Advertising analysis system and advertising analysis method

Abstract

We provide advertising analysis systems that can analyze the effectiveness of specific advertisements. [Solution] The advertising analysis system is an advertising analysis system that analyzes the effects of advertising using an electronic information terminal 5. The electronic information terminal 5 comprises an advertising-related information acquisition means 51 that acquires advertising-related information including basic information, viewing information, and performance information for each advertisement, such as the advertising user itself, products, and services, and a correlation analysis means 52 that analyzes the correlation between elements included in the advertising-related information. Viewing information and performance information are pairs of information for each predetermined period unit. The correlation analysis means 52 is a means that excludes viewing information or performance information that has noise basis, which can be grasped from advertising-related information or other related information during the analysis period, from the correlation analysis, along with the viewing information or performance information that is paired with that information, and analyzes them separately.

Description

Technical Field

[0001] The present invention relates to an advertisement analysis system and an advertisement analysis method for analyzing the effects of advertisements.

Background Art

[0002] Conventionally, advertisements have been widely used as a means to provide consumers with information about products and services and to enhance their purchasing desire and awareness. In recent years, with the development of digital technology, in addition to conventional media such as television, radio, newspapers, magazines, flyers, and billboards, advertisements via the Internet, SNS (Social Networking Service), direct mail, etc. have also become widespread.

[0003] Regarding the content of advertisements, in addition to information regarding the functions and performance of products and services handled by advertisers (hereinafter referred to as "advertising users"), advertisements regarding the advertising users themselves have also been increasing. Thereby, improvements in the awareness and brand image of the advertising users themselves are expected. Also, personalized advertisements and the like are being utilized in accordance with the interests and concerns of consumers, and advertisements targeting specific consumer groups have also been increasing.

[0004] Thus, with the diversification of advertising methods in the advertising industry, the need to efficiently place advertisements has been increasing. Conventionally, for example, Patent Document 1 and the like are known as systems for analyzing the effects of web advertisements.

[0005] In Patent Document 1, there is proposed an advertisement effect analysis system provided with performance registration means for registering performance for each of a plurality of action items set in accordance with five processes (AIDMA), which are the basic principles of advertising activities, totaling means for totaling the performance status for each of the five processes based on the performance data registered by the performance registration means, and analysis result output means for separately outputting the performance status totaled for each of the five processes by the totaling means in one screen.

Prior Art Documents

Patent Documents

[0006] [Patent Document 1] Japanese Patent Publication No. 2003-44738 [Overview of the Initiative] [Problems that the invention aims to solve]

[0007] In modern times, with the spread of social media and video streaming services, companies, organizations, and individuals can freely disseminate information, and trends and fads are changing rapidly. In this information-saturated modern age, even if an advertisement for a product is placed in a specific medium, there are many factors that could have led consumers to purchase that product. Therefore, analyzing the effectiveness of a specific advertisement is not easy.

[0008] This invention has been made in view of these circumstances, and aims to provide an advertising analysis system and an advertising analysis method that can analyze the effectiveness of specific advertisements. [Means for solving the problem]

[0009] The present invention relates to an advertising analysis system that, when an advertising user places an advertisement, analyzes the effect of the advertisement using an electronic information terminal, wherein the electronic information terminal comprises: an advertising-related information acquisition means for acquiring advertising-related information that includes at least basic information, viewing information, and performance information for each advertisement, for advertisements selected from the advertising user themselves, the products purchased by the advertising user, and the services handled by the advertising user; and a correlation analysis means for analyzing the correlation between elements included in the advertising-related information, wherein the viewing information and performance information in the advertising-related information are pairs of information for each predetermined period unit, and the correlation analysis means is a means for excluding viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period, and which has a noise basis that can be grasped from the advertising-related information or other related information during the analysis period, from the analysis of the correlation, together with the paired viewing information or performance information.

[0010] The above-mentioned predetermined period unit is 1 day, and the above-mentioned predetermined analysis period is characterized by being between 3 days and 3 months.

[0011] The noise basis determination means for determining the presence or absence of the above-mentioned noise basis is characterized by having means for determining the presence or absence of noise basis for each period unit in the analysis target period with respect to at least one type of information from the above-mentioned advertising-related information, or information derived from this information, and for each period in which the above-mentioned standard value is outside a predetermined range and deviates from the standard, from the above-mentioned advertising-related information or other related information belonging to each period that is different from the subject used when calculating the above-mentioned standard value.

[0012] The above-described noise basis determination means is characterized by being a means for determining the presence or absence of noise basis from temporary or periodic current events information, which is related information other than the above-described advertising-related information, belonging to each period in which the above-described standard deviation is outside a predetermined range and deviates from the standard.

[0013] The above advertising-related information includes the advertising costs of a specified media, the viewing information and performance information before and during the advertising period, and the correlation analysis means is characterized by calculating the actual increase or decrease in the number of specified awareness items included in the viewing information and the advertising costs during the analysis period, and calculating the advertising costs required to obtain an increase of one awareness item as the correlation.

[0014] The present invention relates to an advertising analysis method that uses the advertising analysis system of the present invention to analyze the effectiveness of an advertisement when an advertising user places an advertisement, comprising: an information acquisition step of acquiring advertising-related information, which includes at least basic information, viewing information, and performance information for each advertisement selected from the advertising user itself, the products purchased by the advertising user, and the services handled by the advertising user, using the advertising-related information acquisition means; and a correlation analysis step of analyzing the correlation between elements included in the advertising-related information using the correlation analysis means, wherein the correlation analysis step comprises an analysis prerequisite step of identifying viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period and has noise basis that can be grasped from the advertising-related information or other related information during the analysis period; and an actual analysis step of excluding the identified information together with the paired viewing information or performance information and analyzing the correlation.

[0015] The above-mentioned predetermined period unit is one day, the above-mentioned predetermined analysis period is 3 days or more and within 3 months, and the noise basis determination step for determining the presence or absence of the above-mentioned noise basis includes a first step of calculating a standard score for each day of the analysis period for at least one type of information from the above-mentioned advertising-related information, or information derived from this information, and a second step of determining the presence or absence of noise basis for each day on which the above-mentioned standard score is outside the predetermined range and deviates from the standard, from the above-mentioned advertising-related information or other related information belonging to each day that is different from the subject used when calculating the above-mentioned standard score.

[0016] The above advertising-related information includes the advertising costs of a specified media, the viewing information and performance information before and during the advertising period, and the correlation analysis step is characterized by calculating the actual increase or decrease in the number of specified awareness items included in the viewing information and the advertising costs during the analysis period, and calculating the advertising costs required to obtain an increase of one awareness item as the correlation. [Effects of the Invention]

[0017] The advertising analysis system of the present invention comprises advertising-related information acquisition means for acquiring advertising-related information that includes at least basic advertising information, viewing information, and performance information, and correlation analysis means for analyzing the correlation between elements included in the advertising-related information. In the advertising-related information, viewing information and performance information are pairs of information for each predetermined period unit. The correlation analysis means excludes viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period, and which has a noise basis that can be grasped from the advertising-related information or other related information during the analysis period, from the correlation analysis along with the viewing information or performance information that is paired with that information. By excluding viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period and which has a noise basis that can be grasped from the advertising-related information or other related information, the above-mentioned noise information is not uniformly excluded, and information without a noise basis can be included in the analysis, thereby enabling a proper analysis of the effect of a particular advertisement.

[0018] Since the specified period unit is one day and the specified analysis period is between three days and three months, it is possible to analyze the effectiveness of advertising over a relatively short period. Furthermore, while advertising over a relatively short period is more susceptible to noise, by excluding specific information that is considered noise and for which noise justification has been found from the analysis, it is possible to properly analyze the effectiveness of advertising even over a relatively short period.

[0019] As noise basis determination means for determining the presence or absence of the above-mentioned noise basis, for at least one type of information among the advertisement-related information or information derived from this information, the deviation value for each period in the analysis target period is calculated for each period unit, and in each period where the deviation value is outside the predetermined range and deviates from the standard, the presence or absence of the noise basis is determined from advertisement-related information different from the target at the time of calculating the deviation value or other related information belonging to each period. Therefore, the noise information itself can be easily extracted, the amount of information required for determining the noise basis is limited, and the efficiency of analysis can be improved.

[0020] Since the above-mentioned noise basis determination means is means for determining the presence or absence of the noise basis from temporary or regular time situation information, which is related information other than the advertisement-related information, belonging to each period in each period where the deviation value is outside the predetermined range and deviates from the standard, it is easy to determine the presence or absence of the noise basis, and the effect of the advertisement can be appropriately analyzed.

Brief Description of Drawings

[0021] [Figure 1] It is a schematic diagram showing an example of the configuration of an advertisement distribution system. [Figure 2] It is a schematic diagram showing an example of the configuration of an advertisement analysis system. [Figure 3] It is a diagram showing an example of listing advertisement-related information. [Figure 4] It is a schematic diagram showing the extraction of noise information from advertisement-related information. [Figure 5] It is a schematic diagram showing different advertisement-related information serving as the noise basis, etc. [Figure 6] It is a schematic diagram showing the determination of the presence or absence of the noise basis. [Figure 7] It is a schematic diagram for calculating CPA, etc. [Figure 8] It is a diagram showing an example of advertisement-related information, etc. when the distribution area is limited. [Figure 9] It is a flowchart showing an example of the procedure of the advertisement analysis method of the present invention. [Modes for carrying out the invention]

[0022] In the advertising analysis system of the present invention, the advertising media to be analyzed are not particularly limited. For example, various forms of advertising are included, such as television commercials, radio commercials, newspaper advertisements, magazine advertisements, search engine service advertisements, social media advertisements, video streaming service advertisements, direct mail, and outdoor advertisements such as electronic bulletin boards and billboards.

[0023] Examples of search engine services include Google (registered trademark) and Yahoo! (registered trademark). Examples of social networking services (SNS) include Facebook (registered trademark), X, Instagram (registered trademark), TikTok, and LINE (registered trademark). An example of a video streaming service is YouTube (registered trademark).

[0024] The content of an advertisement may include information about the advertiser itself (such as the company's business activities, corporate philosophy, and corporate image), information about the products the advertiser sells, and information about the services the advertiser provides.

[0025] Furthermore, the analysis period for analyzing the effectiveness of advertising is not particularly limited and can be set to, for example, daily, weekly, monthly, or yearly. It is preferable that the analysis period be relatively short so that the effectiveness of advertising can be quickly assessed and budget allocations can be concentrated on more effective advertisements. For example, it could be between one day and three months, between three days and one month, or between three days and two weeks. The advertising period (the period during which the advertisement is run) is also not particularly limited and can be set to, for example, the same period as the analysis period.

[0026] The configuration of the advertising analysis system of the present invention will be described below with reference to the drawings.

[0027] Figure 1 first shows an overview diagram of an example of an advertising delivery system configuration. Figure 1 shows an analysis of advertisements delivered via a network.

[0028] In Figure 1, the advertising distribution system includes a distribution terminal 2, an advertising user terminal 3, and terminals 4a, 4b, and 4c. Distribution terminal 2, advertising user terminal 3, and terminals 4a, 4b, and 4c are connected to each other via a network N. Network N is an electronic communication line capable of sending and receiving data, and examples include wired LAN, wireless LAN, WAN, and the internet.

[0029] Distribution terminal 2 is a terminal that delivers advertisements. Distribution terminal 2 is an information processing terminal operated by an advertising media provider (e.g., a website operator), and can be a server computer or a personal computer. Distribution terminal 2 accepts bids and advertisement submissions from advertising user terminal 3 and delivers the advertisements when the delivery conditions are met.

[0030] The advertising user terminal 3 is an information processing terminal operated by advertising users or advertising agencies, and can be, for example, a server computer or a personal computer. The advertising user terminal 3 notifies the distribution terminal 2 of settings such as bid amounts and ad submission settings. It also obtains various information about the delivered ads from the distribution terminal 2 and other devices.

[0031] Terminals 4a, 4b, and 4c are personal computers, smartphones, tablet devices, etc., and are operated by consumers. Here, "consumer" refers to anyone who uses or may use advertisements, and does not necessarily have to be a consumer who ultimately purchases goods or services. Consumers can view advertisements delivered from distribution terminal 2 through their respective terminals.

[0032] For example, in the case of banner ads on web pages such as social media, consumers are redirected to a linked website when they click on the banner ad. The linked website is a web page (a so-called landing page (LP)) that contains information introducing products or services, and is used to promote products and services and encourage conversions such as purchases. Similarly, advertisements on video streaming services are shown between videos, piquing the consumer's interest and encouraging them to visit the website intended by the advertiser.

[0033] In Figure 1, the advertising analysis system 1 analyzes the effectiveness of advertisements delivered by the advertising distribution system described above. The advertising analysis system 1 includes an electronic information terminal 5. The electronic information terminal 5 is, for example, a server computer or a personal computer, and has a processing unit such as a CPU (Central Processing Unit) and a memory device. The electronic information terminal 5 can function as an advertising analysis device by executing various programs stored in the memory device using its processing unit.

[0034] In Figure 1, the electronic information terminal 5 is connected to the distribution terminal 2 and the advertising user terminal 3 via the network N, but it is sufficient to obtain the advertising-related information described later by any method, and it is not necessarily required to be connected to the network N.

[0035] Figure 2 illustrates the electronic information terminal 5. As shown in Figure 2, the electronic information terminal 5 includes an advertising-related information acquisition means 51 for acquiring advertising-related information and a correlation analysis means 52. Furthermore, the correlation analysis means 52 includes a noise basis determination means 52a and a calculation means 52b.

[0036] The advertising-related information acquisition means 51 acquires advertising-related information. Each piece of advertising-related information may be acquired, for example, via the network N from the distribution terminal 2 or the advertising user terminal 3, or via any storage device, or by manual input. The advertising-related information includes at least basic advertising information, viewing information, and performance information. Note that the detailed information acquired will differ depending on the individual advertising medium to which the advertisement is delivered.

[0037] Basic information refers to information about the advertiser. Examples of basic information include the advertiser's company name, an identifier that identifies the advertiser, the ad name, the campaign name, the consumer target (age, gender, etc.), and the area (prefecture, etc.).

[0038] Viewing information indicates how much consumers viewed an advertisement. Examples of viewing information include advertising costs, impressions, clicks, sessions, total users, new users, new user rate, and visits. Advertising costs represent the amount paid for advertising, impressions represent the number of times the advertisement was displayed, clicks represent the number of times it was clicked, and sessions represent the number of times a consumer visits a site and leaves it, counted as one session.

[0039] Performance information refers to information that shows the results of advertising. For example, if the objective is the purchase of a product or service, it refers to the number of times that objective was achieved, i.e., the number of purchases of the product or service (hereinafter simply referred to as the number of conversions (CV)).

[0040] Here, in advertising-related information, viewing information and performance information are pairs of information for each predetermined period unit within the advertising period. The predetermined period unit is, for example, one day, two days, one week, etc., and is usually set to one day.

[0041] Figure 3 shows a table in which each piece of information is arranged and listed in pairs for each day. Such a table is displayed on the screen of the electronic information terminal 5, and the analyst performs operations based on this table.

[0042] Figure 3 shows an advertising period (which is also the analysis period) of two weeks from January 1st to January 14th, 2024. Here, we assume that the advertisement being analyzed is related to the product "xxx" and is a banner ad on a specific search engine service (e.g., Google). The basic information includes the advertisement name, "Anniversary Campaign." The viewing information includes advertising cost, impressions, and clicks on a daily basis. The performance information includes the number of conversions on a daily basis. In this way, each element of the basic information, viewing information, and performance information is arranged in correspondence with the date. Note that Figure 3 is merely an example, and the elements acquired and displayed in the basic information, viewing information, and performance information are not limited to those shown.

[0043] As shown in Figure 3, the numbers decrease in the order of impressions, clicks, and conversions. This reflects the changes in the numbers that correspond to the series of purchasing activities a consumer goes through, from becoming aware of an advertisement (corresponding to impressions), becoming interested (corresponding to clicks), checking it out, and finally making a purchase (corresponding to conversions). Advertising costs fluctuate not only due to impressions but also due to bidding conditions, and generally, impressions increase as advertising costs rise. Thus, the numbers for each element change from day to day.

[0044] In Figure 2, the correlation analysis means 52 of the electronic information terminal 5 is a means for analyzing the correlation between elements contained in advertising-related information as shown in Figure 3. Specifically, the correlation analysis means 52 uses the noise basis determination means 52a to extract noise information from the advertising-related information during the analysis period (for example, two weeks in Figure 3). Then, from the extracted noise information, viewing information or performance information that has a noise basis that can be grasped from the advertising-related information or other related information during the analysis period is excluded from the correlation analysis along with the viewing information or performance information that is paired with that information and analyzed separately.

[0045] An example of the process from correlation analysis to exclusion is explained using Figures 4 to 6. Note that the lists shown in Figures 4 and 6 are based on the contents of the list in Figure 3.

[0046] From the advertising-related information shown in Figure 4, noise information is extracted first. This noise information is extracted, for example, by calculating the standard score for each period within the analysis period.

[0047] In Figure 4, the standard score for advertising costs, among the viewing information, is calculated for each day over the two-week analysis period. If the calculated standard score is outside a predetermined range (for example, ±10 or more), the viewing information for that date is extracted as noise information. In Figure 4, standard scores within the predetermined range are indicated as "OK," and standard scores outside the predetermined range are indicated as "NG," and the viewing information for "January 6, 2024" and "January 7, 2024" is extracted as noise information. Although not shown in Figure 4, standard scores may also be calculated for other elements of the viewing information, such as the number of impressions and the number of clicks, and these calculated standard scores may also be used to extract noise information. It is sufficient to calculate a standard score for at least one element of the viewing information, and noise information may be extracted by combining standard scores for multiple elements.

[0048] Furthermore, Figure 4 shows that the daily standard score for the number of conversions (CVs) among the outcome information is calculated for the two-week analysis period. If the calculated standard score is outside a predetermined range (for example, ±10 or more), the outcome information for that date is extracted as noise information. In Figure 4, the outcome information for "January 9, 2024" and "January 12, 2024" is extracted as noise information.

[0049] Furthermore, the extraction of noise information from viewing information and outcome information is not limited to the methods described above. For example, instead of using standard scores as the information (calculated values) derived from viewing information, indicators showing variability such as standard deviation or variance may be calculated, and information (viewing information or outcome information) to which elements with a variability above a certain level belong may be extracted as noise information.

[0050] After extracting noise information as described above, the presence or absence of noise is determined for each period during which the noise information was acquired (in Figure 4, these are the four days of "January 6, 2024", "January 7, 2024", "January 9, 2024", and "January 12, 2024"). Specifically, the presence or absence of noise is determined from advertising-related information or other related information that belongs to each of the above periods and is different from the target used when calculating standard scores, etc. For example, regarding the noise information for "January 6, 2024", the presence or absence of noise is determined for the information belonging to "January 6, 2024".

[0051] Figure 5 shows an example of information that constitutes noise (hereinafter also referred to as "noise-based information"). For example, different advertising-related information concerning the product "xxx" could include press releases for "xxx" on the advertiser's website, posts on the advertiser's social media or blog, web advertisements on different media, flyers, and local events, all belonging to a specific period (for example, "January 7, 2024" in Figure 4). When such different advertising-related information exists, it is possible that consumers become aware of the product through advertising-related information other than the advertisement being analyzed (i.e., become aware through other routes), which then becomes noise information. In other words, it may have led to an increase in the number of clicks or the final number of conversions for the advertisement being analyzed, and therefore, it is determined that there is noise-based information.

[0052] In Figure 5, other relevant information regarding the product "XXX" includes temporary, timely information such as posts on social media and blogs by celebrities, and product introductions on TV and in magazines. Although such timely information is not based on the actions intended by the advertiser, it is possible that consumers become aware of the product (i.e., become aware of it through other channels), and therefore it may have become noise information. For this reason, it is judged to have noise evidence.

[0053] Other relevant information regarding product "xxx" includes periodic current events. Depending on the characteristics of the product or service, the number of conversions (CVs) may be affected by dates and timing. For example, the number of contracts related to mobile carriers tends to increase at the end of the month. Therefore, if information on dates at or near the end of the month is extracted as noise, it may be possible to determine that there is noise based on such periodic current events.

[0054] Noise-based information is collected automatically by noise-based detection methods or through the operation of information processing devices by analysts. For example, noise-based information can be collected by accessing the advertiser's website or blog during the period in which the noise information was extracted (for example, "January 7, 2024" in Figure 4), searching for events related to the advertised product, or searching for posts about the product on various social media platforms. Note that at least one piece of noise-based information is sufficient.

[0055] The presence or absence of such noise-related information determines whether each piece of noise information has a noise basis. In the example in Figure 6, "January 7, 2024" and "January 12, 2024" are determined to have a noise basis, while "January 6, 2024" and "January 9, 2024" are determined to have no noise basis. Based on this determination, for "January 7, 2024" and "January 12, 2024," the viewing information and outcome information are removed (for example, the entire row is deleted), and analysis (also called actual analysis) is performed based on the information shown in the lower part of Figure 6.

[0056] As shown in Figure 6, even if information is initially extracted as noise, if it is determined that there is no basis for the noise, it will be included in the analysis. When evaluating the effectiveness of advertising, for example, one could uniformly exclude viewing information or performance information with large variations and analyze based on the information remaining after exclusion. However, by including information without a basis for noise in the analysis, the analysis process can be made more efficient while maintaining accuracy.

[0057] Figure 7 shows an overview of the calculation of each value as part of the subsequent analysis flow. The table in the upper section shows the total number of conversions (CVs) for the same number of days before and during the distribution period. Alternatively, the average number of CVs per day may also be used. Based on each total number of CVs, the growth rate (%) due to advertising is calculated. Using the calculated growth rate, the increase or decrease in awareness is calculated. Furthermore, by dividing the advertising cost by the increase or decrease in awareness, the CPA (cost per acquisition) is calculated. Each value is calculated by the calculation unit 52b of the correlation analysis means (see Figure 2).

[0058] In Figure 7, the period immediately preceding the distribution period is used as the pre-distribution information for comparison with the currently distributed information. However, this is not limited to this; for example, information from the same period one month prior may be used, or information from the same period one year prior may be used.

[0059] Furthermore, depending on the advertising format, ads may be delivered in different areas, time slots, or days of the week. Even in such cases, the series of analytical methods described above can be applied.

[0060] Figure 8(a) shows an example where the advertising distribution area is limited to Tokyo. In this example as well, basic information, viewing information, and performance information are acquired as advertising-related information, and these are acquired as paired information on a daily basis during the advertising period. Then, as described above, noise information is extracted, and the presence or absence of noise basis is determined for the extracted noise information, and the actual analysis is performed.

[0061] In Figure 8(b), when calculating the growth rate and increase / decrease in actual analysis, the performance of non-delivery areas is also taken into consideration to calculate the effective growth rate and the effective increase / decrease in actual numbers. In Figure 8(b), first, the number of sessions and conversions before and during delivery are calculated for "Tokyo," which is the delivery area, and "Osaka and Aichi prefectures," which are non-delivery areas. Here, "Osaka and Aichi prefectures" are selected as the non-delivery area because they are not adjacent prefectures and have relatively similar population sizes, but for example, "the whole country excluding Tokyo" could also be used. Then, the growth rate during delivery compared to before delivery is calculated for each.

[0062] Using the obtained growth rates, the real growth rate is calculated. For example, the real growth rate (%) of the number of CVs in Tokyo is calculated to be 119 (=151 / 127). Then, the real increase / decrease is calculated using this real growth rate. For example, the real increase / decrease in the number of CVs in Tokyo is calculated to be 3.0 (=(16 × 1.19) - 16). The CPA is calculated using this real increase / decrease.

[0063] As shown in Figure 8(c), the effectiveness of advertising can be evaluated more appropriately by subtracting the difference in non-delivery areas, rather than just evaluating the difference in the delivery area during delivery. In other words, in addition to simply comparing the situation before and during the advertising period, a counterfactual scenario is created in which advertising was not run, and the growth rate or increase / decrease against that predicted value is used as the actual growth rate or actual increase / decrease.

[0064] Furthermore, it is possible to calculate the actual growth rate and actual increase / decrease not only by area, but also by time of day and day of the week for advertisements. For example, for an advertisement delivered on a specific day of the week (e.g., Wednesday), in addition to comparing it with the time before the advertisement (e.g., Tuesday), it is possible to understand the trend of that particular day of the week before the advertisement (e.g., what percentage increase trend there is on that day) and take that trend into account to calculate the actual increase / decrease for that specific day of the week.

[0065] It should be noted that the advertising analysis system of the present invention is not limited to the system described in Figures 1 to 8 above. For example, although the above description refers to advertisements delivered via a network, it may also refer to TV commercials, magazine advertisements, flyer advertisements, billboard advertisements, etc. For example, with TV commercials, viewing information can be obtained based on TV viewership ratings, etc. With magazine advertisements, viewing information can be obtained based on the number of magazines sold, with flyer advertisements, viewing information can be obtained based on the number of flyers distributed, etc. With billboard advertisements, viewing information can be obtained based on road traffic volume, the number of passengers getting on and off trains, the number of users, etc., depending on the location where it is installed.

[0066] Figure 9 shows a flowchart of an example of the advertising analysis method of the present invention. This advertising analysis method uses the advertising analysis system described above to analyze the effectiveness of advertising when an advertiser places an advertisement.

[0067] The method shown in Figure 9 comprises an information acquisition step (corresponding to step S1) for acquiring the advertising-related information described above, and a correlation analysis step (corresponding to steps S2 to S6) for analyzing the correlation between elements included in the advertising-related information using the correlation analysis means described above. The correlation analysis step also includes an analysis prerequisite step (corresponding to steps S2 to S3) for identifying viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period and has noise basis that can be grasped from the advertising-related information or other related information during the analysis period, and an actual analysis step (corresponding to steps S4 to S6) for analyzing the correlation by excluding the identified information along with its corresponding viewing information or performance information.

[0068] Furthermore, the analysis prerequisite steps include a first step (corresponding to step S2) of calculating a daily standard score for at least one type of advertising-related information, or information derived from this information, for the analysis period, and a second step (corresponding to step S3) of determining whether there is any basis for noise from advertising-related information or other related information belonging to each day that is different from the subject used to calculate the standard score, for each day in which the standard score is outside the predetermined range and deviates from the standard.

[0069] Furthermore, the correlation analysis step includes calculating the advertising costs and the actual increase or decrease in the number of predetermined awareness units included in the viewing information during the analysis period (corresponding to steps S4-S5), and calculating the advertising costs required to obtain an increase of one awareness unit as a correlation (corresponding to step S6).

[0070] It should be noted that the advertising analysis method of the present invention is not limited to the method described in Figure 9 above, and the details of each step may be modified as appropriate. [Explanation of Symbols]

[0071] 1. Advertising Analysis System 2. Distribution terminals 3. Advertisement user terminal 4a, 4b, 4c terminals 5. Electronic Information Terminals 51. Means of obtaining advertising-related information 52 Correlation Analysis Methods 52a Noise basis determination means 52b Calculation means

Claims

1. An advertising analysis system that analyzes the effectiveness of an advertisement using an electronic information terminal when an advertiser places an advertisement, The electronic information terminal comprises an advertising-related information acquisition means for acquiring advertising-related information, which includes at least basic information, viewing information, and performance information for each advertisement selected from the advertising user itself, the products purchased by the advertising user, and the services handled by the advertising user, and a correlation analysis means for analyzing the correlation between elements included in the advertising-related information. In the aforementioned advertising-related information, the viewing information and the performance information are pairs of information for each predetermined period unit. The advertising analysis system is characterized in that the correlation analysis means is a means for excluding viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period, and which has a noise basis that can be grasped from the advertising-related information or other related information during the analysis period, from the analysis of the correlation relationship, along with the viewing information or performance information that is paired with that information.

2. The advertising analysis system according to claim 1, characterized in that the predetermined period unit is one day, and the predetermined analysis period is three days or more and within three months.

3. The advertising analysis system according to claim 1 or 2, characterized in that, as a means for determining the presence or absence of noise, it calculates a standard score for each period unit in the analysis target period with respect to at least one type of information from the advertising-related information, or information derived from this information, and in each period in which the standard score is outside a predetermined range and deviates from the standard, it has means for determining the presence or absence of noise from advertising-related information or other related information belonging to each period that is different from the subject used when calculating the standard score.

4. The advertising analysis system according to claim 3, characterized in that the noise basis determination means is a means for determining the presence or absence of noise basis from temporary or periodic current events information other than the advertising-related information that belongs to each period in which the standard deviation is outside a predetermined range and deviates from the standard.

5. The aforementioned advertising-related information includes the advertising costs of the specified media, the viewing information and performance information before and during the advertising period, The advertising analysis system according to claim 1 or 2, characterized in that the correlation analysis means calculates the advertising cost and the actual increase or decrease in the number of predetermined recognitions included in the viewing information during the analysis period, and calculates the advertising cost required to obtain an increase of one recognition as the correlation.

6. An advertising analysis method, comprising using the advertising analysis system described in claim 1, for analyzing the effectiveness of an advertisement when an advertiser places an advertisement, The system comprises: an information acquisition step in which the advertising-related information acquisition means acquires advertising-related information, which includes at least basic information, viewing information, and performance information for each advertisement selected from the advertising user itself, the products purchased by the advertising user, and the services handled by the advertising user; and a correlation analysis step in which the correlation analysis means analyzes the correlation between elements included in the advertising-related information. The aforementioned correlation analysis step is characterized by comprising: an analysis prerequisite step of identifying viewing information or performance information that constitutes noise information among the advertising-related information during a predetermined analysis period and has noise basis that can be grasped from the advertising-related information or other related information during the analysis period; and an actual analysis step of excluding the identified information together with the paired viewing information or performance information and analyzing the correlation relationship.

7. The aforementioned predetermined period unit is one day, and the aforementioned predetermined analysis period is between three days and three months. The advertising analysis method according to claim 6, characterized in that, as a noise basis determination step for determining the presence or absence of the aforementioned noise basis, a first step of calculating a daily standard score for at least one type of information from the advertising-related information, or information derived from this information, for the analysis period, and a step of determining the presence or absence of noise basis from the advertising-related information or other related information belonging to each day that is different from the subject used when calculating the standard score, for each day in which the standard score is outside a predetermined range and deviates from the standard.

8. The aforementioned advertising-related information includes the advertising costs of the specified media, the viewing information and performance information before and during the advertising period of the advertisement, The advertising analysis method according to claim 6 or 7, characterized in that the correlation analysis step includes the step of calculating the advertising cost and the actual increase or decrease in a predetermined number of recognitions included in the viewing information during the analysis period, and calculating the advertising cost required to obtain an increase of one recognition as the correlation.

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