Data analysis device and its program

Abstract

To provide a data analyzer and a program thereof, by which, even in a small area unit such as a zip code area, a municipality, and a mesh, an appropriate viewing state or a browsing state in the area can be grasped.SOLUTION: A data analyzer and a program thereof are configured to: aggregate viewing data for each specific area from viewing data for each of a plurality of television receivers; extract an analysis area that is an area in which the number of viewers or a viewing rate based on the viewing data is higher than a specific value; set a wide range area including the analysis area as a comparison area; multiply the number of viewers in the analysis area by each statistical value of statistical data to calculate a composition ratio by weighting; calculate a lift value using the composition ratio and a composition ratio of each statistical value of the comparison area; analyze regional characteristics of the analysis area regarding the viewing state; and display the viewing state in a small area unit on a map.SELECTED DRAWING: Figure 9

Description

Technical Field

[0001] The present invention relates to a data analysis apparatus, and more particularly to a data analysis apparatus and a program thereof that can grasp an appropriate viewing situation or browsing situation even with a small amount of sample of viewing data or browsing data.

Background Art

[0002] [Prior Art] With the advent of television receivers connected to a network, television stations or television manufacturers can acquire viewing data for each television receiver, and there is a movement to utilize the viewing data. In particular, it has been studied to grasp the viewing situation in units of small areas such as zip code areas and use it for area marketing or area targeting.

[0003] In addition, site operating companies can acquire browsing data of sites for each terminal device of a computer connected to a network, and similarly, it has been studied to use the browsing situation in units of small areas for area marketing or area targeting.

[0004] [Related Art] In addition, as related prior art documents, there are JP-A-2004-220337 "Television Broadcast Receiver and Television Broadcast Transmission / Reception System" (Patent Document 1) and JP-A-2002-077866 "Electronic Program Information Providing System, Electronic Program Information Utilization System, Electronic Program Information Providing Apparatus, Medium, and Information Aggregate" (Patent Document 2).

[0005] Patent Document 1 describes delivering a moving image linked to a program of a television broadcast. Patent Document 2 describes providing information associated with program information or advertisement information when providing an electronic program on the Internet.

Prior Art Documents

Patent Documents

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-220337 [Patent Document 2] Japanese Patent Application Laid-Open No. 2002-077866 [Summary of the Invention] [Problems to be Solved by the Invention]

[0007] However, in the above conventional technology, when aggregating viewing data or browsing data by postal code area unit, since the population in the area is originally small, the samples of the obtained viewing data or browsing data become fewer, and it is impossible to properly grasp the characteristics of the area unit with a small number of samples, and there is a problem that it cannot be used for area marketing or the like.

[0008] In addition, Patent Documents 1 and 2 do not describe a configuration that can supplement a small amount of viewing data in an area by utilizing regional characteristics and grasp an appropriate viewing situation.

[0009] The present invention has been made in view of the above actual situation, and an object of the present invention is to provide a data analysis apparatus and a program thereof that can grasp an appropriate viewing situation or browsing situation in an area even in a small area unit such as a postal code area, a municipality, or a mesh. [Means for Solving the Problems]

[0010] The present invention for solving the problems of the above conventional example is a data analysis apparatus for analyzing television viewing data From characterized by performing processing for each television receiver connected to a network for viewing data Aggregate the viewing data for each specific area from the タ, extract the areas where the number of viewers or the viewing rate based on the viewing data is higher than a specific value as analysis areas, set the wide area that includes the analysis areas and is viewed as the comparison area, multiply each statistical value of the statistical data stored for the number of viewers in the analysis areas to perform weighting and calculate the composition ratio, use the composition ratio and the composition ratios of the statistical values of the comparison area to calculate the lift value, and analyze the regional characteristics of the analysis areas regarding the viewing situation thereof.

[0011] The present invention is A data analysis device for analyzing the browsing data of a website, which aggregates the browsing data for each specific area from the browsing data of each terminal device of a computer connected to a network, extracts the areas where the number of browsers or the browsing rate based on the browsing data is higher than a specific value as analysis areas, sets the wide area that includes the analysis areas and is browsed as the comparison area, multiplies each statistical value of the statistical data stored for the number of browsers in the analysis areas to perform weighting and calculate the composition ratio, uses the composition ratio and the composition ratios of the statistical values of the comparison area to calculate the lift value, and performs the process of analyzing the regional characteristics of the analysis areas regarding the browsing situation characterized in that of the - data analysis apparatus.

[0012] The present invention is In the above data analysis device, for the output of the viewing situation or the browsing situation, display the viewing situation or the browsing situation in area units on the map in color tones characterized by

[0013] In the above data analysis device, the present invention is characterized in that when a coupon issued on the screen of a TV program or the screen of a terminal device is read at a store, usage information of the coupon is obtained from the store and used for measuring the effect of commercials.

[0014] In the above data analysis device, the present invention uses the area where a viewer who uses a coupon watched or the area where a browser who uses a coupon browsed as the visitor analysis area, uses the wide area that includes the visitor analysis area and is viewed or browsed as the comparison area, multiplies each statistical value of the statistical data stored in the number of visitors in the visitor analysis area to perform weighting and calculates a composition ratio, and calculates a lift value using the composition ratio and the composition ratios of the statistical values in the comparison area, and performs processing to analyze the regional characteristics of the visitor analysis area regarding the store visit situation.

[0015] The present invention is related to the viewing data of a TV From A processing program that operates in a data analysis device for analyzing data, which causes the data analysis device to perform processing for each TV receiver connected to a network regarding the viewing data Aggregate the viewing data for each specific area from the タ, extract the areas where the number of viewers or the viewing rate based on the viewing data is higher than a specific value as analysis areas, set the wide area that includes the analysis areas and is viewed as the comparison area, multiply each statistical value of the statistical data stored for the number of viewers in the analysis areas to perform weighting and calculate the composition ratio, use the composition ratio and the composition ratios of the statistical values of the comparison area to calculate the lift value, and analyze the regional characteristics of the analysis areas regarding the viewing situation characterized by functioning to perform such processing.

[0016] The present invention is A processing program that operates on a data analysis device for analyzing site browsing data, causing the data analysis device to aggregate the browsing data for each specific area from the browsing data of each terminal device of a computer connected to a network, extract an area where the number of viewers or the viewing rate based on the browsing data is higher than a specific value as an analysis area, set a wide area including the analysis area that has been browsed as a comparison area, perform weighting by multiplying each statistical value of the statistical data stored in the number of viewers in the analysis area to calculate a composition ratio, calculate a lift value using the composition ratio and the composition ratios of the statistical values in the comparison area, and function to perform processing for analyzing the regional characteristics of the analysis area regarding the browsing situation characterized by this.

[0017] In the program of the above data analysis device, the present invention is characterized in that for the output of the viewing situation or browsing situation, the viewing situation in area units on a map is displayed in tones.

[0018] In the program of the above data analysis device, when a coupon issued on the screen of a TV program or the screen of a terminal device is read at a store, the present invention is characterized by functioning to obtain usage information of the coupon from the store and use it for measuring the effect of commercials.

[0019] In the program of the above data analysis device, the present invention uses the area viewed by the viewer who used the coupon or the area browsed by the browser who used the coupon as the visitor analysis area, uses the widely viewed area including the visitor analysis area as the comparison area, multiplies each statistical value of the statistical data stored in the number of visitors in the visitor analysis area to perform weighting and calculates the composition ratio, and calculates the lift value using the composition ratio and the composition ratio of each statistical value in the comparison area, and functions to perform processing for analyzing the regional characteristics of the visitor analysis area regarding the visitor situation.

Effect of the Invention

[0020] According to the present invention, since it is a data analysis device that performs processing on the viewing data for each television receiver connected to the network Aggregate the viewing data for each specific area from the viewing data of each terminal device of a computer connected to a network, extract an area where the number of viewers or the viewing rate based on the viewing data is higher than a specific value as an analysis area, set a wide area including the analysis area that has been viewed as a comparison area, perform weighting by multiplying each statistical value of the statistical data stored in the number of viewers in the analysis area to calculate a composition ratio, calculate a lift value using the composition ratio and the composition ratios of the statistical values in the comparison area, and analyze the regional characteristics of the analysis area regarding the viewing situation there is an effect that the viewing situation or browsing situation for each area can be grasped even if the sample of the viewing data or browsing data for each area is small.

[0021] According to the present invention, from the browsing data of the sites for each terminal device of the computer connected to the network o aggregate the browsing data for each specific area to extract an area where the number of browsers or the browsing rate based on the browsing data is higher than a specific value as the analysis area, use the widely browsed area including the analysis area as the comparison area, browse multiply each statistical value of the statistical data stored in the number of browsers in the analysis area to perform weighting and calculate the composition ratio, and calculate the lift value using the composition ratio and the composition ratio of each statistical value in the comparison area browsing Since it is a data analysis device that performs processing for analyzing the regional characteristics of the analysis area regarding the browsing situation, browsing even if the sample of the browsing data for each area is small browsing there is an effect that the regional characteristics of the browsing situation can be grasped. browsing even if the sample of the browsing data for each area is small browsing there is an effect that the regional characteristics of the browsing situation can be grasped.

Brief Description of the Drawings

[0022]

Figure 1

Figure 2

Figure 3

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Figure 8

Figure 9

Mode for Carrying Out the Invention

[0023] Embodiments of the present invention will be described with reference to the drawings. [Outline of Embodiment] The data analysis device (this device) according to the embodiment of the present invention aggregates viewing data for each small area such as a postal code area, a city, town, and village area, and a mesh area from the viewing data for each television receiver, assigns a code of regional characteristics obtained by cluster analysis or the like to the small area, re-aggregates the viewing data in units of the code, calculates the ratio of each code to the total for each item of the analyzed code, recalculates lift value data indicating the viewing status based on the number of households, population, or number of connections for each code using the ratio, outputs the viewing status for each code, and displays the viewing status in units of small areas on the map. Therefore, even if the sample of viewing data in units of areas is small, the viewing status for each area can be grasped.

[0024] In addition, this device issues a coupon in the CM (commercial) of a program. When a viewer acquires (takes a picture of) the coupon with a smartphone or the like and uses it at a store, the store side can determine which postal code area and which program the coupon was acquired from. Therefore, the effect of the advertisement on the viewing status in the area can be confirmed.

[0025] In addition, this device aggregates the viewing data for each specific small area from the viewing data for each television receiver, extracts an area where the number of viewers or the viewing rate based on the viewing data is higher than a specific value as an analysis area, sets a wide area including the analysis area as a comparison area, multiplies each statistical value of the statistical data by the number of viewers in the analysis area for weighting to calculate a composition ratio, calculates a lift value using the composition ratio and the composition ratios of the respective statistical values in the comparison area, and analyzes the regional characteristics of the analysis area regarding the viewing situation. Therefore, even if the sample of the viewing data per area is small, the regional characteristics of the viewing situation can be grasped.

[0026] In addition, this device is applicable not only to viewing data but also to the browsing data for each terminal device of a computer connected to a network, can grasp the browsing situation for each area, confirm the effect of an advertisement, and grasp the regional characteristics of the browsing situation. Details will be described later.

[0027] [Configuration of This Device: Figure 1] The configuration of this device will be described with reference to Figure 1. Figure 1 is a configuration block diagram of this device. As shown in Figure 1, this device (viewing data analysis device) 1 includes a control unit 11, a storage unit 12, and an interface unit 13. A display unit 14 and an input unit 15 are connected to the interface unit 13. Further, a viewing data storage unit 21, an area aggregation data storage unit 22, an area characteristic storage unit 23, an area characteristic re-aggregation data storage unit 24, a lift value data storage unit 25, and a map information storage unit 26 are connected, and it is further connected to a network 3.

[0028] [Each Part of This Device] The control unit 11 executes a processing program stored in the storage unit 12 to execute the processing described later. The storage unit 12 stores a processing program and also stores data, parameters, etc. necessary for the processing. The interface unit 13 is an interface for connecting to an external device and a network. The display unit 14 displays various data described below and also displays map information indicating the viewing status. The input unit 15 inputs instructions for processing, instructions for display, and the like.

[0029] [Viewing data storage unit 21: Figure 2] The viewing data storage unit 21 stores viewing data for each ID of the television receiver. Specifically, as shown in Figure 2, the viewing data for each television receiver ID stores the viewing start time, viewing end time, and viewing duration for a specific commercial (CM) for each television receiver ID. Figure 2 is a schematic diagram showing the viewing data.

[0030] [Area aggregation data storage unit 22: Figure 3] Based on this viewing data, the area aggregation data storage unit 22 stores area aggregation data obtained by aggregating the viewing data for each postal code area, as shown in Figure 3. Figure 3 is a schematic diagram showing the area aggregation data. The area aggregation data is, for each postal code for a specific CM, the number of connected sets within the postal code area, the total viewing time (total viewing duration) within the area, the number of households or connection rate (number of households / number of connections) within the area. Note that the viewing count may be aggregated in time units of less than 5 minutes (0 - 5), 5 minutes or more and less than 10 minutes (5 - 10), 10 minutes or more and less than 20 minutes (10 - 20), 20 minutes or more and less than 30 minutes (20 - 30). Also, the above viewing time distribution is arbitrary.

[0031] The number of households is obtained from statistical data such as the census. The statistical data should be stored in the area characteristic storage unit 23. The number of connections is the total number of televisions (TVs) that have been connected to the network within the area. The number of TVs that are hard - connectable to the network but have not actually been connected to the network is excluded.

[0032] The multiple postal codes shown in Figures 2 and 3 are within a wide - area that includes the postal code areas of those multiple postal codes. The wide area may include municipalities, prefectures, areas spanning multiple prefectures, etc. However, from the perspective of area marketing and the like, it is desirable to define it as a wide area including multiple prefectures.

[0033] [Area characteristic storage unit 23] The area characteristic storage unit 23 stores profiling data (PFD) obtained by analyzing the characteristics of each postal code area and its code (PFD code). That is, each postal code area has been pre-profiled for regional characteristics, and the postal code area is associated with the PFD code. Profiling by cluster analysis is conceivable as profiling of regional characteristics, and the PFD code becomes a cluster classification code.

[0034] In the above example, the regional characteristics of the area are represented by the PFD and its code, but data other than the PFD may also be used. For example, using statistical data, grouping (classification) by population, male-female ratio, age ratio, etc., and representing the regional characteristics with the numerical data and code of the group may also be possible.

[0035] [Area characteristic re-aggregated data storage unit 24: Figure 4] As shown in Figure 4, the area characteristic re-aggregated data storage unit 24 stores area aggregated data with a PFD code assigned, which is the area aggregated data of Figure 3 with the PFD code corresponding to the postal code area. Figure 4 is a schematic diagram showing the area aggregated data with a PFD code assigned. Alternatively, instead of the PFD code, a code grouped by statistical data may be assigned.

[0036] [Area characteristic re-aggregated data storage unit 24: Figure 5] Furthermore, as shown in Figure 5, the area characteristic re-aggregated data storage unit 24 stores area characteristic re-aggregated data obtained by re-aggregating viewing data in units of PFD codes. Figure 5 is a schematic diagram showing the area characteristic re-aggregated data. Since the PFD codes are aggregating the number of units, the total viewing time (total viewing time), the number of households / (or) connection rate for each PFD code in the same postal code area, the numerical values are larger than the area aggregation data in Figure 3.

[0037] [Lift value data storage unit 25: Figure 6] As shown in Figure 6, the lift value data storage unit 25 stores data of lift values (lift value data) calculated based on the area characteristic re-aggregation data. The lift value is calculated based on the ratio of each PFD code to all PFD codes for each item, and is a value indicating the viewing status for each PFD code. Figure 6 is a schematic diagram showing lift value data. The generation of lift value data will be described later.

[0038] The map information storage unit 26 stores map data that can be color-coded for each small area such as a postal code area. The network 3 assumes a network such as the Internet.

[0039] [Processing in this device: Figure 7] Next, the processing of this device will be described with reference to Figure 7. Figure 7 is a flowchart showing the processing in this device. In this device, as shown in Figure 7, the control unit 11 reads the processing program from the storage unit 12 and executes the following processing. The control unit 11 reads the viewing data for each TV receiver ID in Figure 2 from the viewing data storage unit 21 (S1), aggregates the viewing data in units of the postal code area to which the TV receiver ID belongs, generates the area aggregation data in Figure 3, and stores it in the area aggregation data storage unit 22 (S2).

[0040] Next, the control unit 11 reads the PFD code corresponding to the postal code area from the area characteristic storage unit 23 (S3), assigns the PFD code to the area aggregation data, and generates the area aggregation data with PFD code assignment in Figure 4 (S4).

[0041] Furthermore, the control unit 11 re-aggregates the viewing data in units of PFD codes, generates the area characteristic re-aggregated data in FIG. 5, and stores it in the area characteristic re-aggregated data storage unit 24 (S5). Since the area characteristic re-aggregated data calculates the total of the postal code areas to which the PFD code is assigned, the numerical value becomes larger compared to FIG. 4.

[0042] Then, the control unit 11 calculates the percentage (%) of each item for each PFD code with the total of the vertical axis for each item in the area characteristic re-aggregated data as 100% (S6). For example, for the number of connected units of a specific PFD code, (the number of connected units / the total number of connected units) × 100 (%) is obtained.

[0043] Similarly, the percentages are calculated for the viewing time and the number of households (or the number of connections). Here, the calculated values become the "unit composition ratio", the "total viewing time composition ratio", and the "household number composition ratio (or connection rate)". The connection rate is the appearance rate of the number of TVs (number of households) connected (wired) to the network for each PFD code. Instead of the number of households, the population within the area may be used.

[0044] Next, the control unit 11 calculates the lift value and stores it in the lift value data storage unit 25 (S7). Specifically, the control unit 11 converts the percentage of each item calculated in process S6 based on the household number composition ratio of each PFD code into a lift value. That is, for each PFD code, the control unit 11 divides the values of the "household number composition ratio", the "unit composition ratio", and the "total viewing time composition ratio" calculated in process S6 by the value of the "household number composition ratio" to calculate the lift values of the number of households, the number of units, and the viewing time.

[0045] For example, when the percentage of the number of households (household number composition ratio) calculated in process S6 is 90% (0.9), the lift value of the number of households is "1.00 (0.9 / 0.9)", and the lift values of the number of units and the viewing time are the values obtained by dividing the corresponding "unit composition ratio" and "total viewing time composition ratio" by "0.9", respectively.

[0046] As a result, the number composition ratio and the total viewing time composition ratio based on the number of households are calculated, and the viewing characteristics corresponding to the PFD code are obtained. This process is performed for all PFD codes to generate the lift value data (lift value table) shown in FIG. 6 and store it in the lift value data storage unit 25. In the above example, the arithmetic processing is performed based on the number of households, but the arithmetic processing may be performed based on the number of connections or the population to generate lift value data.

[0047] That is, the calculation formula for the lift value is any of the following formulas. Lift value = (number composition ratio or total viewing time composition ratio) / household number composition ratio Lift value = (number composition ratio or total viewing time composition ratio) / connection rate Lift value = (number composition ratio or total viewing time composition ratio) / population composition ratio (proportion of population)

[0048] In the lift value data, if each value excluding the number of households is "1" or more, it means a cluster with a high viewing probability, and if it is less than "1", it means a cluster with a low viewing probability. The control unit 11 performs color-coded display numerically in this lift value data (S8). Specifically, values of "1" or more are displayed in green, and values less than "1" are displayed in red. If values that are "1" or more but close to "1" are displayed in light green, and values that are less than "1" but close to "1" are displayed in orange, and the color-coded display is performed step by step, the distribution of the viewing probability can be easily grasped.

[0049] [Example of viewing status display: FIG. 8] In addition, the control unit 11 reads the map information of a specific wide area from the map information storage unit 26 according to an instruction from the input unit 14, and performs display in terms of color tone such as color shading based on the numerical value of the PFD code corresponding to the postal code area unit as shown in FIG. 8. FIG. 8 is a schematic diagram showing an example of the viewing status display for each postal code area. For example, when the numerical value of the number of a specific PFD code is "1.5", all the postal code areas corresponding to the PFD code are set to the number "1.5", and color shading is displayed on the map.

[0050] The shading display of the map can be made for each selection item by selecting the number of units and the total viewing time in the lift value table of FIG. 6. Also, when displaying each item, different colors may be used for distinction. Further, the colors of all items may be changed and the shading displays may be superimposed and displayed together.

[0051] The map information display based on this lift value data visually represents the viewing status for each area that reflects regional characteristics based on the PFD. Therefore, even if the number of samples of the viewing data for each area is smaller than the number of samples of the viewing data for the wide area, the regional characteristics analyzed by profiling can be used to supplement and provide an appropriate viewing status for each area unit, which can be effectively used for area marketing or area targeting.

[0052] Therefore, this device aggregates the viewing data for each postal code area from the viewing data for each TV receiver to generate area-aggregated data, assigns a PFD code to the postal code area, re-aggregates the viewing data in units of the PFD code to generate area-characteristic re-aggregated data, calculates the ratio of each code to the total for each item of the code, recalculates the lift value based on the number of households for each code using the ratio to generate lift value data, outputs the viewing status for each code, and displays the viewing status for each postal code area on the map. Thus, even if the samples of the viewing data for each area unit are few, the viewing status for each area can be grasped.

[0053] Also, for the PFD code, for example, the cluster code, if the explanations of the clusters corresponding to codes such as code A01 being "middle class", code A02 being "suburban blue collar", and code A03 being "factory worker" are displayed in the column of the PFD code in FIG. 6, the viewing status for each cluster can be easily recognized and grasped.

[0054] Also, the viewing status for each small area analyzed by this device may be displayed and output on the display unit 14, or may be printed and output as a report by a printer (not shown). Furthermore, based on the viewing status in small areas, it is conceivable that the user can complement the weaknesses of TV commercials with further commercials such as train station commercials, Internet commercials, and newspaper inserts.

[0055] In this device, the postal code area is described as an example of a small area, but it may also be applied to areas of the administrative boundaries of municipalities. Furthermore, location information can be obtained using the Wi-fi IP address of a TV connected to the Internet, and a mesh area (mesh region) can be defined and applied to this mesh area.

[0056] [Application Example] Collect the viewing numbers in small areas such as postal code areas, and in a wide area including these small areas, extract areas with high viewing numbers (areas higher than a specific threshold), and analyze the regional characteristics of the entire extracted area. For a wide area, areas where the number of samples obtained with respect to the population of the postal code area exceeds the threshold may be extracted for analysis of regional characteristics. Here, although the threshold indicates a specific ratio with respect to the population, postal code areas with one or more samples may be extracted.

[0057] This analysis infers attributes such as the gender, age, affluence, and consumption tendency of viewers in the area. Public statistical data such as the census, the number of households by annual income class, consumption expenditure, and resident profiling are overlaid on the viewer's address data (address data indicated by the postal code), and for the four elements of the census (gender / age, occupation, number of household members, family type, housing form, length of residence), annual income, consumption expenditure (food, dining out, housing, transportation, education and entertainment), and resident profiling data (cluster, factor), the composition ratio and lift value are calculated and output respectively.

[0058] [Analysis Process of Application Example: Figure 9] Next, the specific analysis process of the application example will be described with reference to Figure 9. Figure 9 is a flowchart of the analysis process of the application example. A wide area is defined as a "comparison business area" (comparison area), and a set of small areas extracted as areas with high viewership or ratings is defined as an "analysis business area" (analysis area). It is assumed that the public statistical data is stored in the area characteristic storage unit 23.

[0059] As shown in FIG. 9, the apparatus sets a "comparison business area" and an "analysis business area" based on the postal code area from the area aggregation data storage unit 22 (S11). The comparison business area is the entire postal code area (wide area) measured for viewership, and the analysis business area is an area obtained by extracting areas with a viewership or rating higher than a specific threshold and combining them.

[0060] Next, the apparatus aggregates the number of viewers in small areas (postal code areas) within the analysis business area and each statistical value in that area (S12). Then, each statistical value is multiplied by the number of viewers in the analysis business area to perform weighted calculation (S13). Furthermore, an operation (weighted composition ratio operation) is performed to convert the multiplied numbers into composition ratios (S14).

[0061] Also, an operation is performed to convert each statistical value within the comparison business area into a composition ratio (S15). And then, the lift value is calculated (S16). The lift value is calculated by the following formula. Lift value = Composition ratio within the analysis business area (weighted composition ratio) / Composition ratio within the comparison business area As described above, the regional characteristics of viewers are analyzed for each statistical value.

[0062] [CM effect measurement / Coupon issuance] Next, a method for measuring the effect of a TV CM by issuing a coupon will be described. The TV station issues a coupon during the CM in the program using a two-dimensional barcode or the like. The TV station includes information in the two-dimensional barcode or the like that can identify which postal code area and which program the coupon was issued for. Then, the viewer reads and captures the 2D barcode of the coupon or the like using a smartphone.

[0063] The viewer goes to the store, presents the coupon, and purchases goods. By reading the coupon, the store recognizes the postal code area, date, time, and program in which the coupon was issued, and further obtains information on the purchased goods and prices as purchase record data (POS data). This information is coupon usage information.

[0064] Since the store cooperates with the coupon for customer acquisition, it notifies the TV station or TV manufacturer that provided the viewing data, or the advertising agency, research company, analyst, etc. that conducts the aggregation, of the coupon usage information. The TV station etc. receives the coupon usage information and aggregates it by postal code area to grasp the usage status of the coupons issued during the CM of the TV program and confirm the effect of the CM. To confirm the effect of this CM, the coupon usage information may be aggregated and displayed overlaid on the map of the viewing status display screen in FIG. 8.

[0065] Also, when the TV station etc. causes the app to be installed when using the coupon, the TV station etc. may use the location information obtained by the installed app. Also, the TV station etc. may obtain information on store visits using geo fencing such as Wi-Fi or beacons to determine whether a terminal such as a smartphone on which the app is installed has entered the store area.

[0066] Also, when a coupon is obtained from an Internet advertisement or a flyer advertisement and used in the store, the TV station etc. may obtain information on the source of transmission and the information on the purchased goods and prices from the store. In this case, the results of the Internet advertisement or flyer advertisement can be evaluated. So far, the above examples have described watching TV, but they are also applicable to listening to the radio on terminals such as smartphones that can identify the area and connect to the network.

[0067] [Application Example of CM Effect Measurement] The analysis method shown in FIG. 9 can also be applied to coupon utilization. Specifically, all areas where the CM is broadcast are regarded as the comparison business area, and the collective area of the residential areas (such as postal code areas) of viewers who visited the store and used the coupon is regarded as the analysis business area (visitor analysis area). In FIG. 9, by identifying (limiting) the viewers within the analysis business area as the viewers who visited the store, the regional characteristics of the viewers who visited the store can be analyzed for each statistical value.

[0068] [Application to Website Browsing] Next, an example of applying this device to website browsing in a network will be described. In this case, the "viewing data analysis device 1" in FIG. 1 becomes a "browsing data analysis device" that analyzes the browsing status of websites in the network, and the "viewing data storage unit 21" becomes a "browsing data storage unit" that stores the browsing data of website browsing. Therefore, the viewing data analysis device and the browsing data analysis device may be simply referred to as the "data analysis device" together.

[0069] Also, for the viewing data in FIG. 2, instead of the "TV receiver ID", data related to the postal code and browsing corresponding to the IP address or terminal ID of the terminal device of a personal computer (PC) becomes the browsing data.

[0070] In recent years, there is a technology to determine the postal code area by the IP address. In the case of a smartphone or tablet, the postal code area is identified by the IP address of the base station or in-home Wi-Fi. Also, if an app for website browsing is operating on a smartphone or the like, the position of the smartphone or the like may be identified by the location information by GPS, and the postal code area may be determined by the position coordinates.

[0071] Furthermore, the "number of connections" in FIGS. 3 to 6 can be read as the "number of connections" to the network, the "number of viewers" can be read as the "number of browsers", and the "viewing rate" can be read as the "browsing rate". Also, if coupons are issued on the website and the viewers' smartphones are made to acquire the coupons and use them at the store, the advertising effect of the website can be measured. The application examples of the CM effect measurement examples described above can also be applied to the analysis of website browsing data.

[0072] [Effects of the Present Embodiment] This device aggregates viewing data or browsing data for each small area such as a postal code area from the viewing data for each television receiver or the browsing data for each terminal device of a computer to generate area-aggregated data, assigns a PFD code to the small area, re-aggregates the viewing data or browsing data in units of the PFD code to generate area characteristic re-aggregated data, calculates the ratio of each code to the total for each item of the code, recalculates lift value data based on the number of households, population, number of connections or connections for each code using the ratio, outputs the viewing status or browsing status for each code, and displays the viewing status or browsing status in units of small areas on a map. Therefore, even if there is a small sample of viewing data or browsing data in units of areas, there is an effect that the viewing status or browsing status for each area can be grasped.

[0073] Also, when the television station or website operator etc. acquires coupon usage information by having the viewers or browsers' smartphones acquire the coupons issued during the CM of the program and use them at the store and reflects it in the lift value data, there is an effect that the effect of the CM can be measured.

[0074] In addition, the present device displays on the display unit 14 a map of an area composed of small areas such as a postal code area, etc., so that it can grasp in which area and to what extent the CM has been viewed or browsed. In addition, it can display stores where coupons can be used, and further display stores where coupons have been used (including those with a large or small number of usage times). It is also possible to specify one or more areas and track stores where coupons issued in the specified area have been used. Using data from coupon acquisition to coupon use, it is effective in measuring the effects of TV commercials or website advertisements. And according to the present device, it is effective in grasping the purchasing behavior of coupon users among viewers or browsers.

[0075] In addition, the present device aggregates the viewing data for each TV receiver or the browsing data of the website for each terminal device of a computer for each specific area, extracts an area where the number of viewers or viewing rate based on the viewing data or the number of browsers or browsing rate based on the browsing data is higher than a specific value as an analysis area, sets a wide area including the analysis area as a comparison area, multiplies each statistical value of the statistical data by the number of viewers in the analysis area to perform weighting and calculate a composition ratio, and calculates a lift value using the composition ratio and the composition ratios of the statistical values in the comparison area, so as to analyze the regional characteristics of the analysis area regarding the viewing situation or browsing situation. Therefore, even if the sample of the viewing data or browsing data per area is small, it is effective in grasping the regional characteristics of the viewing situation or browsing situation.

[0076] In addition, the present device sets the area viewed by a viewer who uses a coupon or the area browsed by a browser who uses a coupon as a visitor analysis area, sets a wide area including the visitor analysis area as a comparison area, multiplies each statistical value of the statistical data by the number of visitors in the visitor analysis area to perform weighting and calculate a composition ratio, and calculates a lift value using the composition ratio and the composition ratios of the statistical values in the comparison area, so as to analyze the regional characteristics of the visitor analysis area regarding the visitor situation. Therefore, it is effective in easily grasping the regional characteristics of coupon-using visitors who have come to the store.

Industrial Applicability

[0077] The present invention is suitable for a data analysis apparatus and its program that can grasp an appropriate viewing situation or browsing situation in an area even in small area units such as a postal code area, a municipality, a mesh, etc.

Explanation of Signs

[0078] 1... viewing data analysis apparatus, 3... network, 11... control unit, 12... storage unit, 13... interface unit, 14... display unit, 15... input unit, 21... viewing data storage unit, 22... area aggregation data storage unit, 23... area characteristic storage unit, 24... area characteristic re-aggregation data storage unit, 25... lift value data storage unit, 26... map information storage unit

Claims

1. A data analysis device for analyzing television viewing data, comprising: A data analysis device characterized by performing a process of aggregating viewing data for each specific area from viewing data for each television set connected to a network, extracting areas where the number of viewers or viewing rate based on the viewing data is higher than a specific value to be used as analysis areas, determining a wide range of viewed areas including the analysis area to be a comparison area, multiplying the number of viewers in the analysis area by each statistical value of the statistical data stored to perform weighting and calculate a composition ratio, calculating a lift value using this composition ratio and the composition ratio of each of the statistical values ​​in the comparison area, and analyzing the regional characteristics of the analysis area in terms of viewing conditions.

2. A data analysis device for analyzing site browsing data, comprising: A data analysis device characterized by performing a process of aggregating site browsing data for each specific area from site browsing data for each computer terminal device connected to a network, extracting areas in which the number of viewers or browsing rate based on the browsing data is higher than a specific value to be used as analysis areas, determining a wide range of viewed areas including the analysis area to be comparison areas, multiplying the number of viewers in the analysis area by each statistical value of the statistical data stored to perform weighting to calculate a composition ratio, calculating a lift value using the composition ratio and the composition ratio of each of the statistical values ​​in the comparison area, and analyzing the regional characteristics of the analysis area in terms of browsing conditions.

3. 3. The data analysis device according to claim 1, wherein the viewing status or browsing status is output by displaying the viewing status or browsing status in area units on a map using color tones.

4. A data analysis device as described in any one of claims 1 to 3, characterized in that when a coupon issued on a television program screen or a terminal device screen is read at a store, coupon usage information is obtained from the store and used to measure the effectiveness of commercials.

5. A data analysis device as described in any one of claims 1 to 4, characterized in that an area viewed by viewers who used a coupon or an area viewed by viewers who used a coupon is defined as a visitor analysis area, a wide area viewed or viewed including the visitor analysis area is defined as a comparison area, the number of visitors in the visitor analysis area is multiplied by each statistical value of the statistical data stored to perform weighting and calculate a composition ratio, and a lift value is calculated using the composition ratio and the composition ratio of each statistical value in the comparison area to analyze the regional characteristics of the visitor analysis area in terms of visitation.

6. A processing program that operates on a data analysis device that analyzes television viewing data, A program for a data analysis device that causes the data analysis device to perform processing to analyze the regional characteristics of the analysis area in terms of viewing conditions by aggregating viewing data for each television receiver connected to a network for each specific area, extracting areas in which the number of viewers or viewing rate based on the viewing data is higher than a specific value and designating them as analysis areas, designating a wide range of viewed areas including the analysis area as comparison areas, multiplying the number of viewers in the analysis area by each statistical value of the statistical data stored by weighting to calculate a composition ratio, calculating a lift value using this composition ratio and the composition ratio of each of the statistical values ​​in the comparison area, and so on.

7. A processing program that operates on a data analysis device that analyzes site browsing data, A program for a data analysis device that functions to perform processing to analyze the regional characteristics of the analysis area in terms of browsing conditions by aggregating browsing data for sites from each terminal device of a computer connected to a network, extracting areas in which the number of viewers or browsing rate based on the browsing data is higher than a specific value and setting them as analysis areas, setting a wide range of viewed areas including the analysis area as comparison areas, multiplying the number of viewers in the analysis area by each statistical value of the statistical data stored by the number of viewers to calculate a composition ratio by weighting, and calculating a lift value using the composition ratio and the composition ratio of each statistical value of the comparison area.

8. 8. The program for a data analysis device according to claim 6 or 7, wherein the viewing status or browsing status is outputted by displaying the viewing status or browsing status in area units on a map using color tones.

9. A program for a data analysis device as described in any one of claims 6 to 8, characterized in that when a coupon issued on a television program screen or a terminal device screen is read at a store, the program functions to obtain coupon usage information from the store and use the information to measure the effectiveness of commercials.

10. A program for a data analysis device as described in any one of claims 6 to 9, characterized in that the program functions to perform processing to analyze the regional characteristics of the visitor analysis area in terms of store visitation by setting an area viewed by a viewer using a coupon or an area viewed by a viewer using a coupon as a visitor analysis area, setting a wide range of areas viewed or viewed including the visitor analysis area as a comparison area, multiplying the number of visitors in the visitor analysis area by each statistical value of the statistical data stored and weighting it to calculate a composition ratio, and calculating a lift value using the composition ratio and the composition ratio of each statistical value in the comparison area.

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