to the consumer attribute information to buy consumer goods, said vending machine sales information includes the time zone information that goods have been sold in the vending machine, the information associated with the server, the consumer consumer attribute information acquiring system according to claims 1 to 4 or which is characterized by selecting a segment Classification sets only the current-time zone information for purchase timing information and the vending machine sales information of the attribute information. Specific vending based on consumer attribute information including consumer preference product ranking, purchase location ranking, consumer profile and vending machine sales information including vending machine sales ranking and location ranking information The consumer attribute information that combines the consumer preference product ranking and the purchase place ranking based on the questionnaire information from the consumer and the information association server that outputs the sales strategy information of the product on the machine for each consumer segment category The vending machine sales information that combines the sales ranking and the location ranking of the vending machine based on the sales classification results and the location information from the vending machine based on the consumer classification procedure repository unit that stores the procedure for classification Vending machine classification procedure list that stores the procedure for classifying Phase of each combination of the consumer segment table, the consumer classification table unit storing the consumer attribute information, the vending machine classification table unit storing the vending machine sales information, the consumer segment classification and the vending machine segment classification A coefficient calculation procedure repository unit storing a procedure for calculating the number of relationships, an inter-segment correlation coefficient result storage unit storing a correlation coefficient for each combination of the segment classifications calculated by the coefficient calculation procedure repository unit, and the segment A classification processing master table unit storing a procedure for outputting vending machine strategy information including a correlation coefficient for each combination of the consumer segment category and the vending machine segment category stored in the inter-correlation coefficient result storage unit A consumer attribute information acquisition method of a consumer attribute information acquisition system comprising an information association database I,
Calculating a correlation coefficient for each combination of the consumer segment classification and the vending machine segment classification with reference to the procedure of the classification processing master table section in the information association server;
Consumer attribute information acquisition method characterized in that to execute a process of outputting the vending machine strategy information including a correlation coefficient for each vending machine between the combination of the segment classification, which is calculated by the process. The consumer attribute information includes public information published on the Internet web and system log information recording the consumer's purchase trends, and the consumer classification procedure repository unit has questionnaire information from the consumer. The consumer attribute information acquisition method according to claim 6, further comprising a step including a step of storing consumer attribute information based on the public information and the system log information in a consumer classification table unit. Vending machine strategy in which the questionnaire information and public information include feature information of consumer gender, age, and preference information, and the information association database includes correlation coefficients between calculated combinations of segment categories and the feature information 8. The consumer attribute information acquisition method according to claim 6, wherein a step of outputting information is executed. The information associated with the server, the correlation coefficient between a combination of the calculated segment indicator and executes a process of storing the combination of the consumer segment configuration and the vending machine business segments larger than a predetermined value The consumer attribute information acquisition method according to any one of claims 6 to 8. The consumer attribute information includes purchase timing information for purchasing a consumer product, the vending machine sales information includes time zone information when the product of the vending machine is sold, and the information association server includes the consumer consumer attribute information acquisition according to claims 6, characterized in that executing the attribute information of the purchase timing information and a step of selecting a segment Classification sets only the current-time zone information of the vending machine sales information to 9 or Way .

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