Measurement device, measurement method, and measurement program

Abstract

To make it possible to provide an advertiser with information regarding a segment to which a user who has come into contact with a web site or web advertisement related to the advertiser belongs.SOLUTION: A measurement device includes: a storage unit that stores segment information regarding users belonging to a plurality of segments respectively; an acquisition unit that acquires user information regarding user devices owned by users who have visited an advertiser's store; and a counting unit that counts the number of users who have visited the advertiser's store after coming into contact with a website or web advertisement related to the advertiser, for each of the plurality of segments, based on the segment information and the user information.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to a measurement apparatus, a measurement method, and a measurement program. [Background technology]

[0002] In recent advertising delivery systems, in advertising measures to attract customers, the number of results (for example, the number of times a potential customer reaches a turning point of becoming a prospective customer, such as visiting a store) is counted to measure the effectiveness of the advertisement. Specifically, a technology is known that visualizes the extent to which an advertisement contributed to store visits by counting the number of store visits by users who came into contact with the advertisement as the number of results.

[0003] For example, in the prior art, a technique is known that calculates the advertising effectiveness of each advertisement medium based on the timing of a user's viewing of the advertisement medium and preset weight information (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

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

[0005] However, the above conventional technology calculates the effectiveness of advertisements for each advertisement medium or advertisement campaign using the contribution degree calculated for each advertisement medium based on the log of advertisement viewing by users. Therefore, the above conventional technology does not necessarily enable the provision of information about the advertiser's website or the segment to which the users who came into contact with the web advertisement belong to the advertiser. [Means for solving the problem]

[0006] The measurement device of the present application is characterized by having a memory unit that stores segment information regarding users belonging to each of a plurality of segments, an acquisition unit that acquires user information regarding user devices owned by users who have visited an advertiser's store, and a counting unit that counts the number of users who have visited the advertiser's store after coming into contact with a website or web advertisement related to the advertiser, for each of the plurality of segments, based on the segment information and the user information. Effect of the Invention

[0007] According to one aspect of the embodiment, it is possible to provide the advertiser with information regarding a segment to which a user who has come into contact with a website or web advertisement related to the advertiser belongs. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing a configuration of an advertising effect measurement system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of store visit detection logic according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of a device configuration of the advertising effect measurement system according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an outline of the counting conditions according to the embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of user information according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of output information according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of output information according to the embodiment. [Figure 8] FIG. 8 is a flowchart showing an example of a measurement procedure according to the embodiment. [Figure 9] FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the functions of the measurement device according to this embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, a detailed description will be given of a mode for carrying out a measurement device, a measurement method, and a measurement program according to the present invention (hereinafter, referred to as an "embodiment") with reference to the drawings. Note that the measurement device, the measurement method, and the measurement program according to the present invention are not limited to the present embodiment. In addition, the same parts in the following embodiments are given the same reference numerals, and duplicated descriptions will be omitted.

[0010] [1. Overall overview] First, the configuration of an advertising effect measurement system 1 according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the configuration of an advertising effect measurement system 1 according to an embodiment.

[0011] 1, the advertising effect measurement system 1 may be configured to include a user device 10, an advertiser device 20, a detection device 30, and a measurement device 100. The user device 10, the advertiser device 20, the detection device 30, and the measurement device 100 may be connected to each other via a network NW in a wired or wireless manner so as to be able to communicate with each other.

[0012] The user device 10 is an information processing terminal used by a user, and may be, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. The user here refers to a general consumer (end user) who goes to a real store to shop or receive services.

[0013] For example, the user device 10 displays a screen (advertising medium) including a delivered advertisement (e.g., a Web advertisement). In such a case, the user is a user who has come into contact with the advertisement. In this embodiment, contact with an advertisement may include not only the advertisement being posted, but also a predetermined user operation on the advertisement (e.g., a click). In this embodiment, contact with a predetermined Web page that is not an advertisement (e.g., a Web page included in a website related to an advertiser) may also be expressed as "contact with an advertisement" for convenience. A user whose interest has been heightened by contact with an advertisement in this way may visit the advertised store.

[0014] The advertiser device 20 is an information processing terminal used by an advertiser, and may be, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, etc. The advertiser here refers to a source that submits advertisements, and may be, for example, a company that is a client of a distribution company that mediates advertisement distribution, and may operate a store.

[0015] For example, the advertiser device 20 can perform various settings related to advertisement delivery and store visit measurement in response to the operation of the advertiser, for the measurement device 100. In addition, the advertiser device 20 can also submit the advertisement itself to the measurement device 100 in response to the operation of the advertiser.

[0016] The detection device 30 is a device installed in a real store operated by an advertiser (e.g., a client company of a distribution service provider) and is a device for detecting visitors. For example, the detection device 30 may be a Wi-Fi access point installed in the store of the client company, and detects a user having a user device 10 as a visitor to the store when an interaction is obtained with a specific tag that is pre-assigned to a web page or web advertisement included in a website related to the advertiser. The detection device 30 may be provided by the distribution service provider or a partner company of the distribution service provider.

[0017] The measurement device 100 is an example of an information processing device according to this embodiment, and performs a series of information processing related to store visit measurement. The measurement device 100 in this embodiment is a measurement device that counts the number of users who visit an advertiser's store after coming into contact with a website or web advertisement related to the advertiser, for each of multiple segments, based on segment information on users belonging to each of multiple segments and user information on user devices owned by users who visit the advertiser's store. The measurement device 100 is capable of performing the following processing as a premise.

[0018] The measurement device 100 can obtain a hierarchical structure in which multiple types of management units for managing advertisements are configured as one hierarchy. The measurement device 100 can also accept a setting from an advertiser to set one of the registered items registered for each management unit as a measurement unit of advertisement effectiveness. In this state, the measurement device 100 can, for example, count the advertising effectiveness of one advertisement determined to have contributed to a visit to a store by an advertisement-exposed user among a group of advertisements associated with a registered item defined as a measurement unit.

[0019] The measurement device 100 acquires the location information of the user device 10 from the user device 10. The measurement device 100 acquires the location information of the user device 10 as location information of the user who owns the user device 10. In the following, the location information of the user device 10 may be referred to as "user location information". In addition, in the following, location history information regarding the location history of the user device 10 may be referred to as "user location history information". Here, the user location history information refers to information that associates the user's location information with information indicating the acquisition date and time of the user's location information.

[0020] The measurement device 100 may utilize a global navigation satellite system (GNSS) positioning technology including a global positioning system (GPS) when acquiring the user's location information. For example, the measurement device 100 may acquire location information acquired based on the GNSS positioning technology or the like by an application installed in the user device 10. When acquiring the user's location information, the measurement device 100 stores the user's location information, information indicating the acquisition date and time of the user's location information, and terminal information for identifying the user device 10 (hereinafter, sometimes referred to as "user device identification information") in the user information storage unit 123 in association with each other.

[0021] In addition, the user device 10, the advertiser device 20, and the detection device 30 are edge computers that perform edge processing near the customer, while the measurement device 100 may be a cloud computer that performs processing on the cloud side. In other words, the measurement device 100 may be a server device.

[0022] (About store visit logic) Next, the logic of store visit detection will be described with reference to FIG. 2. FIG. 2 is a diagram showing an example of the store visit detection logic according to the embodiment. First, according to the example of FIG. 2, in the advertisement distribution service provided by the distribution company, medium M1, medium M2, and medium M3 are defined as the advertising media on which the submitted advertisement is to be placed. Furthermore, a tag TG for store visit detection is inserted into the submitted advertisement. Note that the insertion of the tag TG may be performed by the measurement device 100.

[0023] In this state, when the user device 10 displays the medium M1, which is a screen including an advertisement with the tag TG inserted therein, the user device 10 transmits contact information of the user device 10 (information indicating that the user has come into contact with a Web page or Web advertisement included in a Web site related to an advertiser, hereinafter simply referred to as "contact information") to the measurement device 100. The contact information may include user device identification information, the posting date and time of the advertisement, medium information indicating the medium M1 on which the advertisement was posted, and the like. The contact information may also be accumulated in the contact / visit information database 121 as one record in the distribution history of the advertisement distribution.

[0024] Assume that a user who has become an advertisement-exposed user by coming into contact with an advertisement visits a real store equipped with a detection device 30, as shown in FIG. 2. In this case, the user device 10 and the detection device 30 are connected by short-range wireless communication, and as a result, the detection device 30 detects the user having the user device 10 as a visitor to the store via short-range wireless communication. The detection device 30 then transmits store visit information indicating the detection of the visit to the measurement device 100. The store visit information may include user device identification information, store information for identifying the store, and the like. The store visit information may be accumulated in the contact / store visit information database 121 as one record serving as a delivery history in the delivery of advertisements. Examples of short-range wireless communication include Bluetooth (registered trademark) and WiFi (registered trademark).

[0025] Although the above explanation has been given on the assumption that an advertisement is distributed, the advertisement may be a web page included in a website related to an advertiser. In this case, the above-mentioned tag TG may be inserted into the web page included in the website related to the advertiser, instead of the advertisement. 2. Embodiment From here, an embodiment realized by the advertising effect measurement system 1 of this embodiment will be described. In this embodiment, the measurement device 100 counts the number of users who visit the advertiser's store after coming into contact with the advertiser's website or web advertisement for each of multiple segments, based on segment information on users belonging to each of multiple segments and user information on user devices owned by users who visited the advertiser's store. Note that, hereinafter, "Web advertisement for the advertiser" may be abbreviated as "advertisement". Also, hereinafter, "Web page included in the advertiser's website" may be abbreviated as "Web page".

[0026] [2-1. Configuration of advertising effectiveness measurement system] Next, an advertising effect measurement system 1 according to an embodiment will be described. Fig. 3 is a diagram showing an example of a device configuration of the advertising effect measurement system 1 according to an embodiment. As shown in Fig. 3, the advertising effect measurement system 1 has a configuration in which a measurement device 100 and a detection device 30 are connected via a predetermined network NW. Note that the number of detection devices 30 included in the advertising effect measurement system 1 is not limited, and multiple detection devices 30 may be included.

[0027] [2-2. Configuration of the measurement device] First, a configuration example of the measurement device 100 according to the embodiment will be described. As shown in FIG.

[0028] (Regarding communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC) etc. The communication unit 110 is connected to the network NW by wire or wirelessly, and transmits and receives information between the measuring device 100 and the detection device 30.

[0029] (Regarding the storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk, an optical disk, etc. As shown in FIG. 3, the storage unit 120 has a contact / visit information database 121, a counting condition storage unit 122, and a user information storage unit 123.

[0030] (About Contact / Visit Information Database 121) The contact / visit information database 121 stores the contact information and visit information of the user. For example, the contact / visit information database 121 can store contact information transmitted when the user device 10 displays a medium M1, which is a screen including an advertisement (or a Web page) into which a tag TG is inserted, as shown in Fig. 2. Specifically, the contact / visit information database 121 may store, as the contact information, user device identification information, the posting date and time of the advertisement (or Web page), information on the inserted tag, medium information indicating the medium on which the advertisement is posted, and the like.

[0031] 2, when the user device 10 visits a real store equipped with a detection device 30 and is detected based on short-range wireless communication technology, the contact / store visit information database 121 can store store visit information indicating the detection of the visit transmitted by the detection device 30. Specifically, the contact / store visit information database 121 may store, as the above-mentioned store visit information, user device identification information, advertisement (or web page) information, inserted tag information, store information identifying the store, and the like.

[0032] The above-mentioned information is merely an example, and the contact / visit information database 121 can store any information that falls within the category of contact information or visit information, without any limitations.

[0033] (Regarding the counting condition storage unit 122) The counting condition storage unit 122 stores information on counting conditions used by the counting unit 132 described below to perform a predetermined counting. Specifically, the counting condition storage unit 122 stores report information 122a on a report period, pre-report information 122b on a pre-report period, and post-report information 122c on a post-report period as information on the counting conditions.

[0034] From here, an overview of the counting conditions stored in the counting condition storage unit 122 will be described with reference to Fig. 4. Fig. 4 is a diagram showing an overview of the counting conditions according to the embodiment.

[0035] 4 shows a report period 122a, a pre-report period 122b, and a post-report period 122c as information related to the counting conditions. The counting condition storage unit 122 may store the information shown in FIG. 4 in a table format or the like.

[0036] (For reporting period 122a) The report period 122a is information about a period during which the measurement device 100 measures contact information about a user's contact with a website or Web advertisement related to an advertiser. In the example of FIG. 4, the report period 122a is set to a period from 6 / 1 to 6 / 30. The measurement device 100 can acquire contact information of a user who has contacted a website or Web advertisement related to an advertiser during the report period 122a. In FIG. 4, the measurement device 100 acquires the user's contact information on 6 / 5. In addition, a user who visits a store during the report period 122a after the contact information is acquired by the measurement device 100 is counted as a user who has visited the store of the advertiser after contacting a website or Web advertisement related to the advertiser.

[0037] (Regarding pre-reporting period 122b) The pre-report period 122b is a period set immediately before the report period 122a. For example, in the example of FIG. 4, the pre-report period 122b is set as a period from 5 / 1 to 5 / 31. Note that users who visit the advertiser's store during the pre-report period 122b and are detected are counted as "total visits (total number of users who visited the advertiser's store regardless of whether they came into contact with a website or web advertisement related to the advertiser)". Note that the pre-report period 122b does not have to be set. For example, if the pre-report period 122b is not set, users who visit the advertiser's store before the report period 122a and are detected are counted as "total visits (total number of users who visited the advertiser's store regardless of whether they came into contact with a website or web advertisement related to the advertiser)".

[0038] (Post-reporting period 122c) The post-report period 122c is a period set immediately after the report period 122a. The post-report period 122c is a period set in consideration of the time lag between a user coming into contact with a website or web advertisement related to an advertiser during the report period 122a and visiting the store. For example, in the example of FIG. 4, the post-report period 122c is set to a period from 7 / 1 to 7 / 31. In the post-report period 122c, the measurement of contact information by the measurement device 100 ends, but the detection of users who have visited the advertiser's store by the detection device 30 continues. In other words, users who have visited the store during the post-report period 122c are counted as users who have visited the advertiser's store after coming into contact with a website or web advertisement related to the advertiser.

[0039] (Regarding the user information storage unit 123) From here, an overview of the user information stored in the user information storage unit 123 will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of user information according to the embodiment.

[0040] The user information storage unit 123 stores user information related to a user device owned by a user who visits an advertiser's store. In the example shown in FIG. 5, the user information storage unit 123 stores, as user information, user device identification information, which is terminal information for identifying the user device 10, location history information related to the user's location history, and segment information related to a segment to which the user who owns the user device 10 belongs. The user information storage unit 123 stores segment information related to users who belong to each of a plurality of segments. In the example shown in FIG. 5, the user information storage unit 123 stores, as segment information, information such as "business people who work overtime continuously," "people who commute for long periods of time," "people who were in Shibuya on weekdays," and "people who use supermarkets at least once a week." In this way, the storage unit 120 stores segment information related to users who belong to each of a plurality of segments.

[0041] (Regarding the control unit 130) Here, the explanation will be continued by returning to Fig. 3. The control unit 130 is realized by a CPU, an MPU (Micro Processing Unit), or the like executing various programs stored in a storage device inside the measuring device 100 using a RAM as a working area. The control unit 130 is also realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in Fig. 3, the control unit 130 has an acquisition unit 131, a counting unit 132, a generation unit 133, and a provision unit 134.

[0042] (Regarding the acquisition unit 131) The acquisition unit 131 receives information on the counting conditions from the advertiser. Specifically, the acquisition unit 131 receives a report period, a pre-report period, and a post-report period as the counting conditions. For example, the acquisition unit 131 acquires report information, pre-report information, and post-report information from the advertiser device 20.

[0043] Furthermore, the acquisition unit 131 can accept changes to the periods set for the report period, the pre-report period, and the post-report period. For example, in the example of Fig. 4, the report period, the pre-report period, and the post-report period are each set to "30 days", but the acquisition unit 131 is not limited to 30 days and can accept any period (for example, 15 days, 45 days, 60 days, etc.) based on the target advertisement or business.

[0044] The acquisition unit 131 also acquires contact information of the user with a website or a web advertisement related to the advertiser from the user device 10. For example, the acquisition unit 131 can acquire, as the contact information, user device identification information, the date and time of contact with a website or a web advertisement related to the advertiser, the URL of the website or the web advertisement related to the advertiser, a query string following the end of the URL of the website or the web advertisement related to the advertiser, information on a tag inserted in the website or the web advertisement related to the advertiser, medium information indicating the medium on which the advertisement is to be published, and the like from the user device 10. Furthermore, when the contact information is stored in an external device other than the user device 10, the acquisition unit 131 can acquire the contact information from the external device.

[0045] The acquisition unit 131 also acquires store visit information from the detection device 30. For example, the acquisition unit 131 can acquire user device identification information, website or web advertisement information related to an advertiser, inserted tag information, store information for identifying a store, and the like, as the user's store visit information. Note that the acquisition unit 131 is not limited to the above-mentioned information, and can acquire any information used to perform a predetermined counting operation.

[0046] Furthermore, the acquisition unit 131 acquires user information related to the user device 10 owned by the user who visited the advertiser's store. For example, the acquisition unit 131 acquires user information related to the user device 10 owned by the user who visited the advertiser's store after contacting a website or a Web advertisement related to the advertiser from the user device 10. Specifically, the acquisition unit 131 may acquire user device identification information, user location history information, and user contact information as the user information.

[0047] In addition, the acquisition unit 131 acquires, as the user information, segment information related to a segment to which a user who visits a store of an advertiser after contacting a website or a web advertisement related to the advertiser belongs. For example, the acquisition unit 131 refers to the user information storage unit 123 and acquires segment information associated with the user device identification information acquired from the user device 10.

[0048] (Regarding the counting unit 132) The counting unit 132 counts the number of users who visited the advertiser's store after contacting a website or web advertisement related to the advertiser for each of a plurality of segments based on the segment information and the user information. The counting unit 132 counts the number of users who visited the advertiser's store after contacting a website or web advertisement related to the advertiser for each segment. For example, the counting unit 132 counts the number of users who visited the advertiser's store within the report period or post-report period described in FIG. 4 after contacting a website or web advertisement related to the advertiser within the report period described in FIG. 4. The counting unit 132 may count the number of unique users.

[0049] Furthermore, the counting unit 132 identifies inflow information related to an inflow path to a website or a web advertisement based on a query string identified from the user information, and counts the number of users for each inflow information. Specifically, the counting unit 132 identifies a query string following the URL of a website or a web advertisement related to the advertiser based on the contact information. Next, the counting unit 132 identifies information related to a source of inflow to the website or the web advertisement related to the advertiser based on the query string, and counts the number of users (hereinafter, sometimes referred to as inflow users) who have inflowed to the website or the web advertisement related to the advertiser for each inflow source. For example, the counting unit 132 identifies a search site that is a source of inflow, and counts the number of inflow users for each identified search site.

[0050] (Regarding the generation unit 133) The generating unit 133 generates segment information based on the user's location information. Specifically, the generating unit 133 estimates information on the visited places visited by the user, the user's stay time at the visited places, and the visit time or visit frequency when the user visited the visited places based on the location history information of the user device 10 (in other words, the user's location history information), and generates segment information based on the information on the visited places, the stay time, the visit time, or the visit frequency. More specifically, when the generating unit 133 estimates the information on the visited places, the stay time, the visit time, or the visit frequency, the generating unit 133 estimates the user's behavior pattern based on the information on the visited places, the stay time, the visit time, or the visit frequency. Next, the generating unit 133 classifies the user into a segment corresponding to the estimated behavior pattern. Next, when the generating unit 133 classifies the user into a segment corresponding to the estimated behavior pattern, the generating unit 133 generates segment information indicating the estimated behavior pattern. When the generating unit 133 generates segment information, the generating unit 133 stores the user device identification information owned by the user and the segment information on the segment into which the user is classified (the segment to which the user belongs) in the user information storage unit 123 in association with each other.

[0051] For example, the generating unit 133 estimates information on the places visited by the user within a predetermined period and the user's stay time at the visited places based on the user's location history information and the address information of the facilities corresponding to each business type. For example, the generating unit 133 identifies the places frequently visited by the user (e.g., the places visited by the user a predetermined number of times or more within a predetermined period. Hereinafter, these will be referred to as "places visited with a predetermined frequency") based on the user's location history information and the address information of the facilities corresponding to each business type. In addition, the generating unit 133 calculates the user's stay time at the identified places (e.g., the average stay time per visit, etc.). Next, the generating unit 133 estimates the user's behavior pattern based on the places visited by the user with a predetermined frequency and the user's stay time at the places, and classifies the user into a segment corresponding to the estimated behavior pattern. For example, the generating unit 133 identifies the visited places where the user stayed for a predetermined time or more (e.g., 40 hours per week) within a predetermined period as the user's workplace based on the user's location history information and the address information of the facilities corresponding to each business type. Furthermore, the generating unit 133 calculates the average stay time of the user at the identified workplace. Next, when the average stay time of the user at the workplace exceeds a predetermined time (for example, 10 hours), the generating unit 133 estimates that the user has a behavior pattern of working overtime every day. Furthermore, when the generating unit 133 estimates that the user has a behavior pattern of working overtime every day, the generating unit 133 may classify the user into a segment indicating that the user is a "business person who works overtime continuously." Furthermore, when the generating unit 133 classifies the user into a segment indicating that the user is a "business person who works overtime continuously," the generating unit 133 stores the user device identification information of the user device 10 owned by the user and the segment information indicating that the user is a "business person who works overtime continuously" in the user information storage unit 123 in association with each other.

[0052] Furthermore, the generating unit 133 may estimate travel information related to a travel route along which the user travels with a predetermined frequency and travel time required for the user to travel along the travel route based on the location history information of the user device 10, and generate segment information based on the travel information. For example, the generating unit 133 identifies a travel route along which the user travels with a predetermined frequency (e.g., a travel route along which the user travels a predetermined number of times or more within a predetermined period. Hereinafter, this will be referred to as a "travel route along which the user travels with a predetermined frequency") based on the user's location history information and information on route maps of railways, expressways, etc. Furthermore, the generating unit 133 calculates travel time required to travel along the identified travel route (e.g., an average travel time required for one trip, etc.). Next, the generating unit 133 estimates the user's behavior pattern based on the travel route along which the user travels with a predetermined frequency and the travel time, and classifies the user into a segment corresponding to the estimated behavior pattern. For example, the generating unit 133 identifies the user's commuting route based on the user's location history information and information on route maps of railways, expressways, etc. For example, the generating unit 133 identifies a route that the user has traveled back and forth on a predetermined number of times (for example, five times a week) or more within a predetermined period as the user's commuting route based on the user's location history information and information on route maps of railways, expressways, etc. Furthermore, the generating unit 133 calculates an average travel time (hereinafter, commuting time) required for travel along the identified commuting route. Next, when the user's commuting time exceeds a predetermined time (for example, two hours), the generating unit 133 estimates that the user has a behavior pattern of commuting over a long period of time. Furthermore, when the generating unit 133 estimates that the user has a behavior pattern of commuting over a long period of time, the generating unit 133 may classify the user into a segment indicating that the user is a "long-term commuter". Furthermore, when the generating unit 133 classifies the user into a segment indicating that the user is a "long-term commuter", the generating unit 133 stores the user device identification information of the user device owned by the user in association with the segment information indicating that the user is a "long-term commuter" in the user information storage unit 123.

[0053] Further, the generation unit 133 identifies a place (hereinafter, a visited place) visited by the user at a visit time such as a specific day (for example, July 1, 2023), a day of the week (for example, a weekday or a holiday), or a time period (for example, 10:00 to 11:00, daytime or nighttime) based on the user's position history information and map information. Next, the generation unit 133 estimates the user's behavior pattern based on the user's visit place and visit time, and classifies the user into a segment corresponding to the estimated behavior pattern. For example, the generation unit 133 identifies that the user visited a specific visited place at a specific visit time with a predetermined frequency based on the user's position history information and map information. For example, the generation unit 133 identifies a place visited by the user on a specific day of the week with a predetermined frequency based on the user's position history information and map information. For example, the generation unit 133 identifies that the user visited Shibuya-ku on a weekday (any day of the week from Monday to Friday) a predetermined number of times or more within a predetermined period based on the user's position history information and map information. Next, when the generation unit 133 determines that the user has visited Shibuya-ku on weekdays a predetermined number of times or more within a predetermined period, it estimates that the user has a behavior pattern of being in Shibuya-ku on weekdays. Furthermore, when the generation unit 133 estimates that the user has a behavior pattern of being in Shibuya-ku on weekdays, it classifies the user into a segment indicating that the user is "a person in Shibuya-ku on weekdays". Furthermore, when the generation unit 133 classifies the user into a segment indicating that the user is "a person in Shibuya-ku on weekdays", it stores the user device identification information of the user device owned by the user in association with segment information indicating that the user is "a person in Shibuya-ku on weekdays" in the user information storage unit 123.

[0054] Furthermore, the generation unit 133 specifies that the user has visited the supermarket at least once a week, a predetermined number of times or more within a predetermined period. Next, when the generation unit 133 specifies that the user has visited the supermarket at least once a week within a predetermined period, the generation unit 133 estimates that the user has a behavior pattern of using the supermarket at least once a week. Furthermore, when the generation unit 133 estimates that the user has a behavior pattern of using the supermarket at least once a week, the generation unit 133 classifies the user into a segment indicating that the user is a "person who uses a supermarket at least once a week". Furthermore, when the generation unit 133 classifies the user into a segment indicating that the user is a "person who uses a supermarket at least once a week", the generation unit 133 stores the user device identification information of the user device owned by the user in association with the segment information indicating that the user is a "person who uses a supermarket at least once a week" in the user information storage unit 123.

[0055] Furthermore, the generation unit 133 generates output information based on the counting result by the counting unit 132. Specifically, the generation unit 133 generates, as the output information, information regarding the ratio of the number of users belonging to each of a plurality of segments to the total number of users. For example, the generation unit 133 generates output information 51 as shown in FIG. 6 and output information 52 as shown in FIG. 7, which will be described later, as information regarding the ratio of the number of users belonging to each of a plurality of segments to the total number of users. Note that, hereinafter, a unique user who has flowed into a website or web advertisement related to an advertiser may be referred to as a "unique contact user."

[0056] FIG. 6 is a diagram showing an example of output information according to the embodiment. The generating unit 133 generates output information 51 as shown in FIG. 6. In FIG. 6, the generating unit 133 generates output information 51 indicating that, among unique contact users who have flowed from the search site A to a website or web advertisement related to the advertiser, the ratio of users belonging to a segment indicating that they are "business people who work overtime continuously" is 75%, and the ratio of users belonging to a segment indicating that they are "long-term commuters" is 90%. In addition, the generating unit 133 generates output information 51 indicating that, among unique contact users who have flowed from the search site B to a website or web advertisement related to the advertiser, the ratio of users belonging to a segment indicating that they are "business people who work overtime continuously" is 83%, and the ratio of users belonging to a segment indicating that they are "long-term commuters" is 92%.

[0057] FIG. 7 is a diagram showing an example of output information according to the embodiment. The generating unit 133 generates output information 52 as shown in FIG. 7. In FIG. 7, the generating unit 133 generates output information 52 indicating that, among unique contact users who have visited a website or a web advertisement related to the advertiser and who belong to a segment indicating that they are "business people who work overtime all the time," the ratio of users who have visited from search site A is 60%, and the ratio of users who have visited from search site B is 30%. In addition, the generating unit 133 generates output information 52 indicating that, among unique contact users who have visited a website or a web advertisement related to the advertiser and who belong to a segment indicating that they are "long-term commuters," the ratio of users who have visited from search site A is 50%, and the ratio of users who have visited from search site B is 40%.

[0058] (About the provider 134) The providing unit 134 provides the advertiser with the output information generated by the generating unit 133. For example, the providing unit 134 transmits the output information to the advertiser device 20.

[0059] [2-3. Configuration of the detection device] Next, a configuration example of the detection device 30 according to the embodiment will be described. As shown in FIG.

[0060] (Regarding communication unit 31) The communication unit 31 is realized by, for example, a NIC etc. The communication unit 31 is connected to the network NW by wire or wirelessly, and transmits and receives information between the detection device 30 and the measurement device 100.

[0061] (Regarding the storage unit 32) The storage unit 32 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 3, the storage unit 32 has radio wave intensity 32a, number of days elapsed 32b, and staying time 32c.

[0062] (Radio wave strength 32a) The radio wave intensity 32a is a condition used by a detection unit 33b described later when detecting a target user device 10. Specifically, the radio wave intensity 32a is information on a threshold for determining whether or not to treat the user device 10 as a detection target based on the radio wave intensity in radio wave communication between the user device 10 and the detection device 30.

[0063] (Regarding the number of days passed 32b) The number of days elapsed 32b is information regarding a threshold for determining whether or not a user (user device 10) who has come into contact with a website or Web advertisement related to an advertiser is to be detected based on the number of days from when the user came into contact with the website or Web advertisement related to the advertiser to when the user visits the store.

[0064] (About stay time 32c) The staying time 32c is information about a threshold for determining whether or not a user (user device 10) who has come into contact with a Web site or Web advertisement related to an advertiser is counted based on the time spent in the store from when the user enters the store until when the user leaves the store.

[0065] (Regarding the control unit 33) The control unit 33 is realized by a CPU, an MPU, or the like executing various programs stored in a storage device inside the detection device 30 using a RAM as a working area. The control unit 33 is also realized by an integrated circuit such as an ASIC or an FPGA. As shown in Fig. 3, the control unit 33 has a receiving unit 33a and a detection unit 33b.

[0066] (Regarding the reception unit 33a) The reception unit 33a receives detection conditions used by the detection unit 33b described below when detecting the user device 10. The reception unit 33a receives detection conditions input in each field displayed on a detection condition input screen 60 (not shown). The detection condition input screen 60 (not shown) displays fields such as "radio signal strength 61," "number of days elapsed 62," "lower limit stay time 63a," "upper limit stay time 63b," "business hours (start)," "business hours (end)," and "remarks."

[0067] For example, information entered in radio wave strength 61 on the detection condition input screen 60 is stored as radio wave strength 32a. Information entered in number of days elapsed 62 is stored as number of days elapsed 32b. Information entered in lower limit stay time 63a or upper limit stay time 63b is stored as stay time 32c.

[0068] In this way, the receiving unit 33a can receive information input to the detection condition input screen 60 displayed on a terminal device, etc. Note that the number of items, item names, etc. described above are merely examples, and are not limited to the above contents.

[0069] (Regarding the detection unit 33b) When a user having the user device 10 visits an advertiser's store, the detection unit 33b detects the user device 10 using a predetermined short-range wireless communication technology (e.g., Bluetooth (registered trademark), WiFi (registered trademark), etc.). Note that although it is written as short-range wireless communication technology here, the detection unit 33b may detect the user device 10 using, for example, a GNSS positioning technology, LTE communication, etc., without being limited to short-range wireless communication.

[0070] Specifically, the detection unit 33b detects a user device 10 that satisfies the conditions of a predetermined radio wave intensity in the short-range wireless communication technology, the number of days elapsed from contact with a website or web advertisement related to a preset advertiser until the user visits the advertiser's store, and the length of stay after visiting the store. The detection unit 33b can use one or a combination of the above conditions as the detection condition.

[0071] For example, the detection unit 33b can detect that the user (user device 10) has visited the store when the radio wave strength between the user (user device 10) and the detection device 30 exceeds a predetermined threshold set in the radio wave strength 32a. The detection unit 33b can also detect that the user has visited the store when the number of days from when the user (user device 10) who has come into contact with the website or web advertisement related to the advertiser came into contact with the website or web advertisement related to the advertiser until the user comes into the store does not exceed the number of days set in the number of elapsed days 32b. The detection unit 33b can also detect that the user has visited the store when the stay time from when the user (user device 10) who has come into contact with the website or web advertisement related to the advertiser comes into the store exceeds the stay time set in the stay time 32c.

[0072] 3. Processing Procedure From here, the procedure of information processing by the measurement device 100 and the detection device 30 according to the present embodiment will be described. FIG. 8 is a flowchart showing an example of the measurement procedure according to the embodiment. First, the acquisition unit 131 acquires contact information of the user with a website or a web advertisement related to the advertiser from the user device 10 (step S101). The detection unit 33b of the detection device 30 detects the user device 10 of the user who visited the store of the advertiser after contacting the website or the web advertisement related to the advertiser (step S102). Then, the acquisition unit 131 acquires the visit information from the detection device 30. The counting unit 132 counts the number of users who visited the store of the advertiser after contacting the website or the web advertisement related to the advertiser for each segment (step S103). The generation unit 133 generates output information based on the counting result by the counting unit 132 (step S104). The provision unit 134 presents the output information generated by the generation unit 133 to the advertiser (step S105).

[0073] [4. Effects] As described above, the measurement device 100 according to this embodiment includes a memory unit 120, an acquisition unit 131, and a counting unit 132. The memory unit 120 stores segment information on users belonging to each of a plurality of segments. The acquisition unit 131 acquires user information on user devices 10 owned by users who have visited an advertiser's store. The counting unit 132 counts the number of users who have visited the advertiser's store after coming into contact with a website or web advertisement related to the advertiser, for each of a plurality of segments, based on the segment information and the user information. This enables the measurement device 100 to provide the advertiser with information on the segment to which the users who have come into contact with the website or web advertisement related to the advertiser belong.

[0074] The counting unit 132 also identifies inflow information related to the inflow path to the website or web advertisement based on the query string identified from the user information, and counts the number of users for each inflow information. This enables the measurement device 100 to provide the advertiser with information related to the inflow path of users who came into contact with the website or web advertisement related to the advertiser.

[0075] Moreover, the measurement device 100 according to this embodiment further includes a generation unit 133 and a provision unit 134. The generation unit 133 generates output information based on the counting result by the counting unit 132. The provision unit 134 provides the output information generated by the generation unit 133 to the advertiser. This enables the measurement device 100 to provide the advertiser with information on a website related to the advertiser or a segment to which a user who has come into contact with a web advertisement belongs.

[0076] Furthermore, the generating unit 133 generates, as output information, information on the ratio of the number of users belonging to each of a plurality of segments to the total number of users. This enables the measuring device 100 to provide the advertiser with information on the ratio of the segments to which the users who have come into contact with the advertiser's website or web advertisement belong.

[0077] Furthermore, the generation unit 133 generates segment information based on the location information of the user device 10. For example, the generation unit 133 estimates information on the places visited by the user, the user's stay time at the visited places, and the visit time or visit frequency at which the user visited the visited places based on the location history information of the user device 10, and generates segment information based on the information on the visited places, the stay time, the visit time, or the visit frequency. This enables the measurement device 100 to provide the advertiser with information on the segment of users who have come into contact with a website or Web advertisement related to the advertiser, for example, on the behavior pattern of the user estimated based on the user's location information.

[0078] Furthermore, the generation unit 133 estimates movement information related to a movement route along which the user moves with a predetermined frequency and a movement time required for the user to move along the movement route based on the location history information of the user device 10, and generates segment information based on the movement information. This enables the measurement device 100 to provide the advertiser with information related to a segment of users who have come into contact with a website or Web advertisement related to the advertiser, for example, a segment related to a movement pattern of the user estimated based on the user's location information.

[0079] [5. Hardware Configuration] The measuring device 100 or the detection device 30 included in the advertising effect measurement system 1 described above is realized, for example, by a computer 1000 configured as shown in FIG. 9. The measuring device 100 will be described below as an example. FIG. 9 is a hardware configuration diagram showing an example of a computer that realizes the functions of the measuring device 100 according to this embodiment. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD 1400, a communication interface (communication I / F) 1500, an input / output interface (input / output I / F) 1600, and a media interface (media I / F) 1700.

[0080] The CPU 1100 operates and controls each unit based on a program stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, programs that depend on the hardware of the computer 1000, and the like.

[0081] The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, etc. The communication interface 1500 receives data from other devices via a predetermined network NW and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined network NW.

[0082] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0083] The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0084] For example, when the computer 1000 functions as the measuring device 100, the CPU 1100 of the computer 1000 realizes the function of the control unit by executing programs loaded onto the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined network NW.

[0085] Furthermore, for example, when the computer 1000 functions as the measuring device 100, the CPU 1100 of the computer 1000 executes a program loaded onto the RAM 1200 to realize the functions of the control unit.

[0086] [6. Other] Furthermore, among the processes described in each of the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0087] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0088] Furthermore, the above-described embodiments can be appropriately combined as long as the processing contents are not contradictory.

[0089] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be obtained.

[0090] Although some of the embodiments of the present invention have been described in detail above with reference to the drawings, these are merely examples, and it is possible to implement the present invention in other forms that include various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section. [Explanation of symbols]

[0091] 1. Advertising effectiveness measurement system 10 User equipment 20 Advertiser Equipment 30 Detection Device 31 Communications Department 32 Storage section 33 Control Unit 33a Reception 33b Detection unit 100 Measuring Equipment 110 Communications Department 120 Storage section 121 Contact / Visit Information Database 122 Counting condition memory section 123 User information storage unit 130 Control section 131 Acquisition Department 132 Counting Department 133 Generation part 134 Provision Department

Claims

1. A storage unit that stores segment information regarding users belonging to each of a plurality of segments; an acquisition unit that acquires user information related to a user device owned by a user who visits the advertiser's store; a counting unit that counts the number of users who visited a store of the advertiser after contacting a website or a web advertisement related to the advertiser, for each of the plurality of segments, based on the segment information and the user information; A measuring device comprising:

2. The counting unit is Identifying inflow information regarding an inflow path to the website or the web advertisement based on a query string identified from the user information, and counting the number of users for each of the inflow information; 2. The measuring device according to claim 1 .

3. a generation unit that generates output information based on a counting result by the counting unit; a providing unit for providing the output information generated by the generating unit to the advertiser; The measurement device according to claim 1 , further comprising:

4. The generation unit is generating, as the output information, information regarding the ratio of the number of users belonging to each of the plurality of segments to the total number of users; 4. The measuring device according to claim 3.

5. A generation unit that generates the segment information based on location information of the user device. The measurement device according to claim 1 , further comprising:

6. The generation unit is Based on the location history information of the user device, estimate information regarding a place visited by the user, a stay time of the user at the visited place, a visit time or a visit frequency at which the user visited the visited place, and generate the segment information based on the information regarding the visited place, the stay time, the visit time or the visit frequency.

6. The measuring device according to claim 5.

7. The generation unit is estimating travel information relating to a travel route along which the user travels with a predetermined frequency and a travel time required for the user to travel along the travel route based on location history information of the user device, and generating the segment information based on the travel information; 6. The measuring device according to claim 5.

8. a storage step of storing segment information regarding users belonging to each of the plurality of segments in a storage unit; An acquisition step of acquiring user information related to a user device owned by a user who has visited the advertiser's store; a counting step of counting the number of users who visited a store of the advertiser after contacting a website or a web advertisement related to the advertiser, for each of the plurality of segments, based on the segment information and the user information; Measurement methods including.

9. a storage step of storing segment information regarding users belonging to each of a plurality of segments in a storage unit; An acquisition step of acquiring user information related to a user device owned by a user who visits the advertiser's store; a counting step of counting the number of users who visited a store of the advertiser after contacting a website or a web advertisement related to the advertiser, for each of the plurality of segments, based on the segment information and the user information; A measurement program for causing a measurement device to execute the above.

Images