JP2014164620A - Advertisement effect measurement device, advertisement effect measurement method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an advertisement effect measurement device, an advertisement effect measurement method and a program by which an influence of an advertisement on the number of visitors is found out.SOLUTION: An advertisement effect measurement device comprises: a human flow measurement part which determines whether or not the respective persons detected in a first measurement area visit a store by referring to human flow information representing positions of the persons detected in the first measurement area including an area through which persons who visit the store pass; a human number measurement part which calculates the number of browsing visitors which is the number of persons who browse the advertisement and visit the store by referring to browsing information representing positions of persons detected in a second measurement area including an area common with the first measurement area, and an area in which persons who browse the advertisement are located, browsing measurement information showing whether or not the respective persons detected in the second measurement area browse the advertisement, the human flow information, and determination results of the human flow measurement part; and a content effect calculation part which calculates an index representing a customer-collection effect by the advertisement by using the number of browsing visitors.

Description

  The present invention relates to an advertisement effect measuring device, an advertisement effect measuring method, and a program.

  In recent years, for advertisements using advertising media such as billboards and digital signage, the impact on the number of people viewing the advertisement is calculated, such as the advertising audience rating that shows how many of the people in front of the advertising media were watching the advertisement. The technology to do is known.

  For example, Patent Document 1 discloses a technique for measuring the front of an advertising medium and detecting the number of people browsing the advertisement to calculate the effect on the number of people browsing the advertisement. (See Patent Document 1).

JP 2012-123727 A

  By the way, in the case of an advertisement using an advertising medium installed in front of a store or the like, if it is possible to know the influence of the advertisement on the number of people entering the store, it is possible to perform an advertisement operation with a high effect of attracting customers. The technique described in No. 1 has a problem that the influence on the number of people entering the advertisement is not known.

  Therefore, the present invention has been made in view of the above-described problems of the prior art, and provides an advertisement effect measuring device, an advertisement effect measuring method, and a program that can understand the influence on the number of people entering an advertisement.

  The present invention has been made to solve the above-described problem, and one aspect of the present invention provides a human flow representing a position of a person detected in a first measurement region including a region through which a person entering a store passes. A person flow measurement unit that determines whether each person detected in the first measurement area has entered the store with reference to the information, an area common to the first measurement area, and Browsing information indicating the position of the person detected in the second measurement area including the area where the person browsing the advertisement is located, and whether each person detected in the second measurement area has browsed the advertisement The number of people entering the store, which is the number of people who browsed the advertisement and entered the store with reference to the browsing measurement information indicating the person flow information and the determination result of the person flow measurement unit Using the number-of-people counting unit to calculate and the number of visitors entering the store, the effect of attracting customers by the advertisement is displayed. An advertisement effect measurement apparatus, characterized in that it comprises a content effects calculator for calculating an index.

  According to the present invention, the influence on the number of people entering the advertisement can be understood.

It is a figure explaining the measurement area | region by the advertisement effect measuring device which concerns on one Embodiment of this invention. It is a schematic block diagram of the advertising effectiveness measuring device in a 1st embodiment. It is the table | surface showing an example of the flow table and flow measurement table in 1st Embodiment. It is the table | surface showing an example of the browsing table in 1st Embodiment, and a browsing measurement table. It is a table | surface showing an example with the content effect table in 1st Embodiment. It is a schematic block diagram of the advertising effectiveness measuring device in a 2nd embodiment. It is a schematic block diagram of the advertising effectiveness measuring device in a 3rd embodiment. It is a table | surface showing an example of the external environment advertisement table in 3rd Embodiment. It is a schematic block diagram of the advertising effectiveness measuring device in a 4th embodiment. It is the table | surface showing an example of the regression analysis external environment advertisement table in 4th Embodiment. It is a schematic block diagram of the advertising effectiveness measuring device in a 5th embodiment. It is a table | surface showing an example of the importance level table in 5th Embodiment.

[First embodiment]
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a plan view showing a configuration of an advertisement effect measurement system. The advertisement effect measurement system includes an advertisement effect measurement device 100, a human flow measurement sensor 80, and a browsing measurement sensor 90. r100 is the area of the building of the store where the advertising medium is installed (hereinafter referred to as the store area). c100 is an advertising medium (hereinafter referred to as an advertising panel) installed in the store.

  The human flow measurement sensor 80 sets a measurement region (hereinafter referred to as a human flow measurement region) for detecting a person passing in front of the store so as to include a region through which a person entering the store passes. In the present embodiment, the person flow measurement region r101 is set in front of the store as in the region surrounded by the thin broken line in FIG. 1, but the present invention is not limited to this. Further, the human flow measurement sensor 80 is installed as shown in FIG. 1 in order to detect a person passing in front of the store in the human flow measurement area.

  In addition, the browsing measurement sensor 90 includes a measurement area for detecting a person browsing an advertisement (hereinafter referred to as an area where a person browsing the advertisement is located) including an area common to the human flow measurement area. Set the browsing measurement area). In the present embodiment, it is assumed that a person browsing the advertising panel c100 is detected by setting the browsing measurement area r102 as in the area surrounded by the thick broken line in FIG. 2, but the present invention is not limited to this. Further, the browsing measurement sensor 90 is installed as shown in FIG. 1 in order to detect a person browsing the advertisement in the browsing measurement area.

  In addition, the human flow measurement sensor 80 and the browsing measurement sensor 90 set the x axis a100, the y axis a101, and the coordinate origin o100 in the human flow measurement region r101 and the browsing measurement region r102, respectively. Represents the position coordinates of the person who entered the area. The person h101, the person h102, and the person h103 are persons who have entered the human flow measurement region r101 during a time zone in which the advertisement panel c100 displays an advertisement (hereinafter referred to as an advertisement display time zone). A person who is given a human flow ID to be described later.

  Accordingly, in the present embodiment, the human flow measurement sensor 80 performs measurement for each advertisement display time period, but is not limited thereto. The person to whom the person flow ID is given is determined by the person flow measuring unit 101 whether or not the person has passed through the store entry line g100. 1 is given. In the present embodiment, the store entry line is set at the entrance / exit of the store area r100, but is not limited thereto. In addition, the human flow measurement sensor 80 and the browsing measurement sensor 90 are connected to the advertisement effect measurement device 100 installed in the store via a connection cable w100 and a connection cable w101, respectively.

  Since the person h101 and the person h102 are also included in the browsing measurement area r102 during the advertisement display time zone, the browsing detection unit 190 is also given a browsing ID described later. An arrow f101 and an arrow f102 represent the face orientations of the person h101 and the person h102, respectively. Since the browsing detection unit 190 detects a human eye to determine whether the face is directed toward the advertising panel c100, the orientation of the face is set in a predetermined direction toward the advertising panel c100. If it has turned more than the time, it is determined that the person whose face is facing the direction of the advertisement panel c100 is browsing the advertisement.

  FIG. 2 is a schematic block diagram illustrating a configuration of the advertisement effect measuring apparatus 100 according to the present embodiment. The advertising effect measuring apparatus 100 is connected to a human flow measuring sensor 80 and a browsing measuring sensor 90. The human flow measurement sensor 80 detects the position coordinates of the person in the human flow measurement area. For example, the human flow measurement sensor 80 irradiates infrared rays in the human flow measurement region, measures the distance to the target by the degree of reflection from the target, and based on the measured distance, the position coordinates of the target (E.g., a sensor using a laser range finder).

As another example, the human flow measurement sensor 80 detects the luminance change due to the difference between the current image and the previous image based on the image taken by the video camera in the human flow measurement region, and thereby the target object. However, the position coordinates are not limited to these. In the present embodiment, the human flow measurement sensor 80 is a sensor using the video camera.
The human flow measurement sensor 80 includes a first video camera 81 and a first image storage unit 82. The first video camera 81 is a video camera included in the human flow measurement sensor 80. The first video camera 81 continues to shoot the human flow measurement area during the advertisement display time period, and whenever an image for each frame is generated during the advertisement display time period, the first video camera 81 (hereinafter referred to as human flow). Image) and the shooting time of the image for each frame (hereinafter referred to as “human flow shooting time”) are stored in the first image storage unit 82.

  When the first image storage unit 82 receives a human flow image and a human flow shooting time from the first video camera 81, the first image storage unit 82 associates each with the human flow image and arranges them in time series later. Allocate an image ID. The first image storage unit 82 generates a human flow image table and records the human flow image ID and the human flow photographing time for each human flow image. Further, the first image storage unit 82 continues to store and accumulate human flow images during the advertisement display time period.

Next, the browsing measurement sensor 90 will be described. The browsing measurement sensor 90 includes a second video camera 91 and a second image storage unit 92. The browsing measurement sensor 90 detects the shape of the person based on the image captured by the second video camera 91, and displays coordinates (hereinafter referred to as browsing position coordinates) indicating the position of the person browsing the advertising panel c100. It is a sensor to detect.
The second video camera 91 is a video camera included in the browsing measurement sensor 90. The second video camera 91 continues to capture the browsing measurement area during the advertisement display time zone, and every time an image for each frame is generated during the advertisement display time zone, Hereinafter, the second image storage unit 92 stores the browsing image) and the shooting time of the image for each frame (hereinafter referred to as the browsing shooting time).

  When the second image storage unit 92 receives the browsing image and the browsing shooting time from the second video camera 91, the second image storage unit 92 browses the browsing image in order to associate them with each other and arrange them in time series later. Allocate an image ID. The second image storage unit 92 generates a browsing image table and records the browsing image ID and browsing shooting time for each browsing image. In addition, the second image storage unit 92 continues to store and accumulate browse images during the advertisement display time period.

Next, the advertisement effect measuring apparatus 100 will be described. The advertising effect measuring apparatus 100 includes a human flow detection unit 180, a human flow table storage unit 181, a browsing detection unit 190, a browsing table storage unit 191, a human flow measurement unit 101, a browsing measurement unit 102, and a people counting unit 103. The content effect calculation unit 104 and the content effect storage unit 105 are provided.
Upon receiving the human flow image and the human flow image table from the first image storage unit 82, the human flow detection unit 180 detects the human flow position coordinates based on the human flow image table and the human flow image. Specifically, the human flow detection unit 180 compares the human flow image at a certain time and the human flow image at the immediately preceding time, which are arranged in time series, and detects the luminance change to obtain the human flow position coordinates. To detect. Whenever a new person appears in the flow measurement area, the flow detection unit 180 assigns a flow ID to the flow position coordinates indicating the person, and identifies the flow position coordinates indicating other persons.

  Also, the human flow detection unit 180 detects how the position coordinates of the person indicated by the human flow ID have moved on the human flow image arranged in time series based on the human flow image and the human flow image table. Therefore, a human flow table is generated. The human flow table is a table in which the human flow ID, the human flow position coordinates of the person indicated by the human flow ID, and the human flow photographing time of the human flow image in which the human flow position coordinates are detected are written. Details of the human flow table will be described later. When the human flow detection unit 180 generates the human flow table, the human flow table is stored in the human flow table storage unit 181.

  Upon receiving the browsing image and the browsing image table from the second image storage unit 92, the browsing detection unit 190 detects the browsing position coordinates based on the browsing image table and the browsing image. Specifically, the browsing detection unit 190 compares the browsing image at a certain time and the browsing image at the immediately preceding time, which are arranged in time series, and detects the luminance change, thereby obtaining the browsing position coordinates. To detect. Each time a new person appears in the browsing measurement area, the browsing detection unit 190 assigns a browsing ID to the browsing position coordinates indicating the person, and identifies the browsing position coordinates indicating another person.

  Also, the browsing detection unit 190 determines how the position coordinates of the person indicated by the browsing ID have moved on the browsing image arranged in time series based on the browsing image and the browsing image table. A browsing table is generated for detection. The browsing table is a table in which the browsing ID, the browsing position coordinates of the person indicated by the browsing ID, and the browsing shooting time of the browsing image in which the browsing position coordinates are detected are written. Details of the browsing table will be described later.

  Furthermore, the browsing detection unit 190 detects whether or not the person has browsed the advertisement by detecting the eyes of the person from the browsing images arranged in time series, and when the person has browsed the advertisement ( 1 is displayed when the eye is detected), 0 is displayed when the person does not view the advertisement (when the eye is not detected), and the browsing identification ID is displayed in the record including the position coordinates of the person. Generate and write the field to be In the present embodiment, since the browsing measurement sensor 90 is installed from the advertisement panel c100 side toward people who browse the advertisement, the browsing detection unit 190 is browsing the advertisement by detecting eyes. It can be determined whether or not. When the browsing detection unit 190 generates the browsing table, the browsing table 190 stores the browsing table in the browsing table storage unit 191.

  When the human flow measurement unit 101 acquires the human flow table, the human flow measurement unit 101 reconfigures the movement of each person indicated by the human flow ID in the human flow measurement area based on the human flow table, and detects a person who has left the human flow measurement area. . Specifically, the human flow measurement unit 101 determines whether or not the human flow position coordinates of the person indicated by the human flow ID have disappeared from the human flow measurement area at a time immediately after being detected on the coordinates indicating the outer frame of the human flow measurement area. Then, it is determined whether or not the person indicated by the person flow ID has gone out of the person flow measurement area.

  In addition, the person flow measurement unit 101 also determines whether or not the person flow measurement unit 101 has disappeared from the person flow measurement area at the time immediately after being detected on the coordinates indicating the store entry line g100. When the person flow measurement unit 101 goes out of the person flow measurement area through the coordinates representing the store entry line g100, the person flow measurement unit 101 gives 1 as the store entry identification ID and goes out of the person flow measurement area without passing through the store entry line g100. In this case, 0 is assigned as the store entry identification ID. Furthermore, the human flow measurement unit 101 calculates the stay time of the person indicated by each human flow ID in the human flow measurement area based on the shooting time of the human flow table.

  When the calculation of the stay time is completed, the flow measurement unit 101 generates a record for each flow ID, and the flow of the flow that the flow ID, the store identification ID, the stay time, and the person indicated by the flow ID first appear. A human flow measurement table in which position coordinates (hereinafter referred to as initial human flow position coordinates) are written is generated. Details of the human flow measurement table will be described later. When the human flow measurement unit 101 generates the human flow measurement table, the human flow measurement unit 101 outputs the human flow measurement table to the number of people measurement unit 103.

  The browsing measurement unit 102 browses the advertisement in the browsing measurement area of the person indicated by each browsing ID based on the shooting time of the browsing table and the record whose browsing identification ID is 1 (hereinafter, (Referred to as browsing time). Specifically, in the present embodiment, the browsing measurement unit 102 counts the number of records having a browsing identification ID of 1 for each browsing ID, and the second video camera 91 has one frame for the counted number. A value obtained by multiplying a unit time for generating each image is set as the browsing time of the person indicated by the browsing ID, but is not limited thereto.

  After completing the calculation of the browsing time, the browsing measuring unit 102 generates a record for each browsing ID, and the browsing ID, the browsing time, and the time when the person indicated by the browsing ID first appears (hereinafter referred to as initial browsing shooting). Time) and a browsing position coordinate in which a person corresponding to the browsing ID first appears (hereinafter referred to as initial browsing position coordinate) is generated. Details of the browsing measurement table will be described later. When the browsing measurement unit 102 generates the browsing measurement table, the browsing measurement unit 102 outputs the browsing measurement table to the number of people measurement unit 103 for each advertisement display time.

  Upon receiving the human flow measurement table from the human flow measurement unit 101, the number of people measurement unit 103 acquires the human flow table from the human flow table storage unit 181. In addition, the person counting unit 103 acquires a browsing measurement table from the browsing measuring unit 102. The number-of-people counting unit 103 counts the number of people who have entered the store by counting the records whose store entry ID is 1 in the flow measurement table, and counts the records whose store ID is 0. In this way, the number of non-entries, which is the number of people who did not enter the store, is counted. In addition, when the browsing measurement table is acquired, the number-of-people counting unit 103 counts the number of browsing users who are the number of people whose browsing time is longer than a predetermined time (hereinafter referred to as browsing humans). In the present embodiment, the predetermined time is determined in advance, but is not limited thereto.

  Next, based on the browsing measurement table and the human flow table, the number of people counting unit 103 matches the browsing human and the person indicated by the human flow ID (hereinafter referred to as a human flow human). Specifically, in the browsing measurement table, the initial browsing shooting time corresponding to the browsing person and the initial browsing position coordinates are detected in the same way as the human shooting time of the human flow table and the human flow position coordinates. The human flow ID of the record is associated with the browsing ID corresponding to the browsing person.

  In the present embodiment, the coincidence between the initial viewing position coordinates and the human flow position coordinates does not have to be exactly the same coordinates, but is not limited thereto. Further, in the present embodiment, it is sufficient that the match is such that the human flow position coordinates are included in a predetermined range centered on the initial viewing position coordinates, and the predetermined range is determined in advance. A circle having a certain radius and centered on the initial viewing position coordinate is not limited to this.

The number-of-persons measurement unit 103 counts the number of people IDs associated with the store entry ID 1 among the user IDs associated with the browse IDs indicating the viewers, and sets the number as the number of visitors entering the store.
Thereafter, the number-of-people counting unit 103 generates a number-of-peoples measurement table that stores the number of people entering the store, the number of people not entering the store, the number of viewers, and the number of viewers entering the store. Details of the number counting table will be described later. When the people counting unit 103 generates the people counting table, the people counting unit 103 outputs the people counting table to the content effect calculator 104.

  Here, in the present embodiment, since the browsing measurement area is completely included in the human flow measurement area, the number-of-people counting unit 103 is as described above, the number of people entering the store, the number of non-stores, the number of viewers, and the browsing The number of people entering the store was calculated, but when the viewing measurement area and the human flow measurement area were set to partially overlap, the number of people counting unit 103 overlapped the browsing measurement area and the human flow measurement area. By counting the number of human flow IDs detected from both the coordinates in the area and the coordinates on the store entry line g100, the number of people entering the store is counted without using the browsing measurement table.

  The content effect calculation unit 104 acquires a people count table from the people count unit 103. When the content effect calculation unit 104 acquires the number-of-people measurement table, the number of people who have not browsed is obtained by subtracting the number of viewers from the value obtained by adding the number of visitors to the store and the number of non-entries in the number-of-peoples measurement table. (Hereinafter referred to as the non-viewing number) is calculated. In addition, the content effect calculation unit 104 subtracts the number of visitors entering the store from the number of visitors in the number measurement table, thereby calculating the number of people who have entered the store without browsing (hereinafter referred to as the number of non-viewed visitors). calculate.

  The content effect calculation unit 104 calculates the number of people who have not entered the store since browsing by subtracting the number of people who have entered the store from the number of people in the table for counting people (hereinafter referred to as the number of people who have not visited the store). To do. The content effect calculation unit 104 subtracts the browsing non-entry number from the non-entry number in the number-of-persons measurement table, so that the number of people who did not browse or enter the store (hereinafter referred to as non-browsing non-entry number). ) Is calculated. Based on these values, the content effect calculation unit 104 calculates a browsing entry rate, a browsing rate, and an advertising effectiveness rate.

  The browsing entry rate is calculated by dividing the number of visitors entering the store by the number of visitors, and viewing the displayed advertisement for the number of people who viewed the advertisement displayed on the advertisement panel c100 (hereinafter referred to as display advertisement). It is the ratio of the number of people who have entered the store since then. The browsing store entry rate is one of the indexes indicating the effect of attracting customers for display advertisements. The browsing rate is calculated by dividing the number of viewers by the sum of the number of viewers and the number of non-viewers (or the number of visitors and the number of non-entries). This is the ratio of the number of people who viewed the advertisement to the number of people.

The content effect calculation unit 104 further calculates an advertisement effect rate by multiplying the calculated browsing entry rate by the browsing rate. The advertising effectiveness rate is a value representing the proportion of people who entered the store after viewing the advertisement among all the people who passed in front of the store, and is one of the indexes indicating the effect of attracting customers. When calculating the advertisement effectiveness rate, the content effect calculation unit 104 writes the advertisement ID indicating the advertisement displayed on the advertisement panel c100, the browsing entry rate, the browsing rate, and the advertising effectiveness rate. The content effect table is generated and stored in the content effect storage unit 105.
In the present embodiment, the advertisement ID is a name representing the displayed advertisement and is registered in advance, but is not limited thereto.
The content effect storage unit 105 stores a content effect table.

  FIG. 3 is a table representing the human flow table t100 and the human flow measurement table t200. The human flow table t100 displays a human flow ID t101, a human flow shooting time t102, and a human flow position coordinate t103. The human flow detection unit 180 can calculate the stay time in which the person indicated by the human flow IDt 101 is in the human flow measurement area based on the shooting time of the human flow. Also, the human flow detection unit 180 reconstructs the movement of the person indicated by the human flow ID t101 based on the human flow position coordinate t103, and determines whether or not the store entry line has been exceeded when the person leaves the human flow measurement area. The person flow measurement table t200 displays a person flow ID t101, a store entry ID t201, a stay time t202 for each person indicated by the person flow ID t101, and an initial person flow position coordinate t203 for each person.

  FIG. 4 is a table representing the browsing table t300 and the browsing measurement table t400. The browsing table t300 displays a browsing ID t301, a browsing shooting time t302, a browsing position coordinate t303, and a browsing identification ID t304. The browsing measurement unit 102 calculates the browsing time of the person indicated by the browsing ID t301 based on the browsing shooting time. The browsing measurement table t400 displays a browsing ID t301, a browsing time t401 for each person indicated by the browsing ID t301, an initial browsing shooting time t402 for each person, and an initial browsing position coordinate t403 for each person. Based on the browsing measurement table t400 and the flow table t100 of FIG. 3, the number-of-people measurement unit 103 matches the person indicated by the flow ID t101 with the person indicated by the read ID 301.

  FIG. 5 is a table showing a content effect table t700. The content effect table t700 displays an advertisement ID t701, a browsing entry rate t702, a browsing rate t703, and an advertising effectiveness rate t704. The advertisement ID t701 is the name of the advertisement displayed in the advertisement display time zone. In this embodiment, the advertisement ID t701 displays the names of three different advertisements. That is, as a result of the user displaying different advertisements and measuring with the advertisement effect measuring device 100 in the same advertisement display time zone on different days, the content effect table t700 includes three display advertisements corresponding to three display advertisements. The record has been written.

  The browsing entry rate t702 and the browsing rate t703 are values of the browsing entry rate and the browsing rate calculated by the content effect calculation unit 104 for each display content t701. The advertising effectiveness rate t704 is a value obtained by multiplying the browsing store entry rate t701 by the browsing rate t702. The user of the advertising effect measuring device 100 can easily compare the customer attraction effect of each advertisement based on any of the browsing entrance rate, the browsing rate, and the advertising effectiveness rate of the content effect table, It will be possible to operate advertisements with a high effect of attracting customers.

  Thus, in this embodiment, the advertisement effect measuring apparatus 100 is based on the human flow image acquired from the human flow measurement sensor 80 and the browsing measurement sensor 90, the human flow image table, the browsing image, and the browsing image table. , You can match the viewers with the people. Further, based on the process of matching the viewer and the flower, the store entry rate, the browse rate, and the advertisement effectiveness rate, which are indexes indicating the effect of attracting customers of the display advertisement in front of the store, are calculated and stored. The user using the advertisement effect measuring device 100 can understand the influence on the number of people entering the advertisement based on any one of the browsing entry rate, the browsing rate, and the advertisement effectiveness rate. .

[Second Embodiment]
2nd Embodiment demonstrates the case where the effect for every time slot | zone is measured about each of several advertisements, and the advertisement displayed in each time slot | zone is determined. The three advertisement display time zones are 6 o'clock to 12 o'clock, 12 o'clock to 18 o'clock, and 18 o'clock to 24 o'clock, respectively. The three display advertisements are referred to as content A, content B, and content C, respectively.
FIG. 6 is a schematic block diagram showing a configuration of the advertisement effect measuring device 100 in which the human flow measuring sensor 80 and the browsing measuring sensor 90 are connected in the second embodiment. In the figure, parts corresponding to those in FIG.

  The content effect calculation unit 104d acquires information (hereinafter referred to as advertisement schedule information) indicating which advertisement is to be displayed for each advertisement display time zone on the content display unit 107 from the content selection unit 106. In the present embodiment, the first advertisement schedule information is registered by the user, but is not limited thereto.

  When the content effect calculation unit 104d acquires the advertisement schedule information, the content effect calculation unit 104d acquires a number measurement table for each advertisement display time period from the number measurement unit 103 every time the advertisement display time period passes. In the present embodiment, since the measurement of the human flow measurement sensor 80 and the browsing measurement sensor 90 is performed for each advertisement display time zone, the number of people measurement table is displayed for each advertisement display time zone. Acquired as a number of people counting table.

  In addition, the content effect calculation unit 104d uses the number of people entering the store, the number of people not entering the store, the number of viewers, and the number of viewers entering the store, as in the first embodiment. The store rate, the browsing rate, and the advertising effectiveness rate are calculated. The content effect calculation unit 104d refers to the advertisement schedule information, and obtains an advertisement ID and time zone information, which is information indicating which advertisement display time zone and for which advertisement the person counting table is for. It detects, and produces | generates the content effect table classified by time zone which stored this browsing entrance rate, this browsing rate, and this advertising effectiveness rate with this advertisement ID and this time zone information.

  The content selection unit 106 detects a display advertisement with the highest advertisement effect rate for each advertisement display time period based on the advertisement effect rate of the time period content effect table stored in the content effect storage unit 105d, and displays the display advertisement. An advertisement ID indicating an advertisement and information indicating the advertisement display time zone are generated as new advertisement schedule information. In this embodiment, the advertisement effect rate is used when generating the advertisement schedule information. However, the present invention is not limited to this, and for example, a store entry rate or a browsing rate may be used.

When the content scheduler 109 acquires the advertisement schedule information from the content selection unit 106, based on the advertisement schedule information, the content scheduler 109 receives an advertisement ID corresponding to the advertisement display time zone for each advertisement display time zone. Request display of advertisements to show.
When the content display unit 107 receives a request for displaying the advertisement indicated by the advertisement ID corresponding to the advertisement display time period from the content scheduler 109, the content display unit 107 reads the advertisement indicated by the advertisement ID from the content storage unit 108, and the content display unit 107 In the display area. The display area corresponds to the advertisement panel c100 in FIG.

The content storage unit 108 stores an advertisement ID and an advertisement in association with each other. The advertisement is an image or a moving image, but is not limited thereto.
Thus, in the second embodiment, not only the same effect as the first embodiment can be obtained, but also the advertisement to be displayed is automatically changed based on the advertisement effect rate for each advertisement display time zone. The user can more easily and more effectively carry out advertisement operations.

[Third embodiment]
The advertising effect measurement apparatus 100 according to the third embodiment does not generate a time-based content effect table, but generates an external environment and a content effect table for each advertisement (hereinafter referred to as an external environment-specific content effect table). Automatically display advertisements with high advertising effectiveness for each environment. The external environment is, for example, temperature, humidity, weather, and the like. Therefore, in this embodiment, the advertisement display time zone is a period during which the external environment does not change. However, since the temperature and the humidity are continuous values that are likely to change, it is determined that the measured values do not change unless the measured values exceed a predetermined range. Details of the range will be described later.

  FIG. 7 is a schematic block diagram illustrating a configuration of the advertising effect measurement device 100 in which the human flow measurement sensor 80, the browsing measurement sensor 90, and the external environment sensor 300 are connected in the third embodiment. The advertisement effect measuring apparatus 100 of this embodiment is further connected to the server 600 via the network 500. In the figure, the same reference numerals are given to portions corresponding to the respective portions in FIG.

When the external environment sensor 300 receives a request for acquiring information indicating the external environment (hereinafter referred to as external environment information) from the external environment management unit 301, the external environment sensor 300 measures temperature, humidity, and weather.
The external environment management unit 301 reads external environment information from the external environment sensor 300. The external environment management unit 301 generates an external environment information table based on the external environment information. The external environment information table is a table in which a weather ID indicating the weather of the external environment information, an air temperature ID indicating the level of temperature, a humidity ID indicating the temperature, and a humidity ID, and humidity are written.

  The weather ID is an ID indicating weather by 2 if clear, 1 if clear, 0 if cloudy, -1 if rain, -2 if snow. The temperature ID is, for example, an ID indicated by 1 when the temperature is less than 10 ° C., 0 when the temperature is -10 ° C. or more and less than 20 ° C. The humidity ID is, for example, an ID indicated by -1 when less than 40% is low, 0 when 40% or more and less than 60% is normal, and 1 when 60% or more is high. In addition, the external environment management unit 301 reads external environment prediction information from the communication unit 302. The external environment prediction information is information indicating the weather immediately after the weather forecast or the like, the temperature, the humidity, or the like. Immediately after this, it may be a few minutes later, a few hours later, or a few days later, but it indicates the display start time of the next advertisement display time zone by the next advertisement effect measuring device 100. It is not limited to.

  The content effect calculation unit 104a acquires a person count table for each external environment. In the present embodiment, since the advertisement display time period is from immediately after the external environment changes to the next change, the acquired number measurement table is a number measurement table for each external environment. When the content effect calculation unit 104a acquires the number-of-peoples measurement table for each external environment, the browsing entry rate, the browsing rate, and the advertising effectiveness rate are browsed for each external environment as in the first embodiment. Calculated as a store entry rate, a browsing rate, and an advertising effectiveness rate. Thereafter, the content effect calculation unit 104a acquires an external environment information table.

The content effect calculation unit 104a refers to the external environment information table, and inputs the weather ID, temperature ID, humidity ID, temperature, humidity, and advertisement ID of the external environment table for each external environment. A content effect table for each external environment stored together with a store rate, a browsing rate, and an advertisement effect rate is generated. When the content effect calculation unit 104 generates the content effect table for each external environment, the content effect storage unit 105 stores the content effect table for each external environment in the content effect storage unit 105.
The content effect storage unit 105a stores a content effect table for each external environment.

  The content selection unit 106a reads from the content effect storage unit 105 all the external environment-specific content effect tables (hereinafter referred to as all external environment-specific content effect tables) accumulated so far. The content selection unit 106a refers to the content effect table for all external environments, selects a display advertisement with the highest advertising effectiveness rate for each external environment, and represents a weather ID, an air temperature ID, and the external environment. An external environment advertisement table in which the humidity ID, the temperature, the humidity, and the advertisement ID indicating the display advertisement selected for each external environment are written is generated. Details of the external environment advertisement table will be described later.

When the content selection unit 106 generates the external environment advertisement table, the content selection unit 106 reads external environment prediction information from the external environment management unit 301. The content selection unit 106 detects a record that matches information indicating the external environment immediately after the external environment prediction information from the external environment advertisement table, determines a display advertisement immediately after, and displays the determined display advertisement The ID is output to the content scheduler 109.
Upon receiving the advertisement ID, the content scheduler 109 causes the content display unit 107 to display the advertisement indicated by the advertisement ID.
When the content display unit 107 receives an advertisement display request indicated by the advertisement ID from the content scheduler 109, the content display unit 107 reads and displays the corresponding advertisement.

The communication unit 302 reads external environment prediction information from the server 600 via the network 500 and outputs the external environment prediction information to the external environment management unit 301.
The network 500 is, for example, a network such as the Internet or a mobile communication network, but is not limited thereto.
The server 600 is a server on the Internet that stores external environment prediction information.

FIG. 8 is a table showing an external environment advertisement table. The external environment advertisement table t800 displays a weather ID t801, a temperature ID t802, a humidity ID t803, and an advertisement ID t701. Based on the external environment advertisement table t800 and the external environment prediction information, the content selection unit 106 can display an advertisement with a high advertising effectiveness rate that is considered to have a higher effect of attracting customers for each immediately following external environment. .
Thus, in the third embodiment, not only the same effect as in the first embodiment is obtained, but also the advertisement to be displayed is automatically changed based on the advertising effectiveness rate for each external environment. More easily, it is possible to carry out advertisement operations with a high effect of attracting customers for each external environment.

[Fourth Embodiment]
The advertisement effect measuring apparatus 100 according to the fourth embodiment calculates an advertisement effect rate for the rare external environment by performing regression analysis. The rare external environment is, for example, a case where the weather is snowy, the temperature is high, and the humidity is low.
FIG. 9 is a schematic block diagram illustrating a configuration of the advertising effect measurement device 100 in which the human flow measurement sensor 80, the browsing measurement sensor 90, and the external environment sensor 300 are connected in the fourth embodiment. In the figure, portions corresponding to the respective portions in FIG.

The content effect storage unit 105b outputs the same content effect table for all external environments as in the third embodiment to the regression analysis unit 110.
When the regression analysis unit 110 acquires the content effect table for all external environments, the regression analysis unit 110 performs regression analysis based on the weather ID, temperature, and humidity of the content effect table for all external environments, so that the regression for each external environment is performed. Calculate the coefficient.

Here, the weather ID is a dummy variable representing the weather, and the temperature and humidity are continuous variables. The regression formulas for calculating the browsing rate, browsing rate, and advertising effectiveness rate for each external environment are a1, b1, c1 for constant terms, a2, b2, c2, and humidity for the temperature regression coefficients, respectively. If the regression coefficients are a3, b3, c3 and the regression coefficients of weather ID are a4, b4, c4,
Browsing rate = a1 + a2 x temperature + a3 x humidity + a4 x weather ID
Browsing rate = b1 + b2 x temperature + b3 x humidity + b4 x weather ID
Advertising effectiveness rate = c1 + c2 x temperature + c3 x humidity + c4 x weather ID
It becomes.

The regression analysis unit 110 generates a regression analysis external environment advertisement table using the regression equation. The regression analysis external environment advertisement table selects an advertisement having the highest advertising effectiveness rate for each external environment calculated using the regression formula, an advertisement ID indicating the advertisement selected for each external environment, and the It is a table in which the weather ID, temperature, and humidity of the content effect table for all external environments are written. Details of the regression analysis external environment advertisement table will be described later.
The content selection unit 106b reads the regression analysis external environment advertisement table. The content selection unit 106b determines an advertisement to be displayed immediately after based on the regression analysis external environment advertisement table and the external environment prediction information, the advertisement ID indicating the determined display advertisement, and the corresponding external environment prediction information Are output to the content scheduler 109 as external environment advertisement schedule information.

FIG. 10 is a table showing a part of an example of the regression analysis external environment advertisement table. The regression analysis external environment advertisement table t900 displays the weather ID t801, the temperature t902, the humidity t903, and the advertisement ID t701. The content selection unit 106 determines a display advertisement to be displayed immediately after the regression analysis external environment advertisement table and the external environment prediction information.
Thus, in the fourth embodiment, not only the same effects as those of the first embodiment, the second embodiment, and the third embodiment are obtained, but also the advertising effectiveness rate for a rare external environment is obtained by regression analysis. By calculating, selecting an advertisement with a high effect of attracting customers for the rare external environment, and automatically displaying the advertisement, it is possible to perform an advertisement operation with a higher effect of attracting customers.

[Fifth Embodiment]
The advertisement effect measuring apparatus 100 according to the fifth embodiment calculates, for example, a content effect table for each gender and age that the user wants to attract customers (hereinafter referred to as a gender and age content effect table). Furthermore, the advertising effectiveness measuring apparatus 100 according to the present embodiment performs weighting in the order of the customer demographic targeted by the user, and the weights are used as the browsing entrance rate, the browsing rate, and the advertising effectiveness rate of the gender and age content effect table. Finally, for each gender and age, the sum of each browsing entrance rate, each browsing rate, and each advertising effectiveness rate is calculated, and the effect of attracting display advertisements in consideration of the target customer segment is calculated. It is assumed to be an index to be expressed (hereinafter referred to as a target customer acquisition effect).

FIG. 11 is a schematic block diagram illustrating a configuration of the advertisement effect measuring device 100 in which the human flow measuring sensor 80 and the browsing measuring sensor 90 are connected in the fifth embodiment. In FIG. 6, parts corresponding to those in FIG. 6 are denoted by the same reference numerals and description thereof is omitted. The human flow detection unit 180 c indicates the human flow ID from the human flow image stored in the first image storage unit 82. Detect the gender and age of a person. The human flow detecting unit 180c generates and writes the detected gender and age in the human flow table by generating fields for displaying the sex and age.

  The person counting unit 103c generates a person counting table for each combination of gender and age (hereinafter referred to as gender and age) based on the person flow table, the person flow measurement table, and the browsing measurement table. In addition, the number of people counting unit 103 includes a gender corresponding to the number of people counting table for each gender and age, and a age corresponding to the number of people counting table for each gender and age, respectively. Create and write a field to display.

The importance setting unit 200 gives a large weight to a target customer group and a small weight to a non-target customer group by user input for each gender and age, and generates the input weight as an importance table. To do. The weight is a ratio representing relative importance such that the sum is 1. Details of the importance table will be described later. When the importance level setting unit 200 generates the importance level table, the importance level setting unit 200 outputs the importance level table to the importance level storage unit 201 for storage. In the present embodiment, the user inputs arbitrary weights to the importance table by the user. However, the present invention is not limited to this. For example, a combination of predetermined weights is prepared in advance, and the combination of weights is determined by the user. May be selected.
The importance storage unit 201 stores an importance table.

  When the content effect calculation unit 104c receives the number of people measurement table for each gender and age, as in the first embodiment, the content entry calculation unit 104c sets the browsing entry rate, the browsing rate, and the advertising effectiveness rate for each gender and age. It calculates as a browsing entrance rate, a browsing rate, and an advertising effectiveness rate. In addition, the number-of-people measurement table for each sex and age shall be obtained for each combination of a time zone and an advertisement, as in the second embodiment. Thereafter, the content effect calculation unit 104c reads the importance level table.

  The content effect calculation unit 104c refers to the importance level table, and multiplies the gender and age weight by the browsing entry rate for each gender and age, the viewing rate, and the advertisement effect rate. The content effect calculation unit 104c stores the browsing entrance rate, the browsing rate, and the advertising effectiveness rate for each gender and age, multiplied by the weight for each gender and age, together with the gender and age of the number measurement table. The content effect table for each sex and age is generated.

The content effect calculation unit 104c refers to the content effect table for each gender and age, and displays the browsing entry rate, browsing rate, and advertisement effectiveness rate for each gender and age, for each browsing entry rate, for each browsing rate, and for advertisements. For each effectiveness rate, the age is added, and the browsing entrance rate, the browsing rate, and the advertising effectiveness rate for each gender are calculated. The content effect calculation unit 104c adds the browsing entry rate, the browsing rate, and the advertising effectiveness rate for each gender, this time with respect to the gender, the browsing entry rate reflecting the importance, the browsing rate, Calculate the advertising effectiveness rate.
The content effect calculation unit 104c generates a new content effect table as a table for storing the browsing entrance rate, the browsing rate, and the advertisement effect rate reflecting the importance, and stores the new content effect table as a content effect storage. Store in the unit 105. Details of the multiplication of the weight and the addition will be described later.

  FIG. 12 is an example of the importance table. The importance level table t600 displays numbers representing weights for each age and sex in increments of 10 years. In the present embodiment, all of the 70s and above are represented by one weight for each gender, but the present invention is not limited to this, and the age increment is not limited to the 10-year increment. As an example, the weight t601 represents the weight for a teenage male, and the value is 0.4. Since the weight t601 is the highest value compared to other weights, it can be seen that the customer target of the user who created the importance level table t800 is a teenage male.

  Here, the multiplication of the weights and the addition will be specifically described. As a simple example, the browsing entry rate, browsing rate, and advertising effectiveness rate for all genders and ages are the browsing entrance rate t701, browsing rate t702, and advertising effectiveness of the content A in the content effect table t700 of FIG. Consider a case where the value is the rate t703. Also, consider the case where the importance level table is the same as the importance level table t600 of FIG. First, for each gender and age, a weight corresponding to the gender and age is multiplied to the browsing entrance rate, the browsing rate, and the advertisement effect rate. For example, a male teenage browsing entrance rate, a browsing rate, and an advertising effectiveness rate are: a sex y age x generation browsing entrance rate multiplied by weight WyxRER, a browsing rate WyxRR, an advertising effectiveness rate WyxCER Then, it becomes as follows.

W Male 10RER = 0.143 × 0.4 = 0.0572
W Male 10RR = 0.667 × 0.4 = 0.0267
W Male 10CER = 0.0950 × 0.4 = 0.0380
The content effect calculation unit 104 calculated as described above sets the browsing entry rate, the browsing rate, and the advertising effectiveness rate for each gender and age. Increase the effectiveness rate, and calculate the browsing entry rate, browsing rate, and advertising effectiveness rate for each gender.

The browsing entry rate, browsing rate, and advertising effectiveness rate for each gender multiplied by weight are the browsing entry rate, browsing rate, and advertising effectiveness rate for each sex y multiplied by weight, respectively, as WyRER, WyRR, and WyCER.
W male RER = W male 10 RER + W male 20 RER + ... + W male 70 RER
W male RR = W male 10RR + W male 20RR + ... + W male 70RR
W male CER = W male 10 CER + W male 20 CER + ... + W male 70 CER
It becomes.

Thereafter, the content effect calculation unit 104c adds the browsing entry rate, the browsing rate, and the advertising effectiveness rate for each gender, and calculates the browsing entrance rate, the browsing rate, and the advertising effectiveness rate in consideration of the target customer segment. . Therefore, the browsing entrance rate, browsing rate, and advertising effectiveness rate in consideration of the target customer segment are the browsing entrance rate, browsing rate, and advertising effectiveness rate in consideration of the target customer segment, respectively, WRER, WRR, and WCER. ,
WRER = W Male RER + W Female RER
WRR = W Male RR + W Female RR
WCER = W male CER + W female CER
It becomes.

The content effect calculation unit 104c generates and stores a content effect table for each time period as the browsing entry rate, the browsing rate, and the advertisement effect rate for the WER, the WRR, and the WCER, respectively. Further, the content effect calculation unit 104c acquires the advertisement schedule information, refers to the advertisement schedule information, and obtains the advertisement ID corresponding to the content effect table for each time zone and the time zone information, and the content for each time zone. Store in the effect table.
As described above, in the fifth embodiment, not only the same effect as that obtained in the first embodiment and the second embodiment is obtained, but also more attracting customers considering the gender and age as a target to attract customers. It is possible to automatically display highly effective advertisements according to time periods. In addition, although the importance of this embodiment was only sex and age, it is not necessarily restricted to this.

The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and design changes and the like within a scope not departing from the gist of the present invention are included. .
Note that a program for realizing the functions of the human flow measurement unit, the number of people measurement unit, and the content effect calculation unit in FIG. 2 is recorded on a computer-readable recording medium, and the program recorded on the recording medium is stored in the computer. The advertising effectiveness rate may be calculated by loading it into the system and executing it. Here, the “computer system” includes an OS and hardware such as peripheral devices.

Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used.
The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system.

  Furthermore, the “computer-readable recording medium” dynamically holds a program for a short time like a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line. In this case, a volatile memory in a computer system serving as a server or a client in that case, and a program that holds a program for a certain period of time are also included. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

(1) According to one aspect of the present invention, in the first measurement region, referring to the human flow information indicating the position of the person detected in the first measurement region including the region through which the person entering the store passes. A human flow measurement unit that determines whether each detected person has entered the store, a region that includes a region that is common to the first measurement region, and that includes a region where a person who views the advertisement is located. Browsing information indicating the position of the person detected in the second measurement area, browsing measurement information indicating whether or not each person detected in the second measurement area has browsed the advertisement, the human flow information, With reference to the determination result of the human flow measuring unit, the number measuring unit that calculates the number of people entering the store who browses the advertisement and enters the store, and the number of people entering the browsing And a content effect calculation unit that calculates an index representing the effect of attracting customers by the advertisement. An advertisement effect measurement apparatus, wherein the door.

(2) According to another aspect of the present invention, the number-of-persons counting unit calculates the number of people who have browsed the advertisement with reference to the browsing measurement information, and the content effect calculation unit includes: The advertising effect measuring apparatus according to (1), wherein a browsing store rate obtained by dividing the browsing store number by the browsing number is calculated as an index representing the customer attraction effect.
(3) Moreover, the other aspect of this invention is provided with the content selection part which selects the content displayed as the said advertisement, The said content effect calculation part calculates the parameter | index showing the said customer collection effect for every said content, The content selection unit is the advertising effect measurement device according to (1) or (2), wherein the content to be displayed is selected using the index calculated by the content effect calculation unit.

(4) According to another aspect of the present invention, in the content effect calculation unit, the index representing the effect of attracting customers is calculated for each combination of an external environment and the content. It is an advertising effect measuring device.
(5) According to another aspect of the present invention, the human flow information includes information indicating at least one of sex and age, and the content effect calculation unit performs weighting according to the information indicating the at least one. The advertising effect measuring device according to any one of (1) to (4), wherein an index representing the customer attracting effect is calculated.

(6) Moreover, the other aspect of the present invention is a method in which the advertisement effect measuring device calculates an index representing the effect of attracting customers by the advertisement, and includes a first measurement including a region through which a person entering the store passes. A first process of determining whether each person detected in the first measurement area has entered the store with reference to human flow information representing the position of the person detected in the area; Browsing information indicating the position of the person detected in the second measurement area including the area where the person who browses the advertisement is located, including the area common to the one measurement area, and detected in the second measurement area Browsing the advertisement with reference to the browsing measurement information indicating whether or not each person browsed the advertisement, the human flow information, and the determination result of the first process, and in the store A second process of calculating the number of visitors entering the store, which is the number of people entering the store, and the number of visitors entering the store Used, an advertisement effect measurement method characterized in that it comprises a third step of calculating an index representing the attracting effect of the advertisement.

(7) Moreover, the other aspect of this invention is a program for functioning a computer as the advertisement effect measuring device in any one of (1) to (6).

  Although this invention is used suitably when displaying an advertisement with an advertising medium, it is not restricted to this.

80: Human flow measurement sensor 81 ... First video camera 82 ... First image storage unit 90 ... Browsing measurement sensor 91 ... Second video camera 92 ... Second image Storage unit 100: Advertising effect measurement device 101 ... Human flow measurement unit 102 ... Browsing measurement unit 103 ... Number of people measurement unit 104 ... Content effect calculation unit 105 ... Content effect storage unit 106 ... Content selection unit 107 ... Content display unit 108 ... Content storage unit 109 ... Content scheduler 110 ... Regression analysis unit 180 ... Human flow detection unit 181 ... Human flow table storage unit 190 ... Browsing detection unit 191 ... Browsing table storage unit 200 ... Importance level setting unit 201 ... Importance level storage unit 300 ... External environment sensor Sir 301: External environment management unit 302 ... Communication unit 500 ... Network 600 ... Server greeting

Claims (7)

Each person detected in the first measurement area enters the store with reference to human flow information indicating the position of the person detected in the first measurement area including the area through which the person entering the store passes. A human flow measurement unit for determining whether or not a store has been established;
Browsing information indicating the position of a person detected in a second measurement area that includes an area common to the first measurement area and includes an area where a person who views an advertisement is located; and the second measurement area The advertisement is browsed with reference to browsing measurement information indicating whether or not each person detected in the browsing has browsed the advertisement, the human flow information, and the determination result of the human flow measurement unit, and the store A people counting unit that calculates the number of people entering the store,
An advertisement effect measuring apparatus comprising: a content effect calculation unit that calculates an index representing an effect of attracting customers by the advertisement by using the number of visitors to the store. The number-of-people counting unit calculates the number of people who browsed the advertisement with reference to the browsing measurement information,
The advertisement effect measuring device according to claim 1, wherein the content effect calculation unit calculates a browsing store rate obtained by dividing the browsing store number by the browsing number as an index representing the customer collection effect. . A content selection unit for selecting content to be displayed as the advertisement;
The content effect calculation unit calculates an index representing the customer attraction effect for each content,
The advertisement effect measuring apparatus according to claim 1, wherein the content selection unit selects the content to be displayed using the index calculated by the content effect calculation unit. The advertisement effect measuring apparatus according to claim 3, wherein the content effect calculation unit calculates an index representing the customer attraction effect for each combination of an external environment and the content. The human flow information includes information indicating at least one of gender and age,
The advertisement effect measuring apparatus according to claim 1, wherein the content effect calculation unit calculates an index representing the customer collection effect by performing weighting according to the information indicating the at least one. A method in which the advertising effect measuring device calculates an index representing an effect of attracting customers by the advertisement,
Each person detected in the first measurement area enters the store with reference to human flow information indicating the position of the person detected in the first measurement area including the area through which the person entering the store passes. A first step of determining whether or not a store has been established;
Browsing information indicating the position of a person detected in a second measurement area that includes an area common to the first measurement area and includes an area where a person who views an advertisement is located; and the second measurement area Browsing the advertisement with reference to the browsing measurement information indicating whether or not each of the people detected in the browsing has browsed the advertisement, the human flow information, and the determination result of the first process, and A second process of calculating the number of visitors entering the store, which is the number of people entering the store;
And a third step of calculating an index representing an effect of attracting customers by the advertisement using the number of visitors to the store.   A program for causing a computer to function as the advertisement effect measuring device according to any one of claims 1 to 6.

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