Information processing device, information processing method, and information processing program

Abstract

To measure an advertising effect so as to satisfy a demand of an advertiser.SOLUTION: An information processing apparatus includes: an acquisition unit which acquires a hierarchical structure comprising layers for multiple types of management units for managing an advertisement, as advertisement account information; a reception unit which receives settings in which one of registration items to be registered for each of the management units is defined as a measurement unit for measuring an advertising effect; and a counting unit which counts the advertising effect for one advertisement that is determined to have contributed to off-line action of a person who had contact with the advertisement, in a group of advertisements associated under the registration item defined as the measurement unit.SELECTED DRAWING: Figure 8

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] In recent years, advertising delivery systems have been measuring store visit conversions to measure the effectiveness of advertising measures to attract customers. For example, by measuring store visit conversions, it becomes possible to visualize how much advertising contributed to store visits.

[0003] In addition, the advertisement delivery system can set an advertisement set for each campaign set for an advertiser's account, and can set multiple pieces of operation information for each advertisement set. As a result, for example, the advertisement delivery system can present effectiveness information for each advertisement set to the advertiser. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-64782 A Summary of the Invention [Problem to be solved by the invention]

[0005] As described above, advertisers can set the granularity of their advertising operations by hierarchically linking campaigns and ad groups to accounts. However, this method only provides reports on advertising effectiveness on an ad set basis, making it difficult to measure store visits or provide reports on the basis desired by the advertiser.

[0006] For example, the hierarchical structure of advertising accounts set by an advertiser may be subdivided according to purpose, product, budget, etc. However, the advertiser may only make such detailed settings to manage advertisement delivery, and may not wish to measure store visits or tally advertising effectiveness based on the advertising account structure. For this reason, there is a need to individually set the unit of store visit measurement and the unit of advertising effectiveness tally.

[0007] The above-mentioned conventional technology does not necessarily satisfy the needs of such advertisers. Specifically, the conventional technology merely calculates the evaluation value of the advertising medium based on the number of clicks and weights in various advertising media as a measure to effectively support advertising activities. For this reason, it can be said that the conventional technology has room for improvement in terms of realizing measurement of advertising effectiveness that satisfies the needs of advertisers.

[0008] Therefore, the present disclosure proposes an information processing device, an information processing method, and an information processing program capable of realizing measurement of advertising effectiveness that satisfies the needs of advertisers. [Means for solving the problem]

[0009] In order to solve the above problem, an information processing device of one embodiment according to the present disclosure includes an acquisition unit that acquires, as advertising account information, a hierarchical structure in which multiple types of management units for managing advertisements are each configured as one hierarchy, a reception unit that accepts a setting to set one of the registration items registered for each management unit as a measurement unit for advertising effectiveness, and a counting unit that counts the advertising effectiveness for one advertisement among a group of advertisements linked under the registration item defined as the measurement unit, which advertisement is determined to have contributed to the offline behavior of an advertisement exposed to the advertisement. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing a configuration of a system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of store visit detection logic according to the embodiment. [Diagram 3] FIG. 3 is a diagram showing a method for calculating the advertising effect. [Figure 4] FIG. 4 is a diagram showing the rules for calculating the advertising effect. [Diagram 5] FIG. 5 is a diagram showing the rules for calculating the advertising effect. [Figure 6] FIG. 6 is a diagram showing the rules for calculating the advertising effect. [Figure 7] FIG. 7 is an explanatory diagram illustrating a hierarchical structure of an account according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of the configuration of a measurement device according to an embodiment. [Figure 9] FIG. 9 is a diagram (1) showing a specific example of an account structure. [Figure 10] FIG. 10 is a diagram (1) showing a specific example of advertising effectiveness measurement. [Figure 11] FIG. 11 is a diagram (2) showing a specific example of an account structure. [Figure 12] FIG. 12 is a diagram (2) showing a specific example of advertising effectiveness measurement. [Figure 13] FIG. 13 is a diagram (3) showing a specific example of an account structure. [Figure 14] FIG. 14 is a diagram (3) showing a specific example of advertising effectiveness measurement. [Figure 15] FIG. 15 is a flowchart showing an information processing procedure executed by the measuring device. [Figure 16] FIG. 16 is a diagram showing an example of advertising effectiveness measurement taking into consideration the type of event that occurred in response to an advertisement. [Figure 17] FIG. 17 is a hardware configuration diagram showing an example of a computer that realizes the functions of the measuring device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present disclosure will be described in detail with reference to the drawings. Note that the information processing device and the information processing method according to the present disclosure are not limited to the embodiment. In addition, in the following embodiments, the same components are denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0012] <Embodiment> [1. System Configuration] First, the configuration of a system according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the configuration of a system according to an embodiment. Fig. 1 shows a system 1 as an example of a system according to an embodiment.

[0013] 1, the system 1 may be configured to include a user device 10, an advertiser device 20, a detection device 30, and a measurement device 100. The user device 10, the advertiser device 20, the detection device 30, and the measurement device 100 may be connected to each other via a network N in a wired or wireless manner so as to be able to communicate with each other.

[0014] The user device 10 is an information processing terminal used by a user, and examples of such terminals include a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. The term "user" as used herein refers to a general consumer (end user) who goes to a real store to shop or receive services.

[0015] For example, the user device 10 displays a screen (advertising medium) including an advertisement delivered from the measurement device 100 described below. In such a case, the user becomes an advertisement contactor who has come into contact with the advertisement. Note that contact with an advertisement may include not only the advertisement being displayed, but also a specific user operation on the advertisement (e.g., clicking). A user whose interest has been heightened by being exposed to the advertisement in this way may visit the store that is the subject of the advertisement.

[0016] Here, a visit to a real store by an advertisement contact is an example of an offline behavior according to the embodiment, but the offline behavior is not limited to a visit to a real store. For example, the offline behavior may be a purchase of a product or a reception of a service at a real store by an advertisement contact.

[0017] The advertiser device 20 is an information processing terminal used by an advertiser, and examples of such terminals include a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, and a PDA. The advertiser here refers to a source that submits advertisements. For example, the advertiser may be a company that is a client of a distributor T that mediates advertisement distribution, and may operate a store.

[0018] For example, the advertiser device 20 performs various settings related to advertisement delivery and store visit measurement in response to the operation of the advertiser for the measurement device 100. In addition, the advertiser device 20 also submits the advertisement itself to the measurement device 100 in response to the operation of the advertiser.

[0019] The detection device 30 is a device installed in a real store operated by an advertiser (e.g., a client company of the distribution provider T) and is a device for detecting visitors. For example, the detection device 30 may be a Wi-Fi access point installed in the client company's store, and detects a user having the user device 10 as a visitor to the store when an interaction is obtained with a specific tag that is previously assigned to an advertisement delivered to the user device 10. The detection device 30 may be provided by the distribution provider T or a partner company of the distribution provider T.

[0020] The measurement device 100 is an example of an information processing device according to an embodiment of the present disclosure, and performs a series of information processes related to store visit measurement. In addition, the measurement device 100 may be a device belonging to a distribution company T.

[0021] The measurement device 100 performs the following process as information processing according to the embodiment. The measurement device 100 acquires a hierarchical structure in which multiple types of management units for managing advertisements are each configured as one layer. The measurement device 100 also accepts a setting from the advertiser to set one of the registered items registered for each management unit as the measurement unit of the advertising effectiveness. In this state, the measurement device 100 counts the advertising effectiveness of one advertisement determined to have contributed to the offline behavior of an advertisement exposed person among a group of advertisements linked to the registered item defined as the measurement unit.

[0022] In this embodiment, the measurement device 100 is described as having an advertisement delivery function. Specifically, the measurement device 100 not only performs the information processing according to the above-described embodiment, but also delivers advertisements submitted by advertisers. Meanwhile, advertisement delivery may be realized by a dedicated server device separate from the measurement device 100.

[0023] In addition, the user device 10, the advertiser device 20, and the detection device 30 are edge computers that perform edge processing near the customer, while the measurement device 100 may be a cloud computer that performs processing on the cloud side. In other words, the measurement device 100 may be a server device.

[0024] [2. Store visit detection logic] Next, the logic of store visit detection will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the store visit detection logic according to the embodiment. First, according to the example of Fig. 2, in the advertisement distribution service SA provided by the distribution provider T, medium M1, medium M2, and medium M3 are defined as the advertising media in which the submitted advertisement Xn is to be published. In addition, a tag TG for store visit detection is inserted into the submitted advertisement. The insertion of the tag TG may be performed by the measurement device 100.

[0025] In this state, when the user device 10 displays medium M1, which is a screen including advertisement X1 (an example of advertisement Xn) with tag TG1 (an example of tag TG) inserted therein, the user device 10 transmits advertisement contact information indicating that the user of the user device 10 has come into contact with advertisement X1 to the measurement device 100. The advertisement contact information may include terminal information for identifying the user device 10, the publication date and time of advertisement X1, medium information indicating the medium M1 on which advertisement X1 was published, and the like. Furthermore, the advertisement contact information may be accumulated in the contact / store visit information database 121 as one record serving as a delivery history in the advertisement delivery.

[0026] Assume that a user who has become an advertisement contact by viewing the advertisement X1 visits a real store equipped with a detection device 30 as shown in FIG. 2. In this case, the user device 10 and the detection device 30 are connected by short-range wireless communication, and as a result, the detection device 30 reads the tag TG1 via short-range wireless communication and detects the user having the user device 10 as a visitor to the store. Then, the detection device 30 transmits store visit information indicating the detection of the visit to the measurement device 100. The store visit information may include terminal information for identifying the user device 10, information on the advertisement X1, information on the tag TG1, store information for identifying the store, and the like. In addition, the store visit information may be accumulated in the contact / store visit information database 121 as one record as a distribution history in the advertisement distribution. Note that examples of short-range wireless communication include Bluetooth (registered trademark) and WiFi (registered trademark). In addition, the wireless connection between the user device 10 and the detection device 30 is not limited to short-range wireless communication, and may utilize, for example, GPS positioning technology.

[0027] [3. Methods and rules for calculating advertising effectiveness] Next, the method and rules for counting the advertising effect will be described with reference to Figures 3 to 6. The method and rules described in Figures 3 to 6 are used to count the advertising effect in the measurement unit defined in the account structure for store visit measurement, which will be described later.

[0028] [3-1. Methods and rules for calculating advertising effectiveness (1)] FIG. 3 is a diagram showing a method for calculating the advertising effect. FIG. 3 shows a case where, for an arbitrary user Ux, advertisements X3, X2, and X1 are posted in order according to the time series Time, and then the user Ux is detected to visit the store at time T1 on June 30, 2022. Although not shown in FIG. 3, the advertiser who submitted advertisement X3 posted at time T3 on June 28, 2022, advertisement X2 posted at time T2 on June 28, 2022, and advertisement X1 posted at time T4 on June 29, 2022 is the same as the operating company of the store where the user Ux visited this time.

[0029] Here, although there are exceptions to be described later, the measurement device 100 basically employs a counting method called last impression. This will be explained with reference to FIG. 3(a). According to the example of FIG. 3(a), the measurement device 100 determines which of advertisements X1, X2, and X3 contributed to the visit of the user Ux, and counts (gives) "1 Walk-in" as an advertising effect indicating one visit to the store for the contributing advertisement determined to have contributed to the visit.

[0030] According to the last impression method, the measurement device 100 determines that the advertisement X1, X2, and X3, which was posted immediately before the time when the visit was detected (i.e., time T1 on June 30, 2022), contributed to the visit of the user Ux. In the example of FIG. 3(a), the measurement device 100 determines that the advertisement X1 posted at time T4 on June 29, 2022, which is the timing immediately before time T1 on June 30, 2022, contributed to the visit of the user Ux, and sets it as the contributing advertisement. Then, the measurement device 100 gives 1 Walk-in to the contributing advertisement X1.

[0031] The measurement device 100 may also assign 1Walk-in including information indicating the date on which the user Ux visited the store (date on which the visit was detected). This point will be described with reference to FIG. 3(b). According to the example of FIG. 3(b), the measurement device 100 may assign "1Walk-in_6 / 30Walk-in" to the contributing advertisement X1 as 1Walk-in including June 30, 2022, on which the user Ux visited the store. By assigning 1Walk-in including the date on which the user Ux visited the store in this way, it becomes possible to meet the needs of advertisers who want to know how much their advertisement contributed for each visit date, for example.

[0032] As another example, the measurement device 100 may assign 1Walk-in including information indicating the posting date. This point will be described with reference to FIG. 3(c). According to the example of FIG. 3(c), the measurement device 100 may assign "1Walk-in_6 / 29impression" to the contributing advertisement X1 as 1Walk-in including June 29, 2022, when the contributing advertisement X1 was posted. By assigning 1Walk-in including the posting date of the contributing advertisement in this way, it becomes possible to meet the needs of advertisers who want to know, for example, how many customers visited the store in response to the advertisement when it was posted.

[0033] [3-2. Methods and rules for calculating advertising effectiveness (2)] Fig. 4 is a diagram showing the calculation rules for advertising effectiveness. Fig. 4 shows a case where advertisements X4, X5, X1, X2, and X3 are posted in order for an arbitrary user Ux according to the time series Time. Although not shown in Fig. 4, it is assumed that the advertiser who submitted advertisements X1 to X5 is the same company that operates the store that the user Ux visited.

[0034] 4 shows an example in which a store visit behavior W1 by a user Ux is detected when the user Ux visits a store after advertisements X4, X5, and X1 are published in the order of advertisement X4, X5, and X1 according to the time series Time. In this example, the measurement device 100 determines that advertisement X1 contributed to the store visit behavior W1 based on the last impression method described in FIG. 3, and sets advertisement X1 as a contributing advertisement. Then, the measurement device 100 gives 1 Walk-in to the contributing advertisement X1.

[0035] 4 also shows an example in which after a store visit behavior W1, advertisements X2 and X3 are further placed in the order of time series Time, and the user Ux visits the store again, and the next store visit behavior W2 by the user Ux is detected. In this way, when an offline behavior (W2) is detected again in a state where the user has come into contact with one or more advertisements (advertisements X2, X3) after the offline behavior (W1), the measurement device 100 determines that advertisement X3 contributed to the store visit behavior W2, which is the offline behavior performed again, based on the last impression method, and sets advertisement X3 as a contributing advertisement. Then, the measurement device 100 gives one Walk-in to the contributing advertisement X1.

[0036] [3-3. Methods and rules for calculating advertising effectiveness (3)] Fig. 5 is a diagram showing the calculation rule for the advertising effect. Fig. 5 also shows a case where advertisements X4, X5, X1, X2, and X3 are published in order for an arbitrary user Ux according to the time series Time.

[0037] FIG. 5 shows an example in which the user Ux visits the store twice in a row after advertisement X4, advertisement X5, and advertisement X1 are published in the order according to the time series Time, and thus store visit actions W1 and W2 by the user Ux are detected. In this way, when offline action (W2) is detected again without contacting one or more advertisements after offline action (W1), the measurement device 100 adopts the last impression method for the store visit action W1, which is the earlier offline action, and does not adopt the last impression method for the store visit action W2, which is the later offline action. In other words, the measurement device 100 determines that advertisement X1 has contributed to the store visit action W1 and sets it as a contributing advertisement. Then, the measurement device 100 gives one Walk-in to the contributing advertisement X1. On the other hand, the measurement device 100 does not give one Walk-in in response to the store visit action W2.

[0038] For example, in the situation shown in Figure 5, a situation is assumed where a person repeatedly enters and leaves a store without exposure to an advertisement in between. In such a case, if one Walk-in is awarded each time, it will be impossible to count the legitimate advertising effect. Therefore, if consecutive visits to a store are detected without exposure to an advertisement in between, in order to prevent such fraudulent situations, only the first visit detection is used as an element for measuring the effectiveness.

[0039] 4 also shows an example in which advertisements X2 and X3 are published in the order of time series Time after the store visit behavior W2, and the next store visit behavior W3 by the user Ux is detected when the user Ux visits the store again. In this example, the measurement device 100 determines that advertisement X3 contributed to the store visit behavior W3 based on the last impression method, and sets it as a contributing advertisement. Then, the measurement device 100 gives 1 Walk-in to the contributing advertisement X3.

[0040] [3-4. Methods and rules for calculating advertising effectiveness (4)] Fig. 6 is a diagram showing the calculation rules for advertising effectiveness. Fig. 6 explains an exceptional counting method that deviates from the above-described method of the impressions and the last impressions. Fig. 6 also shows a case where advertisements X4, X5, X1, X2, and X3 are displayed in order according to the time series Time for an arbitrary user Ux.

[0041] Here, the advertiser may set a period for measuring store visits (period for measuring advertising effectiveness). FIG. 6 shows an example in which the measurement period is set to "January 1, 2022 to June 30, 2022." When the measurement period is set in this manner, the measurement device 100 may dynamically determine a grace period for continuing measurement based on the set measurement period. FIG. 6 shows an example in which the measurement device 100 has set the grace period to one month after June 30, i.e., "July 1, 2022 to July 31, 2022."

[0042] 6 shows an example in which advertisements X4, X5, and X1 are posted in the order of advertisement X4, X5, and X1 according to the time series Time, and then the user Ux visits the store, resulting in the detection of a store visit behavior W1 by the user Ux. Specifically, during the measurement period "January 1, 2022 to June 30, 2022," advertisements X4, X5, and X1 are posted in that order, and the store visit behavior W1 is detected during this measurement period.

[0043] In this way, the store visit behavior W1 that occurred during the measurement period is used as an element of the effectiveness measurement targeting the advertisements posted during the measurement period. That is, as in the previous examples, the measurement device 100 determines that the advertisement X1 contributed to the store visit behavior W1 and sets it as a contributing advertisement. Then, the measurement device 100 gives 1 Walk-in to the contributing advertisement X1.

[0044] 6 also shows an example in which, after the store visit behavior W1, advertisements X2 and X3 are further posted in the order of the time series Time, and the next store visit behavior W2 by the user Ux is detected when the user Ux visits the store again. Specifically, the example shows that advertisement X2 is posted during the measurement period "January 1, 2022 to June 30, 2022", advertisement X3 is posted during the grace period after the measurement period, and store visit behavior W2 is detected during this grace period.

[0045] In this example, if the measurement device 100 follows the last impression method, it will determine that the advertisement X3 contributed to the store visit behavior W2 and set it as a contributing advertisement. However, the measurement device 100 applies an exception to the last impression method to the store visit behavior W2 detected during the grace period after the measurement period. Specifically, the measurement device 100 determines that the advertisement posted immediately before the store visit behavior W2 among the advertisements X4, X5, X1, and X2 posted during the measurement period "January 1, 2022 to June 30, 2022" contributed to the store visit behavior W2. According to the example of FIG. 6, the measurement device 100 determines that the advertisement X2 posted immediately before the store visit behavior W2 contributed to the store visit behavior W2 and sets it as a contributing advertisement. Then, the measurement device 100 gives 1 Walk-in to the contributing advertisement X2.

[0046] For example, a user Ux does not necessarily visit a store immediately after coming into contact with an advertisement. In general, it is said that a user Ux often visits a store several days after coming into contact with an advertisement. In this way, a specific period may be required from coming into contact with an advertisement until offline behavior is initiated, and in a situation where a measurement period is set, offline behavior outside the measurement period may not be reflected in the counting of the advertising effect, resulting in a decrease in accuracy. Therefore, in order to prevent a decrease in the counting accuracy of the advertising effect, the measurement device 100 sets a grace period, and when a visit to a store is detected during the grace period, the detected visit behavior is used as an element of the effectiveness measurement targeting the advertisement posted during the measurement period.

[0047] [4. Account Structure] Next, the hierarchical structure of accounts held by an advertiser will be described with reference to Fig. 7. Fig. 7 is an explanatory diagram for explaining the hierarchical structure of accounts according to an embodiment.

[0048] First, the hierarchical structure of the advertising account (advertising account structure) will be described with reference to Fig. 7(a). The advertising account structure shown in Fig. 7(a) is set by an advertiser to manage advertisements according to the purpose of advertising operations. For this reason, in the following embodiments, the advertising account structure may be referred to as an "advertising management account structure."

[0049] The advertising management account structure corresponds to a hierarchical structure in which multiple types of management units for managing advertisements are each configured as one level. As an example, the advertising management account structure is a hierarchical structure having three levels, the top level account level, the middle level campaign level, and the bottom level ad group level, as shown in Fig. 7(a), and the actual published advertisements are linked to the ad group level. Also, each of the advertising account, campaign, and ad group referred to here corresponds to one management unit for managing advertisements.

[0050] An advertising account is information (identification information) unique to an advertiser, and is the management unit located at the top of a hierarchical structure. An advertising account may be, for example, an advertiser's unique ID, password, or email address, and the advertiser can log in to the measurement device 100 by having the measurement device 100 authenticate the advertising account. For this reason, the advertising account may be used as a login ID.

[0051] A campaign is information indicating the purpose of an advertisement, etc., and is a management unit that is located below (second to) an advertising account in a hierarchical structure. Advertisers can set one or more campaigns for one advertising account. In a campaign, items such as the product name (service name) to be advertised, budget, schedule, and area to deliver the advertisement can be registered. These items registered as a campaign correspond to the registration items registered in one management unit (here, campaign). Note that the registration items are not limited to the above example, and other examples include the day of the week, time period, and bidding method to deliver the advertisement.

[0052] An ad group is information for grouping published advertisements, and is a management unit that is subordinate (third-level) to campaigns in the hierarchical structure. Advertisers can set one or more ad groups for one campaign. In an ad group, for example, items such as keywords and bid prices for grouping published advertisements can be registered. These items registered as an ad group correspond to the registered items registered in one management unit (here, an ad group).

[0053] The management unit for managing advertisements is not limited to an advertisement account, a campaign, or an advertisement group. For example, the name of a business operator (e.g., a mobile communication business operator) that provides a network connected to the user device 10, or the type of the user device 10 (e.g., a smartphone, a tablet, a PC, etc.) may be used as the management unit. In addition, the name of the business operator that provides the network and the type of the user device 10 detected by the detection device 30 may be used.

[0054] Here, according to the advertising management account structure, for example, it is possible to measure store visits by advertising group and provide the advertiser with a report of advertising effectiveness aggregated by advertising group. However, as described above, the advertising management account structure is set according to the purpose of advertising management, and the advertiser may not want to measure store visits or aggregate advertising effectiveness by advertising group, which is one unit of the advertising management account structure. In reality, the advertiser may want to set the unit of store visit measurement and the unit of aggregation of advertising effectiveness individually. In response to the needs of the advertiser, the measurement device 100 accepts the setting of the measurement unit of advertising effectiveness and the setting of the report unit, which is the unit for compiling the aggregation result of advertising effectiveness as a report, and generates a new account structure different from the advertising management account structure based on the set contents.

[0055] In the following embodiments, the unit of measurement for advertising effectiveness may be referred to as a "line item," the report unit as a "report campaign," and the new counting structure consisting of "line items" and "report campaigns" as an "account structure for store visit measurement."

[0056] From here, the store visit measurement account structure will be explained in more detail with reference to Figure 7 (b). The store visit measurement account structure defines which of the registration items registered in the advertising management account structure will be set as line items (units of measurement of advertising effectiveness) and in what units (report units) the advertising effectiveness counted by line items will be aggregated.

[0057] According to the example of Figure 7(b), an advertiser can set up one or more accounts (measurement accounts) corresponding to a single advertising management account structure, which is a hierarchical structure in which each management unit, such as an advertising account, a campaign, and an advertising group, constitutes a single layer.

[0058] In addition, the advertiser can set a registered item included in any of the management units of an advertising account, a campaign, or an advertising group as a line item. In this embodiment, the description is limited to a campaign, and assumes that the measurement device 100 employs a configuration that allows any of the registered items registered as a campaign to be set as a line item. In this example, the advertiser can set one or more registered items of the registered items registered as a campaign as a line item.

[0059] For example, an advertiser can combine multiple registered items and set them as one line item. For example, the advertiser refers to a preset advertising management account structure (FIG. 7(a)) and performs an operation on the measurement device 100 to combine a product name item "XXX" registered as a campaign with another product name item "Product name XX" registered as a campaign into one line item. In such a case, as shown in FIG. 7(b), the measurement device 100 accepts a setting to set an integrated item (product name "XXX" + product name "XX") that combines the product name "XXX" and the product name "XX" into one as a line item.

[0060] With such settings, the measuring device 100 will assign one Walk-in to each advertisement that is determined to have contributed to the offline behavior of the advertisement exposed person as four advertisements linked to the product name "XX" and four advertisements linked to the product name "XX" are posted in chronological order.

[0061] In addition, the advertiser can set a report campaign, which is a report unit, by using the registered items registered as an ad group in an ad group hierarchy lower than the campaign hierarchy having the registered items used in the line items. Note that a configuration may be adopted in which the registered items used in the line items can also be used to set the report campaign.

[0062] For example, assume that an advertiser refers to the advertising management account structure and performs an operation on the measurement device 100 to combine a keyword (campaign) item "July" registered as an ad group with another keyword item "August" registered as an ad group into one report campaign. In this case, as shown in Fig. 7(b), the measurement device 100 accepts the setting of a report campaign that combines the advertising effect of an advertisement belonging to the "July" group and the advertising effect of an advertisement belonging to the "August" group into one report unit.

[0063] With such settings, the measurement device 100 generates a report showing the total number (Total Walkins), which is, for example, the number of advertisements belonging to the "July" group that have one Walk-in added together with the number of advertisements belonging to the "August" group that have one Walk-in added, and provides this report to the advertiser.

[0064] In addition, the measurement device 100 may generate a report that also shows the total number (Total Impressions), which is the sum of the number of advertisements that were actually placed among those belonging to the "July" group and the number of advertisements that were actually placed among those belonging to the "August" group.

[0065] Furthermore, when the measurement device 100 receives settings of the measurement account, the line item, and the report campaign, the measurement device 100 newly sets a hierarchical structure consisting of the measurement account, the line item, and the report campaign as a store visit measurement account structure, as shown in Fig. 7(b). The store visit measurement account structure may be a hierarchical structure having three hierarchical levels: the top measurement account level, the middle line item level, and the bottom report campaign level.

[0066] In this way, the store visit measurement account structure is set separately from the advertising management account, and the advertising effectiveness is measured and the measurement results are reported based on the settings defined in the store visit measurement account structure. For this reason, the store visit measurement account structure can be understood as information that reflects the advertiser's needs in store visit measurement, and by using this, it becomes possible to realize the effectiveness measurement in units desired by the advertiser and the report in units desired by the advertiser.

[0067] The account structure for store visit measurement shown in Figure 7 is a simple hierarchical structure without branches, but depending on how line items and report campaigns are set, various branches may occur with these as nodes, resulting in various hierarchical structures according to the branches. Therefore, variations in hierarchical structures will be explained in detail later.

[0068] 5. Configuration of the measurement device Next, a measurement device 100 (information processing device) according to an embodiment will be described with reference to Fig. 8. Fig. 8 is a diagram showing an example of the configuration of the measurement device 100 according to an embodiment. As shown in Fig. 8, the measurement device 100 has a communication unit 110, a storage unit 120, and a control unit 130.

[0069] (Regarding communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC) etc. For example, the communication unit 110 is wirelessly connected to a network N, and transmits and receives information between, for example, the user device 10, the advertiser device 20, and the detection device 30.

[0070] (Regarding the storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk, an optical disk, etc. The storage unit 120 has a contact / visit information database 121 and an account database 122.

[0071] Contact / store visit information database 121 stores advertisement contact information and store visit information described in Fig. 2. Account database 122 stores account information indicating the account structure described in Fig. 7. Specifically, account database 122 stores, as account information, an account structure for advertising management and an account structure for store visit measurement.

[0072] (Regarding the control unit 130) The control unit 130 is realized by a CPU (Central Processing Unit), MPU (Micro Processing Unit), etc., executing various programs (for example, an information processing program according to the embodiment) stored in a storage device inside the measuring device 100 using a RAM as a working area. The control unit 130 is also realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0073] As shown in Fig. 8, control unit 130 has reception unit 131, counting unit 132, acquisition unit 133, creation unit 134, and presentation unit 135, and realizes or executes functions and actions of information processing described below. Note that the internal configuration of control unit 130 is not limited to the configuration shown in Fig. 8, and may be other configurations as long as they perform information processing described below. Also, the connection relationship between each processing unit in control unit 130 is not limited to the connection relationship shown in Fig. 8, and may be other connection relationships.

[0074] (Regarding the reception unit 131 / counting unit 132) The reception unit 131 receives settings related to the hierarchical structure of accounts. Specifically, the reception unit 131 receives settings of a hierarchical structure in which a plurality of types of management units for managing advertisements are each configured as one tier, that is, an account structure for managing advertisements. According to the example of Fig. 7, the reception unit 131 receives settings of advertisement accounts, campaigns, and advertisement groups, and also receives submission of actual advertisements to be placed in the advertisement groups. More specifically, the reception unit 131 may receive the contents to be registered as advertisement accounts, the contents to be registered as campaigns, and the contents to be registered as advertisement groups.

[0075] The reception unit 131 registers in the account database 122 information on the advertisement management account structure that is configured from the setting contents received from the advertiser.

[0076] The receiving unit 131 may also receive the setting of the account structure for store visit measurement. For example, the acquiring unit 133 described later may acquire the account structure for advertisement management in response to a request from the advertiser to set the account structure for store visit measurement, and transmit the acquired account structure to the advertiser device 20 of the advertiser. In this case, the advertiser sets the account structure for store visit measurement while referring to the account structure for advertisement management.

[0077] The reception unit 131 receives the setting of a measurement unit (line item) of the advertising effect as one of the elements of the account structure for store visit measurement.

[0078] For example, the reception unit 131 receives a setting that sets one of the registered items registered for each management unit as a measurement unit of the advertising effectiveness. In this case, the counting unit 132 counts the advertising effectiveness of one advertisement determined to have contributed to the offline behavior of an advertisement contact person among a group of advertisements associated with the registered item defined as the measurement unit.

[0079] For example, the receiving unit 131 may receive a setting for setting any one of the registered items included in a predetermined one of the management units as a measurement unit of the advertising effectiveness.

[0080] For example, when this one management unit includes multiple registration items, the receiving unit 131 may receive a setting in which each registration item is a measurement unit. In this case, the counting unit 132 counts the advertising effectiveness of one advertisement that is determined to have contributed to the offline behavior of an advertisement exposed to the advertisement, among the advertisements linked to the registration item, for each registration item defined as a measurement unit.

[0081] As another example, when one management unit includes multiple registration items, the reception unit 131 may receive a setting in which, for each set of specified registration items, an integrated item that combines the registration items included in the set into one is used as the measurement unit. In this case, for each integrated item defined as the measurement unit, the counting unit 132 counts the advertising effect of one advertisement determined to have contributed to the offline behavior of an advertisement contact person among the advertisements associated with the integrated item.

[0082] The reception unit 131 also receives, as one element of the store visit measurement account structure, the setting of a report unit (report campaign) which is a unit for compiling the results of counting the advertising effect as a report.

[0083] For example, the reception unit 131 receives a setting of a report unit that is a unit for compiling a counting result of the advertising effect counted by using a registration item defined as a measurement unit or a registration item registered in a management unit lower than the management unit in which the registration item is registered, as a report. For example, the reception unit 131 may receive a setting of one or more registration items arbitrarily designated among the registration items registered in the lower management unit as the report unit.

[0084] In addition, the reception unit 131 accepts the setting of the report unit for each pair of the advertiser's account (measurement account) and the registered item defined as the measurement unit, and sets a hierarchical structure (account structure for store visit measurement) consisting of the accepted account, registered item, and report unit as new account information to be used for measuring the advertising effectiveness and reporting the measurement results.

[0085] The reception unit 131 may also register information about the store visit measurement account structure in the account database 122.

[0086] The counting unit 132 will be described in more detail. As described in Fig. 3, when detecting offline behavior of an advertisement exposed person who has come into contact with an advertisement included in an advertisement group linked to a registration item, the counting unit 132 determines that an advertisement included in the advertisement group that was most recently published before the timing at which the offline behavior was detected contributed to the advertisement exposed person's offline behavior.

[0087] As described in FIG. 4, for example, when an advertisement exposed person who has engaged in offline behavior is detected to again behave offline after being exposed to one or more advertisements after the offline behavior, the counting unit 132 determines that the advertisement that was most recently published before the detection of the offline behavior contributed to the advertisement exposed person's offline behavior.

[0088] On the other hand, as explained in FIG. 5, when an advertisement contact person who has engaged in offline behavior is detected to engage in offline behavior again without coming into contact with an advertisement after the offline behavior, the counting unit 132 does not count the advertising effectiveness corresponding to the offline behavior.

[0089] Also, as explained in Fig. 6, when offline behavior is detected during a predetermined period (e.g., a one-month grace period) after a predetermined measurement period of the advertising effect has elapsed, the counting unit 132 determines that, among the advertisements posted during the measurement period, an advertisement posted immediately before the timing at which the offline behavior was detected contributed to the offline behavior of the advertisement exposed person.

[0090] For example, the counting unit 132 assigns an advertising effect (1 Walk-in) indicating one offline action to an advertisement that was most recently posted before the timing at which the offline action was detected. For example, the counting unit 132 may assign a first advertising effect including the date on which the offline action was performed. The counting unit 132 may also assign a second advertising effect indicating the posting date to an advertisement that was most recently posted before the timing at which the offline action was detected.

[0091] (Regarding the acquisition unit 133) The acquisition unit 133 acquires various information used to measure advertising effectiveness. For example, the acquisition unit 133 acquires an account structure for advertising management in response to a request from an advertiser to set an account structure for store visit measurement. The acquisition unit 133 also acquires the account structure for store visit measurement. The acquisition unit 133 may also acquire advertising contact information and store visit information.

[0092] (About the creation unit 134) The creation unit 134 creates a report to be presented to the advertiser based on the report unit defined in the account structure for store visit measurement. For example, the creation unit 134 tally up the results of one Walk-in being awarded based on the report unit defined in the account structure for store visit measurement and creates a report.

[0093] (Regarding the presentation unit 135) The presentation unit 135 presents the report created by the creation unit 134 to the advertiser. Specifically, the presentation unit 135 transmits the report to the advertiser device 20. Note that the party to which the report is presented is not limited to the advertiser. For example, the presentation unit 135 may also present the report to an advertising agency that undertakes requests from the advertiser, or a predetermined business entity involved in the distribution and measurement of advertisements.

[0094] [6. Account structure for measuring store visits and concrete examples of measuring effectiveness] From here, specific examples of store visit measurement account structures and specific methods of measuring advertising effectiveness using the store visit measurement account structures will be described with reference to Figures 9 to 14. Figures 9 to 14 show a case where an advertising management account structure and a store visit measurement account structure are set by the advertiser C1, and an arbitrary user Ux becomes an advertisement contact person in response to the posting of an advertisement submitted by the advertiser C1. Also, each store visit measurement account structure used in the description of Figures 9 to 14 is a variation of the store visit measurement account structure described in Figure 7(b).

[0095] In addition, in FIG. 9 to FIG. 14, each variation of the store visit measurement account structure is set based on one advertising management account structure AC1.

[0096] [6-1. Account structure for measuring store visits and specific examples of measuring effectiveness (1)] Fig. 9 is a diagram (1) showing a specific example of an account structure. First, with reference to Fig. 9, an advertising management account structure AC1 (abbreviated as "management account AC1") will be described.

[0097] The management account AC1 has a hierarchical structure having three hierarchical levels: a top-level account level, a middle-level campaign level, and a bottom-level ad group level, and the actual published advertisements are linked to the ad group level.

[0098] 9, the management account AC1 has a login ID "C11" in the account hierarchy. This example shows that the login ID "C11" has been registered as an advertising account by the advertiser C1. In other words, the login ID "C11" is a registration item registered as an advertising account.

[0099] Furthermore, management account AC1 has product names "PD1" and "PD2" that are linked to login ID "C11" as subordinates in the campaign hierarchy. This example shows that advertiser C1 has registered product names "PD1" and "PD2" as campaigns that are subordinate (second-level) to advertising account "C11." In other words, product names "PD1" and "PD2" are registered items that are registered as campaigns.

[0100] Furthermore, the management account AC1 has the keywords "July" and "August" that are linked to the product name "PD1" as subordinates in the ad group hierarchy. This example shows that the keywords "July" and "August" have been registered by the advertiser C1 as ad groups that are subordinate (third-ranked) to the campaign "PD1." In other words, the keywords "July" and "August" are registered items that are registered as ad groups.

[0101] Furthermore, the management account AC1 has the keywords "July" and "August" that are linked to the product name "PD2" as subordinates in the ad group hierarchy. This example shows that the keywords "July" and "August" have been registered by the advertiser C1 as an ad group that is subordinate (third-ranked) to the campaign "PD2." In other words, the keywords "July" and "August" are the other registered items registered as an ad group.

[0102] 9, advertisements AD1 and AD2 are linked to the advertisement group "July" corresponding to the campaign "PD1." This example shows an example in which advertisements AD1 and AD2 are submitted by advertiser C1 as advertisements to be subordinate to the advertisement group "July" corresponding to the campaign "PD1."

[0103] Advertisements AD3 and AD4 are linked to the ad group "August" corresponding to the campaign "PD1." In this example, an advertiser C1 submits advertisements AD3 and AD4 as advertisements to be subordinate to the ad group "August" corresponding to the campaign "PD1."

[0104] On the other hand, advertisements AD5 and AD6 are linked to the ad group "July" corresponding to the campaign "PD2." In this example, advertisements AD5 and AD6 are submitted by advertiser C1 as advertisements to be subordinate to the ad group "July" corresponding to the campaign "PD2."

[0105] Advertisements AD7 and AD8 are linked to the ad group "August" corresponding to the campaign "PD2." In this example, the advertiser C1 submits advertisements AD7 and AD8 as advertisements to be subordinate to the ad group "August" corresponding to the campaign "PD2."

[0106] Next, one store visit measurement account structure set using the management account AC1 will be described. Fig. 9 shows a store visit measurement account structure AC11 (abbreviated as "measurement account AC11") as a variation of the store visit measurement account structure.

[0107] According to the example of FIG. 9, the measurement account AC11 has a three-level hierarchical structure including a top level measurement account level, a middle level line item level, and a bottom level report campaign level.

[0108] 9, the measurement account AC11 has a login ID "AC11" in the measurement account hierarchy. This example shows that the login ID "AC11" is registered as a measurement account by the advertiser C1.

[0109] The measurement account AC11 has a line item LA11 that is linked to the login ID "AC11" as a subordinate in the line item hierarchy. The line item LA11 is defined as a combination of the product name "PD1" and the product name "PD2", which are registered items registered as a campaign on the management account AC1 side. This example shows a case where the reception unit 131 receives a setting from the advertiser C1 to set the integrated item (product name "PD1" + product name "PD2"), which combines the product name "PD1" and the product name "PD2", as the measurement unit of the advertising effect.

[0110] In such a setting, the counting unit 132 counts the advertising effect for one advertisement determined to have contributed to the offline behavior of the user Ux while four advertisements (advertisements AD1 to AD4) linked to the product name "PD1" and four advertisements (advertisements AD5 to AD8) linked to the product name "PD2" are posted in chronological order. In other words, the counting unit 132 gives one Walk-in to one advertisement determined to have contributed to the store visit behavior of the user Ux while advertisements AD1 to AD8 are posted in chronological order.

[0111] Furthermore, the measurement account AC11 has a report campaign CP111 that is linked to the line item LA11 as a subordinate in the report campaign hierarchy. The report campaign CP111 is defined by combining the keyword "July" and the keyword "August", which are registered items registered as an ad group on the management account AC1 side. This example shows a case where the reception unit 131 receives a setting from the advertiser C1 to combine the advertising effectiveness of advertisements (ads AD1, AD2, AD5, AD6) belonging to the keyword "July" group and the advertising effectiveness of advertisements (ads AD3, AD4, AD7, AD8) belonging to the keyword "August" group into one report unit.

[0112] In such a setting, the creation unit 134 generates a report showing the total number (Total Walkins) of the number of advertisements with one Walk-in among the advertisements belonging to the "July" group (advertisements AD1, AD2, AD5, AD6) and the number of advertisements with one Walk-in among the advertisements belonging to the "August" group (advertisements AD3, AD4, AD7, AD8), and has the advertiser present this report. In other words, the creation unit 134 counts the number of advertisements with one Walk-in among the advertisements AD1 to AD8, and generates a report summarizing the counting results.

[0113] Next, measurement of advertising effectiveness performed based on the measurement account AC11 will be described with reference to Fig. 10. Fig. 10 is a diagram (1) showing a specific example of advertising effectiveness measurement.

[0114] Fig. 10(a) shows a specific example of advertising effectiveness measurement executed based on the measurement account AC11. Fig. 10(a) shows a case where advertisements AD8, AD4, AD5, AD6, and AD1, which are compiled in the report campaign CP111, are displayed in order for a user U1 (an example of a user Ux) according to the time series Time.

[0115] 10(a) shows an example in which a user U1 visits a store after advertisement AD8 → advertisement AD4 → advertisement AD5 → advertisement AD6 are published in the order of time series Time, and a store visit behavior W1 by the user U1 is detected. In this example, the counting unit 132 determines that advertisement AD6 contributed to the store visit behavior W1 based on the last impression method, and sets it as a contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD6.

[0116] 10(a) shows an example in which, after the store visit behavior W1, advertisements AD5 and AD1 are further published in the order according to the time series Time, and the next store visit behavior W2 by user U1 is detected when user U1 visits the store again. In this example, the counting unit 132 determines that advertisement AD1 contributed to the store visit behavior W2 performed again based on the last impression method, and sets advertisement AD1 as a contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD1.

[0117] 10(b) shows report RP11 as an example of a report summarizing advertising effectiveness based on measurement account AC11. In report RP11, advertising effectiveness is aggregated in units of report campaign CP111 linked to line item LA11. Specifically, in report RP11, "placed advertisements" (advertisement AD1, advertisement AD4, advertisement AD5, advertizement AD6, advertizement AD8) and "contributing advertisements" (advertisement AD1, advertizement AD6) shown in FIG. 10(a) are summarized using report campaign CP111.

[0118] In addition, in report campaign CP111, the "Total number" associated with "Published Advertisements" indicates the total number of advertisements published for user U1, i.e., the total number of advertisements that user U1 came across, and following the example of Figure 10(a), Impression "6" indicating a total number of 6 is entered.

[0119] Furthermore, in report campaign CP111, the “Total Number” associated with the “Contributing Advertisements” indicates the total number of advertisements that were determined to have contributed to user U1’s store visit behavior, and following the example of Figure 10(a), a Walk-in of “2” indicating a total number of 2 is entered.

[0120] [6-2. Account structure for measuring store visits and specific examples of measuring effectiveness (2)] Fig. 11 is a diagram (2) showing a specific example of an account structure. Fig. 11 shows a store visit measurement account structure AC12 (abbreviated as "measurement account AC12") as one store visit measurement account structure set using the management account AC1.

[0121] According to the example of FIG. 11, the measurement account AC12 has a three-level hierarchical structure including a top level measurement account level, a middle level line item level, and a bottom level report campaign level.

[0122] 11, the measurement account AC12 has a login ID "AC12" in the measurement account hierarchy. This example shows that the login ID "AC12" is registered as a measurement account by the advertiser C1.

[0123] The measurement account AC12 has a line item LA12 that is linked to the login ID "AC12" as a subordinate in the line item hierarchy. The line item LA12 is defined as a combination of the product name "PD1" and the product name "PD2", which are registered items registered as a campaign on the management account AC1 side. This example shows a case where the reception unit 131 receives a setting from the advertiser C1 to set the integrated item (product name "PD1" + product name "PD2"), which is a combination of the product name "PD1" and the product name "PD2", as the measurement unit of the advertising effect.

[0124] In such a setting, the counting unit 132 counts the advertising effect for one advertisement determined to have contributed to the offline behavior of the user Ux while four advertisements (advertisements AD1 to AD4) linked to the product name "PD1" and four advertisements (advertisements AD5 to AD8) linked to the product name "PD2" are posted in chronological order. In other words, the counting unit 132 gives one Walk-in to one advertisement determined to have contributed to the store visit behavior of the user Ux while advertisements AD1 to AD8 are posted in chronological order.

[0125] Furthermore, the measurement account AC12 has report campaigns CP121 and CP122 that are linked to the line item LA12 as subordinates in the report campaign hierarchy.

[0126] The report campaign CP121 is defined using the keyword "July", which is a registered item registered as an ad group on the management account AC1 side. This example shows an example in which the reception unit 131 has received from the advertiser C1 a setting for setting the advertising effectiveness of advertisements (ads AD1, AD2, AD5, AD6) belonging to the group of the keyword "July" as one report unit. The report campaign CP122 is defined using the keyword "August", which is a registered item registered as an ad group on the management account AC1 side. This example shows an example in which the reception unit 131 has received from the advertiser C1 a setting for setting the advertising effectiveness of advertisements (ads AD3, AD4, AD7, AD8) belonging to the group of the keyword "August" as one report unit.

[0127] That is, the receiving unit 131 receives from the advertiser C1 a setting to make a report containing separately summarized contents distinguishing between advertisements belonging to the "July" group and advertisements belonging to the "August" group.

[0128] With such settings, the creation unit 134 generates a report that individually shows, for example, the total number of advertisements that have one Walk-in among those belonging to the "July" group (ads AD1, AD2, AD5, AD6) and the total number of advertisements that have one Walk-in among those belonging to the "August" group (ads AD3, AD4, AD7, AD8), and has the report presented to the advertiser.

[0129] Next, measurement of advertising effectiveness performed based on the measurement account AC12 will be described with reference to Fig. 12. Fig. 12 is a diagram (2) showing a specific example of advertising effectiveness measurement.

[0130] Fig. 12(a) shows a specific example of advertising effectiveness measurement executed based on measurement account AC12. Fig. 12(a) shows a case where a group of advertisements (ads AD1, AD5, and AD6) compiled in report campaign CP121 and a group of advertisements (ads AD4 and AD8) compiled in report campaign CP122 are published in that order according to the time series Time for a user U2 (an example of user Ux).

[0131] 12(a) shows an example in which a user U2 visits a store after advertisement AD8 → advertisement AD4 → advertisement AD5 → advertisement AD6 are published in the order of time series Time, and a store visit behavior W1 by the user U2 is detected. In this example, the counting unit 132 determines that advertisement AD6 contributed to the store visit behavior W1 based on the last impression method, and sets advertisement AD6 as a contributing advertisement. Then, the counting unit 132 gives one Walk-in to the contributing advertisement AD6.

[0132] 12(a) shows an example in which, after the store visit behavior W1, advertisements AD5 and AD1 are further published in the order according to the time series Time, and the next store visit behavior W2 by user U2 is detected when user U2 visits the store again. In this example, the counting unit 132 determines that advertisement AD1 contributed to the store visit behavior W2 performed again based on the last impression method, and sets advertisement AD1 as a contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD1.

[0133] 12(b) shows a report RP12 as an example of a report summarizing the advertising effectiveness based on the measurement account AC12. In the report RP12, the advertising effectiveness is aggregated for each unit, which is divided into a unit of a report campaign CP121 linked to the line item LA12 and a unit of a report campaign CP122 linked to the line item LA12.

[0134] Specifically, in the report RP12, the "published advertisements" (advertisement AD1, advertisement AD5, advertizement AD6) and the "contributing advertisements" (advertisement AD1, advertizement AD6) shown in FIG. 12(a) are summarized using the report campaign CP121. In the report campaign CP121, the "total number" associated with the "published advertisements" indicates the total number of advertisements published for the user U2, i.e., the total number of advertisements that the user U2 came into contact with, and following the example of FIG. 12(a), Impression "4" indicating a total number of 4 is input. Also, in the report campaign CP121, the "total number" associated with the "contributing advertisements" indicates the total number of advertisements that were determined to have contributed to the store visit behavior of the user U2, and Walk-in "2" indicating a total number of 2 is input, following the example of FIG. 12(a).

[0135] In addition, in report RP12, the "published advertisements" (advertisement AD4, advert AD8) and "contributing advertisements" (none) shown in Fig. 12(a) are summarized using report campaign CP122. In report campaign CP122, the "total number" associated with the "published advertisements" indicates the total number of advertisements published for user U2, i.e., the total number of advertisements that user U2 came into contact with, and following the example of Fig. 12(a), Impression "2" indicating a total number of 2 is input. In addition, in report campaign CP122, the "total number" associated with the "contributing advertisements" indicates the total number of advertisements determined to have contributed to user U2's store visit behavior, and Walk-in "0" indicating a total number of 0 is input, following the example of Fig. 12(a).

[0136] In the examples of Figs. 9 to 11, one line item (for example, item LA11 in Fig. 9, and item LA12 in the example of Fig. 11) is set. In this case, a contribution judgment of a store visit behavior is performed for one line item, and the advertising effect is measured. However, a user can also set multiple line items. When multiple line items are set, a contribution judgment for each store visit behavior is performed for each line item. This point will be explained with reference to Figs. 13 and 14.

[0137] [6-3. Account structure for measuring store visits and specific examples of measuring effectiveness (3)] Fig. 13 is a diagram (3) showing a specific example of an account structure. Fig. 13 shows a store visit measurement account structure AC13 (abbreviated as "measurement account AC13") as one store visit measurement account structure set using the management account AC1.

[0138] According to the example of FIG. 13, the measurement account AC13 has a three-level hierarchical structure including a top level measurement account level, a middle level line item level, and a bottom level report campaign level.

[0139] 13, the measurement account AC13 has a login ID "AC13" in the measurement account hierarchy. This example shows that the login ID "AC13" is registered as a measurement account by the advertiser C1.

[0140] The metering account AC13 has a plurality of line items associated with the login ID “AC13” in the line item hierarchy. Specifically, the metering account AC13 has a line item LA131 and a line item LA132.

[0141] First, the line item LA131 will be described. The line item LA131 is defined only by the product name "PD1", which is a registered item registered as a campaign on the management account AC1 side. This example shows an example in which the reception unit 131 receives a setting from the advertiser C1 to use the product name "PD1" as a measurement unit of the advertising effect.

[0142] In such a setting, the counting unit 132 counts the advertising effect of one advertisement determined to have contributed to the offline behavior of the user Ux among the four advertisements (advertisements AD1 to AD4) associated with the product name "PD1" that are posted in chronological order. In other words, the counting unit 132 gives one Walk-in to one advertisement determined to have contributed to the store visit behavior of the user Ux among the advertisements AD1 to AD4 that are posted in chronological order.

[0143] Furthermore, the measurement account AC13 has report campaigns CP1311 and CP1312 that are linked to the line item LA131 as subordinates in the report campaign hierarchy.

[0144] The report campaign CP1311 is defined using the keyword "July", which is a registered item registered as an ad group on the management account AC1 side. This example shows an example in which the reception unit 131 has received a setting from the advertiser C1 in which the advertising effectiveness of advertisements (ads AD1, AD2) belonging to the group of the keyword "July" is set as one report unit. The report campaign CP1312 is defined using the keyword "August", which is a registered item registered as an ad group on the management account AC1 side. This example shows an example in which the reception unit 131 has received a setting from the advertiser C1 in which the advertising effectiveness of advertisements (ads AD3, AD4) belonging to the group of the keyword "August" is set as one report unit.

[0145] In other words, the receiving unit 131 receives a setting from the advertiser C1 to prepare a report that separately summarizes the group of advertisements (advertisements AD1, AD2, AD3, AD4) linked to the line item LA131, distinguishing between advertisements belonging to the "July" group and advertisements belonging to the "August" group.

[0146] With such settings, the creation unit 134 generates a report for line item LA131 that individually shows, for example, the total number of advertisements that have one Walk-in among those belonging to the "July" group (ads AD1, AD2) and the total number of advertisements that have one Walk-in among those belonging to the "August" group (ads AD3, AD4), and has the report presented to the advertiser.

[0147] Next, the explanation will be given on the line item LA132 side. The line item LA132 is defined only by the product name "PD2" which is a registered item registered as a campaign on the management account AC1 side. In this example, the reception unit 131 receives a setting from the advertiser C1 to use the product name "PD2" as a measurement unit of the advertising effect.

[0148] In such a setting, the counting unit 132 counts the advertising effect of one advertisement determined to have contributed to the offline behavior of the user Ux among the four advertisements (advertisements AD5 to AD8) associated with the product name "PD2" that are posted in chronological order. In other words, the counting unit 132 gives one Walk-in to one advertisement determined to have contributed to the store visit behavior of the user Ux among the advertisements AD5 to AD8 that are posted in chronological order.

[0149] Furthermore, the measurement account AC13 has report campaigns CP1321 and CP1322 that are linked to the line item LA132 as subordinates in the report campaign hierarchy.

[0150] The report campaign CP1321 is defined using the keyword "July", which is a registered item registered as an ad group on the management account AC1 side. This example shows an example in which the reception unit 131 has received from the advertiser C1 a setting for setting the advertising effectiveness of advertisements (ads AD5, AD6) belonging to the group of the keyword "July" as one report unit. The report campaign CP1322 is defined using the keyword "August", which is a registered item registered as an ad group on the management account AC1 side. This example shows an example in which the reception unit 131 has received from the advertiser C1 a setting for setting the advertising effectiveness of advertisements (ads AD7, AD8) belonging to the group of the keyword "August" as one report unit.

[0151] In other words, the receiving unit 131 receives a setting from the advertiser C1 to prepare a report that separately summarizes the advertisements (advertisements AD5, AD6, AD7, AD8) linked to the line item LA132, distinguishing between advertisements belonging to the "July" group and advertisements belonging to the "August" group.

[0152] With such settings, the creation unit 134 generates a report for line item LA132, which individually shows, for example, the total number of advertisements belonging to the "July" group (ads AD5, AD6) that have one Walk-in assigned, and the total number of advertisements belonging to the "August" group (ads AD7, AD8) that have one Walk-in assigned, and has the report presented to the advertiser.

[0153] Next, measurement of advertising effectiveness performed based on the measurement account AC13 will be described with reference to Fig. 14. Fig. 14 is a diagram (3) showing a specific example of advertising effectiveness measurement.

[0154] FIG. 14(a) shows a specific example of advertising effectiveness measurement performed based on the measurement account AC13.

[0155] The upper part of Figure 14(a) (line item LA131) shows a case in which a group of advertisements (advertisement AD1, advertisement AD2) compiled in report campaign CP1311 and a group of advertisements (advertisement AD3, advertisement AD4) compiled in report campaign CP1312 are displayed in order to user U3 according to the time series Time.

[0156] Also, the lower part of Fig. 14(a) (line item LA132) shows another example of a situation different from that shown in the upper part. The lower part of Fig. 14(a) shows a case where a group of advertisements (ads AD5, AD6) compiled in report campaign CP1321 and a group of advertisements (ads AD7, AD8) compiled in report campaign CP1322 are displayed in that order for user U3 according to the time series Time.

[0157] First, the example in the upper part of Fig. 14(a) will be described. The upper part of Fig. 14(a) shows an example in which a user U3 visits a store after advertisement AD2 and advertisement AD3 are published in that order according to the time series Time, and thus a store visit behavior W1 by the user U3 is detected. In this example, the counting unit 132 determines that advertisement AD3 has contributed to the store visit behavior W1 based on the last impression method, and sets it as a contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD3.

[0158] Also, the upper part of FIG. 14(a) shows an example in which advertisements AD1, AD4 are further published in the order of time series Time after the store visit behavior W1, and the next store visit behavior W2 by user U3 is detected when user U3 visits the store again. In this example, the counting unit 132 determines that advertisement AD4 contributed to the store visit behavior W2 performed again based on the last impression method, and sets advertisement AD4 as a contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD4.

[0159] Next, the example in the lower part of Fig. 14(a) will be described. The lower part of Fig. 14(a) shows an example in which a user U3 visits a store after advertisement AD6 → advertisement AD7 → advertisement 5 are published in the order according to the time series Time, and thus a store visit behavior W1 by the user U3 is detected. In this example, the counting unit 132 determines that advertisement AD5 has contributed to the store visit behavior W1 based on the last impression method, and sets it as a contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD5.

[0160] Here, as shown in the upper and lower parts of FIG. 14(a), when there are multiple line items (in the example of FIG. 14, line items LA131 and LA132), a contribution determination for each store visit behavior is performed for each line item.

[0161] 14(b) shows reports RP13-1 and RP13-2 as examples of reports summarizing advertising effects based on measurement account AC13. Report RP13-1 corresponds to line item LA131, and report RP13-2 corresponds to line item LA132.

[0162] In report RP13-1, the advertising effectiveness is calculated separately for report campaign CP1311 linked to line item LA131 and for report campaign CP1322 linked to line item LA131, and the advertising effectiveness is calculated for each unit.

[0163] Specifically, in report RP13-1, the "Published Ads" (Ads AD1, Ads AD2) and "Contributing Ads" (none) shown in Fig. 14(a) are summarized using report campaign CP1311. In report campaign CP1311, the "total number" associated with the "Published Ads" indicates the total number of ads published for user U3, i.e., the total number of ads that user U3 came across, and Impression "2" indicating a total number of 2 is input, following the example of Fig. 14(a). Also, in report campaign CP1311, the "total number" associated with the "Contributing Ads" indicates the total number of ads determined to have contributed to user U3's store visit behavior, and Walk-in "0" indicating a total number of 0 is input, following the example of Fig. 14(a).

[0164] In addition, in the report RP13-1, the "published advertisements" (advertisement AD3, advert AD4) and the "contributing advertisements" (advertisement AD3, advert AD4) shown in FIG. 14(a) are summarized using the report campaign CP1312. In the report campaign CP1312, the "total number" associated with the "published advertisements" indicates the total number of advertisements published for the user U3, i.e., the total number of advertisements that the user U3 came into contact with, and following the example of FIG. 14(a), Impression "2" indicating a total number of 2 is input. In the report campaign CP1312, the "total number" associated with the "contributing advertisements" indicates the total number of advertisements that were determined to have contributed to the store visit behavior of the user U3, and Walk-in "2" indicating a total number of 2 is input, following the example of FIG. 14(a).

[0165] Next, the report RP13-2 will be described. In the report RP13-2, the "published advertisements" (advertisement AD5, advert AD6) and the "contributing advertisements" (advertisement AD5) shown in FIG. 14(a) are summarized using the report campaign CP1321. In the report campaign CP1321, the "total number" associated with the "published advertisements" indicates the total number of advertisements published for the user U3, i.e., the total number of advertisements that the user U3 came into contact with, and following the example of FIG. 14(a), Impression "2" indicating a total number of 2 is input. Also, in the report campaign CP1321, the "total number" associated with the "contributing advertisements" indicates the total number of advertisements that were determined to have contributed to the store visit behavior of the user U3, and Walk-in "1" indicating a total number of 1 is input, following the example of FIG. 14(a).

[0166] In addition, in report RP13-2, the "Published Ads" (advertisement AD7, advert AD8) and "Contributing Ads" (none) shown in Fig. 14(a) are summarized using report campaign CP1322. In report campaign CP1322, the "total number" associated with the "Published Ads" indicates the total number of ads published for user U3, i.e., the total number of ads that user U3 came into contact with, and following the example in Fig. 14(a), Impression "2" indicating a total number of 2 is input. In addition, in report campaign CP1322, the "total number" associated with the "Contributing Ads" indicates the total number of ads determined to have contributed to user U3's store visit behavior, and Walk-in "1" indicating a total number of 1 is input, following the example in Fig. 14(a).

[0167] Up to now, specific examples of effect measurement and reports using the account structure for store visit measurement have been described with reference to Figs. 9 to 14. In Figs. 9 to 14, for the sake of simplicity, specific examples have been described focusing on one user Ux (user U1, user U2, user U3). However, in reality, the advertisement submitted by the advertiser C1 is distributed to an unspecified number of users. For this reason, a report in which the measurement results of the unspecified number of users are aggregated may be generated in response to detection of a store visit for each of the unspecified number of users.

[0168] For example, report RP11 may show not only the results corresponding to user U1, but also the aggregated results of an unspecified number of users including user U1. On the other hand, report RP11 may show the results of each user individually as information of a unique user. The same can be said about report RP12, report RP13-1, and report RP13-2.

[0169] 7. Processing Procedure Next, an operation procedure in which the measurement device 100 operates according to the information processing method according to the embodiment will be described with reference to Fig. 15. Fig. 15 is a flowchart showing the information processing procedure executed by the measurement device 100. Note that, in the example of Fig. 15, the information processing procedure executed by the measurement device 100 in a state in which the settings of the advertising management account structure and the store visit measurement account structure have already been accepted will be described. Also, the information processing method according to the embodiment is realized by an information processing program installed in the measurement device 100.

[0170] First, the acquisition unit 133 determines whether or not it is time to present a report (step S1501). If it is not time to present a report (step S1501; No), the acquisition unit 133 waits until it is time to present the report.

[0171] On the other hand, when it is time to present the report (step S1501; Yes), the acquisition unit 133 determines whether processing has been completed for all advertisers who wish to present the report at this time (step S1502), or whether processing has been completed for all advertisers.

[0172] When it is determined that the process has not been completed for all advertisers (step S1502; Yes), the acquisition unit 133 extracts one advertiser to be processed from the unprocessed advertisers (step S1503). The extracted advertiser to be processed is designated as advertiser Cx.

[0173] Then, the acquiring unit 133 acquires the management account (advertising management account structure) and the measurement account (advertising measurement account structure) accepted from the advertiser Cx (step S1504).

[0174] In addition, the acquisition unit 133 acquires store visit information of a store operated by the advertiser Cx (step S1505). For example, the acquisition unit 133 acquires the store visit information from the contact / store visit information database 121.

[0175] Furthermore, the acquisition unit 133 acquires the distribution history (advertisement contact information) of the advertisement submitted by the advertiser Cx according to the management account (step S1506).

[0176] In this state, the counting unit 132 determines, based on the measurement unit defined in the measurement account, the advertisement that contributed to the store visit indicated by the store visit information, among the advertisements that the user Ux has come into contact with (Step S1507).

[0177] Then, the counting unit 132 gives one Walk-in to the advertisement that is determined to have contributed to the store visit (step S1508).

[0178] The creation unit 134 compiles the results of one Walk-in based on the report unit defined in the measurement account and creates a report (step S1509). At this point, the process returns to step S1502.

[0179] The acquisition unit 133 again determines whether the process has been completed for all advertisers or not (step S1502). If it is determined that the process has been completed for all advertisers (step S1502; No), the presentation unit 135 presents the report created for each advertiser Cx by the creation unit 134 to each advertiser Cx (step S1510).

[0180] 8. Modifications The information processing by the measuring device 100 is not limited to the above example. Therefore, a modified example of the information processing according to the embodiment will be described below.

[0181] [8-1. Measuring effectiveness according to the type of event that occurred in the advertisement] The counting unit 132 may assign a priority to each advertisement that was posted before the timing at which the offline behavior was detected, depending on the type of event that occurred for the advertisement submitted using the advertisement management account structure, and may determine which advertisements contributed to the offline behavior of the advertisement contact based on the assigned priority.

[0182] For example, when an advertisement with a higher priority than the most recently published advertisement was published earlier among the advertisements published before the timing of detecting the offline behavior, the counting unit 132 may determine that the advertisement with the higher priority contributed to the offline behavior of the advertisement contact person. This point will be described with reference to Fig. 16. Fig. 16 is a diagram showing an example of advertising effectiveness measurement in which the type of event occurring in response to the advertisement is taken into consideration.

[0183] FIG. 16(a) shows the correspondence between the event type and the score (importance, priority) given to an advertisement in which an event of that type has occurred.

[0184] 16(a) shows an example in which the event type "impression" is associated with a score "SC1." This example shows an example in which a condition is set such that the score "SC1" is assigned to a published advertisement.

[0185] An example is shown in which the event type "viewable impression" is associated with a score "SC2." This example shows an example in which a condition is set such that the score "SC2" is assigned to an advertisement placed in a viewable area of ​​a user.

[0186] An example is shown in which the event type "click" is associated with a score "SC3." This example shows an example in which a condition is set such that a score "SC3" is assigned to an advertisement that has been clicked.

[0187] An example is shown in which the event type "video advertisement / playback start" is associated with a score "SC4." This example shows an example in which a condition is set to give a score "SC4" when playback of a video advertisement is started.

[0188] An example is shown in which the event type "video advertisement / continues to play for 3 seconds" is associated with a score "SC5." This example shows an example in which a condition is set to give a score "SC5" when the playback of a video advertisement continues for at least 3 seconds.

[0189] An example is shown in which the event type "video advertisement / continues to play for 10 seconds" is associated with a score "SC6." This example shows an example in which a condition is set to give a score "SC6" when the playback of a video advertisement continues for at least 10 seconds.

[0190] An example is shown in which the event type "video advertisement / viewed 25% of the total playback time" is associated with the score "SC7." This example shows an example in which a condition is set to give the score "SC7" when at least 25% of the total playback time is viewed.

[0191] An example is shown in which the event type "video advertisement / viewed 50% of the total playback time" is associated with the score "SC8." This example shows an example in which a condition is set to give the score "SC8" when at least 50% of the total playback time is viewed.

[0192] An example is shown in which the event type "video advertisement / viewed 75% of the total playback time" is associated with the score "SC9." This example shows an example in which a condition is set to give the score "SC9" when at least 75% of the total playback time is viewed.

[0193] An example is shown in which the event type "video advertisement / viewed 100% of the total playback time" is associated with a score "SC10." This example shows an example in which a condition is set to give a score "SC10" when a video advertisement is viewed to the end.

[0194] Next, an example of assigning 1 Walk-in based on the correspondence between the event type and the score will be described. In FIG. 16(b), an example of assigning 1 Walk-in based on the correspondence will be described with reference to the example in FIG. 12(a). In FIG. 16(b), for simplicity, the types of events in which advertisements occur will be limited to type ev1 (impression), type ev2 (viewable impression), and type ev3 (click). In addition, the magnitude relationship between the scores of types ev1, ev2, and ev3 is score SC1<score SC2<score SC3.

[0195] In the example of Fig. 12(a), the counting unit 132 determined that the advertisement AD6 contributed to the store visit behavior W1 and assigned one Walk-in to the advertisement AD6. Also, the counting unit 132 determined that the advertisement AD1 contributed to the store visit behavior W2 and assigned one Walk-in to the advertisement AD1. However, when considering the scores assigned to the advertisements AD1, AD4, AD5, AD6, and AD8 according to the type of event that occurred, one Walk-in may be assigned differently from the example of Fig. 12(a).

[0196] FIG. 16(b) shows an example in which the counting unit 132 assigns a score SC2 to advertisement AD1 in response to an event of type ev2, that is, a viewable impression, occurring for advertisement AD1.

[0197] Also, an example is shown in which the counting unit 132 assigns a score SC3 in response to an event of type ev3, i.e., a click, occurring on advertisement AD5.

[0198] Also, an example is shown in which the counting unit 132 assigns a score SC2 to advertisement AD6 in response to the occurrence of an event of type ev2, i.e., a viewable impression.

[0199] Also, an example is shown in which the counting unit 132 assigns a score SC1 in response to the occurrence of an event of type ev1, that is, an impression, for advertisement AD5.

[0200] Also, an example is shown in which the counting unit 132 assigns a score SC3 in response to an event of type ev3, i.e., a click, occurring on advertisement AD4.

[0201] Also, an example is shown in which the counting unit 132 assigns a score SC1 in response to the occurrence of an event of type ev1, that is, an impression, to the advertisement AD8.

[0202] Here, after advertisement AD8 → advertisement AD4 → advertisement AD5 → advertisement AD6 are posted in this order according to the time series Time, a store visit behavior W1 by user U2 is detected, so the counting unit 132 would normally give one Walk-in to advertisement AD6. However, in the example of FIG. 16(b), advertisement AD4, which has a higher score than advertisement AD6, is posted before advertisement AD6. In this example, the counting unit 132 determines that advertisement AD4 has contributed to the store visit behavior W1 in preference to advertisement AD6, and sets advertisement AD4 as the contributing advertisement. Then, the counting unit 132 gives one Walk-in to the contributing advertisement AD4.

[0203] Also, since the store visit behavior W2 by user U2 is detected after advertisement AD5 is posted in the order of advertisement AD1 according to the time series Time, the counting unit 132 would normally give one Walk-in to advertisement AD1. However, in the example of FIG. 16(b), advertisement AD5, which has a higher score than advertisement AD1, is posted before advertisement AD1. In this example, the counting unit 132 determines that advertisement AD5 has contributed to the store visit behavior W2 in priority to advertisement AD1, and sets advertisement AD5 as the contributing advertisement. Then, the counting unit 132 gives one Walk-in to the contributing advertisement AD5.

[0204] FIG. 16(b) shows an example in which the counting unit 132 assigns 1 Walk-in to the most recent advertisement for a store visit behavior among advertisements in which an event with a higher score has occurred based on the last impression method. However, the counting unit 132 may assign 1 Walk-in based on the last impression method in which a specific event is prioritized. Here, among the event types listed in FIG. 16(a), for example, the highest priority may be assigned to an event of type ev3, i.e., a click event. This is because the user operation of clicking can be said to be an action that most reflects the user's interest.

[0205] Therefore, when the click-prioritized last impression method is adopted, the counting unit 132 may narrow down the ads to those where a click event occurred and assign 1 Walk-in to the last ad published among the group of ads, even if the score of the event that occurred for the most recent advertisement for the store visit behavior was the highest.

[0206] On the other hand, in the click-priority last impression method, if there is no advertisement for which a click event has occurred, the counting unit 132 may assign 1 Walk-in to the most recent advertisement for the store visit behavior based on the normal last impression method.

[0207] [8-2. Expanded Estimates] In the above example, the counting unit 132 measures the advertising effectiveness based on the store visit detection result (store visit information) of a first user who subscribes to a communication service provided by a first communication carrier CA1 that is a partner company of the distribution provider T. However, the counting unit 132 may estimate the advertising effectiveness of a second user who subscribes to a communication service provided by a second communication carrier CA2 that is different from the first communication carrier CA1, based on the advertising effectiveness measurement result obtained for the first user.

[0208] For example, the counting unit 132 calculates the ratio between the number of users among the first users who have come into contact with any of the advertisements submitted according to the advertising management account structure and the number of users among the second users who have come into contact with any of the advertisements submitted according to the advertising management account structure.

[0209] In addition, the counting unit 132 obtains the number of advertising contacts among the first users who were exposed to the advertisement submitted according to the advertising management account structure and who were detected to have visited the store, and calculates an expanded estimation coefficient by multiplying this number by the above ratio.

[0210] The counting unit 132 may calculate the expanded estimation coefficient for each registered item registered as a campaign in the advertising management account structure. The counting unit 132 may also calculate the expanded estimation coefficient for each registered item registered as an ad group in the advertising management account structure. The counting unit 132 may also calculate the expanded estimation coefficient for each published advertisement belonging to an ad group in the advertising management account structure.

[0211] In this state, the counting unit 132 may correct the result of the advertising effectiveness measured for the first user (for example, the total number of advertisements to which one Walk-in was given) with the expanded estimation coefficient. Then, the counting unit 132 may estimate the corrected value as the advertising effectiveness for the second user.

[0212] [8-3. Anonymous processing] As described above, the presentation unit 135 presents the report created by the creation unit 134 to the advertiser, etc., and when the advertising effectiveness counting result included in the report satisfies a predetermined condition, the presentation unit 135 may present the counting result after anonymizing it. For example, when there is an advertisement with the number of 1 Walk-in granted (i.e., the number of advertising store visits) less than a predetermined value (e.g., less than 10), the presentation unit 135 may anonymize it so that the advertiser, etc. cannot recognize the number of 1 Walk-in granted.

[0213] For example, if the number of Walk-ins given is less than a predetermined value, there is a high possibility that the advertiser or the like can guess the person who visited the store. Therefore, the presentation unit 135 performs anonymity processing to prevent such inconvenience.

[0214] The presentation unit 135 may perform anonymization even if the number of assigned Walk-ins obtained as a result of the expanded estimation is a predetermined value or more (e.g., 10 or more). The presentation unit 135 may perform anonymization even if the number of assigned Walk-ins obtained as a result of the expanded estimation is a predetermined value or more (e.g., 10 or more), if the number of assigned Walk-ins obtained as a result of the expanded estimation is less than a predetermined value (less than 10).

[0215] [8-4. Detection devices] In the above embodiment, an example was shown in which the advertiser and the operating company of the store in which the detection device 30 is installed are the same. However, there are also store formats such as a collection of stores operated by different companies, i.e., shopping malls. In such examples, the advertiser can be either the operating company of the shopping mall (hereinafter referred to as the "mall operator") or the operating companies of each of the stores in the shopping mall in which the detection device 30 is installed (hereinafter referred to as the "store operator").

[0216] In this way, if the store in which the detection device 30 is installed is located in a shopping mall, the store operator can act as an advertiser and set information related to advertisement distribution (e.g., a management account, a measurement account). Furthermore, the data acquired by the detection device 30 may be provided to the mall operator at the discretion of the store operator. If the mall operator wishes to distribute advertisements, the mall operator can request data from the store operator and set information related to advertisement distribution (e.g., a management account, a measurement account) based on the provided data.

[0217] On the other hand, the detection device 30 may not be installed in a store in a shopping mall, but may be installed in a shared space (e.g., a passage in front of a store) in the shopping mall that does not belong to each store. In such an example, the detection device 30 may be installed at the discretion of the mall operator, and the rights to the data acquired by the detection device 30 may be held by the mall operator. In such an example, the mall operator can freely use the data acquired by the detection device 30 to set information related to advertisement delivery.

[0218] [9. Hardware Configuration] Moreover, the measuring device 100 according to the above embodiment is realized by a computer 1000 having a configuration as shown in Fig. 17, for example. Fig. 17 is a hardware configuration diagram showing an example of the computer 1000 that realizes the functions of the measuring device 100. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0219] The CPU 1100 operates and controls each unit based on a program stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, programs that depend on the hardware of the computer 1000, and the like.

[0220] The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, etc. The communication interface 1500 receives data from other devices via the communication network 50 and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the communication network 50.

[0221] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0222] The media interface 1700 reads a program or data stored in the recording medium 1800, and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0223] For example, when the computer 1000 functions as the measuring device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes a program (e.g., an information processing program according to the embodiment) loaded onto the RAM 1200, thereby realizing the function of the control unit 130. Furthermore, the HDD 1400 stores data in the storage unit 120. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be obtained from another device via the communication network 50.

[0224] [10. Other] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0225] [11. Summary] The above describes the embodiments of the present application in detail with reference to several drawings. However, these are merely examples, and the present invention can be embodied in other forms that incorporate various modifications and improvements based on the knowledge of those skilled in the art, including the aspects described in the Disclosure of the Invention section. [Explanation of symbols]

[0226] 1 System 100 Measuring Equipment 120 Storage section 121 Contact / Visit Information Database 122 Account Database 130 Control section 131 Reception 132 Counting Department 133 Acquisition Department 134 Creation Department 135 Presentation section

Claims

1. an acquisition unit that acquires, as advertising account information, a hierarchical structure in which each of a plurality of types of management units for managing advertisements is configured as one hierarchical level; a reception unit that receives a setting of one of the registered items registered as a management unit as a measurement unit of the advertising effectiveness for a measurement account for managing the measurement of the advertising effectiveness, and manages information in which the received measurement unit is linked to the measurement account as measurement account information that is new account information different from the advertising account information; a counting unit that executes, for each of the measurement account information, a process of counting an advertising effect for one advertisement determined to have contributed to the offline behavior of an advertisement contact person among a group of advertisements associated with the registration items included in the measurement account information; 13. An information processing device comprising:

2. The reception unit receives a setting for setting any one of the registered items included in a predetermined one of the management units as a measurement unit of an advertising effect. The information processing device according to claim 1 .

3. When the one management unit includes a plurality of registered items, the reception unit receives a setting for each registered item as the measurement unit; The counting unit counts, for each registered item defined as the measurement unit, an advertising effect for one advertisement determined to have contributed to the offline behavior of an advertisement contact person among a group of advertisements associated with the registered item. The information processing device according to claim 2 .

4. The reception unit receives a setting for setting, when a plurality of registration items are included in the one management unit, an integrated item obtained by combining the registration items included in each specified group of registration items into one as the measurement unit, for each specified group of registration items; The counting unit counts, for each integrated item defined as the measurement unit, an advertising effect for one advertisement determined to have contributed to the offline behavior of an advertisement contact person among a group of advertisements associated with the integrated item. The information processing device according to claim 2 .

5. The reception unit further receives a setting of a report unit, which is a unit for compiling a counting result of the advertising effect by using the registration item registered as the measurement unit or the registration item registered as a management unit lower than the management unit in which the registration item is registered, as a report. The information processing device according to claim 2 .

6. The reception unit receives a setting that one or more arbitrarily designated registration items among the registration items registered as the lower management unit are set as the report unit. The information processing device according to claim 5 .

7. The reception unit receives the setting of the report unit for each pair of an advertiser's account and a registration item to be registered as the measurement unit, and sets a hierarchical structure consisting of the account, the registration item, and the report unit as new account information to be used for measuring the advertising effectiveness and for a measurement result report. The information processing device according to claim 5 .

8. When detecting offline behavior of an advertisement exposed person who was exposed to an advertisement included in the advertisement group, the counting unit determines that an advertisement included in the advertisement group that was most recently published before the timing at which the offline behavior was detected contributed to the offline behavior of the advertisement exposed person. The information processing device according to claim 1 .

9. When an offline action is detected again from an advertisement contact person who has performed the offline action while in contact with one or more advertisements after the offline action, the counting unit determines that the advertisement contact person contributed to the offline action of the advertisement contact person with respect to the advertisement that was most recently published before the timing at which the offline action was detected. The information processing device according to claim 8.

10. When the offline behavior is detected during a predetermined period after a predetermined measurement period for the advertising effect has elapsed, the counting unit determines that an advertisement that was published immediately before the timing at which the offline behavior was detected, among the advertisements published during the measurement period, contributed to the offline behavior of the advertisement contact person. The information processing device according to claim 8.

11. The counting unit assigns a priority to each advertisement that was published before the timing at which the offline behavior was detected, according to a type of event that occurred with respect to the advertisements included in the advertisement group, and determines which advertisements contributed to the offline behavior of the advertisement contact person based on the assigned priority. The information processing device according to claim 8.

12. When an advertisement having a higher priority than a most recently published advertisement among advertisements published before the timing of detecting the offline behavior was published earlier, the counting unit determines that the advertisement having a higher priority contributed to the offline behavior of the advertisement contact person. The information processing device according to claim 11.

13. The counting unit counts a first advertising effect indicating a date on which the offline behavior was performed for an advertisement that was placed immediately before the timing at which the offline behavior was detected. The information processing device according to claim 8.

14. The counting unit counts a second advertising effect indicating a posting date of an advertisement that was posted immediately before the timing at which the offline behavior was detected. The information processing device according to claim 8.

15. When an offline action is detected again from an advertisement contact person who has engaged in the offline action without contacting an advertisement after the offline action, the counting unit does not count the advertising effect corresponding to the offline action. The information processing device according to claim 8.

16. The counting unit counts an advertising effect for one advertisement determined to have contributed to the offline behavior, for the advertising contacts who are first users using a communication service provided by a first communication carrier and who have performed the offline behavior, and estimates an advertising effect for a second user who uses a communication service provided by a second communication carrier different from the first communication carrier, based on the counting result. The information processing device according to claim 1 .

17. The counting unit corrects the counting result with a coefficient calculated based on the ratio of the number of users among the second users who have been exposed to the advertisements included in the advertisement group to the number of users among the first users who have been exposed to the advertisements included in the advertisement group, and the number of people exposed to the advertisements, and estimates the corrected counting result as the advertising effect targeted at the second users. The information processing device according to claim 16.

18. An information processing method executed by an information processing device, an acquisition step of acquiring, as advertising account information, a hierarchical structure in which each of a plurality of types of management units for managing advertisements is configured as one hierarchical level; a receiving step of receiving a setting of a measurement unit of advertising effectiveness for a measurement account for managing measurement of advertising effectiveness, the setting being such that any of the registered items registered as the management unit is a measurement unit of advertising effectiveness, and managing information in which the received measurement unit is linked to the measurement account as measurement account information which is new account information different from the advertising account information; a counting step of executing, for each of the measurement account information, a process of counting the advertising effect of one advertisement determined to have contributed to the offline behavior of an advertisement contact person among a group of advertisements associated with the registration items included in the measurement account information; An information processing method comprising:

19. An acquisition step of acquiring a hierarchical structure as advertising account information, the hierarchical structure being configured with a plurality of types of management units for managing advertisements as one hierarchy; a receiving step of receiving a setting of a measurement unit of advertising effectiveness for a measurement account for managing measurement of advertising effectiveness, the setting being such that any of the registered items registered as the management unit is a measurement unit of advertising effectiveness, and managing information in which the received measurement unit is linked to the measurement account as measurement account information which is new account information different from the advertising account information; a counting step of executing, for each of the measurement account information, a process of counting an advertising effect for one advertisement determined to have contributed to the offline behavior of an advertisement contact person among a group of advertisements associated with the registration items included in the measurement account information; An information processing program for causing an information processing device to execute the above.

Images