Data analyzer and program thereof

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 device, and more particularly to a data analysis device and a program therefor that can grasp an appropriate viewing situation or browsing situation even if there are only a few samples of viewing data or browsing data. [Background technology]

[0002] [Prior Art] With the advent of network-connected television sets, television stations and television manufacturers have become able to obtain viewing data for each television set, and there is a movement to utilize viewing data. In particular, consideration is being given to grasping viewing conditions in small area units such as postal code areas and using this information for area marketing or area targeting.

[0003] In addition, it has become possible for site operators to obtain site browsing data for each computer terminal device connected to the network, and it is being considered to similarly use browsing status on a small area basis for area marketing or area targeting.

[0004] [Related Technology] Related prior art documents include JP 2004-220337 A, “Television broadcast receiving device and television broadcast transmitting / receiving system” (Patent Document 1) and JP 2002-077866 A, “Electronic program information providing system, electronic program information utilization system, electronic program information providing device, medium, and information collection” (Patent Document 2).

[0005] Patent Document 1 describes the distribution of moving images linked to television broadcast programs. Patent Document 2 describes providing information associated with program information or advertisement information when providing electronic programs over the Internet. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2004-220337 A [Patent Document 2] JP 2002-077866 A Summary of the Invention [Problem to be solved by the invention]

[0007] However, with the above-mentioned conventional technology, when viewing data or browsing data is aggregated by postal code area, the population size within the area is inherently small, so the number of samples of viewing data or browsing data obtained is small. This means that it is not possible to properly grasp the characteristics of each area with such a small sample, and the data cannot be used for area marketing, etc.

[0008] Incidentally, Patent Documents 1 and 2 do not disclose a configuration that can utilize regional characteristics to supplement the limited viewing data within an area and grasp an appropriate viewing situation.

[0009] The present invention has been made in consideration of the above-mentioned situation, and aims to provide a data analysis device and a program therefor that can grasp the appropriate viewing or browsing conditions in an area, even if it is a small area unit such as a postal code area, city, ward, town, or village, or a mesh area. [Means for solving the problem]

[0010] In order to solve the above problems of the conventional example, the present invention provides a television viewing data Ta A data analysis device that analyzes viewing data for each television receiver connected to a network. The viewing data is aggregated for each specific area from the data, and areas where the number of viewers or the viewing rate based on the viewing data is higher than a specific value are extracted and set as analysis areas, and a wide range of areas where viewing is performed including the analysis area are set as comparison areas, and the number of viewers in the analysis area is multiplied by each statistical value of the stored statistical data 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 analysis area in terms of viewing conditions. The present invention is characterized by the above-mentioned processing.

[0011] The present invention relates to A data analysis device that analyzes site browsing data, which aggregates the browsing data for each specific area from the site browsing data for each computer terminal device connected to a network, extracts areas where the number of viewers or the browsing rate based on the browsing data is higher than a specific value and sets the areas as analysis areas, sets a wide range of viewed areas including the analysis area as comparison areas, multiplies the number of viewers in the analysis area by each statistical value of the stored statistical data to perform weighting and calculates a composition ratio, calculates a lift value using the composition ratio and the composition ratio of each statistical value in the comparison area, and performs processing to analyze the regional characteristics of the analysis area in terms of browsing conditions It is characterized by Rude Data analysis equipment.

[0012] The present invention relates to In the data analysis device, the viewing status or browsing status is outputted by displaying the viewing status or browsing status in area units on a map in color tones. It is characterized by:

[0013] The present invention is characterized in that, in the above-mentioned data analysis device, when a coupon issued on the screen of a television program or the screen of a terminal device is read at a store, coupon usage information is obtained from the store and used to measure the effectiveness of commercials.

[0014] The present invention is characterized in that, in the above-mentioned data analysis device, 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 range of areas 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.

[0015] The present invention relates to a television viewing data Ta A processing program that runs on a data analysis device that analyzes viewing data for each television receiver connected to a network. The viewing data is aggregated for each specific area from the data, and areas where the number of viewers or the viewing rate based on the viewing data is higher than a specific value are extracted and set as analysis areas, and a wide range of areas where viewing is performed including the analysis area are set as comparison areas, and the number of viewers in the analysis area is multiplied by each statistical value of the stored statistical data 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 analysis area in terms of viewing conditions. The present invention is characterized in that the device is made to function to perform processing to achieve the above-mentioned object.

[0016] The present invention relates to A processing program that operates on a data analysis device that analyzes site browsing data, the processing program causing the data analysis device to perform processing for analyzing regional characteristics of the analysis area with respect to browsing conditions by aggregating the browsing data for each specific area from the site browsing data for each terminal device of a computer connected to a network, extracting areas in which the number of viewers or the 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 stored statistical data to perform weighting and calculating a composition ratio, and calculating a lift value using the composition ratio and the composition ratio of each statistical value in the comparison area, It is characterized by:

[0017] The present invention is characterized in that in the program for the data analysis device, the viewing status or browsing status is outputted by displaying the viewing status in area units on a map using color tones.

[0018] The present invention is characterized in that the program of the data analysis device functions to obtain coupon usage information from the store when a coupon issued on a television program screen or a terminal device screen is read at a store, and to use the information to measure the effectiveness of a commercial.

[0019] The present invention is characterized in that the program of the data analysis device functions to perform processing to analyze the regional characteristics of the visitor analysis area in terms of visitor visitor usage, 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 viewed areas 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, thereby analyzing the regional characteristics of the visitor analysis area in terms of visitor usage. Effect of the Invention

[0020] According to the present invention, viewing data for each television receiver connected to a network is The viewing data is aggregated for each specific area from the data, and areas where the number of viewers or the viewing rate based on the viewing data is higher than a specific value are extracted and set as analysis areas, and a wide range of areas where viewing is performed including the analysis area are set as comparison areas, and the number of viewers in the analysis area is multiplied by each statistical value of the stored statistical data 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 analysis area in terms of viewing conditions. Since the data analysis device performs the process of determining whether or not viewing or browsing is performed on an area basis, the viewing or browsing status for each area can be grasped even if there are only a few samples of viewing or browsing data on an area basis.

[0021] According to the present invention, Ruko From site browsing data for each computer terminal device, for each specific area In The browsing data is aggregated , View The areas where the number of visitors or the viewing rate based on the browsing data is higher than a certain value are extracted as analysis areas, and View The wide area surveyed was used as the comparison area, and the analysis area was View The number of visitors is multiplied by each statistical value of the statistical data stored in the database to calculate the composition ratio, and the lift value is calculated using the composition ratio and the composition ratio of each statistical value of the comparison area. , View The data analysis device is designed to analyze the regional characteristics of the analysis area for the viewing situation, so View Even if the sample of the data is small, , View This has the effect of allowing us to understand the regional characteristics of viewing conditions. [Brief description of the drawings]

[0022] [Figure 1] FIG. 2 is a configuration block diagram of the present device. [Diagram 2]FIG. 2 is a schematic diagram showing viewing data. [Diagram 3] FIG. 13 is a schematic diagram showing area aggregation data. [Figure 4] FIG. 1 is a schematic diagram showing PFD code assigned area summary data. [Diagram 5] FIG. 13 is a schematic diagram showing area characteristic recount data. [Figure 6] FIG. 4 is a schematic diagram showing lift value data. [Figure 7] FIG. 2 is a flow chart showing the processing in the present device. [Figure 8] FIG. 13 is a schematic diagram showing an example of a display of viewing conditions for each postcode area. [Figure 9] FIG. 11 is a flow diagram showing an analysis process of an application example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described with reference to the drawings. [Outline of the embodiment] A data analysis device (this device) according to an embodiment of the present invention aggregates viewing data for each television set into small areas such as postal code areas, city / town / village areas, mesh areas, etc., assigns a code of regional characteristics that has been subjected to cluster analysis or the like to each small area, re-aggregates the viewing data on a code basis, calculates the percentage of each code in relation to the total for each analyzed code item, uses this percentage to recalculate lift value data indicating the viewing situation based on the number of households, population or number of connections for each code, outputs the viewing situation for each code, and displays the viewing situation by small area on a map, so that even if there are only a few samples of viewing data by area, it is possible to grasp the viewing situation for each area.

[0024] In addition, this device issues coupons during program commercials, and when viewers obtain (photograph) the coupons using their smartphones or other devices and use them at a store, the store can determine which postcode area and which program the coupon was obtained for, allowing them to check the effectiveness of advertising in relation to viewing conditions in the area.

[0025] In addition, this device aggregates viewing data for each television set for each specific small area, extracts areas where the number of viewers or viewing rate based on the viewing data is higher than a specific value and sets this as the analysis area, sets a wide area including the analysis area as the comparison area, multiplies the number of viewers in the analysis area by each statistical value of the statistical data and weights it to calculate a composition ratio, calculates a lift value using this composition ratio and the composition ratio of each statistical value in the comparison area, and analyzes the regional characteristics of the viewing conditions in the analysis area, so that even if there are only a small number of samples of viewing data by area, it is possible to grasp the regional characteristics of the viewing conditions.

[0026] In addition, this device is not limited to viewing data, but can also be applied to browsing data for each terminal device of a computer connected to a network, and can grasp the browsing status for each area, confirm the effectiveness of advertisements, and grasp the regional characteristics of the browsing status. Details will be described later.

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

[0028] [Parts of this device] The control unit 11 executes a processing program stored in the storage unit 12 to execute the processing described below. The storage unit 12 stores processing programs as well as data, parameters, etc. required for 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 showing the viewing situation. The input unit 15 inputs processing instructions, display instructions, and the like.

[0029] [Viewing data storage unit 21: Figure 2] The viewing data storage unit 21 stores the viewing data for each television receiver ID. Specifically, 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, as shown in Fig. 2. Fig. 2 is a schematic diagram showing the viewing data.

[0030] [Area aggregate data storage unit 22: Figure 3] The area total data storage unit 22 stores area total data that is obtained by totaling the viewing data for each postal code area based on this viewing data, as shown in Fig. 3. Fig. 3 is a schematic diagram showing area total data. The area aggregation data is for each postal code, and includes the number of connections within that postal code area for a specific commercial, the total viewing time within that area (total viewing time), and the number of households or connection rate (number of households / number of connections) within that area. The number of viewers may be counted in units of less than 5 minutes (0-5), 5 to 10 minutes (5-10), 10 to 20 minutes (10-20), or 20 to 30 minutes (20-30). The above viewing time allocation is arbitrary.

[0031] The number of households is obtained from statistical data such as the population census. The statistical data is stored in the area characteristics storage unit 23. The number of connections is the total number of televisions (TVs) that have ever been connected to the network within the area. It does not include TVs that have the hardware to connect to the network but have never actually connected to the network.

[0032] The multiple postal codes shown in Figures 2 and 3 are within a wide area that includes the postal code area of ​​the multiple postal codes. The wide area may be a city, ward, town, village, prefecture, or an area spanning multiple prefectures, but from the perspective of area marketing, it is preferable to have a wide area including multiple prefectures.

[0033] [Area characteristic storage unit 23] The area characteristic storage unit 23 stores profiling data (PFD) that analyzes the characteristics of each postal code area and its code (PFD code). In other words, the postal code area is profiled in advance for regional characteristics, and the postal code area and the PFD code are associated with each other. Profiling of regional characteristics can be carried out using cluster analysis, and the PFD code will serve as 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, statistical data may be used to group (classify) areas based on population, male / female ratio, age ratio, etc., and regional characteristics may be expressed by the numerical data and codes of the groups.

[0035] [Area characteristic reaggregation data storage unit 24: Figure 4] The area characteristic recount data storage unit 24 stores PFD code-assigned area count data in which a PFD code corresponding to a postal code area is assigned to the area count data in Fig. 3, as shown in Fig. 4. Fig. 4 is a schematic diagram showing PFD code-assigned area count data. Also, instead of the PFD code, a code grouped by statistical data may be assigned.

[0036] [Area characteristic re-aggregation data storage unit 24: Figure 5] Furthermore, the area characteristic recounted data storage unit 24 stores area characteristic recounted data obtained by recounting viewing data for each PFD code, as shown in Fig. 5. Fig. 5 is a schematic diagram showing area characteristic recounted data. The number of units, total viewing time (total viewing time), number of households / (or) connection rate are compiled for each PFD code in postal code areas with the same PFD code, so the figures are higher than the area summary data in Figure 3.

[0037] [Lift value data storage unit 25: Figure 6] As shown in FIG. 6, the lift value data storage unit 25 stores data on lift values ​​calculated based on the area characteristic reaggregation data (lift value 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 that indicates the viewing status for each PFD code. 6 is a schematic diagram showing lift value data, the generation of which will be described later.

[0038] The map information storage unit 26 stores map data that can be displayed in different colors for each small area, such as a postal code area. The network 3 is assumed to be a network such as the Internet.

[0039] [Processing by this device: Figure 7] Next, the processing of this device will be described with reference to Fig. 7. Fig. 7 is a flow chart showing the processing in this device. In this device, as shown in FIG. 7, the control unit 11 reads a processing program from the storage unit 12 and executes the following processing. The control unit 11 reads the viewing data for each television receiver ID in Figure 2 from the viewing data storage unit 21 (S1), aggregates the viewing data by postal code area to which the television receiver ID belongs, generates the area aggregate data of Figure 3, and stores it in the area aggregate 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 compilation data, and generates the PFD code-assigned area compilation data of FIG. 4 (S4).

[0041] Furthermore, the control unit 11 recounts the viewing data for each PFD code, generates the area characteristic recounted data of Fig. 5, and stores it in the area characteristic recounted data storage unit 24 (S5). The area characteristic recounted data is calculated as the total for the postal code area to which the PFD code is assigned, so the numerical value is larger than that of Fig. 4.

[0042] Then, the control unit 11 calculates the percentage (%) of each item for each PFD code, assuming that the total of the vertical axis for each item in the area characteristic recounted data is 100% (S6). For example, to find the number of connected devices for a specific PFD code, calculate (number of connected devices / total number of connected devices) x 100 (%).

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

[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 proportion of each item calculated in step S6 into a lift value based on the household number composition ratio of each PFD code. In other words, for each PFD code, the control unit 11 divides the values ​​of "household number composition ratio," "number of units composition ratio," and "total viewing time composition ratio" calculated in process S6 by the value of "household number composition ratio," to calculate lift values ​​for the number of households, number of units, and viewing time.

[0045] For example, if the proportion of households calculated in process S6 (household composition ratio) is 90% (0.9), the lift value for the number of households will be "1.00 (0.9 / 0.9)", and the lift values ​​for number of units and viewing time will be the corresponding "unit composition ratio" and "total viewing time composition ratio" divided by "0.9", respectively.

[0046] This allows the ratio of units based on the number of households and the ratio of total viewing time to be calculated, thereby obtaining the viewing characteristics corresponding to the PFD code. This process is performed for all PFD codes to generate the lift value data (lift value table) shown in FIG. In the above example, the calculation process is performed based on the number of households, but the calculation process may be performed based on the number of connections or the population to generate lift value data.

[0047] In other words, the lift value is calculated using one of the following formulas. Lift value = (Unit ratio or total viewing time ratio) / Number of households ratio Lift value = (Unit composition ratio or total viewing time composition ratio) / Connection rate Lift value = (Unit composition ratio or total viewing time composition ratio) / Population composition ratio (proportion of population)

[0048] In the lift value data, if each value except for the number of households is "1" or more, it is a cluster with a high viewing probability, and if it is less than "1", it is a cluster with a low viewing probability. The control unit 11 displays this lift value data in a color-coded manner according to the numerical value (S8). Specifically, values ​​equal to or greater than "1" are displayed in green, and values ​​less than "1" are displayed in red. By displaying the colors in a gradual manner, such as displaying values ​​that are equal to or greater but close to "1" in light green, and values ​​that are less than "1" but close to "1" in orange, the distribution of viewing probabilities can be easily grasped.

[0049] [Example of viewing status display: Figure 8] Furthermore, the control unit 11 reads map information of a specific wide area from the map information storage unit 26 in response to an instruction from the input unit 14, and displays it in a color tone such as a shade of color 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 viewing status display for each postal code area. For example, if the number of vehicles for a particular PFD code is "1.5," then all postal code areas corresponding to that PFD code will have a number of "1.5" and will be displayed in different shades of color on the map.

[0050] The shading of the map can be displayed for each selected item by selecting the number of units and total viewing time in the lift value table in Figure 6. Also, when displaying each item, different colors may be used to distinguish them. Furthermore, the colors of all items may be changed and the shading may be superimposed to display them all together.

[0051] The map information display based on this lift value data is a visual representation of the viewing situation for each area, reflecting regional characteristics based on the PFD. Therefore, even if the number of viewing data samples for each area is small compared to the number of viewing data samples for the wider area, it is possible to compensate for this with the regional characteristics analyzed through profiling, providing appropriate viewing situations for each area, which can be effectively used for area marketing or area targeting.

[0052] Therefore, this device aggregates viewing data for each television set by postal code area to generate area aggregated data, assigns a PFD code to that postal code area, re-aggregates the viewing data by that PFD code to generate area characteristic re-aggregated data, calculates the percentage of each code to the total for each code item, uses that percentage to recalculate the lift value based on the number of households for each code to generate lift value data, outputs the viewing status for each code, and displays the viewing status by postal code area on a map, so that even if there are only a few samples of viewing data by area, it is possible to grasp the viewing status for each area.

[0053] In addition, if an explanation of the cluster corresponding to the PFD code, for example, the cluster code A01 being "middle class," A02 being "suburban blue-collar worker," A03 being "factory worker," etc., is displayed in the PFD code column in Figure 6, the viewing situation by cluster can be easily recognized and understood.

[0054] The viewing conditions for each small area analyzed by this device may be displayed on the display unit 14, or may be printed out as a report on a printer (not shown). Furthermore, it is conceivable that users will supplement the weaknesses of TV advertising with additional advertising such as train advertising, Internet advertising, and newspaper inserts, based on viewing conditions in small area units.

[0055] Although the present device has been described taking a postal code area as an example of a small area, it may also be applied to areas of administrative boundaries of cities, wards, towns, and villages. Furthermore, location information can be obtained using the IP address of the Wi-Fi of a television connected to the Internet, and a mesh area (mesh region) can be defined, and the location information can be applied to this mesh area.

[0056] [Application example] It is also possible to collect the number of viewers in small areas such as postal code areas, extract areas with high viewing numbers (areas with viewing numbers higher than a specific threshold) from a wide area that includes those small areas, and analyze the regional characteristics of the entire extracted area. For a wide range of areas, areas where the number of samples obtained relative to the population of the zip code area exceeds a threshold may be extracted to analyze regional characteristics. Here, the threshold indicates a specific percentage of the population, but zip code areas with a sample count of one or more may be extracted.

[0057] This analysis infers attributes such as the gender, age, level of wealth, and consumption trends of viewers in a given area by overlaying viewer address data (address data indicated by postal code) with public statistical data such as the census, number of households by income bracket, consumer expenditure, and resident profiling, and calculates and outputs the composition ratio and lift value for each of the four elements: census (gender, age, occupation, number of people in household, family type, living arrangement, length of residence), annual income, consumer expenditure (food, eating out, housing, transportation, education and entertainment), and resident profiling data (cluster, factors).

[0058] [Analysis processing of application example: Figure 9] Next, a specific analysis process of the application example will be described with reference to Fig. 9. Fig. 9 is a flow diagram of the analysis process of the application example. A wide area is considered to be the "comparison trade area" (comparison area), and a collection of small areas extracted as areas with high viewing numbers or viewing rates is considered to be the "analysis trade area" (analysis area). It is assumed that the official statistical data is stored in the area characteristics storage unit 23.

[0059] As shown in FIG. 9, the device sets a "comparison trade area" and an "analysis trade area" based on the postal code area from the area aggregation data storage unit 22 (S11). The comparison trade area is the entire zip code area measured for viewership (the broad area), while the analysis trade area is the combined area of ​​areas with viewership or viewership rates higher than a certain threshold.

[0060] Next, the device compiles the number of viewers for each small area (zip code area) within the analyzed trade area and each statistical value for that area (S12). Then, the number of viewers within the analyzed trade area is multiplied by each statistical value to perform a weighting calculation (S13). Furthermore, the multiplied figure is calculated as a composition ratio (weighted composition ratio calculation) (S14).

[0061] In addition, a calculation is performed to convert each statistical value within the comparison trade area into a composition ratio (S15). Then, the lift value is calculated (S16). The lift value is calculated by the following formula. Lift value = Composition ratio within the analysis trade area (weighted composition ratio) / Composition ratio within the comparison trade area In this way, the regional characteristics of viewers are analyzed for each statistical value.

[0062] [CM effectiveness measurement / coupon issuance] Next, we will explain how to issue coupons in television commercials and measure the effectiveness of the commercials. Television stations issue coupons in the form of two-dimensional barcodes during commercials in their programs. The two-dimensional barcodes contain information that identifies which postcode area the coupon was issued in and which program it was issued in. The viewer then scans the coupon's two-dimensional barcode with their smartphone and imports it.

[0063] Viewers can go to a store, present the coupon and make a purchase. By reading the coupon, the store can determine which postcode area, date, time, and program the coupon was issued for, and also obtain information on the purchased item and price as purchase history data (POS data). This information is coupon usage information.

[0064] Since stores cooperate with the coupons to attract customers, they notify the TV station or TV manufacturer that provided the viewing data, or the advertising agency, research company, analysis company, etc. that compiles the data, of coupon usage information. Television stations and other such organizations can receive coupon usage information and compile it by postal code area, thereby understanding the usage status of coupons issued during TV program commercials and verifying the effectiveness of the commercials. In order to confirm the effectiveness of this commercial, coupon usage information may be compiled and displayed superimposed on the map on the viewing status display screen of FIG.

[0065] Furthermore, in cases where a television station or the like requires an application to be installed when using a coupon, the television station or the like may use the location information acquired by the installed application. In addition, a television station or the like may obtain store visit information using geolocation such as Wi-Fi or a beacon to determine whether or not a device such as a smartphone on which the app is installed has entered the store area.

[0066] In addition, when a coupon is obtained from an online advertisement or a flyer advertisement and used at a store, the TV station or the like may obtain information on the sender and the purchased product and price from the store. In this case, the success of the online advertisement or flyer advertisement can be evaluated. Although the above example has been described with respect to watching television, the present invention can also be applied to listening to the radio on a terminal such as a smartphone that can identify an area and connect to a network.

[0067] [Application example of measuring commercial effectiveness] The analysis method shown in FIG. 9 can also be applied to coupon usage. Specifically, all areas in which the commercial was broadcast are considered to be the comparison trade area, and the collection area of ​​residential areas (postal code area, etc.) of viewers who visited the store and used the coupon is considered to be the analysis trade area (customer analysis area).In Figure 9, viewers within the analysis trade area are specified (limited) to viewers who visited the store, making it possible to analyze the regional characteristics of viewers who visited the store for each statistical value.

[0068] [Application to site browsing] Next, an example in which this device is applied to browsing a site on 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 sites on a network, and the “viewing data storage unit 21” becomes a “browsing data storage unit” that stores browsing data of site browsing. Therefore, the viewing data analysis device and the browsing data analysis device may be collectively referred to simply as the "data analysis device."

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

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

[0071] In addition, the "number of connections" in Figures 3 to 6 can be interpreted as the "number of connections" to the network, the "number of viewers" as the "number of viewers," and the "viewing rate" as the "viewing rate." In addition, if a website issues a coupon and allows the visitor to download the coupon onto their smartphone and use it at a store, the advertising effectiveness of the website can be measured. The above-mentioned application example of measuring the effectiveness of commercials can also be applied to analyzing website browsing data.

[0072] [Advantages of this embodiment] This device aggregates viewing data or browsing data for each small area such as a postal code area from viewing data for each television set or site browsing data for each computer terminal device to generate area aggregated data, assigns a PFD code to each small area, re-aggregates the viewing data or browsing data by PFD code to generate area characteristic re-aggregated data, calculates the percentage of each code to the total for each code item, uses this percentage to recalculate lift value data based on the number of households, population, number of connections or number of connections for each code, outputs the viewing or browsing status by code, and displays the viewing or browsing status by small area on a map, thus having the effect of making it possible to grasp the viewing or browsing status for each area even if there are only a few samples of viewing or browsing data by area.

[0073] In addition, this device allows viewers or viewers to retrieve coupons issued during program commercials onto their smartphones and use them in stores, and when the coupon usage information is obtained by the television station or site operator, etc., it can be reflected in lift value data, making it possible to measure the effectiveness of the commercials.

[0074] In addition, this device can display regions made up of small areas such as postal code areas on a map on the display unit 14, making it possible to know in which area and to what extent a commercial was viewed or read, and can also display stores where coupons can be used, as well as stores where coupons have been used (including those where coupons have been used frequently or infrequently).It is also possible to specify one or more areas and track stores where coupons issued in those areas have been used, making it possible to measure the effectiveness of television commercials or site advertising using data from the time a coupon is obtained to the time it is used. Furthermore, this device has the effect of making it possible to grasp the purchasing behavior of viewers or viewers who use coupons.

[0075] In addition, this device aggregates viewing data or browsing data for each specific area from viewing data for each television set or site browsing data for each computer terminal device, extracts areas where the number of viewers or viewing rate based on the viewing data or the number of viewers or viewing rate based on the browsing data is higher than a specific value and sets this as the analysis area, sets a wide area including the analysis area as the comparison area, multiplies the number of viewers or viewers in the analysis area by each statistical value of the statistical data and weights it to calculate a composition ratio, calculates a lift value using this composition ratio and the composition ratio of each statistical value in the comparison area, and analyzes the regional characteristics of the analysis area with regard to the viewing or browsing conditions, thereby having the effect of making it possible to grasp the regional characteristics of the viewing or browsing conditions even if there are only a small number of samples of viewing or browsing data on an area-by-area basis.

[0076] In addition, this device uses the area viewed by viewers who used a coupon or the area viewed by viewers who used a coupon as a visitor analysis area, uses a wide area including the visitor analysis area as a comparison area, multiplies the number of visitors in the visitor analysis area by each statistical value of the statistical data and weights it to calculate a composition ratio, calculates a lift value using this composition ratio and the composition ratio of each statistical value in the comparison area, and analyzes the regional characteristics of the visitor analysis area in terms of store visits, thereby having the effect of easily grasping the regional characteristics of coupon users who visit a store. [Industrial Applicability]

[0077] The present invention is suitable for a data analysis device and a program therefor that can grasp appropriate viewing or browsing conditions in an area, even if it is a small area unit such as a postal code area, a city, a town, a village, or a mesh. [Explanation of symbols]

[0078] REFERENCE SIGNS LIST 1... Viewing data analysis device, 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 reaggregation 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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