JP5426309B2 - Information analyzer - Google Patents

Description

  The present invention relates to a data processing technique, and more particularly to a technique for analyzing response information to a questionnaire.

  In recent years, attempts have been made to obtain useful information in business by causing a computer to analyze various information. In the following Patent Document 1, the present applicant proposes a technique for analyzing product sales information and creating information for supporting user sales activities. Specifically, with regard to the area where the purchaser of the product resides (hereinafter also referred to as “area”), the purchaser pays attention to a group of areas (hereinafter also referred to as “area cluster”) with similar attributes of residents. Proposes a technique for creating useful information for merchandise sellers by analyzing sales information based on the area cluster in which they live.

JP 2009-169698 A

  Companies conduct questionnaires to consumers to investigate consumer thinking and living environments. This questionnaire may include an item for filling in the attributes of the respondents in order to analyze the response tendency to the survey items based on the attributes of the respondents. If detailed attributes of respondents are required in this analysis, the number of questions in the questionnaire may increase and the burden on respondents may increase.

  The present invention has been made in view of these problems, and its main purpose is to provide a technology that supports efficient questionnaire implementation by applying the concept of area clusters in analysis of questionnaire results. is there.

  In order to solve the above problems, an information analysis apparatus according to an aspect of the present invention provides a correspondence relationship between each of a plurality of geographically partitioned areas and an area cluster that is a group of areas having similar attributes related to residents. Area cluster information holding unit to be held, questionnaire obtaining unit for acquiring a questionnaire result including information indicating an area where the respondent resides among a plurality of areas, and an answer to the survey item, and referring to the questionnaire result, the area An aggregation processing unit that aggregates responses to survey items in units of clusters, and an aggregation result output unit that outputs the results of aggregations in units of area clusters to external devices as response trends for survey items by residents attribute for each area cluster; .

  It should be noted that any combination of the above-described constituent elements and a representation of the present invention converted between an apparatus, a method, a system, a program, a recording medium storing the program, and the like are also effective as an aspect of the present invention.

  According to the present invention, efficient questionnaire implementation can be supported.

It is a figure which shows the structure of the analysis system which is embodiment of this invention. It is a figure which shows the image of the internet questionnaire in this Embodiment. It is a block diagram which shows the function structure of an information analyzer. It is a figure which shows the data structure of area cluster information. It is a figure which shows the relationship between a prior recognition rate, a subsequent recognition rate, and an advertising effect. It is a flowchart which shows operation | movement of an information analyzer. It is a figure which shows the relationship between a prior recognition rate, a subsequent recognition rate, and an advertising effect.

Before describing the embodiment of the present invention, an outline will be described first.
While various companies conduct advertisements using mass media, it is becoming increasingly important to quantitatively grasp the effects of the advertisements. For this reason, the level of consumer awareness before advertising (hereinafter referred to as “pre-recognition”) and the level of consumer awareness after advertising (hereinafter also referred to as “post-recognition”) In comparison, the increase may be considered to be the effect of the advertisement. In order to obtain the prior recognition degree and the subsequent recognition degree, a questionnaire for confirming the presence or absence of recognition of the advertisement target product may be performed on the consumer.

  By the way, in the advertising target product, a main customer group (hereinafter, also referred to as “target customer group”) expected to be purchased is often determined in advance. This customer segment can be said to be the main target of sales promotion events such as advertisements. Therefore, when considering the effect of advertising, it is important to understand the degree of improvement in product recognition in the target customer segment.

  The attributes of the target customer group include various elements such as age, income level, living environment and family composition. Therefore, conventionally, in order to determine whether or not the respondent of the questionnaire is the target customer group, it has been necessary to set a large number of questions regarding the attributes of the respondent in the questionnaire. As a result of the increase in the number of questions in the questionnaire, the burden on respondents may be increased, and the cost required for analyzing the questionnaire results may be increased. In addition, some respondents were reluctant to answer their detailed attributes, and there were cases where a sufficient number of responses were not collected.

  Therefore, in this embodiment, an analysis system is proposed that applies the concept of area clusters in the analysis of questionnaire results. According to this analysis system, the respondent of the questionnaire only has to answer the area in which he / she resides as his / her attribute at the town level. In other words, there is no need to reply with detailed personal information such as address and annual income. Nevertheless, in the analysis of questionnaire responses, it is possible to grasp the degree of improvement in product recognition in the target customer segment based on the resident attributes associated with the area cluster to which the respondent's residence area belongs in advance. Thereby, the effect of the advertisement with respect to the target customer group can be confirmed without increasing the number of questions in the questionnaire and without causing the psychological resistance of the respondent.

  FIG. 1 shows a configuration of an analysis system 100 according to an embodiment of the present invention. In the analysis system 100, the information analysis apparatus 10 and the questionnaire execution apparatus 12 are connected via a communication network 16 including known communication means such as LAN, WAN, and the Internet. The analysis system 100 is connected via a communication network 16 to a first respondent terminal 14a, a second respondent terminal 14b, and a third respondent terminal 14c, which are collectively referred to as the respondent terminal 14.

  The questionnaire execution device 12 has the function of a web server, and transmits a web page (hereinafter also referred to as “net questionnaire”) on which questions for the questionnaire are described to each of the respondent terminals 14. Then, reply information to the online questionnaire by the respondent is received from the respondent terminal 14. The respondent terminal 14 is a general PC terminal equipped with a web browser.

  FIG. 2 shows an image of a net questionnaire in the present embodiment. The question 50 in the figure is to answer the area where the respondent resides at the “machichome” level as the respondent attribute. The “machi chome” is a geographically divided area unit such as OO 1 chome, OO 2 chome, and characters. In this net questionnaire, the only questions related to the attributes of respondents are those that answer the streets where the respondents live. That is, questions that can specify the residence of the respondent and questions that answer detailed personal information such as annual income and family structure are not included. Question 52 is to answer the survey item in the questionnaire. Is the respondent aware of the target product “△△△” (hereinafter also referred to as “advertisement target product”) using mass media? Whether or not is selected by a radio button. Note that the advertisement using the mass medium is an advertisement performed without limiting the area, such as a television commercial, a radio commercial, a newspaper advertisement, or a magazine advertisement.

  Returning to FIG. 1, the information analysis apparatus 10 is an information processing apparatus that analyzes the answer results of respondents to an online questionnaire. FIG. 3 is a block diagram illustrating a functional configuration of the information analysis apparatus 10. The information analysis apparatus 10 includes a communication processing unit 20, a display control unit 22, a data holding unit 24, and a data processing unit 30.

  Each block shown in the block diagram of the present specification can be realized in terms of hardware by an element such as a CPU of a computer or a mechanical device, and in terms of software, it can be realized by a computer program or the like. The functional block realized by those cooperation is drawn. Therefore, those skilled in the art will understand that these functional blocks can be realized in various forms by a combination of hardware and software. For example, each functional block of FIG. 2 may be stored in a recording medium as software, installed in the hard disk of the information analysis apparatus 10, and appropriately read into the main memory of the information analysis apparatus 10 and executed by the processor.

  The communication processing unit 20 executes communication processing with the questionnaire execution device 12 via the communication network 16. The display control unit 22 sends the display data output from the data processing unit 30 to the display for display. Although the description which overlaps below is abbreviate | omitted, the data processing part 30 displays various images on a display via the display control part 22. FIG.

  The data holding unit 24 is a storage area for storing various data, and includes an area cluster information holding unit 26 and a totaling result holding unit 28. The tabulation result holding unit 28 holds the result of tabulating the net questionnaire for each area cluster. The area cluster information holding unit 26 holds area cluster information in which each of a plurality of area clusters, an area belonging to each area cluster, and a resident attribute of each area cluster are associated with each other.

  FIG. 4 shows the data structure of area cluster information. In the “area cluster” column of the same figure, area cluster identification information is set. In the “area” column, one or more areas belonging to the area cluster are set. For example, each of approximately 180,000 town-chomes throughout Japan may be set as an area and classified into any of about 50 area clusters. In the “population” column, the population of the area is set.

  In the “resident attribute” column, the resident attribute of the area cluster is set, and the resident attribute that is commonly applied to the areas belonging to the same area cluster is set. This inhabitant attribute includes a demographic attribute indicating demographic attribute data for each area cluster, and a psychographic attribute indicating attribute data relating to human psychology such as values and lifestyle of residents of each area cluster. included.

  Examples of demographic attributes include “a nuclear family with a relatively small child in their 30s and 40s” and “income is slightly higher than average and there are many people who have graduated from university”. On the other hand, as an example of psychographic attributes, “For women in their 20s, brand, safety and economy are very important, but there is little environmental orientation”, “For women in their 30s, the brand is slightly emphasized, It is environmentally oriented. That is, the resident attribute of the area cluster is information indicating a consumer image living in the area cluster, and includes the age, income level, occupation, educational background, family structure, living environment, preferences, way of thinking, etc. of the consumer.

  In the “resident index value” field, a resident index value obtained by indexing the resident attributes of the area cluster is set. The resident index value is a plurality of types of index values obtained by indexing the degree of matching of the resident attributes of the area cluster with each of a plurality of types of evaluation criteria using a predetermined evaluation function. Specific examples of the inhabitant index values include average annual income, average number of households, average number of children per household, 30s ratio, 40s ratio, and the like. In other words, it can be said that the resident index value is obtained by converting the resident attribute into a plurality of types of numerical values for calculation processing by a computer.

  An example of a method for creating area cluster information will be described. The area cluster information is created using attribute information about each area, and various public statistical information, original estimation information, and questionnaire result information. The statistical information includes age ratio, gender ratio, occupation ratio, educational ratio, and the like. The estimation information includes average income, average asset, average land price, and the like. The questionnaire result information includes answer results such as lifestyle, values, and consumption preferences. The qualitative information is indexed by a predetermined evaluation function. An area cluster information creating unit (not shown) groups each area by cluster analysis using various attribute information converted into index values for each area as variables. Various index values used for the cluster analysis may be set as values in the resident index value column, and data to be set in the resident attribute column may be set based on human judgment based on the values in the resident index value column. Further, the sales results of various products in each area may be a variable of cluster analysis.

  Returning to FIG. 3, the data processing unit 30 executes the analysis process of the net questionnaire executed in the questionnaire execution device 12 in order to visualize the effect of the advertisement using the mass medium. The data processing unit 30 includes a questionnaire acquisition unit 32, a totalization processing unit 34, a totalization result output unit 36, an advertisement effect calculation unit 38, and an area information output unit 40.

  The questionnaire acquisition part 32 acquires the implementation date and result data of a net questionnaire from the questionnaire execution apparatus 12, when the net questionnaire totaling request is received from the user via a predetermined input device. For example, when the online questionnaire shown in FIG. 2 is executed, area response information that is a response to the question 50 and product recognition response information that is a response to the question 52 are obtained as result data for each respondent of the online questionnaire. Get the associated data.

  The totalization processing unit 34 refers to the area cluster information and totals the result data of the net questionnaire for each area cluster. The tabulation processing unit 34 according to the present embodiment sorts each result data for each area cluster based on the area answer information, and the respondent selects the advertisement target product for each area cluster based on the product recognition answer information. The rate of recognition (hereinafter also referred to as “recognition rate”) is calculated. Specifically, the ratio of the result data including the product recognition response information indicating that the product is recognized in the total number of result data in each area cluster is calculated as the recognition rate.

  The tabulation result output unit 36 stores the tabulation result of the net questionnaire in the tabulation processing unit 34, that is, the recognition rate of the advertising target product for each area cluster, in the tabulation result holding unit 28 in association with the date of the net questionnaire. The total result output unit 36 may display the total result of the net questionnaire on a display, or may output it to another output device such as a printer.

  When the advertisement effect calculation unit 38 receives an advertisement effect calculation request from a user via a predetermined input device, the advertisement effect calculation unit 38 refers to the total result holding unit 28 to calculate the advertisement effect. In this calculation request, the date of questionnaire to be applied to the prior recognition rate and the date of questionnaire to be applied to the subsequent recognition rate are specified. The advertisement effect calculation unit 38 determines the prior recognition rate and the subsequent recognition rate in each area cluster according to the questionnaire implementation date. And the increment of the posterior recognition rate with respect to the prior recognition rate is calculated as an index value of the advertising effect. The advertisement effect calculation unit 38 displays the pre-recognition rate, the post-recognition rate, and the advertisement effect index value in association with each other on the display.

  FIG. 5 shows the relationship between the prior recognition rate, the subsequent recognition rate, and the advertising effectiveness. As shown in the figure, the advertisement effect index value is set with an increment of the post-recognition rate (unit%, the same applies hereinafter) to the prior recognition rate (unit%, the same applies hereinafter). The advertisement effect calculation unit 38 may display the screen in the form of FIG. 5 in response to the advertisement effect calculation request. The user who confirmed the advertising effect in FIG. 5 has a high advertising effect on the cluster D when the target customer segment of the advertisement is the cluster D, that is, when the resident attribute of the target customer segment and the resident attribute of the cluster D match, It can be determined that the advertisement was effective from the viewpoint of improving the recognition of the advertising target product.

  Returning to FIG. 3, when the area information output unit 40 receives an area information presentation request from a user via a predetermined input device, the area information output unit 40 displays information on areas belonging to the area cluster designated by the presentation request on the display. For example, a list of town streets may be displayed for areas belonging to a designated area cluster. In addition, the map image may be displayed at a predetermined scale, and the map image may be displayed in a manner that is easily visible to the user, such as highlighting and highlighting a portion corresponding to the area.

The operation of the above configuration will be described below.
FIG. 6 is a flowchart showing the operation of the information analysis apparatus 10. When the net questionnaire totaling request is accepted (Y in S10), the questionnaire acquisition unit 32 acquires the result data of the net questionnaire from the questionnaire execution device 12 (S12). The aggregation processing unit 34 refers to the area cluster information and calculates the recognition rate of the advertisement target product in units of area clusters based on the result data of the net questionnaire (S14). The tabulation result output unit 36 stores data indicating the recognition rate of the advertising target product calculated for each area cluster in the tabulation result holding unit 28. If there is no net questionnaire totaling request (N in S10), S12 and S14 are skipped.

  When the output request for the advertisement effect is accepted (Y in S16), the advertisement effect calculation unit 38 refers to the total result holding unit 28, and for each of the area clusters, the advertisement effect index according to the prior recognition rate and the subsequent recognition rate. The value is calculated and displayed on the display (S18). If there is no advertisement effect output request (N in S16), S18 is skipped. When an area information output request is received (Y in S20), the area information output unit 40 displays information on areas belonging to the area cluster specified in the output request on the display (S22). If there is no area information output request (N in S20), S22 is skipped.

  According to the information analysis apparatus 10 of the present embodiment, while reducing the number of questions related to the respondent's attributes in the questionnaire, by collecting the answers based on the area clusters, the resident attributes associated with the area clusters (that is, Response tendency by respondent attribute) can be visualized. In other words, even if the question related to the respondent's attributes is only for responding to the town street where the respondent resides, the respondent's detailed attributes are assigned to the respondent by the residents attribute of the area cluster corresponding to that town street. Realize the same analysis as when responding. This reduces the burden on the respondent and eliminates the need for replying with detailed personal information, thereby reducing the resistance felt by the respondent. Furthermore, since it is not necessary for the respondent to disclose detailed personal information that identifies himself / herself, an honest answer can be expected for the survey items. Furthermore, since the area cluster is directly specified according to the respondent's living area, the process is simplified compared to grouping the respondents step by step across multiple questions and required for the analysis process of the questionnaire. Cost is also reduced.

  Further, according to the information analysis apparatus 10, the effect of the advertisement using the mass medium is quantitatively presented for each area cluster. As a result, it becomes easy for the user to intuitively grasp whether or not the advertisement is effective for the target customer segment, and it becomes easy to brush up the advertising strategy such as reviewing the advertisement.

  Furthermore, according to the information analysis apparatus 10, information on areas belonging to the area cluster designated by the user is presented to the user. As a result, the user can grasp the area where the target customer group resides, and can easily plan sales promotion measures in the area local (area only), such as performing an event or exhibition in that area. That is, according to the information analysis apparatus 10, it is possible to support the planning of an advertising strategy that appropriately combines a sales promotion event using a mass medium for a target customer layer and a sales promotion event for each area.

  The present invention has been described based on the embodiments. This embodiment is an exemplification, and it will be understood by those skilled in the art that various modifications can be made to combinations of the respective constituent elements and processing processes, and such modifications are also within the scope of the present invention. is there. A modification is shown below.

  A first modification will be described. Aggregation conditions may be specified by the user in the net questionnaire totalization request, and the aggregation processing unit 34 may execute aggregation processing for each area cluster in accordance with the aggregation conditions. For example, when the condition is that the Kanto region and regions other than Kanto are separately counted, the tabulation processing unit 34 totals the result data in which the area in the Kanto region is designated by the area response information for each area cluster. Calculate the recognition rate at. At the same time, result data in which areas in regions other than Kanto are designated by area response information is aggregated for each area cluster to calculate a recognition rate in regions other than Kanto.

  Similarly, a calculation condition may be specified by the user in the advertisement effect calculation request, and the advertisement effect calculation unit 38 may calculate the advertisement effect for each area cluster according to the calculation condition. For example, in the case where the advertising effect is calculated separately in each of the Kanto region and the regions other than the Kanto region, the advertising effect calculation unit 38 uses the pre-recognition rate in the Kanto region and the post-recognition rate in the Kanto region. Calculate the advertising effectiveness for each area cluster. At the same time, based on the pre-recognition rate and post-recognition rate in regions other than Kanto, the advertising effect for each area cluster in regions other than Kanto is calculated. The advertisement effect calculation unit 38 displays the advertisement effect in each region.

  This modification is suitable for grasping the effect of each type of advertisement when a different type of advertisement is performed for each region. Here, it is assumed that for a certain advertisement target product, both TV commercials and newspaper advertisements are performed in the Kanto region, and only TV commercials are performed in regions other than the Kanto region. FIG. 7 shows the relationship between the prior recognition rate, the subsequent recognition rate, and the advertising effectiveness. In the figure, the advertising effect in regions other than Kanto, that is, the increase in the recognition rate in regions other than Kanto, is the effect of TV commercials alone. On the other hand, the advertising effect in the Kanto region, that is, the increase in the recognition rate in the Kanto region is the sum of the effect of TV commercials and the effect of newspaper advertising. Therefore, it can be considered that the increase in the advertising effect in the Kanto region relative to the advertising effect in regions other than the Kanto region is the effect of the newspaper advertisement.

  By confirming the advertisement effect shown in FIG. 7, the user can determine that the TV commercial is effective for the cluster D that is the target customer segment. On the other hand, it can be determined that the newspaper advertisement is effective against the cluster C rather than appealing to the target customer group. Therefore, it is possible to support the user to improve the advertising strategy, such as reviewing newspaper advertisements while continuing TV commercials. Of course, the advertisement effect calculation unit 38 may automatically calculate and display the “advertisement effect (by advertisement type)” in FIG. 7 according to the above algorithm.

  A second modification will be described. When the area information output unit 40 receives a presentation request for an area where a sales promotion event is to be performed, the area cluster in which the recognition rate and / or the advertisement effect of the advertisement target product using the mass medium are in a predetermined state May be determined. Then, an area belonging to the area cluster is determined as a recommended area for a sales promotion event, for example, an exhibition or the like, in an area unit (that is, area local, area limited) related to the advertisement target product, and presented to the user. Good.

  For example, let us consider a case where an area belonging to an area cluster having a recognition rate or advertisement effect less than a predetermined threshold or relatively low is recommended as an execution area for a sales promotion event. In this case, for an area cluster where consumers who are less effective in advertising using mass media reside, the degree of product recognition can be supplemented by a sales promotion event in the area local area.

  Also, consider a case where an area belonging to an area cluster having a recognition rate or an advertising effect equal to or higher than a predetermined threshold or relatively high is recommended as an execution area for a sales promotion event. In this case, an area where the recognition degree of the product is improved by the advertisement using the mass medium is recommended. Therefore, the sales possibility of the product can be further enhanced by the sales promotion event in the area local area. Note that an appropriate value may be determined as the threshold value in the present modification based on company knowledge or an experiment using the analysis system 100.

  A third modification will be described. Although the questionnaire in the above-described embodiment is an online questionnaire with the presence or absence of recognition regarding the advertisement target product as a survey item, it is not limited to this mode. As a modification, it may be a questionnaire with survey items such as favorability for various products, consumer preferences and ideas. However, in the analysis, it is preferable that the questionnaire should classify the answers according to the attributes of the respondents. Needless to say, the questionnaire is not limited to the internet questionnaire but may be a paper questionnaire. In that case, the information analysis apparatus 10 may acquire the answer information as electronic data from a questionnaire sheet via a scanner, an OCR apparatus, or the like.

  Any combination of the above-described embodiments and modifications is also useful as an embodiment of the present invention. The new embodiment generated by the combination has the effects of the combined embodiment and the modified examples.

  It should also be understood by those skilled in the art that the functions to be fulfilled by the constituent elements described in the claims are realized by the individual constituent elements shown in the embodiments and the modification examples or by their cooperation.

  DESCRIPTION OF SYMBOLS 10 Information analyzer, 12 Questionnaire execution apparatus, 14 Respondent terminal, 26 Area cluster information holding part, 28 Total result holding part, 32 Questionnaire acquisition part, 34 Total processing part, 36 Total result output part, 38 Advertisement effect calculation part, 40 area information output unit, 100 analysis system.

Claims (2)

Corresponding relationship between each of a plurality of geographically partitioned areas , each of a plurality of areas having a greater granularity than a residence number or lot number , and an area cluster that is a group of areas having similar attributes regarding residents An area cluster information holding unit to hold;
Or a question for answer information town chome level as the information indicating the area in which respondents living among the plurality of areas, the implementation advertisement for Shipping over said plurality of areas respondents are aware while including the question of survey items to answer whether, the questions to answer the personal information of the specific levels of the respondents individual and questionnaire acquisition unit that acquires the results of the questionnaire that has been eliminated,
An aggregation processing unit that refers to the results of the questionnaire and calculates the degree of recognition for the target product of the advertisement in units of the area clusters by aggregating answers to the questions of the survey items in units of the area clusters ; ,
Information indicating an answer tendency to the question of the survey item by the resident attribute for each area cluster, information indicating the degree of recognition of the advertisement target product in units of the area cluster, information indicating the effect of the advertisement A totaling result output unit that outputs to a predetermined device as
An information analysis apparatus comprising: A sales area determination unit that determines an area belonging to an area cluster whose degree of recognition of the target product of the advertisement is less than a predetermined standard as an area where a sales promotion event for each area related to the product is to be further implemented; The information analysis apparatus according to claim 1.

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