JP7353317B2 - 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.

A technique has been disclosed that selects an advertisement to be presented to a user from among a plurality of advertisements based on words in which the user has shown interest during a period from the present to the past.

Patent No. 6025155

However, with the above-mentioned conventional technology, although it is possible to present an advertisement to a user based on the user's interests, it is not possible to know whether the user is interested in the presented advertisement.

The present application has been made in view of the above, and aims to estimate whether a user who has come into contact with an advertisement is interested in the advertisement.

The information processing device according to the present application includes an advertisement contact estimating unit that estimates contact with an advertisement using information other than date and time and location out of the user's action history based on various log data; After contacting the user, the user views the advertisement or takes a predetermined action other than the search action that is different from the final action corresponding to the conversion targeted by the ad. an acquisition unit that acquires environmental information regarding the situation; and an interest behavior estimation unit that estimates, from the environmental information, that the predetermined behavior is an action associated with contact with the advertisement, when contact with the advertisement is estimated. It is characterized by comprising the following.

According to one aspect of the embodiment, it is possible to estimate whether a user who has come into contact with an advertisement is interested in the advertisement.

FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to an embodiment. FIG. 3 is a diagram illustrating a configuration example of a terminal device according to an embodiment. FIG. 4 is a diagram illustrating a configuration example of an information providing apparatus according to an embodiment. FIG. 5 is a diagram showing an example of a user information database. FIG. 6 is a diagram showing an example of a history information database. FIG. 7 is a diagram showing an example of the behavior information database. FIG. 8 is a diagram showing an example of the number of people information database. FIG. 9 is a flowchart showing the processing procedure according to the embodiment. FIG. 10 is a diagram showing an example of a hardware configuration.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. In addition, in the following embodiments, the same parts are given the same reference numerals, and redundant explanations will be omitted.

[1. Overview of information processing method]
First, with reference to FIG. 1, an overview of an information processing method performed by an information processing apparatus according to an embodiment will be described. FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. In addition, in FIG. 1, a case will be described as an example in which it is estimated whether a user who has come into contact with an advertisement is interested in the advertisement.

As shown in FIG. 1, the information processing system 1 includes a terminal device 10, an information providing device 100, and an external search device 200. The terminal device 10, the information providing device 100, and the external search device 200 are connected to each other via a network N (see FIG. 2) so that they can communicate with each other by wire or wirelessly. In this embodiment, the terminal device 10 and the external search device 200 cooperate with the information providing device 100.

The terminal device 10 is a smart device such as a smartphone or a tablet used by a user U (user), and can communicate with any server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). This is a mobile terminal device that can perform Further, the terminal device 10 has a screen such as a liquid crystal display, which has a touch panel function, and displays data such as content through a tap operation, a slide operation, a scroll operation, etc. from the user U using a finger or a stylus. Accepts various operations on. Note that an operation performed on an area of the screen where content is displayed may be an operation on the content. Further, the terminal device 10 may be not only a smart device but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

The information providing device 100 cooperates with the terminal device 10 and external search device 200 of each user U, and provides APIs for various applications (hereinafter referred to as apps) to the terminal device 10 and external search device 200 of each user U. (Application Programming Interface) An information processing device that provides services, etc. and various data, and is realized by a server device, cloud system, etc.

Further, the information providing device 100 may be an information processing device that provides some kind of web service online to the terminal device 10 of each user U. For example, the information providing device 100 provides web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce, electronic payment, online games, online banking, online trading, accommodation/ticket reservation, video/music distribution, etc. services may be provided. In reality, the information providing apparatus 100 may cooperate with various servers that provide the above-mentioned Web services, mediate the Web services, or may be in charge of processing the Web services.

Note that the information providing device 100 can acquire user information regarding the user U. For example, the information providing device 100 acquires information regarding attributes of the user U, such as the user's U's gender, age, and area of residence. Then, the information providing device 100 stores and manages information regarding attributes of the user U along with identification information indicating the user U (user ID, etc.).

Further, the information providing device 100 acquires various kinds of history information (log data) indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. For example, the information providing device 100 acquires a location history, which is a history of the user U's location, date and time, from the terminal device 10. The information providing device 100 also acquires a search history, which is a history of search queries input by the user U, from a search server (search engine). The information providing device 100 also acquires a viewing history, which is a history of content viewed by the user U, from the content server. The information providing device 100 also acquires a purchase history, which is a history of product purchases and payment processing by the user U, from the electronic commerce server and the payment processing server. Further, the information providing device 100 may acquire the listing history and the sales history, which are the listing history of the user U on the marketplace, from the electronic commerce server or the payment server. The information providing device 100 also acquires a posting history, which is a history of postings by the user U, from a posting server or SNS server that provides a word-of-mouth posting service.

The external search device 200 is an information processing device that provides an application or website having a search window (search box) to the terminal device 10 of the user U, and is realized by a server device, a cloud system, or the like. For example, the external search device 200 accepts a search query that the user U inputs into the search window using the terminal device 10, and provides the user U's terminal device 10 with search results according to the input search query. . The application having a search window may be a browser, an SNS application, or the like, or may be a search bar on a home screen. Alternatively, it may be a map app, a car navigation app (navigation app), or the like. Additionally, websites with a search window are not limited to search sites and portal sites, but also EC (Electronic Commerce) sites, online malls, price comparison sites, SNS sites, and video sites (video sharing sites, video distribution sites). etc. may be used.

Note that the information providing device 100 and the external search device 200 may be the same device. That is, the information providing device 100 and the external search device 200 may be integrated.

In this embodiment, the information providing device 100 collects various information regarding the user U, and estimates whether the user U is interested in the advertisement when the user U comes into contact with the advertisement. Specifically, the information providing device 100 estimates the contact with advertisements from the daily behavior history of the user U. Furthermore, when the user U takes a predetermined action, environmental information regarding the user U's situation is acquired. Then, when contact with the advertisement is estimated, it is estimated from the environmental information that a predetermined action is an action (interesting action) associated with contact with the advertisement. At this time, the information providing device 100 estimates that the user U is interested in the advertisement by estimating that the predetermined action is an action associated with contact with the advertisement. That is, the information providing device 100 estimates that the user U is interested in the advertisement and has taken an action associated with contact with the advertisement.

Note that the predetermined action is different from the final action (purchase, visit, etc.) that is the purpose of the advertisement. For example, the predetermined action is an intermediate action (intermediate action) performed between contact with an advertisement and an action. Here, as a predetermined action, a case will be explained in which a search is performed using a search engine or the like using a keyword related to the content of the advertisement as a search query. The search engine may be an in-site search engine for electronic commerce used in EC sites, online malls, and the like. Further, the predetermined action is not limited to one action, but may be a plurality of actions. For example, the information providing device 100 may determine that the user U has taken a predetermined action when the user U has taken one of a plurality of predetermined actions. Further, the predetermined action is not limited to a single action, but may be a series of continuous actions. For example, the information providing device 100 may determine that the user U has taken a predetermined action when the user U has taken a series of actions in a predetermined order.

For example, the information providing device 100 estimates the date and time of contact with the advertisement based on the date and time included in the daily behavior history of the user U and the date and time when the advertisement was presented. Note that the date and time when the advertisement was presented may be the period during which the advertisement was presented. Further, as environmental information, information regarding the date and time when the user U took a predetermined action is acquired. If the date and time of contact with the advertisement and the date and time of taking a predetermined action satisfy a predetermined condition, it is estimated that the predetermined action is an action associated with contact with the advertisement.

Alternatively, the information providing device 100 estimates the position of contact with the advertisement based on the position information included in the daily action history of the user U and the position information of the advertisement. Further, as environmental information, position information regarding the position where the user U took a predetermined action is acquired. Then, if the position where the user made contact with the advertisement and the position where the predetermined action was taken satisfy a predetermined condition, it is estimated that the predetermined action is an action associated with contact with the advertisement.

Further, the information providing device 100 acquires, as environmental information, detection information indicating the result of the detection of the surroundings by the terminal device 10 of the user U when the user U takes a predetermined action, and based on the detection information, , it may be estimated that the predetermined behavior is a behavior associated with contact with an advertisement. For example, the information providing device 100 acquires sensor information indicating the detection results of various sensors installed in the terminal device 10 of the user U as the detection information.

Further, the information providing device 100 acquires, as environmental information, device signal detection information indicating that the terminal device 10 of the user U has detected a signal emitted by a device presenting an advertisement, and based on the device signal detection information, , it may be estimated that the predetermined behavior is a behavior associated with contact with an advertisement.

Furthermore, when contact with the advertisement is estimated, the information providing device 100 estimates the user's degree of interest in the advertisement from the timing of a predetermined action. For example, the information providing device 100 estimates the user's degree of interest in the advertisement based on the number of predetermined actions after coming into contact with the advertisement. Alternatively, the information providing device 100 estimates the user's degree of interest in the advertisement based on the interval from the time the user comes into contact with the advertisement until the user takes a predetermined action. Furthermore, when contact with multiple advertisements regarding the same target is estimated, the information providing device 100 may estimate the user's degree of interest in the advertisement for each advertisement based on the timing of a predetermined action. .

[1-1. basic action〕
For example, as shown in FIG. 1, the information providing device 100 collects various information regarding each user U from the terminal device 10 of each user U on a daily basis (step S1). For example, at the time of user registration of each user U, the information providing device 100 acquires user information regarding the attributes of each user U, and uses user identification information for identifying the user U as the user information. Link and memorize. Further, the information providing device 100 constantly or periodically collects user identification information and action history from the terminal device 10 of each user U. At this time, the information providing device 100 collects various kinds of history information indicating the user's U's behavior as the user's U's daily behavior history. Note that among the history information, the location history, which is the history of the location, date and time of the user U, includes a history of movement around town or within a building, a history of visits to facilities, a history of entering stores, and the like. That is, the history information includes position information. The location information includes information regarding the user U's location and date and time.

Subsequently, user U contacts the advertisement (step S2). For example, user U is presented with online advertisements such as listing advertisements and display advertisements (banner advertisements) when viewing various websites or using applications. The advertisement may be pushed to the terminal device 10. Alternatively, the user U is presented with offline advertisements such as television advertisements and ODM (Outdoor Media) advertisements while watching television or traveling. Note that TV advertising is just one example. Actually, it may be an audio advertisement such as a radio advertisement, a newspaper advertisement, a magazine advertisement, or the like. Further, ODM advertisements are advertisements that are used in media that people come into contact with in places other than the home, such as transportation advertisements inside stations, trains, and buses, and outdoor advertisements in cities and commercial facilities. This includes advertisements using digital signage that displays images and text, in-store broadcasts, and vehicle body advertisements. User U also receives leaflets and the like distributed at predetermined locations.

Subsequently, the user U takes an action of interest (step S3). In this embodiment, the user U takes a search action as an interested action. For example, the user U uses the terminal device 10 to input a search query into the search window of an application or website that has a search window (search box), and searches for the transaction target (product, service, etc.) posted in the advertisement. Search for stores that carry the product or advertised facilities. Note that the search behavior may be a map search. For example, the user U uses the terminal device 10 to search for a store that handles the transaction object (product, service, etc.) posted in the advertisement or the location on a map of the facility listed in the advertisement. Good too.

Subsequently, the external search device 200 provides the information providing device 100 with interest information regarding the interesting behavior of the user U (step S4). For example, the external search device 200 provides the information providing device 100 with the search query input by the user U, as well as the user identification information and location information of the user U. This location information includes information regarding the location and date and time when the user U took the search action.

Subsequently, the information providing device 100 estimates that the user U has contacted the advertisement, based on the user U's location and behavior history, among various information regarding the user U (step S5). For example, the information providing device 100 estimates that the user U has come into contact with an online advertisement distributed while viewing the content, based on the viewing history that is the history of the content that the user U has viewed.

Alternatively, the information providing device 100 can determine that the user U was at (or near) the location where the offline advertisement was presented, the period during which the offline advertisement was presented, and the location history that is the history of the user U's location, date and time. It is estimated that the user U was present at that location during the time period, and it is estimated that the user U came into contact with an offline advertisement. Note that the locations where offline advertisements are presented are not limited to the streets or inside buildings, but also include the inside of trains, buses, and other vehicles.

Further, the information providing device 100 can detect that the user U purchases a newspaper or magazine in which an advertisement is published, and that the user U buys the newspaper or magazine based on the purchase history that is the history of the user U's product purchases and payment processing. It may be assumed that the user has come into contact with the posted advertisement. In addition, the information providing device 100 estimates that the user U is watching a predetermined TV or radio program or reading a newspaper every morning as a daily routine based on the user U's SNS, schedule information, etc. It may be assumed that the person came into contact with the advertisement through television, radio, newspaper, etc. Note that the advertisement may be a TV or radio CM (commercial), or an advertisement within a program.

Subsequently, the information providing device 100 estimates, from the interest information from the external search device 200, that the search behavior of the user U is a search behavior associated with contact with an advertisement (step S6). For example, the information providing device 100 receives a search query input by the user U, user identification information and location information of the user U as interest information from the external search device 200, and receives the search query and the user U's user identification information and location information. Based on the location and date and time of the search action, it is estimated that the search action of the user U is a search action associated with contact with an advertisement.

For example, if the location and date and time at which user U took a search action are within a predetermined range (advertisement (within a radius of 200 meters from the location, or within 10 minutes from the time the advertisement was presented, etc.), the search behavior of the user U is estimated to be the search behavior associated with contact with the advertisement. In reality, the information providing device 100 not only compares location and date and time, but also compares keywords such as names/categories/characteristics of transaction objects (products, services, etc.) and facilities posted in advertisements. It is determined whether the search query input by the user U is related, and if it is determined that the search query is related, the search behavior of the user U is presumed to be the search behavior associated with contact with an advertisement. You can also do this. Note that the relationship between a keyword and a search query may be determined by natural language processing such as word distributed expression (word vector).

Subsequently, when the information providing device 100 estimates that the search behavior of the user U is a search behavior associated with contact with an advertisement, the information providing device 100 estimates that the user U is interested in the advertisement (step S7). At this time, the information providing device 100 may estimate the degree of user U's interest in the advertisement. For example, the information providing device 100 determines the user U's response to advertisements based on the number of times the user U has taken a search action (search frequency, etc.), or the interval (time, distance, etc.) from contact with the advertisement to the search action. The degree of interest may be quantified (scored). In addition, the information providing device 100 determines the degree of relevance between keywords such as names/categories/characteristics of transaction objects (products, services, etc.) and facilities posted in advertisements and the search query input by the user U. It may also be the degree of user U's interest in the advertisement. Note that the degree of association between a keyword and a search query may be estimated by natural language processing such as word distributed expression (word vector).

Next, the information providing device 100 estimates the number and percentage of users who have come into contact with the advertisement and become interested, based on the search behavior of an unspecified number of users (step S8). For example, the information providing device 100 estimates how many (how many users, what percentage) of users who are estimated to have come into contact with the advertisement have taken a search action associated with contact with the advertisement. That is, the information providing device 100 estimates the number and proportion of users who have taken a search action in response to contact with the advertisement, among the users who are estimated to have come into contact with the advertisement.

Subsequently, the information providing device 100 provides estimated information based on the above estimation result to the external search device 200 (step S9). For example, the information providing device 100 provides the external search device 200 with information that can identify that the search behavior of the user U is a search behavior associated with contact with an advertisement, as estimated information. That is, the information providing device 100 notifies the external search device 200 that the search behavior of the user U is a search behavior associated with contact with an advertisement.

Next, the external search device 200 provides information to the terminal device 10 of the user U who has input the search query, based on the search results corresponding to the search query and the estimated information from the information providing device 100 ( Step S10). For example, the external search device 200 identifies, based on the estimated information from the information providing device 100, that the search behavior of the user U is a search behavior associated with contact with an advertisement, and identifies the transaction object or facility listed in the advertisement. The search results related to are provided to the user U's terminal device 10 preferentially.

At this time, the external search device 200 rearranges the order of the search results according to the search query based on the estimated information from the information providing device 100, and selects the advertisement that the user U is estimated to have come into contact with on the terminal device 10. Search results related to listed transaction targets or facilities may be displayed preferentially. That is, the external search device 200 may rearrange (sort) the search results according to the search query based on the estimated information and provide them to the terminal device 10 of the user U.

Alternatively, based on the estimated information from the information providing device 100, the external search device 200 searches for an online advertisement (originally an online advertisement (re-present if applicable), various information related to the transaction target or facility posted in the advertisement (detailed information, word-of-mouth information, coupon/benefits information, etc.), other products related to the advertised product (products in the same category, Online advertisements for products of the same brand, etc.) may also be provided.

In this way, in this embodiment, using actions such as searches that accompany contact with advertisements, we can calculate the relationship between "ad contact" and "actions such as purchasing/visiting" (behavior) as a result of contact with advertisements. Measure “interest”.

Until now, when measuring the effectiveness of non-digital advertising, the only way to confirm ``ad exposure'' was through vague questionnaire surveys based on memory, such as ``Did you see the ad?'' In addition, "actions" can be measured using questionnaire surveys of people who have purchased products or services or visited stores or facilities, as well as increases and decreases in purchases and visits that are affected by various other measures, and advertisements. The only way to do this was to correlate exposure.

Therefore, in the present embodiment, an index of "interest" between "contact" and "action" that is relatively objective and can capture nearly complete information is created and used for effect measurement.

For example, advertisements such as TV and radio commercials in which the transmission time of specific information can be specified in seconds, and ODM advertisements such as outdoor advertisements and train advertisements in which the time when the advertisement was visible can be determined based on location information. In specific cases, if a person performs a related search during or within a few minutes of contact with the ad, it is assumed that the user is interested in the ad as a result of the ad exposure and this is measured. In this way, actions caused by "contact" and "interest" are linked based on the overlap and time difference between the sending time and the action time.

In addition, the level of "interest" is determined by the amount and duration of "interesting behavior" (number of searches, whether the person directly led to a purchase, whether they conducted a related search after some time, whether they began to watch related news, etc.). It is also possible to measure In other words, it is possible to measure not only a simple "interest" index but also the strength of interest.

[1-2. Method for estimating “ad contact” and “action” based on “interest”]
Next, we will explain how to accurately infer "ad contact" and "action" using the "interest" index. Here, we will explain a method for estimating the number of people who have "contacted an ad" or taken an "action" based on the number of people who have taken an "interesting action."

Note that "interesting behavior" and "action" are different behaviors. For example, "interesting behavior" indicates behavior (such as a search) that does not achieve the purpose of the advertisement but is caused by contact with the advertisement. "Action" indicates the final action (purchasing a product, visiting a facility, etc.) to achieve the purpose of the advertisement.

First, the information providing device 100 identifies users in advance, creates a panel of 100 or 1000 people whose "ad contact" and "actions" can be completely tracked, and selects "ad contact" from "ad contact" in the panel. The overall ratio of "ad contact" and "action" is estimated from the ratio of "interesting behavior" to "action", the ratio of "interesting behavior" to "action", and the overall index of "interesting behavior".

For example, the information providing device 100 prepares a panel of 1000 people. Then, the "ad exposure" of these 1,000 users and the "actions" such as purchases and visits resulting from the ad exposure are accurately grasped by some method. Note that contact with advertisements may be ascertained through a questionnaire survey of users or by taking pictures with a camera installed on a device such as a television. In addition, regarding purchasing, online purchases may be made through the company's EC site, and offline purchases may be made through electronic payments, credit card payments, etc.

In addition, by accurately understanding the "interesting behavior" (mainly searches) caused by these 1000 people's exposure to advertisements, the information providing device 100 can determine the ratio of "interesting behavior" from "advertising exposure" to "interesting behavior" (e.g. 2%). ) and measure the ratio (such as 1%) from "interesting behavior" to "action". For example, the information providing device 100 calculates the ratio from "ad contact" to "interesting action" based on the total number of "ad contact" and the total number of "interesting action." Furthermore, the information providing device 100 calculates the ratio from "interesting behavior" to "action" based on the total number of "interesting behavior" and the total number of "actions." Thereby, the information providing apparatus 100 can grasp the respective ratios of "ad contact" and "action" to the total number of "interesting actions."

In actual measurement, the information providing device 100 is able to grasp the total number of "interesting actions", not limited to the number of 1000 people on the panel, so the total number of "interesting actions" and each of "ad contact" and "action" can be grasped. Using the ratio, the total number of "ad contact" and the total number of "actions" due to ad contact are estimated by analogy. For example, if the total number of "interesting actions" is "100,000 people", the ratio of "ad contact" is "2%", and the ratio of "ad-induced purchases" is "1%", then the information providing device 100 The total number of ``ad contact'' is estimated to be ``5 million people'' (100,000 people/2%), and the total number of ``ad-induced purchases'' is ``100,000 people x 1%'', which is ``1,000 people.'' This makes it possible to estimate the number of users who have come into contact with an advertisement or the number of users who have taken an action based on the number of users who have entered a specific keyword and performed a search using the external search device 200, for example.

Note that it is possible to utilize the "interest" index or estimate "ad contact" and "action" using the above-mentioned "interest" index in almost real time. As a result, unlike traditional surveys, you get instant feedback that allows you to modify and optimize your message in near real time. The information providing device 100 has a mechanism for changing the distribution content based on this feedback, and a mechanism for preparing multiple transmission patterns in advance and optimizing them based on the feedback. Something similar to AB testing and optimization in advertising can also be done in non-digital advertising. In this manner, in this embodiment, AB testing and (almost) real-time optimization in non-digital advertising can be realized.

[1-3. Cause and effect between “ad contact” and “action”]
Next, we will explain how to more accurately link the cause and effect between "ad contact" and "action."

Previously, there was no way to link cause and effect between ``ad exposure'' and ``action,'' and the only way to make judgments was through correlation, which made comparisons with a control group difficult. For example, in the case of online advertisements such as listing advertisements and display advertisements (banner advertisements), it is necessary to know that the advertisement has been clicked or that a user who viewed the advertisement has made a purchase or other conversion (CV). However, it was not possible to know whether users who did not click or convert were interested in the ad. In reality, even if the ad does not lead to a direct click or conversion, users may become interested in keywords such as the name/category/characteristics of the transaction target (product, service, etc.) or facility etc. posted in the ad. be. Furthermore, after a user has deleted a posted advertisement, the user may become interested in the advertisement and desire to display the same advertisement again. Such users may end up purchasing products in the future. For example, if you present your ad to those users again at a later date, there is a possibility that they will click or convert this time. Furthermore, in offline advertisements such as television advertisements and ODM (Outdoor Media) advertisements, it is not possible to know whether users who come into contact with the advertisements are interested in the advertisements. Therefore, we propose the following method.

First, when estimating the total number of "ad contact" and "purchase" (actions) using the above estimation method, the information providing device 100 uses "ad contact and purchase" and "ad contact and purchase". The total number for each group is estimated by classifying them into four groups: "I did not purchase the products without contacting the advertisements," "I did not purchase the products without contacting the advertisements," and "I did not purchase the products without contacting the advertisements."

For example, the information providing device 100 selects in advance from a panel of 1000 people based on the number of people who have "contacted an advertisement," the number of people who have taken an "interesting action" after coming into contact with an advertisement, and the number of people who have "purchased" after an interested action. Find the ``proportion of people who were exposed to the advertisement and made a purchase'' and ``the proportion of people who were exposed to the advertisement and did not make a purchase'' in the group. Then, the information providing device 100 uses the total number of actually measured "interesting behaviors" and the above respective ratios to identify the "persons who purchased after coming into contact with advertisements" and "people who purchased after coming into contact with advertisements." Analogize the total number of "people who don't have any".

Furthermore, the information providing device 100 determines in advance from a panel of 1,000 people that the group's Calculate the percentage of people who made a purchase without being exposed to an ad and the percentage of people who did not make a purchase without being exposed to an ad. Then, the information providing device 100 uses the total number of actually measured "interesting behaviors" and the above-mentioned respective ratios to identify the "people who purchased without contacting advertisements" and "people who purchased without contacting advertisements". Analogize the total number of people who have not.

This makes it possible to more accurately estimate the effect of exposure to advertisements on purchases. Furthermore, in addition to estimating the four groups above, if we also include estimating whether the user is an existing user or not (existing customer or new customer), we can more accurately understand retention effects, contributions to brand switching, etc. It becomes possible to do so.

That is, in the present embodiment, the information providing device 100 determines in advance the number of people who have come into contact with an advertisement out of a predetermined group of people (such as a panel of 1000 people) from which individual users can be identified, and the number of people who have come into contact with an advertisement. Afterwards, the number of people who took a predetermined action (interesting action) is measured. Next, based on the measured number of people who came into contact with the advertisement and the number of people who took a predetermined action, a first ratio indicating the proportion of people who took a predetermined action after contact with the advertisement is calculated. Thereafter, based on the number of people who took a predetermined action among the general population and the first ratio, the number of people who contacted the advertisement among the general public is estimated. Note that the number of people who have taken a predetermined action among an unspecified large number of people is, for example, the number of users who have performed a search using a specific keyword as a search query in a search engine such as the external search device 200. In other words, it is possible to measure the number of people who take a predetermined action among a large and unspecified group of people.

The information providing device 100 also calculates in advance the number of people who took a predetermined action after coming into contact with an advertisement, out of a predetermined group of people from whom individual users can be identified, and the number of people who took a predetermined action after taking a predetermined action. Measure the number of people who took the desired final action. Next, based on the measured number of people who took a predetermined action and the number of people who took an action, a second ratio indicating the proportion of people who took an action from the predetermined action is calculated. Then, based on the number of people who took a predetermined action among the unspecified number of people and the second ratio, the number of people who took the action among the unspecified number of people is estimated.

The information providing device 100 also calculates in advance the number of people who took a predetermined action after coming into contact with an advertisement out of a predetermined group of people for whom individual users can be identified, and the number of people who took a predetermined action after taking the predetermined action. Count the number of people who did not take the test. Next, based on the measured number of people who took the predetermined action and the number of people who did not take the action, a third ratio indicating the ratio of the number of people who took no action from the predetermined action is calculated. After that, based on the number of people who took a predetermined action among the unspecified majority group, the second ratio, and the third ratio, the number of people who took an action from contact with the advertisement among the unspecified majority group, and the number of people who took an action from contact with the advertisement are determined. Estimate the number of people who took no action from contact with

The information providing device 100 also calculates in advance the number of people who have taken a predetermined action without contacting an advertisement among a predetermined group of people for whom individual users can be identified, and the number of people who have taken a predetermined action after taking a predetermined action. Measure the number of people who took the test. Next, based on the measured number of people who took a predetermined action and the number of people who took an action, a fourth ratio indicating the proportion of people who took an action from the predetermined action is calculated. Then, based on the number of people who took a predetermined action among the unspecified number of people and the fourth ratio, the number of people who took the action without contacting the advertisement among the unspecified number of people is estimated.

The information providing device 100 also calculates in advance the number of people who have taken a predetermined action without contacting an advertisement among a predetermined group of people for whom individual users can be identified, and the number of people who have taken a predetermined action after taking a predetermined action. Measure the number of people who did not take the test. Next, based on the measured number of people who took the predetermined action and the number of people who did not take the action, a fifth ratio indicating the ratio of the number of people who took no action from the predetermined action is calculated. Then, based on the number of people who took a predetermined action among the unspecified group and the fifth ratio, the number of people who did not contact the advertisement or take no action among the unspecified large group is estimated. Furthermore, even if you do not interact with the advertisement or take any action, if you are taking the same predetermined behavior (behavior of interest) as the person who came into contact with the advertisement or took an action, you may be considered latent. It can be said that they are consumers. Therefore, as described above, the number of potential consumers can be estimated by estimating the number of people who take a predetermined action but do not come into contact with the advertisement or take any action.

In this way, the information providing device 100 calculates the number of people who took an action after coming into contact with an advertisement, the number of people who did not take an action after coming into contact with an advertisement, and the number of people who took an action without coming into contact with an advertisement among a large number of unspecified groups. Estimate the number of people who took the ad and the number of people who did not interact with the ad or take any action.

Furthermore, the information providing device 100 measures in advance the number of new users and the number of existing users among a group of predetermined number of people from whom individual users can be identified.

The information providing device 100 also calculates in advance the number of new users and existing users who have come into contact with the advertisement among a group of predetermined number of people, and the number of people who have taken a predetermined action after coming into contact with the advertisement. Measure the number of people who took the test. Next, for both new users and existing users, based on the measured number of people who came into contact with the ad and the number of people who took a predetermined action, a predetermined action was taken from the contact with the ad. A first ratio indicating the proportion of people is calculated. Thereafter, the number of people who have come into contact with the advertisement is estimated based on the number of new users and existing users among the unspecified group of users, based on the number of people who have taken a predetermined action and the first ratio.

In addition, the information providing device 100 calculates in advance the number of new users and existing users among a group of predetermined people, the number of people who took a predetermined action after contacting the advertisement, and the number of predetermined users. Measure the number of people who took the final action targeted by the advertisement after taking the action. Next, for new users and existing users, based on the measured number of people who took a predetermined action and the number of people who took an action, the percentage of people who took an action from the predetermined action. A second ratio is calculated. Then, based on the number of new users and existing users who took a predetermined action among the unspecified majority group and the second ratio, actions are taken among the unspecified large group. Estimate the number of people taken.

[1-4. Effects of overlapping multiple advertising methods and their contribution]
Next, a method for measuring the effect of superimposing multiple advertising methods and its degree of contribution will be explained.

Traditionally, when communicating using multiple advertising methods such as TV commercials, digital advertising, and ODM advertising, how effective is each advertising method for the ultimate purpose (improving awareness, purchasing, etc.)? (Effectiveness of each advertising method) could only be estimated by analogy from the correlation between the amount of each advertising method, its change, and the final recognition rate and purchase amount, and it was not possible to accurately understand the contribution rate. . Therefore, we propose the following method.

First, the information providing apparatus 100 prepares a panel in the same manner as in the estimation method described above. In addition, the information providing device 100 combines the identification of the same person through facial recognition using cameras installed around TVs and ODM advertisements, and infers the whole by analogy from data on people who can be linked. do. For example, if someone searches immediately after coming into contact with an ODM advertisement that uses facial recognition, but if there are other people searching at approximately the same time and in the same place, it is considered that they have been in contact. Such a method makes it possible to estimate overall exposure, interest, and actions. In addition, by looking at the correlation between the media (advertisement media) and the number of contacts, and purchases and interests, it is possible to accurately measure effects.

[2. Configuration example of information processing system]
Next, the configuration of the information processing system 1 including the information providing apparatus 100 according to the embodiment will be described using FIG. 2. FIG. 2 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 2, the information processing system 1 according to the embodiment includes a terminal device 10, an information providing device 100, and an external search device 200. These various devices are connected via a network N so that they can communicate by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Furthermore, the number of devices included in the information processing system 1 shown in FIG. 2 is not limited to what is illustrated. For example, in FIG. 2, only one terminal device 10 is shown for simplification of illustration, but this is just an example and is not limited, and there may be two or more terminal devices.

The terminal device 10 is an information processing device used by the user U. For example, the terminal device 10 may be a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game console with a communication function, a car navigation system, a smart watch, or a head-mounted display. wearable devices, smart glasses, etc.

The terminal device 10 also supports wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), Bluetooth (registered trademark), and wireless LAN (Local It is possible to connect to a network N via short-distance wireless communication such as a local area network) and communicate with the information providing device 100.

The information providing device 100 is, for example, a PC, a server device, a mainframe, a workstation, or the like. Note that the information providing device 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be explained using FIG. 3. FIG. 3 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. As shown in FIG. 3, the terminal device 10 includes a communication section 11, a display section 12, an input section 13, a positioning section 14, a sensor section 20, a control section 30 (controller), and a storage section 40. Be prepared.

(Communication Department 11)
The communication unit 11 is connected to a network N (see FIG. 2) by wire or wirelessly, and transmits and receives information to and from the information providing device 100 via the network N. For example, the communication unit 11 is realized by a NIC (Network Interface Card), an antenna, or the like.

(Display section 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic electro-luminescent display (EL display). Further, the display unit 12 is a touch panel type display, but is not limited to this.

(Input section 13)
The input unit 13 is an input device that receives various operations from the user U. Furthermore, the input unit 13 includes, for example, buttons for inputting characters, numbers, and the like. Further, when the display section 12 is a touch panel display, a part of the display section 12 functions as the input section 13. Note that the input unit 13 may be a microphone or the like that receives voice input from the user U. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives a signal (radio wave) sent from a GPS (Global Positioning System) satellite, and based on the received signal, determines position information (for example, latitude and longitude). That is, the positioning unit 14 positions the terminal device 10 . Note that GPS is just one example of GNSS (Global Navigation Satellite System).

Further, the positioning unit 14 can measure the position using various methods other than GPS. For example, the positioning unit 14 may use various communication functions of the terminal device 10 to measure the position as an auxiliary positioning means for position correction and the like, as described below.

(Wi-Fi positioning)
For example, the positioning unit 14 positions the terminal device 10 using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 performs Wi-Fi communication, etc., and determines the position of the terminal device 10 by measuring the distance to nearby base stations and access points.

(Beacon positioning)
Further, the positioning unit 14 may use the Bluetooth (registered trademark) function of the terminal device 10 to measure the position. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting to a beacon transmitter connected by a Bluetooth (registered trademark) function.

(geomagnetic positioning)
Furthermore, the positioning unit 14 positions the terminal device 10 based on the geomagnetic pattern of the structure measured in advance and the geomagnetic sensor included in the terminal device 10 .

(RFID positioning)
Further, for example, if the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used at station ticket gates, stores, etc., or has a function to read an RFID tag. In this case, the location where the terminal device 10 used the terminal device 10 is recorded together with the information that the payment was made. The positioning unit 14 may measure the position of the terminal device 10 by acquiring such information. Further, the position may be determined by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

The positioning unit 14 may position the terminal device 10 using one or a combination of the above-mentioned positioning means, if necessary.

(sensor section 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. Note that the connection may be a wired connection or a wireless connection. For example, the sensors may be a detection device other than the terminal device 10, such as a wearable device or a wireless device. In the example shown in FIG. 3, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, an atmospheric pressure sensor 23, an air temperature sensor 24, a sound sensor 25, an optical sensor 26, a magnetic sensor 27, and an image sensor ( camera) 28.

Note that each of the sensors 21 to 28 described above is merely an example and is not limited to the above. That is, the sensor section 20 may be configured to include a portion of each of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of each of the sensors 21 to 28. .

The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects the physical movement of the terminal device 10, such as the moving direction, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects physical movements of the terminal device 10 such as tilt in three axes directions based on the angular velocity of the terminal device 10 and the like. The atmospheric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

Since the terminal device 10 is equipped with the above-mentioned acceleration sensor 21, gyro sensor 22, atmospheric pressure sensor 23, etc., it is possible to implement technologies such as pedestrian autonomous navigation (PDR) using these sensors 21 to 23, etc. It becomes possible to measure the position of the terminal device 10 using the . This makes it possible to obtain indoor position information that is difficult to obtain using positioning systems such as GPS.

For example, a pedometer using the acceleration sensor 21 can calculate the number of steps, walking speed, and distance walked. Furthermore, by using the gyro sensor 22, it is possible to know the direction of travel of the user U, the direction of the line of sight, and the inclination of the user's body. Further, from the atmospheric pressure detected by the atmospheric pressure sensor 23, it is also possible to know the altitude and the number of floors where the terminal device 10 of the user U is located.

The temperature sensor 24 detects, for example, the temperature around the terminal device 10. The sound sensor 25 detects, for example, sounds around the terminal device 10. The optical sensor 26 detects the illuminance around the terminal device 10 . The magnetic sensor 27 detects, for example, the earth's magnetism around the terminal device 10. The image sensor 28 captures an image of the surroundings of the terminal device 10.

The above-mentioned atmospheric pressure sensor 23, temperature sensor 24, sound sensor 25, optical sensor 26, and image sensor 28 each detect atmospheric pressure, temperature, sound, and illuminance, and capture images of the surroundings, so that the terminal device 10 It is possible to detect the surrounding environment and situation. Furthermore, it is possible to improve the accuracy of the location information of the terminal device 10 based on the environment and situation around the terminal device 10.

(Control unit 30)
The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input/output port, etc., and various circuits. Further, the control unit 30 may be configured with hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control section 30 includes a transmitting section 31, a receiving section 32, and a processing section 33.

(Transmission unit 31)
The transmitting unit 31 receives, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and information measured by the positioning unit 14. The location information of the terminal device 10 and the like can be transmitted to the information providing device 100 via the communication unit 11.

(Receiving unit 32)
The receiving unit 32 can receive various information provided from the information providing device 100 and requests for various information from the information providing device 100 via the communication unit 11 .

(Processing unit 33)
The processing unit 33 controls the entire terminal device 10, including the display unit 12 and the like. For example, the processing unit 33 can output various types of information transmitted by the transmitting unit 31 and various types of information received by the receiving unit 32 from the information providing device 100 to the display unit 12 for display.

(Storage unit 40)
The storage unit 40 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 an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an optical disk. Ru. The storage unit 40 stores various programs, various data, and the like.

[4. Configuration example of information providing device]
Next, the configuration of the information providing apparatus 100 according to the embodiment will be described using FIG. 4. FIG. 4 is a diagram illustrating a configuration example of the information providing apparatus 100 according to the embodiment. As shown in FIG. 4, the information providing device 100 includes a communication section 110, a storage section 120, and a control section 130.

(Communication Department 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). Further, the communication unit 110 is connected to the network N (see FIG. 2) by wire or wirelessly.

(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 or an optical disk. As shown in FIG. 4, the storage unit 120 includes a user information database 121, a history information database 122, an action information database 123, and a number of people information database 124.

(User information database 121)
The user information database 121 stores user information regarding the user U. For example, the user information database 121 stores various information such as user U's attributes. FIG. 5 is a diagram showing an example of the user information database 121. In the example shown in FIG. 5, the user information database 121 includes items such as "user ID (identifier),""age,""gender,""home,""worklocation," and "interest."

“User ID” indicates identification information for identifying user U. Moreover, "age" indicates the age of the user U identified by the user ID. Note that the "age" may be a specific age of the user U identified by the user ID, such as 35 years old. Furthermore, “gender” indicates the gender of the user U identified by the user ID.

Moreover, "home" indicates the location information of the home of the user U identified by the user ID. In the example shown in FIG. 5, "home" is illustrated as an abstract code such as "LC11", but it may also be latitude and longitude information. Furthermore, for example, "home" may be a region name or address.

Moreover, "work place" indicates the location information of the work place (school in the case of a student) of the user U identified by the user ID. In the example shown in FIG. 5, the "work location" is illustrated as an abstract code such as "LC12", but it may also be latitude/longitude information or the like. Further, for example, the "work location" may be a region name or address.

Moreover, "interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object in which the user U identified by the user ID has a high interest. For example, "interest" may be a search query (keyword) that the user U inputs into a search engine. In the example shown in FIG. 5, one "interest" is shown for each user U, but there may be a plurality of "interests".

For example, in the example shown in FIG. 5, the age of the user U identified by the user ID "U1" is "20s", and the gender is "male". Further, for example, the user U identified by the user ID "U1" indicates that his home is "LC11". Further, for example, the user U identified by the user ID "U1" indicates that the work location is "LC12". Further, for example, the user U identified by the user ID "U1" indicates that he is interested in "sports."

Here, in the example shown in FIG. 5, abstract values such as "U1", "LC11", and "LC12" are used for illustration, but "U1", "LC11", and "LC12" have specific values. It is assumed that information such as character strings and numerical values is stored. Below, abstract values may be illustrated in diagrams related to other information as well.

Note that the user information database 121 is not limited to the above, and may store various information depending on the purpose. For example, the user information database 121 may store various information regarding the terminal device 10 of the user U. In addition, the user information database 121 includes information such as demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. of user U. Information regarding attributes may also be stored. For example, the user information database 121 includes name, family composition, place of birth (locality), occupation, position, income, qualifications, type of residence (single-family house, condominium, etc.), presence or absence of a car, commuting/commuting time, commuting/commuting, etc. Memorizes information such as routes, commuter pass sections (stations, lines, etc.), frequently used stations (other than the stations closest to your home or work), lessons (location, time zone, etc.), hobbies, interests, lifestyle, etc. It's okay.

(History information database 122)
The history information database 122 stores various information related to history information (log data) indicating the actions of the user U. FIG. 6 is a diagram showing an example of the history information database 122. In the example shown in FIG. 6, the history information database 122 has items such as "user ID", "location history", "search history", "browsing history", "purchase history", and "posting history".

“User ID” indicates identification information for identifying user U. Further, “position history” indicates a position history that is a history of the user U's position and movement. Further, “search history” indicates a search history that is a history of search queries input by the user U. In addition, “browsing history” indicates a browsing history that is a history of contents that the user U has viewed. Further, “purchase history” indicates a purchase history that is a history of purchases by user U. Moreover, "posting history" indicates a posting history that is a history of postings by user U. Note that the "posting history" may include questions regarding user U's belongings.

For example, in the example shown in FIG. 6, user U identified by user ID "U1" moves as per "location history #1", searches as per "search history #1", and searches as per "view history #1". This indicates that the content was viewed according to "history #1", a predetermined product, etc. was purchased at a predetermined store etc. according to "purchase history #1", and the content was posted according to "posting history".

Here, in the example shown in FIG. 6, abstracts such as "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" are used. Although the figures are shown using typical values, "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" are It is assumed that information such as specific character strings and numerical values is stored.

Note that the history information database 122 is not limited to the above, and may store various information depending on the purpose. For example, the history information database 122 may store the user U's usage history of a predetermined service. Further, the history information database 122 may store the user U's visit history to a physical store, visit history to a facility, or the like. Further, the history information database 122 may store the payment history of user U's electronic payment.

(Behavior information database 123)
The behavior information database 123 stores various information regarding user U's contact with advertisements and interested behavior. FIG. 7 is a diagram showing an example of the behavior information database 123. In the example shown in FIG. 7, the behavior information database 123 includes items such as "user ID,""adcontact,""interestingbehavior," and "action."

“User ID” indicates identification information for identifying user U. Moreover, "ad contact" indicates whether the user U has come into contact with an advertisement. Here, "ad contact" indicates "○" if the user has come into contact with an ad, and "x" if the user has not come into contact with an ad. Note that the "ad contact" item may be provided for each advertisement (or for each category of advertisement). Moreover, "interesting behavior" indicates whether the user U has taken an interesting behavior. Here, "interesting behavior" indicates "〇" if the user has taken an interested action, and "x" if the user has not taken an interested action. Further, "action" indicates whether the user U has taken an action. Here, "action" indicates "○" if the user has taken an action, and indicates "x" if the user has not taken any action.

For example, in the example shown in FIG. 7, the user U identified by the user ID "U1" has "〇" in "Advertising contact", "Interesting behavior" and "Action", and has interest from advertising contact. Show that you have finally taken action.

Note that the behavior information database 123 is not limited to the above, and may store various information depending on the purpose. For example, the behavior information database 123 may store identification information for identifying individual advertisements, information regarding category names indicating categories of advertisements, and the like. Further, the behavior information database 123 may store information regarding behaviors that are determined to be interesting behaviors. Further, the behavior information database 123 may store information regarding the user U's degree of interest in advertisements.

(Number of people information database 124)
The number of people information database 124 stores various information regarding the number of users U who have interacted with an advertisement and taken an action, which is estimated from the number of users U who have taken an action of interest. FIG. 8 is a diagram showing an example of the number of people information database 124. In the example shown in FIG. 8, the number of people information database 124 includes items such as "advertisement ID", "number of people who take an interest action", "first ratio", "number of people exposed to advertisement", "second ratio", and "number of people who take action". have

"Advertisement ID" indicates identification information for identifying an advertisement. Note that, in reality, the advertisement ID may be the category of the advertisement, the corporate brand of the company that provided the advertisement, the product brand of the product published in the advertisement, or the like. Further, if there is no need to specify the advertisement, the item "Advertisement ID" may be omitted.

Further, the "number of people who have taken an interested action" indicates the number of people who have taken an interested action among an unspecified large group of people. Furthermore, the "first ratio" indicates the percentage of people who took an interested action after coming into contact with the advertisement. Note that the first ratio is calculated based on the number of people who have come into contact with an advertisement and the number of people who have taken an interested action among a predetermined group of people (such as a panel of 1000 people) from which individual users can be identified. Moreover, the "number of people who came into contact with the advertisement" is the number of people estimated based on the number of people who have taken an interest and the first ratio, and indicates the number of people who have come into contact with the advertisement among an unspecified number of people.

Furthermore, the "second ratio" indicates the percentage of people who took the final action based on their interested behavior. Note that the second ratio is calculated based on the number of people who have taken an interested action and the number of people who have taken an action among a predetermined group of people (such as a panel of 1000 people) from which individual users can be identified. Further, the "number of people who took action" is the number of people estimated based on the number of people who took an interested action and the second ratio, and indicates the number of people who took an action among an unspecified number of people.

For example, in the example shown in FIG. 8, regarding the advertisement identified by the advertisement ID "advertisement #A," the number of people who took an interested action is "interesting action #A," and it is estimated that the number of people who took an interested action was "interesting action #A." The number of people is the number of people who came into contact with advertisements based on "interesting behavior #A" and "first ratio #A," and the number of people who are estimated to have taken the final action is "interesting behavior #A." ” and “second ratio #A” to indicate that the number of people taking action is “action #A”.

Here, in the example shown in FIG. ", "Advertisement #A," "Interesting Behavior #A," "First Ratio #A," "Advertisement Contact #A," "Second Ratio #A," and " Action #A" stores information such as specific character strings and numerical values.

Note that the number of people information database 124 is not limited to the above, and may store various information depending on the purpose. For example, the number of people information database 124 may store information regarding actions that are determined to be interesting actions. In addition, the number of people information database 124 includes information on a third ratio indicating the percentage of people who did not take action due to interest, the number of people who took action after contacting the advertisement, and the number of people who did not take action after contact with the advertisement. You may memorize it. Additionally, the number of people information database 124 may store information regarding a fourth ratio indicating the percentage of people who took an action based on their interest without coming into contact with an advertisement, and the number of people who took an action without coming into contact with an advertisement. . In addition, the number of people information database 124 includes information regarding a fifth ratio indicating the percentage of people who took an interested action without contacting an advertisement but did not take an action based on the interested action, and the number of people who did not contact an advertisement and took no action. etc. may be stored.

(Control unit 130)
Returning to FIG. 4, the explanation will be continued. The control unit 130 is a controller, and uses, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array) to control the information providing apparatus 100. This is achieved by executing various programs (corresponding to an example of an information processing program) stored in an internal storage device using a storage area such as a RAM as a work area. In the example shown in FIG. 4, the control unit 130 includes an acquisition unit 131, a measurement unit 132, a calculation unit 133, an estimation unit 134, and a provision unit 135.

(Acquisition unit 131)
The acquisition unit 131 acquires a search query input by the user U. For example, when the user U inputs a search query into a search engine or the like and performs a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110.

The acquisition unit 131 also acquires user information regarding the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information indicating the user U (user ID, etc.), location information of the user U, attribute information of the user U, etc. from the terminal device 10 of the user U. Further, the acquisition unit 131 may acquire identification information indicating the user U, attribute information of the user U, etc. at the time of user registration of the user U. The acquisition unit 131 then registers the user information in the user information database 121 of the storage unit 120.

Further, the acquisition unit 131 acquires various types of history information (log data) indicating the behavior of the user U via the communication unit 110. For example, the acquisition unit 131 acquires various types of history information indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. The acquisition unit 131 then registers various types of history information in the history information database 122 of the storage unit 120.

That is, the acquisition unit 131 acquires information regarding the user U's daily behavior history. The acquisition unit 131 also acquires information regarding advertisements. For example, the acquisition unit 131 acquires, as information regarding the advertisement, information regarding the date and time and period in which the advertisement was presented, and location information regarding the place where the advertisement was presented.

Furthermore, the acquisition unit 131 acquires environmental information regarding the situation of the user U when the user U takes a predetermined action. For example, when the user U takes a predetermined action, the acquisition unit 131 obtains information regarding the date and time when the user U took the predetermined action as environmental information regarding the situation of the user U. Further, when the user U takes a predetermined action, the acquisition unit 131 obtains position information regarding the position where the user U took the predetermined action as environmental information regarding the situation of the user U.

Further, the acquisition unit 131 may acquire, as the environmental information, detection information indicating the result of the detection of the surroundings by the terminal device 10 of the user U when the user U takes a predetermined action. For example, the acquisition unit 131 acquires sensor information indicating detection results of various sensors installed in the terminal device 10 of the user U as the detection information. Alternatively, the acquisition unit 131 may acquire, as the environmental information, device signal detection information indicating that the terminal device 10 of the user U has detected a signal emitted by a device presenting an advertisement.

(Measurement unit 132)
The measurement unit 132 measures the number of people who came into contact with the advertisement and the number of people who took a prescribed action after coming into contact with the advertisement, out of a group of a predetermined number of people (a panel of 1000 people, etc.) from which individual users can be identified. do. The measurement unit 132 also calculates the number of people who took a predetermined action after coming into contact with the advertisement among the predetermined group of people mentioned above, and the number of people who took the final action aimed at by the advertisement after taking the predetermined action. Measure the number of people.

Further, the measurement unit 132 measures the number of people who took a predetermined action after coming into contact with the advertisement and the number of people who took no action after taking the predetermined action, among the group of the predetermined number of people described above. In addition, the measurement unit 132 measures the number of people who took a predetermined action without contacting the advertisement and the number of people who took an action after taking the predetermined action out of a group of predetermined number of people. In addition, the measuring unit 132 measures the number of people who took a predetermined action without contacting the advertisement and the number of people who took no action after taking the predetermined action, out of a group of predetermined number of people.

Note that the measuring unit 132 may measure the number of new users and the number of existing users among the group of the predetermined number of users. At this time, the measuring unit 132 calculates the number of people who contacted the advertisement and the number of people who took a prescribed action after coming into contact with the advertisement for each of new users and existing users among the group of predetermined number of people. and to measure. The measuring unit 132 also calculates the number of new users and existing users among a group of predetermined people, the number of people who took a predetermined action after coming into contact with the advertisement, and the number of people who took a predetermined action. Afterwards, the number of people who took the final action targeted by the advertisement is measured.

(Calculation unit 133)
The calculation unit 133 calculates the number based on the number of people who contacted the advertisement and the number of people who took a predetermined action after coming into contact with the advertisement among a group of predetermined number of people (such as a panel of 1000 people) from which individual users can be identified. Then, a first ratio indicating the percentage of people who took a predetermined action after coming into contact with the advertisement is calculated. Note that, when a new user and an existing user are distinguished, the calculation unit 133 calculates the first ratio for each of the new user and the existing user.

In addition, the calculation unit 133 calculates the number of people who took a predetermined action after coming into contact with the advertisement among the group of predetermined number of people mentioned above, and the number of people who took the final action aimed at by the advertisement after taking the predetermined action. A second ratio indicating the percentage of people who took an action from a predetermined action is calculated based on the number of people. In addition, when a new user and an existing user are distinguished, the calculation unit 133 calculates the second ratio for each of the new user and the existing user.

Further, the calculation unit 133 calculates a predetermined number of people based on the number of people who took a predetermined action after coming into contact with the advertisement and the number of people who did not take an action after taking the predetermined action, among the group of the predetermined number of people described above. A third ratio is calculated, which indicates the percentage of people who took no action based on the behavior of the user. In addition, when a new user and an existing user are distinguished, the calculation unit 133 calculates the third ratio for each of the new user and the existing user.

In addition, the calculation unit 133 calculates a predetermined number of people based on the number of people who took a predetermined action without contacting the advertisement and the number of people who took an action after taking the predetermined action, among the group of the predetermined number of people described above. A fourth ratio is calculated, which indicates the percentage of people who took an action based on the behavior of the user. Note that, when a new user and an existing user are distinguished, the calculation unit 133 calculates a fourth ratio for each of the new user and the existing user.

In addition, the calculation unit 133 calculates, based on the number of people who took a predetermined action without contacting the advertisement and the number of people who did not take an action after taking the predetermined action, among the group of the predetermined number of people described above. A fifth ratio indicating the percentage of people who did not take any action from the predetermined action is calculated. Note that, when a new user and an existing user are distinguished, the calculation unit 133 calculates a fifth ratio for each of the new user and the existing user.

(Estimation unit 134)
The estimating unit 134 estimates the contact between the user U and the advertisement, the user's interest in the advertisement and its degree, the number of people who have come into contact with the advertisement and taken actions related to the advertisement, and the like. In this embodiment, the estimating section includes an advertisement contact estimating section 134a, an interest behavior estimating section 134b, a degree estimating section 134c, and a number of people estimating section 134d.

(Advertisement contact estimation unit 134a)
The advertisement contact estimating unit 134a estimates the contact with advertisements from the daily behavior history of the user U. For example, the advertisement contact estimating unit 134a estimates the date and time of contact with the advertisement based on the date and time included in the daily action history of the user U and the date and time when the advertisement was presented. Note that the date and time when the advertisement was presented may be the period during which the advertisement was presented. Alternatively, the advertisement contact estimating unit 134a estimates the position of contact with the advertisement based on the position information included in the daily action history of the user U and the position information of the advertisement.

(Interesting behavior estimation unit 134b)
When the contact with the advertisement is estimated, the interested behavior estimating unit 134b estimates that the predetermined behavior is an action (interesting behavior) associated with the contact with the advertisement from the environmental information regarding the situation of the user U. At this time, it is estimated that the user U is interested in the advertisement by estimating that the predetermined behavior is an action associated with contact with the advertisement by the interested behavior estimation unit 134b regarding the user U's situation. That is, the interested behavior estimation unit 134b estimates that the user U is interested in the advertisement and has taken an action associated with contact with the advertisement.

Note that the predetermined action is different from the final action (purchase, visit, etc.) that is the purpose of the advertisement. For example, the predetermined action is an intermediate action (intermediate action) performed between contact with an advertisement and an action. Here, as a predetermined action, a case will be explained in which a search is performed using a search engine or the like using a keyword related to the content of the advertisement as a search query. The search engine may be an in-site search engine for electronic commerce used in EC sites, online malls, and the like. Further, the predetermined action is not limited to one action, but may be a plurality of actions. Further, the predetermined action is not limited to a single action, but may be a series of continuous actions.

For example, if the date and time of contact with the advertisement and the date and time of taking the predetermined action satisfy a predetermined condition, the interested behavior estimation unit 134b estimates that the predetermined action is an action associated with contact with the advertisement. In addition, when the position where the user came into contact with the advertisement and the position where the user took the predetermined action satisfy a predetermined condition, the interested action estimator 134b estimates that the predetermined action is an action associated with contact with the advertisement.

In addition, when detection information indicating the result of the user U's terminal device 10 detecting the surroundings when the user U takes a predetermined action is acquired as the environmental information, the interested behavior estimation unit 134b detects the detection Based on the information, it may be estimated that the predetermined behavior is a behavior associated with contact with an advertisement.

In addition, when device signal detection information indicating that the terminal device 10 of the user U has detected a signal emitted by a device presenting an advertisement is acquired as the environment information, the interested behavior estimation unit 134b detects the device signal detection information. Based on this, it may be estimated that the predetermined behavior is a behavior associated with contact with an advertisement.

(degree estimation unit 134c)
The degree estimating unit 134c estimates the user's degree of interest in the advertisement from the timing of a predetermined action when contact with the advertisement is estimated. For example, the degree estimating unit 134c estimates the user's degree of interest in the advertisement from the number of predetermined actions after coming into contact with the advertisement. Alternatively, the degree estimating unit 134c estimates the user's degree of interest in the advertisement from the interval from the time of contact with the advertisement until the user takes a predetermined action. Furthermore, when contact with multiple advertisements regarding the same target is estimated, the degree estimating unit 134c may estimate the user's degree of interest in the advertisement for each advertisement based on the timing of a predetermined action. .

(Number of people estimation unit 134d)
The number of people estimating unit 134d estimates the number of unspecified people based on the number of people who took a predetermined action among the unspecified number of people and a first ratio indicating the proportion of people who took the predetermined action after coming into contact with the advertisement. Estimate the number of people in a population who have been exposed to an advertisement.

In addition, the number of people estimating unit 134d calculates the number of people who took a predetermined action among the unspecified number of people and a second ratio indicating the ratio of the number of people who took an action from the predetermined action. Estimate the number of people who took action.

In addition, the number of people estimating unit 134d calculates the number of people who took a predetermined action out of a large number of unspecified groups, a second ratio indicating the proportion of people who took an action from the predetermined action, and a second ratio indicating the proportion of people who took an action from the predetermined action, and a second ratio indicating the proportion of people who took an action from the predetermined action. Based on the third ratio indicating the proportion of people who took action, the number of people who took an action after coming into contact with the advertisement and the number of people who did not take an action after coming into contact with the advertisement are estimated among the unspecified large number of people.

Further, the number of people estimating unit 134d calculates the number of people who have taken a predetermined action among the unspecified large group and a fourth ratio indicating the proportion of people who have taken an action from the predetermined action. Estimate the number of people who took an action without contacting the ad.

In addition, the number of people estimating unit 134d calculates the number of people who took a predetermined action out of the unspecified number of people and a fifth ratio indicating the proportion of people who took no action from the predetermined action. Estimate the number of people in the group who did not interact with the advertisement or take any action.

In this way, the number of people estimating unit 134d calculates the number of people who took an action after coming into contact with an advertisement, the number of people who did not take an action after coming into contact with an advertisement, and the number of people who took an action without coming into contact with an advertisement among a large and unspecified group. Estimate the number of people who took the ad and the number of people who did not interact with the ad or take any action.

In addition, the number of people estimating unit 134d calculates the number of new users and existing users who have taken a predetermined action based on the number of people who have taken a predetermined action and the number of people who have taken a predetermined action from the contact with the advertisement. The number of people who contacted the advertisement is estimated based on the first ratio indicating the percentage of people who received the advertisement.

In addition, the number of people estimating unit 134d calculates the number of people who have taken a predetermined action and the number of people who have taken an action based on a predetermined action for each of new users and existing users among the unspecified large group. Based on the second ratio indicating the proportion, the number of people who took the action among the unspecified large group is estimated.

(Providing Department)
The providing unit 135 sends information to the terminal device 10 and external search device 200 of each user U via the communication unit 110 to the estimating unit 134 (ad contact estimating unit 134a, interest behavior estimating unit 134b, degree estimating unit). 134c, the number of people estimating unit 134d) provides estimation information that is the result of estimation. For example, the information providing device 100 sends, via the communication unit 110, the terminal device 10 or external search device 200 of each user U, as estimated information, that the search behavior of the user U is associated with a search associated with contact with an advertisement. Provide information that identifies the behavior. That is, the information providing device 100 informs each user U's terminal device 10 or external search device 200 via the communication unit 110 that the user U's search behavior is a search behavior associated with contact with an advertisement. Notify.

In addition, the providing unit 135 provides API (Application Programming Interface) services for various applications (hereinafter referred to as applications) to the terminal device 10 and external search device 200 of each user U via the communication unit 110. Provide various data. Further, the providing unit 135 may provide some kind of web service online to the terminal device 10 of each user U via the communication unit 110.

[5. Processing procedure]
Next, a processing procedure by the information providing apparatus 100 according to the embodiment will be described using FIG. 9. FIG. 9 is a flowchart showing the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the information providing device 100.

The acquisition unit 131 of the information providing device 100 obtains, via the communication unit 110, information regarding the daily behavior history of users U who belong to a group of a predetermined number of people (such as a panel of 1000 people) from which individual users can be identified. Acquire (step S101). For example, the acquisition unit 131 acquires identification information indicating the user U (user ID, etc.), as well as daily location information and various historical information of the user U.

Subsequently, the advertisement contact estimating unit 134a of the estimating unit 134 of the information providing device 100 estimates the contact with the advertisement from the daily action history of the user U (step S102). For example, the estimating unit 134 estimates that the user U has come into contact with the advertisement if the user U is near the place where the advertisement is presented on the date and time (or within the period) when the advertisement is presented.

Subsequently, the acquisition unit 131 of the information providing device 100 acquires information regarding the user U's interested behavior and environmental information regarding the situation of the user U when the user U takes the interested behavior. For example, when the user U inputs a search query into a search engine or the like and performs a keyword search, the acquisition unit 131 receives information from the user U's terminal device 10 or the external search device 200 via the communication unit 110. The search query input by user U and the location information at that time are acquired (step S103).

Subsequently, the interested behavior estimating unit 134b of the estimating unit 134 of the information providing device 100 determines whether the interested behavior taken by the user U is related to contact with the advertisement, based on the environmental information regarding the situation of the user U when the user U takes the interested action. It is estimated that this is an interesting behavior (step S104). For example, if the user U inputs a search query and performs a search near the place where the advertisement was presented on the date and time (or within the period) when the advertisement was presented, the interest behavior estimation unit 134b determines whether the search is assumed to be the behavior of interest associated with contact with advertisements.

Subsequently, when contact with the advertisement is estimated, the degree estimation unit 134c of the estimation unit 134 of the information providing device 100 estimates the user's degree of interest in the advertisement from the timing of the interested behavior (step S105). . For example, the degree estimating unit 134c estimates the user's degree of interest in the advertisement based on the number of times the user takes an interested action after coming into contact with the advertisement, or the interval from the time the user comes into contact with the advertisement until the user takes an interested action.

Subsequently, the measuring unit 132 of the information providing device 100 measures the number of people who came into contact with the advertisement and the number of people who took an interested action after coming into contact with the advertisement among the group of predetermined number of people described above (step S106). Here, an example will be described in which the user U inputs a search query into a search engine or the like to perform a keyword search as an interested behavior.

Next, the calculation unit 133 of the information providing device 100 calculates a ratio indicating the proportion of each person in a group of predetermined people based on the measured number of people (step S107). In addition, when a new user and an existing user are distinguished, the calculation unit 133 calculates a ratio for each of the new user and the existing user. For example, the calculation unit 133 determines whether a person has taken an interested action after coming into contact with the advertisement, based on the number of people who have come into contact with the advertisement and the number of people who have taken an interested action after coming into contact with the advertisement, among the predetermined group of people mentioned above. A first ratio indicating the proportion of people is calculated. In addition, the calculation unit 133 calculates the number of people who took an action of interest after coming into contact with the advertisement, and the number of people who took the final action aimed at by the advertisement after taking an action of interest, among the above-mentioned group of predetermined number of people. A second ratio is calculated based on the percentage of people who took an action based on their interest.

Next, the number of people estimating unit 134d of the estimating unit 134 of the information providing device 100 selects advertisements from among the unspecified large group based on the calculated ratio and the number of people who took an interested action among the unspecified large group. The number of people who contacted the user and the number of people who took an action are estimated (step S108). For example, the number of people estimating unit 134d calculates the number of people who have taken an interested action out of the unspecified number of people and a first ratio indicating the proportion of people who have taken an interested action from contact with an advertisement. Estimate the number of people in a population who have been exposed to an advertisement. In addition, the number of people estimating unit 134d calculates the number of people who took an action out of the unspecified number of people based on the number of people who took an action of interest among the unspecified number of people and a second ratio indicating the ratio of the number of people who took an action based on the action of interest. Estimate the number of people who took the test.

Next, the providing unit 135 of the information providing device 100 sends the information to the terminal device 10 or external search device 200 of each user U via the communication unit 110 to the estimating unit 134 (ad contact estimating unit 134a, interest Estimation information based on the estimation results by the behavior estimating unit 134b, the degree estimating unit 134c, and the number of people estimating unit 134d is provided (step S109). Note that the estimation information may be the estimation result itself, or may be various information generated based on the estimation result.

[6. Modified example]
The terminal device 10 and the information providing device 100 described above may be implemented in various different forms other than the above embodiments. Therefore, a modification of the embodiment will be described below.

[6-1. Single operation of terminal device]
In the embodiment described above, a part or all of the processing executed by the information providing device 100 and the external search device 200 may actually be executed by the terminal device 10. For example, the process may be completed stand-alone (by the terminal device 10 alone). In this case, it is assumed that the terminal device 10 has the functions of the information providing device 100 and the external search device 200 in the above embodiment. Furthermore, from the perspective of the user U, it appears that the terminal device 10 is also executing the processing of the information providing device 100 and the external search device 200. That is, from another point of view, the terminal device 10 can be said to include the information providing device 100 and the external search device 200.

[6-2. Behaviors other than search behavior]
Further, in the embodiment described above, a case has been described in which the user U who has come into contact with an advertisement takes a search action, but the search action is only an example of the user's action accompanying contact with an advertisement. In other words, the action is not limited to search action, but may be any action that a user can take upon contact with an advertisement.

For example, user U, who is presumed to have come into contact with an advertisement, may take a picture of the advertisement and post it on SNS, video sites, etc. along with comments, or may contact other users regarding the product featured in the advertisement. Asking for opinions can also be said to be an action that accompanies exposure to advertisements. Posting to SNS, video sites, etc., and contact with other users can be estimated based on various historical information.

In addition, user U, who is presumed to have come into contact with an advertisement outdoors, may enter a physical store that handles the product in order to actually examine the product featured in the advertisement, or Approaching the area around the advertised facility (going up close to check it out) can also be said to be an action associated with exposure to the advertisement. Entry into a physical store or approach to the vicinity of a facility can be estimated based on location information.

In addition, user U, who is presumed to have come into contact with advertisements such as in-store broadcasts and flyers, is not limited to moving from outdoors to a physical store, but also to the store to actually examine the products featured in the advertisement. Moving to the shelf or floor where the product is located within the store and actually purchasing the product can also be considered actions associated with contact with the advertisement. Movement within a store can be estimated using technologies such as beacon positioning and pedestrian autonomous navigation (PDR).

[6-3. Estimation of ad exposure using information other than location information]
Further, in the above embodiment, the information providing device 100 estimates that the user U has contacted an advertisement based on the location information, but in reality, the information providing device 100 does not use the location information and uses other information. Based on this, it may be estimated that the user U has contacted the advertisement.

For example, the information providing device 100 acquires audio information in which surrounding environmental sounds are recorded from the terminal device 10 of the user U, and if the audio information includes the audio of an audio advertisement or a video advertisement, the information providing device 100 It may be assumed that the person has come into contact with the advertisement.

Further, the information providing device 100 acquires surrounding image information using the shooting function from the terminal device 10 of the user U, and if the image information includes an advertisement, the information providing device 100 determines that the user U has come into contact with the advertisement. It may be estimated.

Further, the information providing device 100 acquires sensor information (detection information) indicating the detection result of the sensor from the terminal device 10 of the user U, and if the sensor information indicates that an advertisement has been detected, or the sensor information indicates a numerical value corresponding to a detection result in the surrounding environment of the advertisement, it may be estimated that the user U has come into contact with the advertisement. For example, when an advertisement repeats a special lighting pattern (blinking, changing color, etc.), the information providing device 100 determines that if the sensor information from the terminal device 10 indicates this special lighting pattern, the user U comes into contact with the advertisement. It can be assumed that it did. Further, when the information providing device 100 acquires device signal detection information indicating that a signal from a device presenting an advertisement has been detected from the terminal device 10 of the user U, it is estimated that the user U has contacted the advertisement. You may.

[7. effect〕
As described above, the information providing device 100 according to the present application includes an advertisement contact estimation unit 134a that estimates contact with an advertisement from the action history of the user U, and a An acquisition unit 131 that acquires environmental information regarding the situation of the user U, and an interest behavior estimation that estimates from the environmental information that a predetermined behavior is an action associated with contact with the advertisement when contact with the advertisement is estimated. 134b.

For example, the predetermined action is a search using a keyword related to the content of the advertisement as a search query.

Further, the advertisement contact estimating unit 134a estimates the date and time of contact with the advertisement from the date and time included in the behavior history and the date and time when the advertisement was presented. The acquisition unit 131 also acquires information regarding the date and time when the user U took a predetermined action as the environmental information. Then, when the date and time of contact with the advertisement and the date and time of taking the predetermined action satisfy a predetermined condition, the interested behavior estimation unit 134b estimates that the predetermined action is an action associated with contact with the advertisement.

Further, the advertisement contact estimating unit 134a estimates the position of contact with the advertisement based on the position information included in the action history and the position information of the advertisement. The acquisition unit 131 also acquires, as environmental information, position information regarding the position where the user U took a predetermined action. Then, if the position where the user came into contact with the advertisement and the position where the user took the predetermined action satisfy a predetermined condition, the interested action estimation unit 134b estimates that the predetermined action is an action associated with contact with the advertisement.

The acquisition unit 131 also acquires, as the environmental information, detection information indicating the result of the surroundings detected by the terminal device 10 of the user U when the user U takes a predetermined action. Then, the interested behavior estimating unit 134b estimates that the predetermined behavior is a behavior associated with contact with an advertisement, based on the detected information.

The acquisition unit 131 also acquires, as environmental information, device signal detection information indicating that the terminal device 10 of the user U has detected a signal emitted by a device presenting an advertisement. Then, the interested behavior estimating unit 134b estimates that the predetermined behavior is a behavior associated with contact with an advertisement, based on the device signal detection information.

Further, the information providing device 100 according to the present application further includes a degree estimating unit 134c that estimates the degree of interest of the user U in the advertisement from the timing of a predetermined action when contact with the advertisement is estimated. .

Furthermore, the degree estimating unit 134c estimates the degree of interest of the user U in the advertisement from the number of predetermined actions after coming into contact with the advertisement.

Further, the degree estimating unit 134c estimates the degree of interest of the user U in the advertisement from the interval from the time of contact with the advertisement to the time of taking a predetermined action.

Furthermore, when contact with a plurality of advertisements related to the same target is estimated, the degree estimating unit 134c estimates the degree of interest of the user U in the advertisement for each advertisement from the timing of a predetermined action.

By using any one or a combination of the above-described processes, the information providing device according to the present application can estimate whether a user who has come into contact with an advertisement is interested in the advertisement. Furthermore, the effectiveness of advertisements can be measured without depending on the click through rate (CTR) or conversion rate (CVR) of advertisements.

[8. Hardware configuration]
Further, the terminal device 10 and the information providing device 100 according to the embodiments described above are realized, for example, by a computer 1000 having a configuration as shown in FIG. The information providing apparatus 100 will be described below as an example. FIG. 10 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are connected to a bus. 1090.

The arithmetic unit 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and performs various processes. The arithmetic device 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the calculation device 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and includes a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid Disk Drive). This is realized using flash memory, etc. The secondary storage device 1050 may be a built-in storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

The output I/F 1060 is an interface for transmitting information to be output to the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface) and HDMI (registered trademark) (High Definition Multimedia Interface). Further, the input I/F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, button, scanner, etc., and is realized by, for example, a USB or the like.

Further, the output I/F 1060 and the input I/F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, output device 1010 and input device 1020 may be wireless devices.

Moreover, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I/F 1060 and the input I/F 1070 may also be integrated as an input/output I/F.

Note that the input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

Network I/F 1080 receives data from other devices via network N and sends it to computing device 1030, and also sends data generated by computing device 1030 to other devices via network N.

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070. For example, the arithmetic device 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040, and executes the loaded program.

For example, when the computer 1000 functions as the information providing device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 by executing a program loaded onto the primary storage device 1040. Further, the arithmetic device 1030 of the computer 1000 may load a program obtained from another device via the network I/F 1080 onto the primary storage device 1040, and execute the loaded program. Furthermore, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I/F 1080, and may call and use program functions, data, etc. from other programs of other devices.

[9. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those that are in a so-called equivalent range. Furthermore, the aforementioned components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the constituent elements can be made without departing from the gist of the embodiments described above.

Further, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed manually. All or part of this can also be performed automatically using known methods. In addition, information including the processing procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed arbitrarily, unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

Furthermore, each component of each device shown in the drawings is functionally conceptual, and does not necessarily need to be physically configured as shown in the drawings. In other words, the specific form of distributing and integrating each device is not limited to what is shown in the diagram, and all or part of the devices can be functionally or physically distributed or integrated in arbitrary units depending on various loads and usage conditions. Can be integrated and configured.

For example, the information providing apparatus 100 described above may be realized by a plurality of server computers, and depending on the function, it may be realized by calling an external platform etc. using an API (Application Programming Interface), network computing, etc. can be changed flexibly.

Furthermore, the above-described embodiments and modifications can be combined as appropriate within a range that does not conflict with the processing contents.

Further, the above-mentioned "section, module, unit" can be read as "means", "circuit", etc. For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

1 Information processing system 10 Terminal device 100 Information providing device 110 Communication unit 120 Storage unit 121 User information database 122 History information database 123 Behavior information database 124 Number of people information database 130 Control unit 131 Acquisition unit 132 Measurement unit 133 Calculation unit 134 Estimation unit 134a Advertisement contact estimating unit 134b Interest behavior estimating unit 134c Degree estimating unit 134d Number of people estimating unit 135 Providing unit

Claims (12)

an advertisement contact estimation unit that estimates contact with advertisements using information other than date and time and location among the user's action history based on various log data ;
When the user, after coming into contact with the advertisement, takes a predetermined action other than viewing the advertisement or a final action that corresponds to the conversion targeted by the advertisement, and is not a search action. an acquisition unit that acquires environmental information regarding the user's situation;
an interested behavior estimation unit that estimates, from the environmental information, that the predetermined behavior is an action associated with contact with the advertisement, when contact with the advertisement is estimated;
An information processing device comprising: The advertisement contact estimating unit is configured to detect when the audio information recorded by the user's terminal device of surrounding environmental sounds includes the audio of an audio advertisement or a video advertisement, or when the user's terminal device uses the shooting function of the user's terminal device. 2. The information processing apparatus according to claim 1, wherein if the image information of the surrounding area includes an advertisement, it is presumed that the user has come into contact with the advertisement . The acquisition unit may detect when the user who is estimated to have come into contact with the advertisement takes a picture of the advertisement and posts it on an SNS or video site with a comment, or contacts other users as the predetermined action. 3. The information processing device according to claim 1, wherein the environmental information is acquired when an opinion is requested regarding the product advertised in the advertisement . The acquisition unit is configured to acquire information such as when the user who is estimated to have come into contact with the advertisement enters a physical store that sells the product advertised in the advertisement as the predetermined action; Claims 1 to 3 characterized in that the environmental information is acquired when approaching the vicinity of a facility where the advertised product is placed, or when moving to a product shelf or floor where the advertised product is placed in the store. The information processing device according to any one of the above. The acquisition unit acquires, as the environmental information, detection information indicating a result of sensing the surroundings by the user's terminal device when the user takes the predetermined action;
According to any one of claims 1 to 4, the interested behavior estimation unit estimates, based on the detected information, that the predetermined behavior is a behavior associated with contact with the advertisement. information processing equipment. The acquisition unit acquires, as the environment information, device signal detection information indicating that the user's terminal device has detected a signal emitted by a device presenting the advertisement;
Any one of claims 1 to 5, wherein the interested behavior estimation unit estimates, based on the device signal detection information, that the predetermined behavior is a behavior associated with contact with the advertisement. The information processing device described in . a degree estimation unit that estimates the degree of interest of the user in the advertisement from the timing of the predetermined action when contact with the advertisement is estimated;
The information processing device according to any one of claims 1 to 6, further comprising the following. The information processing device according to claim 7, wherein the degree estimating unit estimates the degree of interest of the user in the advertisement based on the number of times the predetermined behavior occurs after contacting the advertisement. 9. The degree estimation unit estimates the degree of interest of the user in the advertisement based on the interval from the time of contact with the advertisement to the time of taking the predetermined action. Information processing device. The degree estimating unit estimates the user's degree of interest in the advertisement for each advertisement from the timing of the predetermined action when contact with a plurality of advertisements regarding the same target is estimated. The information processing device according to any one of claims 7 to 9. An information processing method executed by an information processing device, the method comprising:
an advertisement contact estimation step of estimating contact with an advertisement using information other than date and time and location among the user's action history based on various log data ;
When the user, after coming into contact with the advertisement, takes a predetermined action other than viewing the advertisement or a final action that corresponds to the conversion targeted by the advertisement, and is not a search action. an acquisition step of acquiring environmental information regarding the user's situation;
an interested behavior estimation step of estimating, from the environmental information, that the predetermined behavior is an action associated with contact with the advertisement, when contact with the advertisement is estimated;
An information processing method characterized by comprising: an advertisement contact estimation procedure for estimating contact with an advertisement using information other than date and time and location among the user's action history based on various log data ;
When the user, after coming into contact with the advertisement, takes a predetermined action other than viewing the advertisement or a final action that corresponds to the conversion targeted by the advertisement, and is not a search action. an acquisition procedure for acquiring environmental information regarding the user's situation;
an interested behavior estimation procedure of estimating, from the environmental information, that the predetermined behavior is an action associated with contact with the advertisement, when contact with the advertisement is estimated;
An information processing program that allows a computer to execute.

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