JP7623337B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

In recent years, advertising delivery systems have been measuring store visit conversions to measure the effectiveness of advertising measures aimed at attracting customers. For example, by measuring store visit conversions, it becomes possible to visualize the extent to which advertising contributed to store visits.

In addition, the ad delivery system can, for example, set an ad set for each campaign set for an advertiser's account, and set multiple pieces of operational information for each ad set. As a result, for example, the ad delivery system can present effectiveness information for each ad set to the advertiser.

JP 2015-64782 A

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

For example, the hierarchical structure of advertising accounts set by advertisers may be subdivided according to purpose, product, budget, etc. However, advertisers may only make such detailed settings to manage ad 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 be able to individually set the units for measuring store visits and the units for tallying advertising effectiveness.

The above-mentioned conventional technologies are not necessarily able to meet the needs of such advertisers. Specifically, the conventional technologies merely calculate the evaluation value of advertising media based on the number of clicks and weights for various advertising media as a measure to effectively support advertising activities. For this reason, it can be said that the conventional technologies have room for improvement in terms of realizing measurement of advertising effectiveness that meets the needs of advertisers.

Therefore, this disclosure proposes an information processing device, an information processing method, and an information processing program that can realize measurement of advertising effectiveness that satisfies the needs of advertisers.

In order to solve the above problem, an information processing device according to one embodiment of the present disclosure has 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 layer, a reception unit that accepts a setting to set one of the registered 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 determined to have contributed to the offline behavior of an advertisement contact person from among a group of advertisements linked under the registered item defined as the measurement unit.

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

Embodiments of the present disclosure will be described in detail below with reference to the drawings. Note that the information processing device and information processing method according to the present disclosure are not limited to these embodiments. In addition, in the following embodiments, the same components are designated by the same reference numerals, and duplicated descriptions will be omitted.

<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.

As shown in FIG. 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.

The user device 10 is an information processing terminal used by a user, and examples of such devices include a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, and a PDA (Personal Digital Assistant). The term "user" here refers to a general consumer (end user) who visits a brick-and-mortar store to shop or receive services.

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 advertised store.

Here, a visit to a physical store by an advertisement contact is an example of an offline action according to the embodiment, but the offline action is not limited to a visit to a physical store. For example, the offline action may be a purchase of a product or the enjoyment of a service at a physical store by an advertisement contact.

The advertiser device 20 is an information processing terminal used by the 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 term "advertiser" refers to the source that submits advertisements. For example, the advertiser may be a company that is a client of a distribution company T that mediates advertisement distribution, and may operate a store.

For example, the advertiser device 20 performs various settings related to advertisement delivery and store visit measurement on the measurement device 100 in response to the advertiser's operation. In addition, the advertiser device 20 also submits the advertisement itself to the measurement device 100 in response to the advertiser's operation.

The detection device 30 is a device installed in a real store operated by an advertiser (e.g., a client company of 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 pre-assigned to an advertisement delivered to the user device 10. The detection device 30 may also be provided by distribution provider T or a partner company of distribution provider T.

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 processing related to store visit measurement. The measurement device 100 may also be a device belonging to distribution company T.

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 for the advertising effectiveness. In this state, the measurement device 100 counts the advertising effectiveness for one advertisement determined to have contributed to the offline behavior of an advertisement exposed person, out of a group of advertisements linked under the registered item defined as the measurement unit.

In this embodiment, the measurement device 100 is described as also having an advertisement distribution function. Specifically, the measurement device 100 not only performs the information processing according to the above-described embodiment, but also distributes advertisements submitted by advertisers. On the other hand, advertisement distribution may be realized by a dedicated server device separate from the measurement device 100.

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.

[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 business operator T, the medium M1, the medium M2, and the 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.

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, it 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 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. In addition, the advertisement contact information may be stored in the contact/visit information database 121 as one record serving as a delivery history in the advertisement delivery.

Assuming that a user who has become an advertisement contact by viewing 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. The detection device 30 then 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 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 a record of the delivery history in the delivery of advertisements. 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.

[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.

[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 advertisements X3, X2, and X1 are posted in order for an arbitrary user Ux according to the time series Time, and then the user Ux is detected to visit a 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 that user Ux visited this time.

Although there are exceptions, which will be described later, the measurement device 100 basically employs a counting method called last impressions. 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 user Ux, and counts (assigns) "1 Walk-in" as the advertising effect indicating one visit to the store for the contributing advertisement that was determined to have contributed to the visit.

According to the last impression method, the measurement device 100 determines that among advertisements X1, X2, and X3, the advertisement that was posted immediately before the timing of the visit detection (i.e., time T1 on June 30, 2022) contributed to the visit of user Ux. In the example of FIG. 3(a), the measurement device 100 determines that advertisement X1, which was 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 user Ux, and sets it as the contributing advertisement. Then, the measurement device 100 assigns 1 Walk-in to the contributing advertisement X1.

The measurement device 100 may also assign 1Walk-in including information indicating the date that the user Ux visited the store (date that the visit was detected). This point will be explained using 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, when the user Ux visited the store. By assigning 1Walk-in including the date that the user Ux visited the store in this way, it becomes possible to meet the needs of advertisers who want to know, for example, how much an advertisement contributed for each visit date.

As another example, the measurement device 100 may assign 1Walk-in including information indicating the posting date. This point will be explained using FIG. 3(c). According to the example of FIG. 3(c), the measurement device 100 may assign "1Walk-in_6/29 impression" 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 store visits were made in response to an advertisement that was posted when it was posted.

[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 according to the time series Time for an arbitrary user Ux. 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 user Ux visited this time.

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

Figure 4 also shows an example in which, after store visit behavior W1, advertisements X2 and X3 are further published in the order of time series Time, and the next store visit behavior W2 by user Ux is detected as the user Ux visits the store again. In this way, when offline behavior (W2) is detected again after offline behavior (W1) in a state of contact with one or more advertisements (advertisements X2, X3), the measurement device 100 determines that advertisement X3 contributed to store visit behavior W2, which was performed again, based on the last impression method, and sets it as a contributing advertisement. Then, the measurement device 100 assigns 1 Walk-in to contributing advertisement X1.

[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 this order for an arbitrary user Ux according to the time series Time.

Figure 5 shows an example in which user Ux visits the store twice in a row after advertisement X4 → advertisement X5 → advertisement X1 are published in the order of time series Time, and store visit actions W1 and W2 by 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 previous offline action, store visit action W1, but does not adopt the last impression method for the subsequent offline action, store visit action W2. In other words, the measurement device 100 determines that advertisement X1 contributed to store visit action W1 and sets it as a contributing advertisement. Then, the measurement device 100 assigns 1 Walk-in to the contributing advertisement X1. On the other hand, the measurement device 100 does not assign 1 Walk-in in response to store visit action W2.

For example, in the situation shown in Figure 5, a situation can be assumed in which a customer 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 calculate the legitimate advertising effectiveness. 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 in measuring the effectiveness.

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

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

Here, the advertiser may set the period for measuring store visits (period for measuring advertising effectiveness). Figure 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. Figure 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."

Figure 6 shows an example in which advertisements X4, X5, and X1 were posted in that order according to the time series Time, and then user Ux visited the store, resulting in store visit behavior W1 by user Ux being detected. Specifically, during the measurement period "January 1, 2022 to June 30, 2022," advertisements X4, X5, and X1 were posted in that order, and store visit behavior W1 was detected during this measurement period.

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 that were published during the measurement period. That is, as in the previous examples, the measurement device 100 determines that advertisement X1 contributed to the store visit behavior W1 and sets it as the contributing advertisement. Then, the measurement device 100 assigns 1 Walk-in to the contributing advertisement X1.

Figure 6 also shows an example in which, after store visit behavior W1, advertisements X2 and X3 are further posted in the order of time series Time, and the next store visit behavior W2 by user Ux is detected when user Ux visits the store again. Specifically, this shows an example in which 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.

In this example, if the measurement device 100 follows the last impression method, it will determine that 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 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 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.

For example, user Ux does not necessarily visit a store immediately after coming into contact with an advertisement. In general, user Ux often visits a store several days after coming into contact with an advertisement. In this way, a specific period of time may be required between exposure to an advertisement and offline behavior, and in a situation where a measurement period is set, offline behavior outside the measurement period may not be reflected in the counting of advertising effectiveness, resulting in reduced accuracy. Therefore, in order to prevent a decrease in the accuracy of counting advertising effectiveness, the measurement device 100 sets a grace period, and if a visit is detected during the grace period, the detected visit is used as an element in measuring the effectiveness of the advertisement posted during the measurement period.

[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.

First, the hierarchical structure of advertising accounts (advertising account structure) will be described using 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."

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, a top-level account level, a middle-level campaign level, and a bottom-level ad group level, as shown in FIG. 7(a), and the actual published advertisements are linked to the ad group level. Furthermore, each of the advertising account, campaign, and ad group referred to here corresponds to one management unit for managing advertisements.

An advertising account is information (identification information) unique to an advertiser, and is the management unit located at the highest level in 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.

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

An ad group is information for grouping published advertisements, and is a management unit that is located below (third level) the campaign 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).

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

Here, according to the advertising management account structure, for example, it is possible to measure store visits by ad group and provide the advertiser with a report of advertising effectiveness aggregated by ad 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 ad 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. Therefore, 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 results of advertising effectiveness as a report, and generates a new account structure different from the advertising management account structure based on the set contents.

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."

From here, the store visit measurement account structure will be described 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 used as line items (units of measurement for advertising effectiveness) and in what units (report units) the advertising effectiveness counted by line items will be aggregated.

According to the example in FIG. 7(b), an advertiser can set up one or more accounts (measurement accounts) that correspond 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 tier.

In addition, the advertiser can set a registered item included in any of the management units of an advertising account, a campaign, or an ad group as a line item. In this embodiment, the description is limited to campaigns, 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.

For example, an advertiser can combine multiple registered items and set them as one line item. For example, the advertiser refers to a pre-set 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, 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 line item, as shown in FIG. 7(b).

With these settings, the measurement device 100 assigns 1 Walk-in to each advertisement that is determined to have contributed to the offline behavior of the advertisement contact as four advertisements linked to the product name "XXX" and four advertisements linked to the product name "XX" are posted in chronological order.

In addition, the advertiser can set up a report campaign, which is a report unit, using the registered items registered as an ad group in an ad group hierarchy that is lower than the campaign hierarchy that has 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 up a report campaign.

For example, 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 such a case, the measurement device 100 accepts the setting of a report campaign that combines the advertising effectiveness of an advertisement belonging to the "July" group and the advertising effectiveness of an advertisement belonging to the "August" group into one report unit, as shown in FIG. 7(b).

With such settings, the measurement device 100 generates a report showing the total number (Total Walkins) of the number of ads in the "July" group that have been given 1 Walk-in and the number of ads in the "August" group that have been given 1 Walk-in, and provides this report to the advertiser.

The measurement device 100 may also generate a report that shows the total number (Total Impressions) of the number of ads that were actually placed among the ads belonging to the "July" group and the number of ads that were actually placed among the ads belonging to the "August" group.

When the measurement device 100 receives settings for a measurement account, a line item, and a report campaign, it newly sets a hierarchical structure consisting of a measurement account, a line item, and a 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: a top measurement account level, a middle line item level, and a bottom report campaign level.

In this way, the store visit measurement account structure is set up separately from the advertising management account, and 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 measure effectiveness in units desired by the advertiser and to provide reports in units desired by the advertiser.

The store visit measurement account structure shown in Figure 7 is a simple hierarchical structure with no branches, but depending on how line items and report campaigns are set up, 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.

5. Configuration of the measuring 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.

(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 the network N, and transmits and receives information between, for example, the user device 10, the advertiser device 20, and the detection device 30.

(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/store visit information database 121 and an account database 122.

The contact/store visit information database 121 stores the advertising contact information and store visit information described in FIG. 2. The account database 122 stores account information indicating the account structure described in FIG. 7. Specifically, the account database 122 stores, as account information, an account structure for advertising management and an account structure for store visit measurement.

(Regarding the control unit 130)
The control unit 130 is realized by a central processing unit (CPU), a micro processing unit (MPU), or the like executing various programs (e.g., 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 application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

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

(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, i.e., 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.

The reception unit 131 registers information about the advertising management account structure, which is composed of the settings received from the advertiser, in the account database 122.

The reception unit 131 may also receive the setting of the account structure for store visit measurement. For example, the acquisition unit 133 described later may acquire the account structure for advertising management in response to a request from an advertiser to set an account structure for store visit measurement, and transmit this to the advertiser's advertiser device 20. In this case, the advertiser sets the account structure for store visit measurement while referring to the account structure for advertising management.

The reception unit 131 receives the setting of the measurement unit (line item) of advertising effectiveness as one of the elements of the store visit measurement account structure.

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

For example, the reception unit 131 may receive a setting to set one of the registered items included in a specific management unit among the management units as the unit of measurement for advertising effectiveness.

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

As another example, when one management unit includes multiple registration items, the reception unit 131 may receive a setting in which, for each specified group of registration items, an integrated item that combines the registration items included in the group 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 effectiveness of one advertisement that is determined to have contributed to the offline behavior of an advertisement contact person from among the group of advertisements linked to the integrated item.

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.

For example, the reception unit 131 receives a setting of a report unit that is a unit for compiling the results of counting the advertising effect as a report 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. For example, the reception unit 131 may receive a setting that sets one or more registration items, which are arbitrarily specified among the registration items registered in the lower management unit, as the report unit.

The reception unit 131 also receives 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 (store visit measurement account structure) consisting of the received account, registered item, and report unit as new account information to be used for measuring the advertising effectiveness and reporting the measurement results.

The reception unit 131 may also register information about the account structure for measuring store visits in the account database 122.

The counting unit 132 will be described in more detail. As described in FIG. 3, when the counting unit 132 detects offline behavior by an advertisement contacted by 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 published most recently before the timing at which the offline behavior was detected contributed to the advertisement contacted by the advertisement.

As described in FIG. 4, for example, when an advertisement contact 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 most recently published before the detection of the offline behavior contributed to the advertisement contact's offline behavior.

On the other hand, as explained in FIG. 5, if 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.

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

For example, the counting unit 132 assigns an advertising effect (1 Walk-in) indicating one offline action to the 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 the advertisement that was most recently posted before the timing at which the offline action was detected.

(Regarding the Acquisition Unit 133)
The acquisition unit 133 acquires various information used to measure the 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.

(Regarding 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 1 Walk-in assignment based on the report unit defined in the account structure for store visit measurement and creates a report.

(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.

[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 in which 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 a submitted advertisement 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).

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

[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, an advertising management account structure AC1 (abbreviated as "management account AC1") will be described with reference to Fig. 9.

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

According to the example in FIG. 9, 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 advertiser C1. In other words, the login ID "C11" is a registration item registered as an advertising account.

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.

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

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

Furthermore, according to the example of FIG. 9, advertisements AD1 and AD2 are linked to the ad group "July" corresponding to the campaign "PD1." This example shows that advertisements AD1 and AD2 are submitted by advertiser C1 as advertisements to be subordinate to the ad group "July" corresponding to the campaign "PD1."

Advertisement AD3 and advertisement AD4 are linked to the ad group "August" corresponding to the campaign "PD1." In this example, advertisements AD3 and AD4 are submitted by advertiser C1 as advertisements to be subordinate to the ad group "August" corresponding to the campaign "PD1."

On the other hand, advertisements AD5 and AD6 are linked to the ad group "July" corresponding to the campaign "PD2." This example shows that advertisements AD5 and AD6 are submitted by advertiser C1 as advertisements to be subordinate to the ad group "July" corresponding to the campaign "PD2."

Advertisement AD7 and advertisement AD8 are linked to the ad group "August" corresponding to the campaign "PD2." In this example, advertisements AD7 and AD8 are submitted by advertiser C1 as advertisements to be subordinate to the ad group "August" corresponding to the campaign "PD2."

Next, we will explain one store visit measurement account structure set using the management account AC1. Figure 9 shows a store visit measurement account structure AC11 (abbreviated as "measurement account AC11") as a variation of the store visit measurement account structure.

In the example of Figure 9, measurement account AC11 has a three-level hierarchical structure with a top level measurement account level, a middle level line item level, and a bottom level report campaign level.

Furthermore, according to the example of FIG. 9, the measurement account AC11 has a login ID "AC11" in the measurement account hierarchy. This example shows that the login ID "AC11" has been registered as a measurement account by advertiser C1.

Measurement account AC11 has line item LA11 linked to login ID "AC11" as a subordinate in the line item hierarchy. Line item LA11 is defined as a combination of product name "PD1" and product name "PD2", which are registered items 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 advertiser C1 to use an integrated item (product name "PD1" + product name "PD2") combining product name "PD1" and product name "PD2" as the unit of measurement for advertising effectiveness.

With these settings, the counting unit 132 counts the advertising effectiveness for one advertisement that is determined to have contributed to the offline behavior of user Ux as four advertisements (ads AD1 to AD4) linked to the product name "PD1" and four advertisements (ads AD5 to AD8) linked to the product name "PD2" are posted in chronological order. In other words, the counting unit 132 assigns one Walk-in to one advertisement that is determined to have contributed to the store visit behavior of user Ux as advertisements AD1 to AD8 are posted in chronological order.

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

With these settings, the creation unit 134 generates a report showing the total number (Total Walkins) of the number of advertisements that have 1 Walk-in assigned among the advertisements belonging to the "July" group (ads AD1, AD2, AD5, AD6) and the number of advertisements that have 1 Walk-in assigned among the advertisements belonging to the "August" group (ads AD3, AD4, AD7, AD8), and has the report presented to the advertiser. In other words, the creation unit 134 tallies up the number of advertisements that have 1 Walk-in assigned among advertisements AD1 to AD8, and generates a report summarizing the tally results.

Next, the 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.

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

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

Figure 10(a) also shows an example in which, after store visit behavior W1, advertisements AD5 and AD1 are published in the order of the time series Time, and user U1 visits the store again, causing the next store visit behavior W2 by user U1 to be detected. In this example, the counting unit 132 determines that advertisement AD1 contributed to the second store visit behavior W2 based on the last impression method, and sets advertisement AD1 as a contributing advertisement. Then, the counting unit 132 assigns 1 Walk-in to contributing advertisement AD1.

Figure 10(b) shows report RP11 as an example of a report that summarizes advertising effectiveness based on measurement account AC11. In report RP11, advertising effectiveness is tallied in units of report campaign CP111 linked to line item LA11. Specifically, report RP11 uses report campaign CP111 to summarize the "placed advertisements" (advertisement AD1, advert AD4, advert AD5, advert AD6, advert AD8) and "contributing advertisements" (advertisement AD1, advert AD6) shown in Figure 10(a).

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 has been entered.

Furthermore, in report campaign CP111, the "total number" associated with "contributing advertisements" indicates the total number of advertisements determined to have contributed to user U1's store visit behavior, and following the example of Figure 10(a), Walk-in "2" indicating a total number of 2 has been entered.

[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.

In the example of Figure 11, measurement account AC12 has a three-level hierarchical structure with a top level measurement account level, a middle level line item level, and a bottom level report campaign level.

Furthermore, according to the example of FIG. 11, the measurement account AC12 has a login ID "AC12" in the measurement account hierarchy. This example shows that the login ID "AC12" has been registered as a measurement account by advertiser C1.

Measurement account AC12 has line item LA12, which is linked to login ID "AC12" as a subordinate in the line item hierarchy. Line item LA12 is defined as a combination of product name "PD1" and product name "PD2", which are registered items registered as a campaign on the management account AC1 side. This example shows an example in which the reception unit 131 receives from advertiser C1 a setting to use an integrated item (product name "PD1" + product name "PD2") combining product name "PD1" and product name "PD2" as the unit of measurement for advertising effectiveness.

With these settings, the counting unit 132 counts the advertising effectiveness for one advertisement that is determined to have contributed to the offline behavior of user Ux as four advertisements (ads AD1 to AD4) linked to the product name "PD1" and four advertisements (ads AD5 to AD8) linked to the product name "PD2" are posted in chronological order. In other words, the counting unit 132 assigns one Walk-in to one advertisement that is determined to have contributed to the store visit behavior of user Ux as advertisements AD1 to AD8 are posted in chronological order.

In addition, measurement account AC12 has report campaign CP121 and report campaign CP122 that are linked to line item LA12 as subordinates in the report campaign hierarchy.

Report campaign CP121 is defined using 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 advertiser C1 a setting to set the advertising effectiveness of advertisements (ads AD1, AD2, AD5, AD6) belonging to the group of keyword "July" as one report unit. Report campaign CP122 is defined using 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 advertiser C1 a setting to set the advertising effectiveness of advertisements (ads AD3, AD4, AD7, AD8) belonging to the group of keyword "August" as one report unit.

In other words, the reception unit 131 receives a setting from the advertiser C1 to make a report containing separately summarized content that distinguishes between advertisements that belong to the "July" group and advertisements that belong to the "August" group.

With these settings, the creation unit 134 generates a report that shows, for example, the total number of advertisements that are assigned 1 Walk-in among those belonging to the "July" group (ads AD1, AD2, AD5, AD6) and the total number of advertisements that are assigned 1 Walk-in among those belonging to the "August" group (ads AD3, AD4, AD7, AD8), and has the advertiser present this report.

Next, the 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.

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

Figure 12 (a) shows an example in which user U2 visits a store after advertisements AD8 → AD4 → AD5 → AD6 are published in this order according to the time series Time, and thus a store visit behavior W1 by user U2 is detected. In this example, the counting unit 132 determines that advertisement AD6 contributed to store visit behavior W1 based on the last impression method, and sets it as a contributing advertisement. Then, the counting unit 132 assigns 1 Walk-in to the contributing advertisement AD6.

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

Figure 12 (b) shows report RP12 as an example of a report that summarizes advertising effectiveness based on measurement account AC12. In report RP12, the advertising effectiveness is summarized by dividing it into units of report campaign CP121 linked to line item LA12 and units of report campaign CP122 linked to line item LA12.

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

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 across, and following the example of FIG. 12(a), Impression "2" indicating a total number of 2 has been input. In report campaign CP122, the "total number" associated with the "contributing advertisements" indicates the total number of advertisements that were determined to have contributed to user U2's store visit behavior, and following the example of FIG. 12(a), Walk-in "0" indicating a total number of 0 has been input.

Now, the examples in Figures 9 to 11 show an example in which one line item (for example, item LA11 in Figure 9, and item LA12 in the example in Figure 11) is set. In this case, a contribution judgment of a store visit behavior is performed for one line item, and the advertising effectiveness 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 using Figures 13 and 14.

[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.

In the example of Figure 13, measurement account AC13 has a three-level hierarchical structure: a top level measurement account level, a middle level line item level, and a bottom level report campaign level.

Furthermore, according to the example of FIG. 13, the measurement account AC13 has a login ID "AC13" in the measurement account hierarchy. This example shows that the login ID "AC13" has been registered as a measurement account by advertiser C1.

The measurement account AC13 has multiple line items that are linked to the login ID "AC13" in the line item hierarchy. Specifically, the measurement account AC13 has line items LA131 and LA132.

First, we will explain line item LA131. Line item LA131 is defined only by product name "PD1", 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 advertiser C1 to use product name "PD1" as a unit of measurement for advertising effectiveness.

With these settings, the counting unit 132 counts the advertising effectiveness for one advertisement that is determined to have contributed to the offline behavior of user Ux, among the four advertisements (ads AD1 to AD4) linked to the product name "PD1" that are posted in chronological order. In other words, the counting unit 132 assigns one Walk-in to one advertisement that is determined to have contributed to the store visit behavior of user Ux, among the advertisements AD1 to AD4 that are posted in chronological order.

In addition, measurement account AC13 has report campaign CP1311 and report campaign CP1312, which are linked to line item LA131 as subordinates in the report campaign hierarchy.

Report campaign CP1311 is defined using 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 advertiser C1 in which the advertising effectiveness of advertisements (ads AD1, AD2) belonging to the group of keyword "July" is to be one report unit. Report campaign CP1312 is defined using 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 advertiser C1 in which the advertising effectiveness of advertisements (ads AD3, AD4) belonging to the group of keyword "August" is to be one report unit.

In other words, the reception unit 131 receives settings from the advertiser C1 to prepare a report that summarizes the contents of the group of advertisements (ads AD1, AD2, AD3, AD4) associated with the line item LA131, dividing them into advertisements belonging to the "July" group and advertisements belonging to the "August" group.

With these settings, the creation unit 134 generates a report for line item LA131 that individually shows, for example, the total number of advertisements that belong to the "July" group (ads AD1 and AD2) that have 1 Walk-in assigned, and the total number of advertisements that belong to the "August" group (ads AD3 and AD4) that have 1 Walk-in assigned, and has the advertiser present this report.

Next, we move on to an explanation of the line item LA132. 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 the unit of measurement for advertising effectiveness.

With these settings, the counting unit 132 counts the advertising effectiveness for one advertisement that is determined to have contributed to the offline behavior of user Ux, among the four advertisements (ads AD5 to AD8) linked to the product name "PD2" that are posted in chronological order. In other words, the counting unit 132 assigns one Walk-in to one advertisement that is determined to have contributed to the store visit behavior of user Ux, among the advertisements AD5 to AD8 that are posted in chronological order.

In addition, measurement account AC13 has report campaign CP1321 and report campaign CP1322, which are linked to line item LA132 as subordinates in the report campaign hierarchy.

Report campaign CP1321 is defined using 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 advertiser C1 in which the advertising effectiveness of advertisements (ads AD5, AD6) belonging to the group of keyword "July" is to be one report unit. Report campaign CP1322 is defined using 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 advertiser C1 in which the advertising effectiveness of advertisements (ads AD7, AD8) belonging to the group of keyword "August" is to be one report unit.

In other words, the reception unit 131 receives a setting from the advertiser C1 to prepare a report that summarizes the contents of the group of advertisements (ads AD5, AD6, AD7, and AD8) associated with the line item LA132, dividing them into advertisements belonging to the "July" group and advertisements belonging to the "August" group.

With these settings, the creation unit 134 generates a report for line item LA132 that individually shows, for example, the total number of advertisements that belong to the "July" group (ads AD5 and AD6) that have 1 Walk-in assigned, and the total number of advertisements that belong to the "August" group (ads AD7 and AD8) that have 1 Walk-in assigned, and has the advertiser present this report.

Next, measurement of advertising effectiveness performed based on 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.

Figure 14 (a) shows a specific example of advertising effectiveness measurement performed based on measurement account AC13.

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

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 in which a group of advertisements compiled in report campaign CP1321 (advertisement AD5, advertisement AD6) and a group of advertisements compiled in report campaign CP1322 (advertisement AD7, advertment AD8) are displayed in that order for user U3 according to the time series Time.

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 user U3 visits a store after advertisement AD2 and then advertisement AD3 are published in the time series Time, and thus store visit behavior W1 by user U3 is detected. In this example, the counting unit 132 determines that advertisement AD3 contributed to store visit behavior W1 based on the last impression method, and sets it as a contributing advertisement. Then, the counting unit 132 assigns 1 Walk-in to contributing advertisement AD3.

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

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 user U3 visits a store after advertisement AD6 → advertisement AD7 → advertisement 5 are published in the time series Time, and thus store visit behavior W1 by user U3 is detected. In this example, the counting unit 132 determines that advertisement AD5 contributed to store visit behavior W1 based on the last impression method, and sets it as a contributing advertisement. Then, the counting unit 132 assigns 1 Walk-in to contributing advertisement AD5.

Here, as shown in the upper and lower rows 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 is performed for each line item.

In FIG. 14(b), reports RP13-1 and RP13-2 are shown as examples of reports summarizing advertising effectiveness based on measurement account AC13. Report RP13-1 corresponds to line item LA131, and report RP13-2 corresponds to line item LA132.

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.

Specifically, in report RP13-1, the "Published Ads" (advertisement AD1, advert AD2) and "Contributing Advertisements" (none) shown in FIG. 14(a) are compiled using report campaign CP1311. In report campaign CP1311, the "total number" associated with the "Published Ads" indicates the total number of advertisements published for user U3, i.e., the total number of advertisements that user U3 came across, and following the example in FIG. 14(a), Impression "2" indicating a total number of 2 has been input. In addition, in report campaign CP1311, the "total number" associated with the "Contributing Ads" indicates the total number of advertisements that were determined to have contributed to user U3's store visit behavior, and following the example in FIG. 14(a), Walk-in "0" indicating a total number of 0 has been input.

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

Next, report RP13-2 will be described. In report RP13-2, the "Published Advertisements" (advertisements AD5, advertisements AD6) and "Contributing Advertisements" (advertisement AD5) shown in FIG. 14(a) are compiled using report campaign CP1321. In report campaign CP1321, the "total number" associated with the "Published Advertisements" indicates the total number of advertisements published for user U3, i.e., the total number of advertisements that user U3 came across, and following the example in FIG. 14(a), Impression "2" indicating a total number of 2 has been input. Also, in report campaign CP1321, the "total number" associated with the "Contributing Advertisements" indicates the total number of advertisements that have been determined to have contributed to user U3's store visit behavior, and following the example in FIG. 14(a), Walk-in "1" indicating a total number of 1 has been input.

In report RP13-2, the "published advertisements" (advertisement AD7, advert AD8) and "contributing advertisements" (none) shown in FIG. 14(a) are summarized using report campaign CP1322. In report campaign CP1322, the "total number" associated with the "published advertisements" indicates the total number of advertisements published for user U3, i.e., the total number of advertisements that user U3 came across, and following the example in FIG. 14(a), Impression "2" indicating a total number of 2 has been input. In report campaign CP1322, the "total number" associated with the "contributing advertisements" indicates the total number of advertisements that were determined to have contributed to user U3's store visit behavior, and following the example in FIG. 14(a), Walk-in "1" indicating a total number of 1 has been input.

So far, specific examples of effect measurement and reports using the store visit measurement account structure have been described using Figures 9 to 14. In Figures 9 to 14, in order to simplify the explanation, specific examples have been described focusing on one user Ux (user U1, user U2, user U3). However, in reality, the advertisement submitted by advertiser C1 is distributed to an unspecified number of users. For this reason, a report that aggregates the measurement results of an unspecified number of users may be generated in response to the detection of a store visit for each of the unspecified number of users.

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 unique user information. The same can be said for report RP12, report RP13-1, and report RP13-2.

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 measurement device 100 describes the information processing procedure executed in a state in which the settings of the advertising management account structure and the store visit measurement account structure have already been accepted. Also, the information processing method according to the embodiment is realized by an information processing program introduced into the measurement device 100.

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

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).

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

Then, the acquisition unit 133 acquires the management account (advertising management account structure) and the measurement account (advertising measurement account structure) received from the advertiser Cx (step S1504).

The acquisition unit 133 also acquires store visit information for 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.

The acquisition unit 133 also acquires the delivery history (advertising contact information) of the advertisement submitted by the advertiser Cx according to the management account (step S1506).

In this state, the counting unit 132 determines, based on the measurement unit defined in the measurement account, which of the advertisements that have been contacted by the user Ux contributed to the store visit indicated by the store visit information (step S1507).

Then, the counting unit 132 assigns 1 Walk-in to the advertisement that is determined to have contributed to the store visit (step S1508).

The creation unit 134 tally up the 1 Walk-in allocation results based on the report unit defined in the measurement account and create a report (step S1509). At this point, the process returns to step S1502.

The acquisition unit 133 again determines whether the processing has been completed for all advertisers or not (step S1502). If it is determined that the processing 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).

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.

[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 published before the timing at which the offline behavior was detected, depending on the type of event that occurred for the advertisement submitted using the advertising management account structure, and may determine which advertisements contributed to the offline behavior of advertisement contacts based on the assigned priority.

For example, if an advertisement with a higher priority than the most recently published advertisement was published earlier among the advertisements published before the timing at which the offline behavior was detected, 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 that takes into account the type of event that occurred in response to the advertisement.

Figure 16 (a) shows the correspondence between event types and the scores (importance, priority) assigned to advertisements in which events of that type occur.

FIG. 16(a) shows an example in which the event type "impression" is associated with the score "SC1." This example shows an example in which a condition is set so that the published advertisement is assigned the score "SC1."

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 so that the score "SC2" is assigned to advertisements that are placed in the user's viewable area.

An example is shown in which the event type "click" is associated with a score "SC3." In this example, a condition is set such that a score "SC3" is assigned to an advertisement that is clicked.

An example is shown in which the event type "video advertisement/playback start" is associated with a score "SC4." In this example, a condition is set such that a score "SC4" is assigned when playback of a video advertisement is started.

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" if the video advertisement continues to play for at least 3 seconds.

An example is shown in which the event type "video advertisement/continues playing 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" if the video advertisement continues playing for at least 10 seconds.

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

An example is shown in which the event type "Video advertisement/viewed for 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.

An example is shown in which the event type "Video advertisement/75% of the total playback time viewed" 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.

An example is shown in which the event type "Video advertisement/viewed 100% of 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.

Next, an example of how 1 Walk-in is awarded based on the correspondence between the event type and the score will be described. In FIG. 16(b), an example of how 1 Walk-in is awarded 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 for which advertising has occurred 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.

In the example of FIG. 12(a), the counting unit 132 determined that advertisement AD6 contributed to store visit behavior W1 and awarded it 1 Walk-in. Also, the counting unit 132 determined that advertisement AD1 contributed to store visit behavior W2 and awarded it 1 Walk-in. However, when considering the scores awarded to advertisements AD1, AD4, AD5, AD6, and AD8 according to the type of event that occurred, 1 Walk-in may be awarded differently from the example of FIG. 12(a).

Figure 16 (b) shows an example in which the counting unit 132 assigns a score SC2 in response to the occurrence of an event of type ev2, i.e., a viewable impression, for advertisement AD1.

An example is also 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.

An example is also shown in which the counting unit 132 assigns a score SC2 to advertisement AD6 in response to an event of type ev2, i.e., a viewable impression, occurring.

An example is also shown in which the counting unit 132 assigns a score SC1 in response to an event of type ev1, i.e., an impression, occurring for advertisement AD5.

An example is also 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.

An example is also shown in which the counting unit 132 assigns a score SC1 in response to an event of type ev1, i.e., an impression, occurring for advertisement AD8.

Here, after advertisement AD8 → advertisement AD4 → advertisement AD5 → advertisement AD6 are posted in this order according to the time series Time, store visit behavior W1 by user U2 is detected, so the counting unit 132 would normally give 1 Walk-in to advertisement AD6. However, in the example of FIG. 16(b), advertisement AD4, which has a higher score than advertisement AD6, was posted before advertisement AD6. In this example, the counting unit 132 determines that advertisement AD4 has contributed to store visit behavior W1 in priority to advertisement AD6, and sets it as the contributing advertisement. Then, the counting unit 132 gives 1 Walk-in to the contributing advertisement AD4.

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 advertisement AD1 1 Walk-in. 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 store visit behavior W2 in priority to advertisement AD1, and sets it as the contributing advertisement. Then, the counting unit 132 gives advertisement AD5 1 Walk-in.

In addition, 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 for which an event with a higher score has occurred based on the last impression method. However, the counting unit 132 may also 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 the behavior that most reflects the user's interests.

Therefore, when the click-prioritized last impression method is adopted, the counting unit 132 may, for example, 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 ad in relation to the store visit behavior was the highest.

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.

[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 service 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.

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

The counting unit 132 also obtains the number of people among the first users who were exposed to the advertisement submitted according to the advertising management account structure and who were detected as visiting the store, and calculates the expansion estimation coefficient by multiplying this number by the above ratio.

The counting unit 132 may calculate the expanded estimation coefficient in units of registered items registered as campaigns in the advertising management account structure. The counting unit 132 may also calculate the expanded estimation coefficient in units of registered items registered as ad groups in the advertising management account structure. The counting unit 132 may also calculate the expanded estimation coefficient in units of published advertisements that belong to ad groups in the advertising management account structure.

In this state, the counting unit 132 may correct the result of the advertising effectiveness measured for the first user (e.g., the total number of advertisements with 1 Walk-in) with the expanded estimation coefficient. The counting unit 132 may then estimate the corrected value as the advertising effectiveness for the second user.

[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 counting result of the advertising effect included in the report satisfies a predetermined condition, the presentation unit 135 may present the counting result after subjecting it to anonymity processing. For example, when there is an advertisement for which the number of 1 Walk-in granted (i.e., the number of visits to the advertising store) is less than a predetermined value (e.g., less than 10), the presentation unit 135 may subject the advertisement to anonymity processing so that the advertiser, etc. cannot recognize the number of 1 Walk-in granted.

For example, if the number of Walk-ins given is small, less than a certain value, there is a high possibility that advertisers or other parties will be able to guess who visited the store. Therefore, the presentation unit 135 performs anonymity processing to prevent such inconvenience.

The presentation unit 135 may perform anonymization even if the number of assigned 1 Walk-in 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 1 Walk-in obtained as a result of the expanded estimation is a predetermined value or more (e.g., 10 or more), as long as the number of assigned 1 Walk-in obtained as a result of the expanded estimation is less than a predetermined value (less than 10).

[8-4. Detection devices]
In the above embodiment, an example has been 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 stores in the form of a collection of stores operated by different companies, i.e., shopping malls. In such an example, 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").

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). In addition, 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.

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 in the shopping mall that does not belong to each store (for example, an aisle in front of a store). In such an example, the detection device 30 may be installed at the discretion of the mall operator, and the mall operator may hold the rights to the data acquired by the detection device 30. In such an example, the mall operator can freely use the data acquired by the detection device 30 to set information related to advertisement distribution.

9. Hardware Configuration
The measuring device 100 according to the embodiment is realized by a computer 1000 having a configuration as shown in Fig. 17. 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.

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

HDD 1400 stores programs executed by CPU 1100 and data used by such programs. Communication interface 1500 receives data from other devices via communication network 50 and sends it to CPU 1100, and transmits data generated by CPU 1100 to other devices via communication network 50.

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 the data it generates to the output devices via the input/output interface 1600.

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.

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 functions of the control unit 130. In addition, the data in the storage unit 120 is stored in the HDD 1400. 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.

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 depending on various loads, usage conditions, etc.

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.

REFERENCE SIGNS LIST 1 System 100 Measurement device 120 Storage unit 121 Contact/visit information database 122 Account database 130 Control unit 131 Reception unit 132 Counting unit 133 Acquisition unit 134 Creation unit 135 Presentation unit

Claims (19)

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 ;
and a counting unit that executes, for each of the measurement account information , a process of counting the advertising effectiveness of one advertisement that is determined to have contributed to the offline behavior of an advertisement contactee among a group of advertisements linked to the registration items included in the measurement account information . The information processing device according to claim 1 , wherein 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. 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 information processing device according to claim 2 , wherein the counting unit 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 each registered item defined as the measurement unit. 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 information processing device according to claim 2 , wherein the counting unit 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 each integrated item defined as the measurement unit. The information processing device of claim 2, wherein the reception unit further receives a setting of a report unit, which is a unit for compiling the counting results of the advertising effect using a registration item registered as the measurement unit or a registration item registered as a management unit lower than the management unit in which the registration item is registered. The information processing apparatus according to claim 5 , wherein the reception unit receives a setting that one or more arbitrarily designated registration items among the registration items registered as the lower-level management units are set as the report unit. The information processing device of claim 5, wherein 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 advertising effectiveness and reporting measurement results. The information processing device according to claim 1 , wherein when the counting unit detects offline behavior of an advertisement contactor who has been 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 time when the offline behavior was detected contributed to the advertisement contactor's offline behavior. The information processing device according to claim 8, wherein when an offline action is detected again from an advertisement contact 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 that was most recently published before the time the offline action was detected contributed to the offline action of the advertisement contact. 9. The information processing device according to claim 8, wherein when the offline behavior is detected during a specified period after a predetermined measurement period for advertising effectiveness has elapsed, the counting unit determines that, among the advertisements posted during the measurement period, an advertisement that was posted immediately prior to the timing at which the offline behavior was detected contributed to the offline behavior of the advertisement contact. The information processing device according to claim 8 , wherein the counting unit assigns a priority to each advertisement that was published before the timing at which the offline behavior was detected, depending on a type of event that occurred for an advertisement included in the group of advertisements, 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 11, wherein the counting unit determines that an advertisement with a higher priority than a most recently published advertisement was published earlier among advertisements published before the timing at which the offline behavior was detected as having contributed to the offline behavior of the advertisement contactee. The information processing device according to claim 8 , wherein 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 , wherein 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 , wherein the counting unit does not count the advertising effectiveness according to an offline behavior of an advertisement contact person who has performed the offline behavior, when the person is detected to have performed offline behavior again without contacting an advertisement after the offline behavior. The information processing device according to claim 1, wherein the counting unit counts the advertising effectiveness of one advertisement that is determined to have contributed to the offline behavior, for a first user who is an advertising contact and who uses a communication service provided by a first telecommunications carrier and who has performed the offline behavior, and estimates the advertising effectiveness of a second user who uses a communication service provided by a second telecommunications carrier different from the first telecommunications carrier based on the counting result. 17. The information processing device according to claim 16, wherein the counting unit corrects the counting result with a coefficient calculated based on the number of advertisement-exposed persons and a 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 estimates the corrected counting result as the advertising effect targeted at the second users. 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 ;
and a counting process for executing, for each of the measurement account information , a process of counting 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 registration items included in the measurement account information . 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 ;
and a counting procedure for executing, for each of the measurement account information , a process of counting 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 registration items included in the measurement account information .

Images