Information processor, information processing method, and information processing program

Abstract

To optimize an advertising approach when delivering an advertisement to a target user according to an advertising purpose.SOLUTION: An information processor comprises a classification part and a distribution part. The classification part classifies an object person into one of several hierarchical stages that the object person transitions through before reaching an advertising conversion according to behavior information of the object person, who is a service user using an online service and who may be a distribution destination of the advertisement. The distribution part distributes the advertisement to the object person using the advertising approach predetermined for each of the stages.SELECTED DRAWING: Figure 4

Description

[Technical Field]

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

[0002] In recent years, technologies for delivering advertisements with the aim of obtaining a predetermined conversion have become known. One example of such a technology is a technology that estimates a user's attribute profile using a reference profile based on the user's known attribute information and expression history, and provides advertisement information based on the estimated user's attribute profile (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 4808207 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional techniques have room for improvement in terms of optimizing the advertising method when providing advertisements to target users in accordance with the purpose of advertising.

[0005] The present application has been made in view of the above, and aims to optimize advertising methods when providing advertisements to target users in accordance with the purpose of advertising. [Means for solving the problem]

[0006] The information processing device according to the present application includes a classification unit and a distribution unit. The classification unit classifies targets who are service users of online services and who may be recipients of advertisements into one of a plurality of hierarchical levels through which the targets transition before converting to the advertisements, based on behavioral information of the targets. The distribution unit distributes advertisements to the targets using advertising methods that are preset for each of the plurality of levels. [Effects of the Invention]

[0007] According to one aspect of the embodiment, it is possible to optimize the advertising method when providing an advertisement depending on the purpose of advertising to a target user. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of information processing according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of the system configuration of the information processing system according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of advertisement information stored in the advertisement information DB according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of user information stored in a user information DB according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of table information stored in the advertising method determination table according to the embodiment. [Figure 8] FIG. 8 is a flowchart illustrating an example of a procedure of information processing executed by the information processing device according to the embodiment. [Figure 9] FIG. 9 is a diagram showing an example of table information stored in the advertising method determination table according to the modified example. [Figure 10]FIG. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, modes for implementing an information processing device, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to these embodiments. Furthermore, the respective embodiments can be appropriately combined within the scope of not causing any contradiction in the processing content. Furthermore, the same components in the following embodiments will be assigned the same reference numerals, and redundant explanations will be omitted.

[0010] [Embodiment] [1. An example of information processing] An example of information processing according to the embodiment will be described below with reference to the drawings: Figures 1 and 2 are diagrams for explaining an example of information processing according to the embodiment.

[0011] As shown in FIG. 1, the information processing according to the embodiment is realized by an information processing system SYS including a plurality of terminal devices 10, a service providing device 20, and an information processing device 100.

[0012] 1 executes information processing according to the embodiment. For example, the information processing device 100 provides advertisements to a service user U who is a user of an online service. The information processing device 100 is realized by, for example, one or more servers or a cloud system.

[0013] 1, the information processing device 100 acquires user information about a service user U from the service providing device 20. The user information includes behavioral information indicating the content of the behavior of the service user U in the online service and attribute information indicating the attributes of the service user U. The information processing device 100 uses the user information acquired from the service providing device 20 to execute information processing according to the embodiment, as described below.

[0014] First, the information processing device 100 classifies a service user U who uses an online service and is the target of the advertisement into one of multiple hierarchical levels through which the target person transitions before converting to the advertisement, based on behavioral information of the target person (step S1).

[0015] An advertising conversion is the final result achieved on the web by the advertising content submitted by the advertiser. For example, a conversion can include the purchase of a specific product, a request for information, or browsing a specific website. The content of the conversion can be determined at the discretion of the advertiser.

[0016] Then, the information processing device 100 distributes advertisements to the target person using an advertising method that is set in advance for each of a plurality of layers (step S2). Hereinafter, the information processing according to the embodiment will be specifically described with reference to FIG.

[0017] First, the information processing device 100 extracts, from among a plurality of service users U, targets to whom advertisements are to be distributed.

[0018] For example, the information processing device 100 may refer to attribute information regarding the psychographic attributes of the service user U and extract as a target a service user U who is presumed to have an interest in the category to which the transaction object, such as a product or service displayed in the advertisement, belongs.

[0019] Next, based on the extracted behavioral information of the target person, the information processing device 100 classifies the target person into one of a "latent layer," a "manifest layer," or a "prospect layer," which are pre-defined as multiple hierarchical levels through which the target person transitions before reaching conversion of the advertisement.

[0020] The "potential demographic" is a tier into which people who are interested in the category of the product displayed in the advertisement, but have not yet taken any concrete action such as gathering information about the product, are classified. The "potential demographic" is an example of the "third tier."

[0021] The "manifest layer" is a layer into which subjects who are taking specific actions, such as gathering information about the category to which the product displayed in the advertisement belongs. The "manifest layer" is an example of the "second layer."

[0022] The "prospective layer" is a layer into which subjects who take more specific actions than subjects classified as the "actual layer," such as gathering information about the product itself advertised or other products of the same type as the product advertised, are classified. The "prospective layer" is an example of the "first layer."

[0023] The volume of subjects classified into the "latent layer," "actual layer," and "prospect layer" (i.e., the number of applicable subjects) becomes smaller as the transition progresses from "latent layer" to "actual layer" to "prospect layer." Note that the multiple hierarchies into which subjects are classified are not limited to the example shown in Figure 2, and the "actual layer" and "prospect layer" may be configured as the same layer and constitute a single layer.

[0024] The information processing device 100 can classify the target into one of the "latent demographic," "actual demographic," or "prospective demographic" by evaluating the similarity between the characteristics of the behavior of a person who has completed a conversion for an advertisement related to the same transaction object as the transaction object displayed in the advertisement and the characteristics of the target's behavior.

[0025] For example, the information processing device 100 classifies, among the subjects, subjects having behavioral characteristics similar to the behavioral characteristics of successful users during a predetermined period from a first time point predating the completion of conversion by a predetermined period to the completion of conversion, into a "prospective group" who are expected to convert. Furthermore, the information processing device 100 classifies, among the subjects, subjects having behavioral characteristics similar to the behavioral characteristics of successful users during a predetermined period from a second time point predating the first time point by a predetermined period to the first time point, into a "potential group" who are expected to transition to the "prospective group". Furthermore, the information processing device 100 classifies, among the subjects, subjects who are not classified into the "prospective group" or the "potential group" into a "latent group" who are expected to transition to the "potential group".

[0026] An example of determining the similarity of behavioral characteristics will be described. Based on the search history of a service user U who is a proven user, the information processing device 100 generates statistical information indicating the trend of search queries in a first interval from a first time point to a conversion completion time point and the trend of search queries in a second interval from a second time point to the first time point.

[0027] Furthermore, based on the generated statistical information and the search history of the subject, the information processing device 100 compares the search queries entered by the performer in the first interval with the search queries entered by the subject, and calculates the match rate of the search queries in the first interval. Similarly, the information processing device 100 compares the search queries entered by the performer in the second interval with the search queries entered by the subject, and calculates the match rate of the search queries in the second interval. Note that search queries meaning the same thing or similar search queries may be included in the match.

[0028] Then, if the matching rate of the search query in the first section is higher than the matching rate of the search query in the second section, the information processing device 100 classifies the subject into the "prospective demographic." On the other hand, if the matching rate of the search query in the first section is lower than the matching rate of the search query in the second section, the information processing device 100 classifies the subject into the "potential demographic."

[0029] Furthermore, if the match rate of the search query in the first section and the match rate of the search query in the second section are the same, the information processing device 100 may classify the subject into a "prospective demographic" or an "expected demographic" based on the number of matches of the search query. For example, if the number of matches of the search query in the first section is greater than the number of matches of the search query in the second section, the information processing device 100 classifies the subject into a "prospective demographic." On the other hand, if the number of matches of the search query in the first section is less than the number of matches of the search query in the second section, the information processing device 100 classifies the subject into a "expected demographic."

[0030] Furthermore, if the matching rate of the search query in the first section and the matching rate of the search query in the second section are the same, the information processing device 100 may classify the target person into a "prospective demographic" or a "potential demographic" based on the tendency of the browsing history, which is other behavioral information of the successful service user U. For example, the information processing device 100 classifies the target person into a "prospective demographic" if the browsing frequency of the website of the business providing the product displayed in the advertisement exceeds a predetermined threshold or if the number of browsing times is on the rise.

[0031] Furthermore, the information processing device 100 classifies subjects who are not classified into the "prospective demographic" or the "potential demographic" into the "latent demographic." In this way, the information processing device 100 can classify subjects into any of the "potential demographic," "potential demographic," and "prospective demographic."

[0032] Returning to Figure 2, the "latent demographic" and the "actual demographic" are associated with advertising methods MA that are set with the goal of stimulating interest. Display advertising is an example of an advertising method that aims to stimulate interest. Also, as shown in Figure 2, the "prospective demographic" is associated with advertising methods MA and MB that are set with the goal of obtaining conversions. Examples of advertising methods that aim to obtain conversions include search advertising, display advertising, and retargeting advertising. Note that Figure 2 shows an example in which multiple advertising methods are set as advertising methods corresponding to the "prospective demographic," but this example is not limiting, and a single advertising method may also be associated with the "prospective demographic."

[0033] The information processing device 100 distributes advertisements related to the target product to be advertised to the target persons classified into the "latent demographic" and the "actual demographic" by the advertising method MA.

[0034] For example, the information processing device 100 delivers advertisements for target products by transmitting advertising information to the target users' terminal devices 10 to display advertisements for the target products as images, videos, text, etc. in advertising spaces on the screens of websites and applications viewed by the target users classified as the "latent demographic" and "actual demographic."

[0035] In addition, when delivering advertisements to targets classified into the "latent demographic" and the "actual demographic," the information processing device 100 may select targets from among the targets classified into the "latent demographic" and the "actual demographic" who resemble the iconic image of such targets, and deliver advertisements to the selected targets.

[0036] Furthermore, the information processing device 100 distributes advertisements related to the target product to be advertised to the target persons classified as the "prospective demographic" by the advertising method MA and the advertising method MB.

[0037] For example, when a target person classified as the "prospect group" performs a keyword search in a search engine by entering the product name of the target product that is the subject of the advertisement, the information processing device 100 delivers an advertisement for the target product by sending advertising information to the target person's terminal device 10 to display an advertisement for the target product in text on the search result screen.

[0038] Furthermore, for example, if a target person classified as a "prospective demographic" has a history of visiting the web page of the product advertised, the information processing device 100 delivers an advertisement for the target product by sending advertising information to the target person's terminal device 10 to display an advertisement for the target product in the form of images, videos, text, etc. in the advertising space of the website viewed by the target person.

[0039] In this way, the information processing device 100 according to the embodiment delivers advertisements using an advertising method that is set in advance according to the purpose of the advertisement for each hierarchical level into which target users to whom the advertisements are to be delivered are classified. This makes it possible to optimize the advertising method used when providing advertisements to target users according to the purpose of advertising.

[0040] [2. System Configuration] The configuration of the information processing system SYS according to the embodiment will be described in detail below with reference to Fig. 3. Fig. 3 is a diagram showing an example of the system configuration of the information processing system SYS according to the embodiment.

[0041] As shown in FIG. 3, the information processing system SYS according to the embodiment includes a plurality of terminal devices 10, a service providing device 20, and an information processing device 100.

[0042] The terminal device 10, the service providing device 20, and the information processing device 100 are connected to a network N by wire or wirelessly. Each of the terminal device 10, the service providing device 20, and the information processing device 100 can communicate with other devices via the network N.

[0043] The network N includes, for example, a WAN (Wide Area Network) such as the Internet, and mobile communication networks such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation: fifth generation mobile communication system).

[0044] The terminal device 10 connects to the network N via short-range wireless communication such as a mobile communication network, Bluetooth (registered trademark), or wireless LAN (Local Area Network), and can communicate with other devices such as the service providing device 20 and the information processing device 100 through the network N.

[0045] The terminal device 10 is used by a service user U (see FIG. 1, for example) of various online services provided by the service providing device 20. Each of the multiple terminal devices 10 is used by a different service user U.

[0046] The terminal device 10 is, for example, a notebook PC (Personal Computer), a desktop PC, a smartphone, a tablet PC, or a wearable device. Examples of wearable devices include, but are not limited to, smart glasses and smart watches.

[0047] A service user U using a terminal device 10 can use various online services by operating the terminal device 10 to access the service providing device 20. For example, the terminal device 10 can display web content provided by the service providing device 20 using a web browser or an application. When the terminal device 10 receives control information for realizing information display processing from the service providing device 20 or the like, the terminal device 10 realizes the display processing in accordance with the control information.

[0048] The service providing device 20 provides various online services to the service user U. For example, the online services provided to the service user U may include a search service, a travel information providing service, a social networking service (SNS), an e-commerce service, an electronic payment service, an online game, an online banking service, an online trading service, a hotel reservation service, a ticket reservation service, a video distribution service, a music distribution service, a news distribution service, a map information service, a route search service, a route guidance service, a line information service, an operation information service, a weather information service, and a question service. The various online services may also include an API (Application Programming Interface) service corresponding to various applications.

[0049] The service providing device 20 is typically a server device, but may also be realized by a mainframe, a workstation, etc. Furthermore, when the service providing device 20 is realized by a server device, it may be realized by a single server device, or may be realized by a cloud system in which multiple server devices and multiple storage devices operate in cooperation with each other.

[0050] The information processing device 100 executes information processing according to the embodiment. The information processing device 100 is typically a server device, but may be realized by a mainframe, a workstation, or the like. Furthermore, when the information processing device 100 is realized by a server device, it may be realized by a single server device, or may be realized by a cloud system in which multiple server devices and multiple storage devices operate in cooperation with each other. The processing function units that the information processing device 100 has for realizing the information processing according to the embodiment will be described later.

[0051] [3. Equipment configuration] An example of the functional configuration of the information processing device 100 included in the information processing system SYS according to the embodiment will be described below with reference to Fig. 4. Fig. 4 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 4, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

[0052] (Communication unit 110) The communication unit 110 is realized by, for example, a communication module or a network interface card (NIC). The communication unit 110 is connected to a network N by wire or wirelessly. The information processing device 100 transmits and receives information to and from other devices such as the terminal device 10 and the service providing device 20 via the network N.

[0053] (Storage unit 120) The storage unit 120 stores, for example, programs and data used for control and calculation by the control unit 130. For example, the storage unit 120 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. For example, the storage unit 120 has an advertisement information DB 121, a user information DB 122, and an advertising method determination table 123. Note that the storage unit 120 is not particularly limited to the example shown in FIG. 4 and can store data and the like required for executing the information processing according to the embodiment as appropriate.

[0054] (Advertising Information DB121) The advertisement information DB 121 stores advertisement information about advertisements to be distributed. Fig. 5 is a diagram showing an example of advertisement information stored in the advertisement information DB 121 according to the embodiment.

[0055] 5, the advertisement information stored in the advertisement information DB 121 according to the embodiment has a plurality of items such as an "advertiser" item, an "advertising ID" item, an "content information" item, and an "conversion content" item. These items in the advertisement information are associated with each other.

[0056] The "advertiser" field stores identification information for identifying the advertiser. The "advertising ID" field stores identification information for identifying the advertising content submitted by the advertiser.

[0057] The "content information" field stores information indicating a storage location of advertising content data. The "conversion details" field stores information indicating the details of conversion set by the advertiser.

[0058] 5 shows an example of advertisement information stored in the advertisement information DB 121, which may store information related to metrics targeted by advertisements. These metrics include metrics related to clicks, such as "number of impressions," "number of clicks," "CTR (Click Through Rate)," and "CPC (Cost Per Click)," and metrics related to conversions, such as "CPA (Cost Per Action)" and "CVR (Conversion Rate)."

[0059] (User information DB122) The user information DB 122 stores user information related to service users U of various online services. The user information stored in the user information DB 122 is acquired by the information processing device 100 from the service providing device 30. Fig. 6 is a diagram showing an example of user information stored in the user information DB 122 according to the embodiment.

[0060] 6, the user information stored in the user information DB 122 has multiple items such as a "user ID" item, a "behavioral information" item, and a "attribute information" item. These items in the user information are associated with each other.

[0061] In the "user ID" field, identification information for uniquely identifying the service user U is stored.

[0062] The "behavioral information" field stores behavioral information about the behavior of the service user U in various online services, such as search history, browsing history, and purchase history.

[0063] The behavioral information stored in the "behavioral information" section may include search queries entered by the service user U in the search engines of various online services, information on the search date and time, etc. The behavioral information may also include behavioral history such as input and selection on a website, the length of time the website was visited (i.e., the time until leaving), and behavioral history such as whether the website led to the purchase of a product or the use of a service.

[0064] The "Attribute Information" item stores attribute information regarding the attributes of service user U in various online services. Attribute information includes information regarding demographic attributes and information regarding psychographic attributes. Information regarding demographic attributes includes information regarding demographic attributes such as name, age, gender, occupation, annual household income, place of residence, and type of housing. Information regarding psychographic attributes includes information regarding psychological attributes such as service user U's interests and concerns, such as travel, clothing, cars, and religion, as well as lifestyle, thoughts, and thought trends.

[0065] (Advertising method determination table 123) Table information to be referenced when determining an advertising method is stored in the advertising method determination table 123. Fig. 7 is a diagram showing an example of table information stored in the advertising method determination table 123 according to the embodiment.

[0066] 7, the table information stored in advertising method determination table 123 has a plurality of items such as a "hierarchy" item and an "advertising method" item. These items in the table information are associated with each other.

[0067] The "Layer" field stores information indicating the layer into which the target users to whom the advertisement is to be delivered are classified. The "Advertising Method" field stores information indicating the advertising method to be used when delivering the advertisement to the target users.

[0068] The information indicating the advertising method stored in the "advertising method" field may be dynamically changed by the administrator of the information processing device 100.

[0069] (control unit 130) The control unit 130 is a controller, and is realized by a CPU (Central Processing Unit), MPU (Micro Processing Unit), etc., executing various programs (examples of "information processing programs") stored in a storage device inside the information processing device 100 using RAM as a working area.

[0070] Furthermore, the control unit 130 may be realized by an integrated circuit such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a general purpose graphic processing unit (GPGPU).

[0071] As shown in FIG. 4, the control unit 130 has an extraction unit 131, a classification unit 132, and a distribution unit 133, and these units realize or execute the functions and actions of the information processing described below.

[0072] Note that control unit 130 may have an internal configuration divided into multiple processing units that realize or execute the information processing functions and actions described below. Also, control unit 130 is not limited to the configuration shown in Fig. 4, and may have other configurations as long as they perform the information processing described below, and may have other functional units other than those shown in Fig. 4.

[0073] (Extraction part 131) The extraction unit 131 extracts, from among a plurality of service users U, target persons to whom the advertisement is to be distributed. For example, the extraction unit 131 refers to attribute information relating to the psychographic attributes of the service users U stored in the user information DB 122, and extracts, as target persons, service users U who are presumed to have an interest in a category to which the transaction object, such as a product or service displayed in the advertisement, belongs.

[0074] (Classification section 132) The classification unit 132 classifies the target into one of a plurality of hierarchical levels through which the target moves until conversion of the advertisement, based on the behavioral information of the target extracted by the extraction unit 131. For example, the classification unit 132 classifies the target into one of a "latent level," a "visited level," or a "prospect level," which are preset as a plurality of levels.

[0075] In addition, the classification unit 132 can classify the target person into one of multiple hierarchies by evaluating the similarity between the characteristics of the behavior of a service user U who has completed a conversion for an advertisement related to the same transaction object as the transaction object displayed in the advertisement and the characteristics of the target person's behavior until the completion of the conversion.

[0076] For example, the classification unit 132 classifies, among the subjects, subjects having behavioral characteristics similar to those of successful users during a predetermined period from a first time point, which is a predetermined period prior to the completion of conversion, to the time of completion of conversion, into a "prospective group" who are expected to complete conversion. Furthermore, the classification unit 132 classifies, among the subjects, subjects having behavioral characteristics similar to those of successful users during a predetermined period from a second time point, which is a predetermined period prior to the first time point, to a "potential group" who are expected to transition to the "prospective group." Furthermore, the classification unit 132 classifies, among the subjects, subjects who are not classified into the "prospective group" or the "potential group" into a "latent group" who are expected to transition to the "potential group."

[0077] An example of determining the similarity of behavioral characteristics by the classification unit 132 will be described. Based on the search history of the service user U who is a successful user, the classification unit 132 generates statistical information indicating the trend of search queries in a first interval from a first time point to a time point at which conversion is completed, and the trend of search queries in a second interval from a second time point to the first time point.

[0078] Furthermore, based on the generated statistical information and the search history of the subject, the classification unit 132 compares the search queries entered by the performers in the first interval with the search queries entered by the subject, and calculates the match rate of the search queries in the first interval. Similarly, the classification unit 132 compares the search queries entered by the performers in the second interval with the search queries entered by the subject, and calculates the match rate of the search queries in the second interval. Note that search queries meaning the same thing or similar search queries may be included in the match.

[0079] Then, if the matching rate of the search query in the first interval is higher than the matching rate of the search query in the second interval, the classification unit 132 classifies the target person into the "prospect layer." On the other hand, if the matching rate of the search query in the first interval is lower than the matching rate of the search query in the second interval, the classification unit 132 classifies the target person into the "potential layer."

[0080] Furthermore, if the matching rate of the search query in the first section and the matching rate of the search query in the second section are the same, the classification unit 132 may classify the target person into a "prospective demographic" or an "expected demographic" based on the number of matches of the search query. For example, if the number of matches of the search query in the first section is greater than the number of matches of the search query in the second section, the classification unit 132 classifies the target person into a "prospective demographic." On the other hand, if the number of matches of the search query in the first section is less than the number of matches of the search query in the second section, the classification unit 132 classifies the target person into a "expected demographic."

[0081] Furthermore, if the matching rate of the search query in the first section and the matching rate of the search query in the second section are the same, the classification unit 132 may classify the target person into a "prospective group" or an "expected group" based on the tendency of the browsing history, which is other behavioral information of the successful service user U. For example, the information processing device 100 classifies the target person into a "prospective group" if the browsing frequency of the website of the business that provides the product displayed in the advertisement exceeds a predetermined threshold or if the number of browsing times is on the rise.

[0082] (Distribution Section 133) The distribution unit 133 refers to the table information stored in the advertising method determination table 123, and distributes advertisements to the target person using the advertising methods set in advance for each of the multiple layers.

[0083] For example, the distribution unit 133 distributes advertisements to targets classified as the "prospective demographic" by a plurality of advertising methods that are set for the "prospective demographic" and that aim to obtain conversions.

[0084] Specifically, when a target person classified as the "prospect group" performs a keyword search in a search engine by entering the product name of the target product that is the subject of the advertisement, the distribution unit 133 distributes an advertisement for the target product by sending advertising information for displaying an advertisement for the target product in text form on the search result screen to the target person's terminal device 10 via the communication unit 110.

[0085] Furthermore, for example, if a target person classified as a "prospect" has a history of visiting the web page of the product advertised, the distribution unit 133 distributes an advertisement for the target product by transmitting advertising information for displaying the advertisement for the target product in the form of images, videos, text, etc. in the advertising space of the website viewed by the target person to the target person's terminal device 10 via the communication unit 110.

[0086] In addition, the distribution unit 133 distributes advertisements to each of the targets classified as the "manifest layer" and the targets classified as the "latent layer" using an advertising method that is set for the "manifest layer" and the "latent layer" and that aims to stimulate interest.

[0087] Specifically, the distribution unit 133 distributes advertisements for the target products by transmitting, via the communication unit 110, advertising information for displaying advertisements for the target products as images, videos, text, etc. in advertising spaces on the screens of websites and applications viewed by the targets classified as the "latent demographic" and the "actual demographic" to the target devices 10 of the targets.

[0088] 4. Processing Procedure According to the Embodiment Hereinafter, the procedure of information processing executed by the information processing device 100 according to the embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of the procedure of information processing executed by the information processing device 100 according to the embodiment. The processing procedure shown in Fig. 8 is executed by the control unit 130 of the information processing device 100. The processing procedure shown in Fig. 8 is repeatedly executed while the information processing device 100 is operating.

[0089] As shown in FIG. 8, the extraction unit 131 extracts, from among the service users U, targets to whom advertisements are to be distributed (step S101).

[0090] Furthermore, the classification unit 132 classifies the target into one of a plurality of hierarchical levels through which the target transitions until the target conversions to the advertisement, based on the behavioral information and attribute information of the target extracted by the extraction unit 131 (step S102).

[0091] Furthermore, the distribution unit 133 distributes advertisements to the target person using the advertising methods set in advance for each of the multiple hierarchical levels (step S103), and ends the processing procedure shown in FIG.

[0092] [5. Modifications] In the above-described information processing, an example has been described in which the distribution unit 133 distributes advertisements to targets using advertising methods that are preset for each of a plurality of hierarchical levels, but the present invention is not limited to this example. For example, the distribution unit 133 may distribute advertisements to targets using advertising methods that are preset for each of a plurality of hierarchical levels, depending on the content of conversion. Table information stored in the advertising method determination table 123 according to a modified example will be described below with reference to FIG. 9. FIG. 9 is a diagram illustrating an example of table information stored in the advertising method determination table 123 according to a modified example.

[0093] As shown in Fig. 9, the advertising method determination table according to the modified example stores information indicating an advertising method that is preset for each hierarchical level in association with the content of the conversion. When distributing an advertisement, the distribution unit 133 refers to the advertising information stored in the advertising information DB 121 and checks the conversion content of the advertisement to be distributed. Furthermore, the distribution unit 133 identifies, for each hierarchical level, the advertising method that is associated with the conversion content of the advertisement to be distributed in the advertising method determination table. Then, the distribution unit 133 uses the identified advertising method to distribute the advertisement to each of the target persons classified into each hierarchical level.

[0094] In the above embodiment, an example has been described in which the information processing system SYS is configured to include the service providing device 20 and the information processing device 100, but this is not limiting. For example, the information processing system SYS may be configured to include, instead of the service providing device 20 and the information processing device 100, a single server device that physically and functionally integrates the service providing device 20 and the information processing device 100.

[0095] [6. Hardware Configuration] Moreover, the information processing device 100 according to the above-described embodiment and modifications is realized, for example, by a computer 1000 configured as shown in Fig. 10. Fig. 10 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 100 according to the embodiment and each modification.

[0096] The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which an arithmetic unit 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected by a bus 1090.

[0097] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The primary storage device 1040 is a memory device, such as a RAM, that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), HDD, flash memory, or the like.

[0098] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface), etc. The input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, and scanner, and is realized by, for example, USB.

[0099] The input device 1020 may be a device that reads information from an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be an external storage medium such as a USB memory.

[0100] The network IF 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0101] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0102] For example, when the computer 1000 functions as the information processing device 100 according to the embodiment, the arithmetic device 1030 of the computer 1000 executes a program (for example, an information processing program) loaded onto the primary storage device 1040, thereby realizing the same functions as the control unit 130. That is, the arithmetic device 1030 cooperates with the program (for example, an information processing program) loaded onto the primary storage device 1040 to realize the processing by the information processing device 100 according to the embodiment.

[0103] [7. Other] Of the processes described in 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 using 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 as desired unless otherwise specified.

[0104] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0105] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0106] The above describes in detail the embodiments of the present application based on several drawings, but these are merely examples, and the present invention can be implemented in other forms that include the embodiments described in the Disclosure of the Invention section and that have been modified and improved in various ways based on the knowledge of those skilled in the art.

[0107] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit," etc. For example, a control section can be read as control means or a control circuit.

[0108] [8. Effects] The information processing device 100 according to the embodiment includes a classification unit 132 and a distribution unit 133. The classification unit 132 classifies targets who are service users who use online services and who may be recipients of advertisements into one of a "latent target," a "promising target," or a "prospective target," which are preset as multiple hierarchical levels through which targets transition before converting to the advertisement, based on behavioral information of the targets. The distribution unit 133 distributes advertisements to targets using advertising methods preset for each of the multiple hierarchical levels.

[0109] In addition, the classification unit 132 may classify the target person into one of multiple hierarchies by evaluating the similarity between the characteristics of the behavior of a person who has completed a conversion for an advertisement related to the same transaction object as the transaction object displayed in the advertisement and the characteristics of the target person's behavior.

[0110] In addition, the classification unit 132 may classify subjects who have behavioral characteristics similar to the behavioral characteristics of successful candidates during a specified period from a first point in time predating the completion of conversion by a specified period to the completion of conversion into a "prospective group" who are expected to complete conversion, classify subjects who have behavioral characteristics similar to the behavioral characteristics of successful candidates during a specified period from a second point in time predating the first point in time to the first point in time into a "manifest group" who are expected to transition to the "prospective group," and classify subjects who are not classified into the "prospective group" or "manifest group" into a "latent group" who are expected to transition to the "manifest group."

[0111] As described above, the information processing device 100 according to the embodiment has the above-described characteristic configuration, and executes advertisement delivery using an advertising method that is set in advance according to the purpose of the advertisement for each hierarchical level into which target users to whom the advertisement is to be delivered are classified. This makes it possible to optimize the advertising method when providing an advertisement according to the purpose of advertising to target users.

[0112] Furthermore, the distribution unit 133 may distribute advertisements to the target person using advertising methods that are set in advance for each of a plurality of hierarchical levels according to the content of the conversion. This allows the information processing device 100 to change the advertising method according to the content of the conversion even for the same hierarchical level.

[0113] Furthermore, the above-described effects can also be realized by the processing executed by each of the above-described units, or by any combination of the processing executed by each unit. [Explanation of symbols]

[0114] SYS Information Processing System N Network 10 Terminal Equipment 20 Service providing device 100 Information processing device 110 Communications Department 120 Storage section 121 Advertising Information DB 122 User information DB 123 Advertising Method Decision Table 130 Control Unit 131 Extraction part 132 Classification Department 133 Distribution Department

Claims

1. a classification unit that classifies target persons, who are service users who use online services and who may be recipients of advertisements, into one of a plurality of hierarchical levels through which the target persons transition until they convert on the advertisement, based on behavioral information of the target persons; a distribution unit that distributes advertisements to the target persons using advertising methods that are set in advance for each of the plurality of hierarchical levels; An information processing device comprising:

2. The classification unit The target person is classified into one of the plurality of classes by evaluating the similarity between the characteristics of the behavior of a person who has completed the conversion in response to an advertisement relating to the same transaction object as the transaction object displayed in the advertisement and the characteristics of the target person's behavior.

2. The information processing apparatus according to claim 1, wherein:

3. The classification unit Among the subjects, those who have behavioral characteristics similar to the behavioral characteristics of the achiever during a predetermined period from a first point in time predating the completion of the conversion by a predetermined period to the completion of the conversion are classified into a first tier where the conversion is expected to be completed, those who have behavioral characteristics similar to the behavioral characteristics of the achiever during a predetermined period from a second point in time predating the first point in time to the first point in time are classified into a second tier where the transition to the first tier is expected, and those who are not classified into the first tier or the second tier are classified into a third tier where the transition to the second tier is expected, The distribution unit Advertisements are delivered to the target persons classified in the first tier by a plurality of advertising methods that are set in the first tier and that aim to acquire the conversions, and advertisements are delivered to the target persons classified in the second tier and the target persons classified in the third tier by advertising methods that are set in the second tier and that aim to stimulate interest.

3. The information processing apparatus according to claim 2, wherein:

4. The distribution unit According to the content of the conversion, an advertisement is delivered to the target person using an advertisement method that is set in advance for each of the plurality of layers.

2. The information processing apparatus according to claim 1, wherein:

5. 1. A computer-implemented information processing method, comprising: a classification step of classifying target persons, who are service users who use an online service and who may be recipients of an advertisement, into one of a plurality of hierarchical levels through which the target persons transition until they convert on the advertisement, based on behavioral information of the target persons; a distribution step of distributing advertisements to the target persons using advertising methods that are set in advance for each of the plurality of hierarchical levels; An information processing method comprising:

6. On the computer, a classification step of classifying target persons, who are service users using an online service and who are potential recipients of an advertisement, into one of a plurality of hierarchical levels through which the target persons transition until they convert on the advertisement, based on behavioral information of the target persons; a delivery step of delivering advertisements to the target persons using advertising methods that are set in advance for each of the plurality of hierarchical levels; An information processing program characterized by causing the program to execute the above.

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