Advertisement delivery method and advertisement delivery platform

Abstract

To provide an advertisement delivery method for improving accuracy of targeting of advertisement delivery to an intended user layer.SOLUTION: A method for delivering advertisements to be displayed on a website using an advertisement delivery platform includes the steps of: acquiring a user identifier, geographic information, and date and time included in an advertisement display request from a website visited by a user, and a user identifier, geographic information, and date and time provided from an associated service of an advertisement delivery platform used by the user (S10); storing the data in chronological order for every user (S20); analyzing the stored data and acquiring movement information and stay information of each user from a relation between a stay location of each user and a date and time (S100); and targeting users to whom advertisements are to be delivered based on the movement information and the stay information (S120). Thereby, the method can improve accuracy of targeting advertisement delivery to an intended user layer.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a method for delivering an advertisement to be displayed on a website to a user by an advertisement delivery platform, and an advertisement delivery platform.

Background Art

[0002] In recent years, for advertisements displayed on websites, some are transacted through RTB (Real-Time Bidding) using an SSP (Supply-Side Platform) and a DSP (Demand-Side Platform) for the advertisement space on the website, and as a result, are delivered from an advertiser who won the bid for the advertisement space via the DSP (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, even when an advertisement is displayed by winning an advertisement space through RTB as described above, if the advertisement is not displayed to the user group targeted by the advertisement, it is difficult to actually lead to the profit of the advertiser. For example, when trying to display advertisements for hotels and tourist destinations to foreign visitors coming to Japan for tourism, if targeting is performed based on the language of the browser used by the user, etc., it often ends up being displayed to foreign residents in Japan who are staying long-term, and in this case, the advertising cost is wasted. The present invention has been made in view of the above problems, and an object thereof is to improve the accuracy of targeting advertisement delivery to an intended user group.

Means for Solving the Problems

[0005] (Aspects of the Invention) The following aspects of the invention illustrate the configuration of the present invention and are described separately for each item in order to facilitate the understanding of various configurations of the present invention. Each item does not limit the technical scope of the present invention. Therefore, even if some of the components of each item are replaced, deleted, or other components are added while taking into consideration the best mode for carrying out the invention, they may be included in the technical scope of the present invention.

[0006] (1) A method for delivering an advertisement to be displayed on a website to a user by an advertisement delivery platform, which includes obtaining a user identifier, geographical information, and date and time included in an advertisement display request from a website visited by the user, and a user identifier, geographical information, and date and time provided from a cooperation service of the advertisement delivery platform used by the user, storing them in chronological order for each user, analyzing the stored data, grasping the movement information and stay information of each user from the relationship between the stay location and date and time of each user, and targeting a user to whom the advertisement is to be delivered based on the movement information and the stay information.

[0007] The advertisement delivery method described in this item is executed by an advertisement delivery platform, which collects geographical information indicating the area where the user is staying and performs advertisement delivery targeting based on it. Specifically, a user identifier, geographical information, and date and time included therein are obtained from an advertisement display request transmitted via an SSP or the like from a website visited by the user. Further, a user identifier, geographical information, and date and time are also obtained from information provided from a cooperation service used by the user. Then, the obtained data is stored in chronological order for each user specified by the user identifier. The acquisition and storage of these data shall be performed continuously. Here, the cooperation service refers to a website, application, information providing service, etc. that has a cooperation relationship with the advertisement delivery platform in use and the company operating it.

[0008] Subsequently, the data obtained and saved as described above is analyzed for each user, and based on the relationship between the staying locations grasped from each user's geographical information and the date and time at that time, the movement information and staying information of each user are grasped. That is, if the relationship between the staying location and the date and time is known for each user, staying information such as how long the user stayed in a certain area and movement information such as the user moved to another area at a certain point in time can be grasped. And from the grasped movement information and staying information, the purpose of the user staying in a certain area, the purpose of moving from one area to another area, etc. are inferred. Therefore, based on these information, the users to whom advertisements are to be delivered are targeted. As a result, the accuracy of targeting advertisement delivery to the intended user group is improved. For this reason, advertisements are accurately delivered to the intended user group, and an improvement in the click-through rate of the advertisements displayed on the website, a decrease in the cost per click, and the exclusion of ad fraud are expected.

[0009] (2) In the above item (1), an advertisement delivery method that targets users during travel and delivers advertisements to users during travel based on the movement information and the staying information. The advertisement delivery method described in this item targets users during travel and delivers advertisements to users during travel based on the movement information and staying information of each user grasped by analyzing the saved data as described in the above item (1). That is, if it is known how long the user stayed in each area, that the user moved from one area to another area, the user's movement frequency, etc., it can be determined whether the user is traveling, and users who are not traveling are excluded from the targeting candidates. As a result, advertisements for travelers are accurately displayed to users during travel. For example, when the travel destination is Japan, long-term staying foreigners in Japan are excluded, and advertisements for hotels, tourist attractions, etc. are displayed for foreign visitors coming to Japan for tourism, which contributes to an increase in inbound revenue.

[0010] (3) In the above (2), from the stored data, predetermined features set in advance are extracted for each user, and based on the extracted predetermined features, a plurality of data are integrated and / or unnecessary data are deleted to compress the data to be stored. An advertisement distribution method. The advertisement distribution method described in this item extracts, for each user, predetermined features set in advance, such as the staying area, staying period, movement between areas, etc., from the data for each user acquired and stored from advertisement display requests and cooperation services. Then, based on the extracted predetermined features, a plurality of data are integrated and compressed into another valuable format, or unnecessary data considered as noise, etc. are deleted to compress the data to be stored. Also by this, the huge amount of data to be stored is compressed without damaging the valuable data of each user, contributing to an improvement in processing speed and a reduction in costs.

[0011] (4) In the above (3), from the stored data, data indicating at least that the staying area of each user has changed is extracted to compress the data to be stored. An advertisement distribution method. The advertisement distribution method described in this item extracts data indicating that the staying area of each user has changed from the data for each user acquired and stored from advertisement display requests and cooperation services. For example, taking as an example the case where for a certain period of a certain user, five pieces of data, namely "data staying in area A", "data staying in area A", "data staying in area B", "data staying in area B", and "data staying in area A", are stored in chronological order in this description order.

[0012] In this case, the third "data staying in Region B" indicating that the staying region has changed from Region A to Region B and the fifth "data staying in Region A" indicating that the staying region has changed from Region B to Region A are extracted. In addition to this, the first "data staying in Region A" indicating the initial staying region may also be extracted. Then, only the extracted data is saved, and the data that was not extracted is deleted, etc., to compress the data to be saved. As a result, the huge amount of data to be saved is compressed while leaving the data necessary to understand the movement information and staying information of each user, which contributes to an improvement in processing speed and a reduction in costs.

[0013] (5) In the above item (3), as the predetermined feature, among the number of stays in a specific region, the staying period in each region in the movement between two or more specific regions, the cumulative staying period in any region, the number of movements between regions, the elapsed period since the previous movement between regions, and the elapsed period between data indicating the movement between regions, at least one is extracted for each user for a specific period in an advertisement distribution method. The advertisement distribution method described in this item specifically identifies the predetermined features extracted from the data for each saved user. That is, among the number of stays in a specific region, the staying period in each region in the movement between two or more specific regions, the cumulative staying period in any region, the number of movements between regions, the elapsed period since the previous movement between regions, and the elapsed period between data indicating the movement between regions, at least one is extracted as a predetermined feature for each user for a specific period. Then, based on each of the extracted features, data integration, deletion, etc. are performed to compress the data to be saved. As a result, while the data to be saved is compressed, a plurality of saved opaque data is converted into more valuable data, so that both compression of the saved data and improvement of targeting accuracy can be achieved.

[0014] (6) An advertising delivery platform that delivers advertisements for display on a website to a user, the advertising delivery platform comprising: a data acquisition unit that acquires a user identifier, geographical information, and date and time included in an advertisement display request from the website visited by the user, and a user identifier, geographical information, and date and time provided from an associated service of the advertising delivery platform used by the user; a data storage unit that stores the data acquired by the data acquisition unit for each user in a time series; a data analysis unit that analyzes the data stored by the data storage unit to grasp movement information and stay information of each user from the relationship between the staying location and date and time of each user; a targeting unit that targets users to whom advertisements are to be delivered based on the movement information and the staying information; and an advertising delivery unit that delivers advertisements to the users targeted by the targeting unit, wherein the targeting unit targets users during travel based on the movement information and the staying information, and the advertising delivery unit delivers advertisements directed to users during travel, and further comprising a data extraction unit that extracts predetermined features set in advance for each user from the data stored by the data storage unit, and compresses the data to be stored by integrating a plurality of data and / or deleting unnecessary data based on the extracted predetermined features. And the advertising delivery platform according to (6) is used in the advertising delivery method of (3) above, and exhibits an equivalent effect corresponding to the advertising delivery method of (3) above.

Advantages of the Invention

[0015] Since the present invention is configured in this way, it is possible to improve the accuracy of targeting in advertising delivery to the intended user group.

Brief Description of the Drawings

[0016]

Figure 1

Figure 2

Embodiments for Carrying Out the Invention

[0017] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Here, throughout the drawings, the same parts or corresponding parts are denoted by the same reference numerals. Also, detailed descriptions of the same parts or corresponding parts as in the prior art will be omitted. FIG. 1 shows an example of the configuration of an advertising distribution platform 10 according to an embodiment of the present invention. Here, the roles of the respective components of the advertising distribution platform 10 will be described, and the specific operations will be described with reference to the flowchart of FIG. 2 described later. Note that the configuration of the advertising distribution platform 10 according to the embodiment of the present invention is not limited to the block diagram of FIG. 1. For example, depending on the procedure and situation of the advertising distribution method, etc., a configuration in which some of the components shown in FIG. 1 are deleted, changed, or appropriately added may also be acceptable.

[0018] As shown in FIG. 1, the advertising distribution platform 10 includes a data acquisition unit 12, a data storage unit 14, a data extraction unit 16, a data analysis unit 18, a targeting unit 20, and an advertising distribution unit 22. The advertising distribution platform 10 of the embodiment in FIG. 1 is used in an RTB (Real-Time Bidding) environment and corresponds to a so-called DSP (Demand-Side Platform). For this reason, the advertising distribution platform 10 exchanges information with a plurality of websites 40 having advertising spaces for bidding and an SSP (Supply-Side Platform) 50. Each of the websites 40 has one or more advertising spaces where advertisements are distributed, and is browsed by a plurality of users U via terminals 30. Further, the advertising distribution platform 10 is also configured to receive information from a plurality of cooperation services 60 as described later.

[0019] The data acquisition unit 12 of the advertisement distribution platform 10 acquires necessary data from the advertisement display request received from the website 40 via the SSP 50 and the information received from the cooperation service 60. For example, the data acquisition unit 12 acquires, from the advertisement display request of the website 40, the IP address of the terminal 30 used by the user U who is browsing the website 40, the transmission date and time (receiving date and time) of the advertisement display request, etc., and further acquires a user identifier that can identify each user U from them, geographical information indicating the region where the user U is considered to be staying, etc.

[0020] Here, the cooperation service 60 is various services that cooperate with the advertisement distribution platform 10 or the company operating the advertisement distribution platform 10. For example, general websites, applications, information provision services using DMP (Data Management Platform), etc. can be mentioned. From such a cooperation service 60, the data acquisition unit 12 acquires, for example, the access log of the user U, the date and time thereof, the IP address, the user agent, the profile (age, gender, occupation, nationality, etc.) input by the user U, the language information set by the user U, the date and time of those, etc. Further, the data acquisition unit 12 acquires a user identifier that can identify each user U determined from them, geographical information indicating the region where the user U is considered to be staying, etc. Note that examples of the user identifier acquired from the advertisement display request and the cooperation service 60 include cookies, advertisement IDs, common IDs, etc.

[0021] The data storage unit 14 stores the data acquired by the data acquisition unit 12 as described above and the data extracted by the data extraction unit 16 as described later. When storing the data acquired by the data acquisition unit 12, it is stored in a time series based on the date and time of each data for each user U based on the user identifier. Here, although the user identifier acquired from the advertisement display request by the data acquisition unit 12 and the user identifier acquired from the cooperation service 60 may have different structures, if it is found that they are user identifiers indicating the same user U, they are stored together as the data of that user U. The determination as to whether user identifiers with different structures belong to the same user U can be made by using the common part between those user identifiers. As the storage destination for the data by the data storage unit 14, an arbitrary database or the like may be used, and separate storage destinations may be used for the data acquired by the data acquisition unit 12 and the data extracted by the data extraction unit 16.

[0022] The data extraction unit 16 extracts, for each user U, data that satisfies specific conditions or preset features from the data acquired by the data acquisition unit 12 and stored by the data storage unit 14 for the purpose of compressing the stored data and the like. Such specific conditions and preset features will be described in detail later. The data extracted by the data extraction unit 16 and the data derived from the features extracted by the data extraction unit 16 as described later are stored by the data storage unit 14 as described above. The data analysis unit 18 analyzes the data stored by the data storage unit 14 to grasp the movement information and stay information of each user U from the relationship between the stay location of the user U determined from the geographical information and the date and time of the data indicating it.

[0023] The targeting unit 20 targets the user U to whom the advertisement is to be delivered based on the movement information and staying information of each user U grasped by the data analysis unit 18. Since the user layer to be targeted varies depending on the content of the advertisement, the targeting unit 20 performs advertisement delivery targeting according to the characteristics of the user U grasped from the movement information and staying information of the user U and the content of the advertisement to be delivered. Here, the targeting means also includes excluding the user U who has not been targeted for a certain advertisement from the delivery candidates of that advertisement. The advertisement delivery unit 22 delivers the advertisement to the user U targeted by the targeting unit 20 for a certain advertisement, and in response to an advertisement display request from the website 40 being browsed by the targeted user U, delivers the advertisement to the advertisement frame of the website 40.

[0024] Here, each component of the advertisement delivery platform 10 as described above is divided in terms of functional units, and is not divided in terms of software or hardware units for actually constructing the advertisement delivery platform 10. Further, any software and hardware can be used for the software and hardware for constructing the advertisement delivery platform 10. Also, the terminal 30 used by the user U can be any terminal as long as it can access the website 40 via the network, for example, a personal computer, a tablet computer, a smartphone, a mobile phone, etc. Although not shown in FIG. 1, various settings and inputs are made to the advertisement delivery platform 10 by an administrator terminal used by an administrator of the advertisement delivery platform 10 or the like.

[0025] Next, along the flow of the flowchart shown in FIG. 2, taking as an example the case of delivering an advertisement targeting user U, a foreigner traveling in Japan, using the advertisement delivery platform 10 shown in FIG. 1, the advertisement delivery method according to an embodiment of the present invention will be described. Regarding the configuration of the advertisement delivery platform 10, refer to FIG. 1 as appropriate. Note that the flowchart shown in FIG. 2 shows an example of the flow of procedures for explaining the advertisement delivery method according to an embodiment of the present invention. Therefore, the advertisement delivery method is not limited to these flowcharts, and for example, depending on the configuration and situation of the advertisement delivery platform 10, etc., a flowchart in which some of the steps shown in FIG. 2 are deleted, changed, or appropriately added may also be acceptable.

[0026] S10 (Data acquisition): The data acquisition unit 12 acquires data including a user identifier, geographical information, and date and time from an advertisement display request transmitted from the website 40 via the SSP. Further, the data acquisition unit 12 also acquires data including a user identifier, geographical information, and date and time from the cooperation service 60. The acquisition of these data is to be performed continuously, and data is acquired each time an advertisement display request is received and each time data is provided from the cooperation service 60.

[0027] S20 (Data storage): The data storage unit 14 stores the data acquired by the data acquisition unit 12 in S10 above. That is, it stores the data including the user identifier, geographical information, and date and time acquired from the advertisement display request and the data including the user identifier, geographical information, and date and time acquired from the cooperation service 60. At this time, each user U is identified using the user identifier, and the data is stored in chronological order for each user U using the date and time data. Also, similar to S10 above, the data storage in this step is also to be performed continuously, and it is stored each time data is acquired in S10, accumulating the data of each user U.

[0028] S30 (Retrieving Data of the Target User): The data extraction unit 16 retrieves data for an arbitrary specific period including the latest data of the target user U (hereinafter referred to as "target user U1" for convenience of explanation) for whom trends are to be grasped, from the data for each user U that is accumulated by being saved in S20 above. At this time, the data of the target user U1 saved in S70 and S90 described later may also be retrieved together. The retrieval of these data may be executed at any timing other than the timing when new data is saved in S20 above.

[0029] S40 (Judging Change in Stay Region): Based on the data of the target user U1 retrieved in S30 above, the data extraction unit 16 judges whether or not the stay region (stay country in this embodiment) of the target user U1 has changed. That is, it is judged whether or not the stay country determined from the geographical information of the latest data of the target user U1 has changed from the stay country determined from the geographical information of the previous data of the target user U1. As a result, if it is judged that the stay country has changed (YES), the process proceeds to S50; if it is judged that the stay country has not changed (NO), the process returns to S10 to continue data retrieval and saving.

[0030] S50 (Judging Number of Changes in Stay Region): The data extraction unit 16 judges whether or not there are changes in the stay region (stay country in this embodiment) of the target user U1 that are equal to or more than a preset fixed number. That is, as will be described in S60 and S70 below, data indicating that the stay country of the target user U1 has changed is extracted and saved, and based on that data, the number of changes is judged. As a result, if it is judged that the number of changes in the stay country is equal to or more than the fixed number (YES), the process proceeds to S80; if it is judged that the number of changes in the stay country is less than the fixed number (NO), the process proceeds to S60.

[0031] S60 (Data Extraction): When it is judged in S40 above that the stay country of the target user U1 has changed, the data extraction unit 16 extracts the original data. That is, since the latest data of the target user U1 retrieved in S30 above is data indicating a change in the stay country, that data is extracted. S70 (Data Compression and Saving): The data storage unit 14 stores the data extracted in S60 separately from the data stored in S20. At this time, among the data of the corresponding user U1 stored in S20, data that is considered unnecessary, such as data that does not show a change in the country of stay in the past compared to the data stored in this step, may be deleted.

[0032] S80 (Feature Extraction): The data extraction unit 16 extracts the characteristic trends of the corresponding user U1 from the data of the country of stay transitions where there are a certain number or more for the corresponding user U1. In this embodiment, "the number of stays in a specific country", "the stay period in each country in the movement between two or more specific countries", "the cumulative stay period in any country", "the number of movements between countries", "the elapsed period since the previous movement between countries", and "the elapsed period between the data indicating the movement between countries" are extracted. Here, taking the case where data such as "2023-12-01@Japan", "2023-12-02@China", "2023-12-03@Japan", "2023-12-04@China", and "2023-12-07@Japan" are stored as data indicating the country of stay transitions of the corresponding user U1 during a specific period as an example, the description of each feature is given.

[0033] "The number of stays in a specific country" refers to the number of stays in each country that the corresponding user U1 has traveled to and from. In the case of the above example, it can be confirmed that the user stayed in Japan 3 times and in China 2 times. Therefore, while retaining the information that the user stayed in Japan 3 times and in China 2 times, since the number of stays in Japan is more, the data is compressed with the country of stay during those periods being Japan. "The stay period in each country during the movement between specific two or more countries" refers to the stay period in each country while the corresponding user U1 travels back and forth between countries. In the case of the above example, it is 1 day in Japan from "2023-12-01@Japan" to "2023-12-02@China", 1 day in China from "2023-12-02@China" to "2023-12-03@Japan", 1 day in Japan from "2023-12-03@Japan" to "2023-12-04@China", and 3 days in China from "2023-12-04@China" to "2023-12-07@Japan". Therefore, while retaining that information, the data is compressed with China, where the longest stay period of 3 days is, as the country of stay during those periods.

[0034] "The cumulative stay period in any country" refers to the cumulative stay period in each country where the corresponding user U1 stayed during a specific period. In the case of the above example, in Japan, it is a total of 2 days for "2023-12-01@Japan" to "2023-12-02@China" and "2023-12-03@Japan" to "2023-12-04@China", and in China, it is a total of 4 days for "2023-12-02@China" to "2023-12-03@Japan" and "2023-12-04@China" to "2023-12-07@Japan". Therefore, while retaining that information, the data is compressed with China, where the cumulative stay period is long, as the country of stay during those periods. "The number of cross-border movements" is to observe the tendency of the number of cross-border movements during a certain period. For example, in the above example, if the period is divided into 4-day intervals of "2023-12-01~04" and "2023-12-04~07", it can be confirmed that the number of movements is 3 times in the former period and 1 time in the latter period. Therefore, while retaining that information, considering the former period as noise, the data is compressed as "2023-12-01~03@Japan", "2023-12-04@China", and "2023-12-07@Japan".

[0035] The "elapsed period since the previous cross-border movement" refers to the elapsed period between movements. For example, it is used to determine whether data indicating a cross-border movement is a valid movement during data compression. For example, in the above example, when determining whether the movement from "2023-12-02@China" to "2023-12-03@Japan" is valid, if the elapsed period since the movement immediately preceding this movement is a certain number of days or more, it is determined to be valid, and it is used in this way. The "elapsed period between data indicating cross-border movements" is for observing the frequency of movements. For example, it is used to exclude user U for whom high-frequency movement information is observed for the purpose of excluding bots such as noise and crawlers. For example, in the above example, the elapsed period between movements is at least 1 day and at most 3 days, and by comparing this with the overall trend, user U who is noise is excluded. In addition to the above-described features, any features such as having moved from a specific country to another specific country, the cumulative stay period in a specific country exceeding a predetermined period, the number of cross-border movements between specific countries exceeding a predetermined number during a specific period, and having no movement information to countries other than a specific country may be extracted.

[0036] S90 (Data Compression and Storage): The data storage unit 14 stores the data compressed based on the features extracted in S80 separately from the data stored in S20. At this time, in anticipation of various future uses, the data may be stored permanently. S100 (Data Analysis): The data analysis unit 18 analyzes the data stored in S20, S70, and S90 to grasp the movement information and stay information of the corresponding user U1. Movement information is information indicating that the user has moved from one country to another country and related information, and stay information is information indicating that the user has stayed in a certain country and related information. In this embodiment, since some data has already been analyzed by the data extraction unit 16 through S60 and S80, that data is utilized.

[0037] S110 (Information Quantity Judgment): Based on the movement information and stay information of the corresponding user U1 grasped in S100 by the targeting unit 20, it is determined whether sufficient information has been collected to enable targeting of the advertisement to be distributed to the corresponding user U1. The advertisement to be distributed in this embodiment is an advertisement targeted at foreign tourists visiting Japan. As a result, if it is determined that sufficient information has been collected (YES), the process proceeds to S120; if it is determined that sufficient information has not been collected (NO), the process returns to S10 to continue data acquisition and storage.

[0038] S120 (Targeting): The targeting unit 20 determines whether to target the advertisement to be distributed to the corresponding user U1, in other words, determines whether the corresponding user U1 is a foreign tourist visiting Japan. As a result, if it is determined to target (YES) because the corresponding user U1 is a foreign tourist visiting Japan, the process proceeds to S130; if it is determined not to target (NO) because the corresponding user U1 is not a foreign tourist visiting Japan, the process proceeds to S140.

[0039] S130 (Advertisement Delivery): The advertisement delivery unit 22 delivers the advertisement to be distributed, which in this embodiment is an advertisement for foreign tourists visiting Japan, to the corresponding user U1 targeted in S120. The advertisement delivery destination is the advertisement frame of the website 40 visited by the corresponding user U1 that sent the advertisement display request. S140 (Excluding the Corresponding User): Since the targeting unit 20 considers that the corresponding user U1 is not a foreign tourist visiting Japan but a foreigner staying in Japan for a long time, etc., the corresponding user U1 is excluded from the targeting candidates (delivery candidates) of the advertisement to be distributed.

[0040] Here, the advertising distribution platform 10 according to the embodiment of the present invention and the advertising distribution method according to the embodiment of the present invention are not limited to only the above-described embodiments, and various changes can be made by those skilled in the art within the technical idea of the present invention. For example, the data obtained from the advertisement display request and the cooperation service 60 is not limited to the user identifier, geographical information, and date and time, and various other information may be obtained and used. In addition, in the description using FIG. 2, geographical information was handled at the country level in order to target foreign tourists visiting Japan, but the granularity of the geographical information is not limited to the country, and may be at the municipality level or the like. Furthermore, the content of the advertisement and its targeting candidates are not limited to foreign tourists visiting Japan, and may be various user groups that can be determined from geographical information of various granularities stored in time series. Also, the advertisement frame for the advertisement distribution destination is not limited to the advertisement frame won in the RTB environment, and may be an advertisement frame in which the advertiser has acquired the right to place an advertisement by any method.

[0041] Now, according to the embodiment of the present invention having the above configuration, the following operational effects can be obtained. That is, the advertising distribution method according to the embodiment of the present invention is executed by, for example, the advertising distribution platform 10 as shown in FIG. 1, collects geographical information indicating the area where the user U is staying, and performs advertising distribution targeting based thereon. Specifically, the user identifier, geographical information, and date and time included therein are obtained from an advertisement display request transmitted via the SSP 50 or the like from the website 40 visited by the user U. Furthermore, the user identifier, geographical information, and date and time are also obtained from the information provided by the cooperation service 60 used by the user U (see S10 in FIG. 2). Then, the obtained data is stored in time series for each user U specified by the user identifier (see S20 in FIG. 2). The acquisition and storage of these data shall be continuously performed.

[0042] Subsequently, the data acquired and saved as described above is analyzed for each user U, and based on the relationship between the staying locations grasped from the geographical information of each user U and the date and time at that time, the movement information and staying information of each user U are grasped (see S100 in FIG. 2). That is, if the relationship between the staying location and the date and time is known for each user U, staying information such as how long the user U stayed in a certain area and movement information such as the user U moving to another area at a certain point in time can be grasped. Then, from the grasped movement information and staying information, it is possible to infer the purpose of the user U staying in a certain area, the purpose of moving from one area to another area, etc. Therefore, based on these information, the user U to whom the advertisement is to be distributed is targeted (see S120 in FIG. 2). As a result, it becomes possible to improve the accuracy of the targeting of the advertisement distribution to the intended user group. For this reason, the advertisement can be accurately distributed to the intended user group (see S130 in FIG. 2), and it is also possible to expect an improvement in the click-through rate of the advertisement displayed on the website 40, a decrease in the click cost, and the exclusion of ad fraud, etc.

[0043] In addition, the advertisement distribution method according to the embodiment of the present invention may target the user U during travel and distribute an advertisement for the user U during travel based on the movement information and staying information of each user U grasped by analyzing the saved data. That is, if it is known how long the user U stayed in each area, that the user U moved from one area to another area, the movement frequency of the user U, etc., it is possible to grasp whether the user U is during travel, and the user U not during travel can be excluded from the targeting candidates. As a result, it becomes possible to accurately display an advertisement for travelers to the user U during travel. For example, when the travel destination is Japan, by excluding foreign residents staying in Japan for a long time (see S140 in FIG. 2), advertisements for hotels, tourist spots, etc. can be displayed for foreign visitors coming to Japan for sightseeing, and it becomes possible to contribute to an increase in inbound revenue.

[0044] Furthermore, the advertisement distribution method according to an embodiment of the present invention extracts data indicating that the staying area of each user U has changed from the data of each user U acquired from an advertisement display request or the cooperation service 60 and stored (see S40 and S60 in FIG. 2). Then, only the extracted data is stored, and the data that has not been extracted is deleted, etc., and the data to be stored is compressed (see S70 in FIG. 2). As a result, it is possible to compress a huge amount of data to be stored while leaving the data necessary to grasp the movement information and staying information of each user U, which contributes to an improvement in processing speed and a reduction in cost.

[0045] Also, the advertisement distribution method according to an embodiment of the present invention extracts, for each user U, predetermined features set in advance regarding, for example, the staying area, staying period, movement between areas, etc. from the data of each user U acquired from an advertisement display request or the cooperation service 60 and stored (see S80 in FIG. 2). Then, based on the extracted predetermined features, a plurality of data are integrated and compressed into another valuable format, or unnecessary data considered as noise, etc. are deleted, and the data to be stored is compressed (see S90 in FIG. 2). Also by this, it is possible to compress a huge amount of data to be stored without impairing the valuable data of each user U, which contributes to an improvement in processing speed and a reduction in cost.

[0046] In addition, the advertising distribution method according to the embodiment of the present invention may have predetermined features extracted from the data for each stored user U as follows. That is, at least one of the number of stays in a specific region, the stay period in each region in the movement between two or more specific regions, the cumulative stay period in any region, the number of movements between regions, the elapsed period since the previous movement between regions, and the elapsed period between data indicating the movement between regions is extracted for each user U as a predetermined feature for a specific period. Then, based on each of the extracted features, data integration, deletion, etc. are performed to compress the data to be stored. As a result, while compressing the data to be stored, a plurality of stored opaque data can be converted into more valuable data, so that it is possible to achieve both compression of the stored data and improvement of targeting accuracy.

[0047] On the other hand, the advertising distribution platform according to the embodiment of the present invention can be used in the advertising distribution method according to the embodiment of the present invention as described above, and can achieve equivalent operational effects corresponding to the advertising distribution method according to the embodiment of the present invention.

Explanation of Signs

[0048] 10: Advertising distribution platform, 12: Data acquisition unit, 14: Data storage unit, 18: Data analysis unit, 20: Targeting unit, 40: Website, 60: Cooperative service, U (U1): User

Claims

1. A method for delivering advertisements to be displayed on a website to a user, by an advertisement delivery platform, comprising: obtaining a user identifier, geographical information, and date and time included in an advertisement display request from a website visited by the user, and a user identifier, geographical information, and date and time provided from a linked service of the advertisement delivery platform used by the user, and storing them in a time series for each user; analyzing the stored data to grasp movement information and stay information of each user from the relationship between the staying location and date and time of each user; targeting users to whom advertisements are to be delivered based on the movement information and the staying information; targeting users during travel based on the movement information and the staying information, and delivering advertisements directed to users during travel; extracting, for each user, predetermined features set in advance from the stored data, integrating a plurality of data and / or deleting unnecessary data based on the extracted predetermined features, and compressing the data to be stored. The advertisement delivery method is characterized by this.

2. The advertisement delivery method according to claim 1, characterized in that data indicating at least that the staying area of each user has changed is extracted from the stored data, and the data to be stored is compressed.

3. As the predetermined features, at least one of the number of stays in a specific area, the staying period of each area in the movement between two or more specific areas, the cumulative staying period in an arbitrary area, the number of movements between areas, the elapsed period from the previous movement between areas, and the elapsed period between data indicating the movement between areas is extracted for each user for a specific period. The advertisement delivery method according to claim 1 is characterized by this.

4. An advertisement delivery platform for delivering advertisements to be displayed on a website to a user, comprising: a data acquisition unit that acquires a user identifier, geographical information, and date and time included in an advertisement display request from a website visited by the user, and a user identifier, geographical information, and date and time provided from a linked service of the advertisement delivery platform used by the user; a data storage unit that stores the data acquired by the data acquisition unit in a time series for each user; a data analysis unit that analyzes the data stored by the data storage unit to grasp movement information and staying information of each user from the relationship between the staying location and date and time of each user; A targeting unit that targets users who receive advertisements based on the movement information and the stay information; An advertisement distribution unit that distributes advertisements to the users targeted by the targeting unit, and the targeting unit targets users during travel based on the movement information and the stay information, and the advertisement distribution unit distributes advertisements directed to users during travel. Furthermore, a data extraction unit that extracts predetermined features set in advance for each user from the data stored by the data storage unit, integrates a plurality of data and / or deletes unnecessary data based on the extracted predetermined features, and compresses the data to be stored, characterized in that the advertisement distribution platform includes the data extraction unit.

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