JP7440582B1 - Systems, methods, and programs for advertising distribution - Google Patents

Abstract

The present invention provides a system, method, and program for advertising distribution that can enhance the effectiveness of distributed advertisements. A system 11 for advertising distribution includes a position acquisition device 16 that identifies mobile devices 23 located within one or more prescribed areas based on location information of one or more mobile devices 23, and a position acquisition device 16 that distributes advertisements. a price setting device 12 that sets a standard price for advertising based on setting information associated with each prescribed area; an advertisement reception device 13 that determines a distribution store based on an advertisement purchase application and the standard price; A distribution device 14 that distributes advertisements to one or more mobile devices 23 located within each specified area, and a user 24 of the mobile device 23 that received the advertisement use the distribution store. A privilege granting device 15 for granting privileges is provided. [Selection diagram] Figure 1

Description

The present disclosure relates to systems, methods, and programs for advertising distribution.

Patent Document 1 discloses a system that distributes advertisements to mobile devices carried by users based on location information of the devices.

Special table 2017-525062 publication

It is desired that advertisements delivered to mobile devices be more effective.
The present disclosure aims to provide a system, method, and program for advertising distribution that can enhance the effectiveness of distributed advertisements.

A system for advertising distribution according to one aspect of the present disclosure is configured to identify one or more mobile devices located within one or more prescribed areas based on location information of the one or more mobile devices. A price configured to set a reference price for distributing an advertisement to a location acquisition device and at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas. The setting device is configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price. an advertisement reception device, a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas, and a user of the mobile device that has received the advertisement; The present invention further includes a benefit granting device configured to grant a benefit to the user when the distribution store that is the distributor of the advertisement is used.

A method for advertising distribution according to one aspect of the present disclosure includes having one or more computers identify one or more mobile devices located within one or more prescribed areas based on location information of the one or more mobile devices. and setting a reference price for distributing advertisements to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas; determining one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the desired store and the standard price; and one or more distribution stores located within each of the specified areas. distributing the advertisement to the mobile device, and granting a benefit to the user when the user of the mobile device that received the advertisement uses the distribution store that is the distributor of the advertisement. It includes doing and causing to be carried out.

A program for advertising distribution according to one aspect of the present disclosure specifies, in one or more computers, one or more mobile devices located within one or more prescribed areas based on location information of the one or more mobile devices. and setting a reference price for distributing advertisements to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas; determining one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the desired store and the standard price; and one or more distribution stores located within each of the specified areas. distributing the advertisement to the mobile device, and granting a benefit to the user when the user of the mobile device that received the advertisement uses the distribution store that is the distributor of the advertisement. to do and to carry out.

According to the present disclosure, the effectiveness of advertisements distributed to mobile devices can be increased.

FIG. 1 is a schematic diagram illustrating the configuration of a system according to an embodiment. FIG. 2 is a block diagram illustrating the electrical configuration of some devices according to the embodiment. FIG. 3 is a schematic diagram illustrating map data and a prescribed area defined on the map data. FIG. 4 is a schematic diagram illustrating an advertisement distribution method within a specified area. FIG. 5 is a flowchart of the advertisement distribution method according to the embodiment.

Examples of the system, method, and program for advertising distribution of the present disclosure will be described below with reference to the drawings. The present invention is not limited to these examples, but is indicated by the scope of the claims, and is intended to include all changes within the meaning and scope equivalent to the scope of the claims.

[overall structure]
As shown in FIG. 1, a system 11 for advertising distribution includes a pricing device 12, an advertisement accepting device 13, a distribution device 14, and a privilege granting device 15. System 11 may include a position acquisition device 16 . The system 11 may include a payment device 17 . The system 11 may include a machine learning device 60. These devices 12 - 17 , 60 may be able to communicate with each other via network 20 . The devices 12-17 may be separate computers or servers, or some of the devices 12-17 may be integrated into one computer or server.

One or more store terminals 21 are configured to communicate with payment device 17 via network 20 . The store terminal 21 may be, for example, a computer, a POS terminal, or a mobile device used in the store 22, but is not limited to these. The store 22 may be a building fixed to land, or may be movable like a food stall or a car. The store 22 may provide products or services.

One or more mobile devices 23 are configured to communicate with reward device 15 via network 20 . Distribution device 14 is configured to distribute notifications including advertisements to one or more mobile devices 23. Each mobile device 23 is carried by a corresponding user 24. The mobile device 23 may be, for example, a PC, a smartphone, or a tablet, but is not limited to these.

The network 20 includes, for example, the Internet, a WAN (Wide Area Network), a LAN (Local Area Network), a provider terminal, a wireless communication network, a wireless base station, a dedicated line, and the like. Not all combinations of devices shown in FIG. 1 need be able to communicate with each other, and network 20 may include some local networks. For example, the machine learning device 60 does not necessarily need to be connected to the network 20, and only needs to be able to exchange information with at least the pricing device 12.

FIG. 2 shows the basic configuration of a computer that is an example of the devices 12 to 17. The devices 12 to 17 include, for example, a processor 31, a memory 32, and a communication IF (interface) 33. Devices 12-17 may further include an input device 34, an output device 35, and a storage 36. These components 31 to 36 are connected to each other by a communication bus 37. The configurations of devices 12-17 may differ from each other. Like the devices 12 to 17, the store terminal 21 and the mobile device 23 may also include a processor 31, a memory 32, a communication IF (interface) 33, an input device 34, an output device 35, and a storage 36.

The processor 31 is, for example, a processing circuit configured to execute various software processes. The processing circuit may include a dedicated hardware circuit (eg, an ASIC, etc.) that handles at least a portion of the software processing. That is, the software processing may be performed by processing circuitry including at least one of one or more software processing circuits and one or more dedicated hardware circuits.

The processor 31 is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an MPU (Micro Processor Unit), an FPGA (Field-Programmable Gate Array), or other arithmetic device. The processor 31 executes a series of instructions included in a program stored in the memory 32 or storage 36 in response to a given signal or in response to the fulfillment of a predetermined condition.

The memory 32 is, for example, RAM (Random Access Memory) or other volatile memory. Memory 32 is configured to temporarily store programs and data. The program is read from the storage 36, for example. Data stored by memory 32 may include data received by devices 12 - 17 and data generated by processor 31 .

Communication IF 33 is configured to connect to network 20. The communication IF 33 is configured to communicate with other devices connected to the network 20. The communication IF 33 is realized, for example, as a LAN or other wired communication IF. The communication IF 33 may be implemented as, for example, Wi-Fi (registered trademark), Bluetooth (registered trademark), or other wireless communication IF, but is not limited thereto.

Input device 34 is, for example, a keyboard and mouse, and may include buttons, keys, switches, touch pads, or microphones. The output device 35 may be, for example, a liquid crystal monitor or an organic EL (Electro Luminescence) monitor, or may be a touch screen having a touch panel that also serves as the input device 34. The output device 35 may be a speaker or a terminal for audio output.

The storage 36 may be, for example, a ROM (Read-Only Memory), a hard disk device, a flash memory, or other non-volatile storage device. The storage 36 may be a removable storage device such as a memory card. Storage 36 is configured to permanently store programs and data. The storage 36 may store an application 38 for realizing various functions and various databases 39.

[Settlement related system]
The mobile device 23 includes, as an application 38, a payment program for mobile devices for receiving electronic payment services. This payment application includes a notification receiving program that receives notifications including advertisements from the distribution device 14. The payment application further includes a notification program for notifying the user 24 of the received notification via the output device 35 of the mobile device 23.

The receiving program and the notification program may be included in an application separate from the payment application. The user 24 can set a notification method and limit notifications through an application installed on the mobile device 23.

The store terminal 21 may include, as the application 38, a store payment application for providing electronic payment services. In electronic payment, the application is activated on both the store terminal 21 and the mobile device 23, and the payment amount is input via the input device 34 of the store terminal 21 or the mobile device 23. Then, the user 24 makes a payment to the store 22 using the functions of both applications. This payment method is also called electronic pay.

The payment device 17 includes, as an application 38, a program for performing authentication and payment processing for a plurality of store terminals 21. The payment device 17 may include a store database and a customer database as the database 39. The store database stores various information regarding the store 22. Information regarding the store 22 includes, but is not limited to, for example, store name, location, account, email address, authentication information, and payment receiving account.

The customer database stores various information regarding the users 24 who use payment. Information regarding the user 24 includes, but is not limited to, name, address, account, email address, and payment information, for example. Examples of payment information are credit card numbers, debit card numbers, or debit account numbers. The customer database may include each user's 24 purchase history. The purchase history includes, for example, the name of the store 22 where the payment was made, the date and time when the payment was made, the items purchased with the payment, and the purchase amount.

[System related to distribution]
The position acquisition device 16 may include one or more map data 25 as shown in FIG. 3 as a database 39. The database 39 may include object data for defining one or more prescribed areas 26 (26A, 26B) on each map data 25. This object data provides geographic coordinate data of each prescribed area 26 by linking with the position information of the map data 25.

The database 39 may include additional information associated with each map data 25. The attached information may be, for example, facility information. Examples of facility information include, but are not limited to, a store 22, a shopping mall, an underground mall, or a large facility 27 (see FIG. 4) such as a commercial building. The facility information may include information regarding the range of the facility, included floor information, and the altitude of each floor.

Area information may be linked to each prescribed area 26. Examples of area information include, but are not limited to, area type, category, keywords, number of potential customers, demographics, or consumption trends. Examples of area types include, but are not limited to, business districts, shopping areas, tourist spots, residential districts, entertainment districts, or in front of stations. Examples of categories include, but are not limited to, food, beverages, and miscellaneous goods. Examples of keywords include, but are not limited to, names that specify the area, such as administrative division names, shopping street names, tourist spot names, and commercial area names.

The number of potential customers may be calculated based on the number of mobile devices 23 located within each specified area 26. The number of existing objects may be, for example, a past performance value for each specific period or a specific time period, a predicted value based on past performance values, or measured in real time. It may be a measured value. The number of potential customers is shown as the number of mobile devices 23 for convenience, but if one user 24 uses multiple mobile devices 23 with one account, the number of accounts or users 24 may be It may be counted as the number of customers.

The number of potential customers may be the number of users 24 existing in each specified area 26 excluding the number of users 24 residing within the specified area 26. That is, the number of potential customers is calculated from the number Na of mobile devices 23 existing in each specified area 26 to the number Nr of users 24 or mobile devices 23 residing in the specified area 26 (hereinafter referred to as the number of resident users). It may be a number Nm obtained by subtracting . Hereinafter, the number Nm (=Na-Nr) will be referred to as the number of floating users.

The demographic statistics may include, for example, fluid demographic trends in arbitrary units of time, such as by season, by day of the week, by divisions such as morning/noon/night, or by time zone. Such demographic statistics do not necessarily have to be compiled using the prescribed area 26 as a boundary. For example, demographic data for each defined area 26 may be generated by overlapping the values aggregated in specific mesh units with the defined area 26. Such fluid demographic trends can be obtained, for example, by the location acquisition device 16 acquiring the location of the mobile device 23. Alternatively, the demographic data may be derived from data obtained by other devices.

Data related to consumption trends can be generated by referring to the purchase history of the user 24 within each prescribed area 26. Such consumption trend data may be, for example, data processed or generated based on user attributes. User attributes are, for example, gender, age, or address, but are not limited to these. For example, the consumption trend data may include attributes of the users 24 who spend a large amount of money at a particular store, such as a convenience store, or use the store frequently.

The position acquisition device 16 may include, as an application 38, an application for defining each defined area 26. The prescribed area 26 may be, for example, a circle centered around a point-like element (for example, a station, a store, or a large facility 27), an administrative district, or a polygon of any shape. It's okay.

The position acquisition device 16 may include, as the application 38, a position detection program for detecting entry/exit of the mobile device 23 into each prescribed area 26 and outputting the detection result as a signal. In other words, the location acquisition device 16 is configured to identify one or more mobile devices 23 located within one or more defined areas 26 based on location information of the one or more mobile devices 23 .

The position information is acquired by, for example, a GPS (Global Positioning System) included in the mobile device 23. For example, when the user 24 allows each application installed on the mobile device 23 to use location information, various applications can use the location information of the mobile device 23. The position acquisition device 16 can determine the position of the mobile device 23 by acquiring this position information.

The position detection program causes the processor 31 to detect the entrance and exit of the mobile device 23 to each specified area 26 by referring to the geographic coordinate data of the specified area 26 and the position information of the mobile device 23, for example. The location detection program may cause the processor 31 to obtain information regarding the altitude of the mobile device 23 within the defined area 26 and to detect on which floor within the large facility 27 the mobile device 23 is located. .

The distribution device 14 is configured to distribute a notification including an advertisement to the mobile device 23 that has entered the specified area 26 based on the detection result of the position acquisition device 16 . The distribution device 14 may include, as an application 38, a distribution program for distributing notifications to a specific mobile device 23. Advertisements may include, for example, text, still images, video, audio, other media, or combinations thereof. In addition to or in place of the advertisement, the notification may include a message related to payment, such as "Electronic payment is available." The distribution device 14 may include, as the database 39, a distribution database that records advertisement distribution history.

The distribution program may include a specific program for specifying the mobile device 23 to which the advertisement is to be distributed. The mobile device 23 specified here is called a distribution target. The specific program may cause the processor 31 to exclude the mobile devices 23 associated with the users 24 that meet the specific conditions from the distribution targets for each specified area 26 .

The exclusion condition is, for example, that the address is within the specified area 26, or that the user 24 himself/herself has set the notification not to be required. This is because if advertisements are distributed to users residing within each specified area 26, the users 24 may feel bothered by the frequent distribution, or the advertisement effect may not be sufficiently exhibited. The distribution device 14 can acquire the address of the user 24 from the customer database of the payment device 17, for example.

The benefit granting device 15 is configured to grant a benefit to the user 24 of the mobile device 23 that received the advertisement, when the user 24 uses the distribution store that is the distributor of the advertisement. The benefit may be, for example, points that can be used in exchange for money at a plurality of stores 22, or a discount valid at the distribution store.

The privilege granting device 15 may include, as a database 39, target users 24 to which privileges are granted and a privilege database for managing points owned by each user 24. The benefit database may be linked to a customer database included in the payment device 17. When the user 24 pays with points instead of money using electronic pay, the privilege granting device 15 may exchange information with the payment device 17.

The privilege granting device 15 may include, as the application 38, a privilege granting program for granting privileges to the user 24. The benefit granting program may include restrictions on the granting or use of the benefits to be granted. For example, the privilege awarding device 15 may award a privilege when the user 24 uses the distribution store within the validity period after distributing the advertisement. Alternatively, if the mobile device 23 to which the advertisement was distributed moves out of the corresponding prescribed area 26, the privilege granting device 15 may exclude the user 24 from receiving the privilege.

[System related to advertising sales]
The advertisement acceptance device 13 may include, as the application 38, a bidding program for bidding for advertisement distribution. The bidding program accepts purchase requests from one or more distribution stores that wish to distribute the advertisement, and determines a distribution store from among the one or more distribution stores based on the received purchase requests and a standard price. The processor 31 may be made to perform the following.

A store desiring distribution specifies advertisement distribution conditions and bids a unit price to the advertisement accepting device 13. The advertisement distribution conditions include, for example, at least one of a location condition, a time condition, or a target condition for distribution. The location condition is, for example, a specific defined area 26. The time condition is, for example, a date, a due date, a time zone, or the weather, but is not limited thereto. The target condition is, for example, a campaign, a user attribute, or a notification limit, but is not limited thereto.

Here, the term "campaign" refers to an advertising activity that specifies an advertising target, such as a specific product or service, a specific store 22, a specific period, or a combination thereof. For example, when performing different advertising activities for one product or one store 22, multiple campaigns can be set for each campaign. An example is a campaign in which a boxed lunch and drink set is sold at a bargain price during lunch time within the designated area 26 in a business district. Another example is a campaign in which a special benefit is given to customers who visit the store on rainy days at a food store or restaurant within the designated area 26 in a residential area.

Examples of due dates include, but are not limited to, holidays, weekends, or the day before a holiday. Examples of time zones include, but are not limited to, commuting hours or lunch hours. Examples of weather include, but are not limited to, when the temperature is above or below a certain temperature threshold, or when it is sunny or rainy. Examples of user attributes include, but are not limited to, gender, age, or address. The limit number of notifications can be set, such as one notification per user 24 in a certain specified area 26 or a certain time period. The limit number can be set to any number.

The distribution store may be determined based on bids from one or more distribution desired stores. For example, the advertisement reception device 13 may select the distribution desired store that has submitted the highest bid or a certain amount or more among the plurality of bids as a candidate for the distribution store. The advertisement reception device 13 may decide a distribution store from among the candidates, taking additional conditions into consideration. Additional conditions may be, for example, the quality of the advertisement, the effectiveness of the advertisement, or the number of notification limits. Bids may be placed in real time based on a program stored in memory 32, or may be placed manually.

The advertising fee may be calculated based on the number of distributed advertisements, or may be calculated based on the effectiveness of distributed advertisements. The effectiveness of the advertisement can be measured, for example, by the usage rate of the store 22 actually used by the user 24 who received the advertisement.

The price setting device 12 may include, as the application 38, an effect calculation program that calculates the advertising effect. For example, the effect calculation program causes the processor 31 to calculate the advertising effect based on the purchase history accumulated in the database of the payment device 17 and the distribution history accumulated in the distribution database of the distribution device 14. Good too. For example, the usage rate can be calculated based on the number of times each prescribed area 26 is used relative to the number of advertisements distributed. The price setting device 12 may store the calculated value in the database 39 as an advertisement effect record.

The pricing device 12 may include, as the application 38, a standard price determination program for determining a standard price that is the lowest bid price based on the setting information associated with each prescribed area 26. This setting information may be included in the area information. The setting information may include, for example, at least one of campaign information, time zone, user attribute information, distribution store attribute information, or weather information for each specified area 26. The reference price may be set based on the time period during which advertisements are distributed. In this way, the price setting device 12 determines the standard price for distributing an advertisement to at least one of the one or more mobile devices 23 based on the setting information or area information associated with each prescribed area 26. It may be configured to set.

The reference price determination program may set the reference price based on the output result of a machine learning model, for example, a regression model. The learning model may be generated by the machine learning device 60, for example. A regression model may be designed to predict the effectiveness of an advertisement using, for example, area information, time of day, distribution history, purchase history, or advertising effectiveness record. Alternatively, the learning model may be designed to extract feature amounts from the contents of distributed advertisements and predict advertisement contents with high advertising effectiveness. The price setting device 12 may be configured to set a higher standard price for conditions in which a higher usage rate is predicted, based on predictions obtained by such a learning model.

The machine learning device 60 may include a processor 31, a memory 32, a communication IF (interface) 33, and a storage 36 as shown in FIG. Processor 31 may include a variety of processors designed for machine learning. Processor 31 may include arithmetic units such as a CPU, GPU, and TPU, for example.

The machine learning device 60 is configured to generalize a model, for example. For example, a deep learning algorithm can be used to generate a machine learning model. A learning model can accumulate data and proceed with learning using that data. This allows more accurate predictions to be made.

[Method for advertising distribution]
A method for advertising distribution will be described with reference to FIGS. 3 to 5. First, with reference to FIGS. 3 and 4, an example of an advertisement that is notified to the mobile device 23A when the user 24A enters the specified area 26A will be described. Among the reference numerals attached to each element in FIGS. 3 and 4, A to D attached to the numbers refer to different targets (store terminal 21, store 22, mobile device 23, user 24, or specified area 26). .

As shown in FIG. 5, the method for advertising distribution includes acquiring area information (step S11), setting a reference price (step S12), determining a distribution store (step S13), and 23 (step S14), specifying the advertisement distribution target (step S15), distributing the advertisement (step S16), and providing benefits (step S17). But that's fine.

In step S11, the price setting device 12 acquires area information of a plurality of prescribed areas 26 from the position acquisition device 16. In this example, the area information includes setting information. For example, the area information includes information regarding campaigns, number of active users, time of day, and weather.

In step S12, the price setting device 12 sets a reference price for selling the advertisement based on various conditions including the acquired area information. For example, the price setting device 12 sets a reference price for each campaign based on the output result of the learning model.

The price setting device 12 may use the standard price calculated by a learning model or other algorithm as is, or may add additional factors to the calculated value, such as limiting the number of advertisements distributed per user 24. The standard price may be set by taking into consideration the number of notifications to be notified. The limit number of notifications may be set for each time period. As another additional element, for example, the reference price may be set lower in the case of bad weather by taking weather information into account, or the reference price may be changed depending on the temperature. For these additional elements as well, predicted values calculated by another learning model may be used.

In step S13, the advertisement accepting device 13 accepts advertisement applications, such as bids, received from one or more distribution-desiring stores. The advertisement acceptance device 13 determines one or more distribution stores from among the one or more distribution desired stores based on the bid amount and the set reference price. In this example, stores 22 located within each specified area 26 where advertisements are distributed are selected as distribution stores.

In step S14, the position acquisition device 16 periodically or irregularly acquires the position information of the mobile device 23. Then, the position acquisition device 16 detects entry/exit of the mobile device 23 into each prescribed area 26 based on the position information of the mobile device 23 . For example, the position acquisition device 16 detects that a certain user 24A has entered the specified area 26A.

In step S15, the distribution device 14 identifies the advertisement distribution target. For example, if the user 24A resides outside the specified area 26A, the distribution device 14 specifies the mobile device 23A as a distribution target when the mobile device 23A enters the specified area 26A. In contrast, the distribution device 14 excludes the mobile device 23D of the user 24D residing in the residence 28 within the specified area 26A from the advertisement distribution target.

In step S16, the distribution device 14, for example, distributes one or more notifications including advertisements to the mobile device 23A that is the distribution target. The distributed advertisement is notified to the user 24A through, for example, a payment application installed on the mobile device 23A. In this case, the notification is a push notification that the application automatically sends. This advertisement includes, for example, campaign information for the store 22A.

In this example, notification is limited to one time for one user 24 in each time period of a certain specified area 26. The distribution device 14 may be configured to distribute advertisements related to each distribution store during a time period that includes the current time based on a time zone associated with each distribution store.

After step S16, for example, the user 24A visits the store 22A and purchases a product by paying electronically through, for example, the mobile device 23A and the store terminal 21A. Then, in step S17, the privilege granting device 15 grants a privilege to the user 24A. For example, when making a payment using electronic pay, points equivalent to 1% of the purchase amount would normally be awarded, but points equivalent to 5% of the purchase amount will be awarded as a bonus. The content of this benefit may also be included in the distributed advertisement.

In another example, an advertisement regarding the large facility 27 within the specified area 26B may be distributed to the mobile device 23B carried by the user 24B who has entered the specified area 26B. In this case, as a restriction on granting a benefit, if the mobile device 23B goes outside the specified area 26B, the benefit may not be granted. Alternatively, the expiration date for granting the benefit may be a certain period (for example, the same day of distribution) after the advertisement is distributed.

[Effects of the present disclosure]
For example, in the case of a web advertisement, the user viewing the web page may be at home and relaxing, or may be at work. Therefore, even if a person clicks on an advertisement link and views an advertisement, the behavioral patterns from there to actually purchasing a product or service vary.

In contrast, in the present disclosure, advertisements are distributed to users 24 who have actually entered the specified area 26. That is, since the user 24 who received the notification has arrived within the specified area 26, the actions leading up to the purchase are relatively simple. Therefore, it is easy to narrow down the advertising content and advertising targets. For example, by targeting the mobile device 23 for distribution, it is possible to promote sales of products or services for personal consumption. Furthermore, by targeting users 24 who use payment services, the advertising target can be further narrowed down.

When predicting advertising effectiveness or advertising methods using a learning model, it is easier to extract effective feature quantities as the number of related elements decreases. Therefore, if the behavior pattern leading to purchase by the user 24 is simple, the prediction accuracy of the model will be high. In particular, since the system of the present disclosure includes a settlement service, it is easy to obtain information regarding the store 22 and user attributes and purchase history that are directly connected to the relationship between advertisement and purchase. Since useful training data for learning can be obtained, the accuracy of the model can be improved.

Furthermore, by using a learning model, even for a new campaign that has not been implemented in the past or a campaign that has few examples, predicted values can be obtained by using other similar cases as training data. In particular, if you set an expiration date for the benefit, you can see the effect in a short period of time. This data can then be analyzed and used for the next campaign.

Even if the user 24 within the specified area 26 is a potential customer who does not know the distribution store, by providing store information through advertisements, the user 24 can be converted into a potential customer who is close to making a purchase. Furthermore, by providing special benefits for using the store 22, it is possible to increase the purchasing desire of actual customers. In particular, if the user 24 allows notifications of advertisements through the mobile device 23, it is considered that the user 24 has a high desire to obtain information through notifications and to obtain benefits associated with electronic pay settlement. Therefore, advertising effects linked to electronic pay payments are expected.

Since the method of the present disclosure includes a settlement service, user attributes and purchase history can be taken into consideration when determining advertisement content and standard price. Such information can be used for analysis separately from the user's 24 personal information. This makes it possible to deliver more targeted advertisements. Therefore, advertising distribution can easily lead to purchases at physical stores. Furthermore, purchasing behavior regarding advertisements can be analyzed in more detail to improve the accuracy of advertisements.

By using points for awarding benefits, there is no need to change the selling price at each store 22. Additionally, if the benefit is electronic, it is easy to set an expiration date. Furthermore, there is no need to set the benefit and confirm the expiration date at the store 22. If the advertisement includes a message related to payment such as "Electronic pay can be used," each store 22 can also notify the user 24 that it has introduced electronic pay payment in conjunction with the campaign. . Therefore, the burden on the store 22 when conducting a campaign is reduced. As a result, the store 22's desire to purchase advertisements increases.

By targeting each specified area 26 in the bidding, the standard price can be appropriately set based on the area information. Since the range of the specified area 26 and the advertisement timing can be set in detail, even if the number of distributions is small, a higher advertising effect can be obtained. Such detailed settings are possible because information about the user 24 and the store 22 obtained through the settlement service can be utilized.

For example, it is also possible to distribute advertisements at different timings or with different contents regarding the stores 22B and 22C located on different floors of the large facility 27. For example, a free electronic ticket for coffee refills can be given as a benefit for advertisements for restaurants (store 22C) distributed during rainy weather. Alternatively, advertisements for time sales can be distributed for the store 22B, targeting times when there are usually fewer customers. In this way, by combining advertisements and benefits according to the situation, the added value of advertisements and benefits can be increased.

By setting the specified area 26, it is possible to implement a campaign limited to a region. For example, advertisements can be distributed to tourists who visit seasonal tourist attractions or events in a specific area. This will encourage sales at physical stores in the area, leading to regional revitalization. By receiving the notification within the specified area 26, the user 24 associates the specified area 26 with the store 22, so that the user 24 can effectively improve his/her recognition of the store 22.

The advertisement is delivered to the user 24 as a push notification. Therefore, even if the user 24 goes to a desired location or area without doing any preliminary research, he or she can obtain information about the stores 22 located there. The user 24 can obtain benefits at the store 22 he or she visits for the first time without having to carry a paper discount ticket or a membership card for each store 22. Providing such information and acquiring benefits is highly convenient for the user 24. Furthermore, since common benefits (for example, points) can be obtained by using different stores 22 in different regions, the value of using the benefits increases. As a result, the user 24's liking and trust in the notification increases, thereby increasing the effectiveness of the advertisement.

[Effects of this disclosure]
According to the present disclosure, the following effects can be achieved.
(1) Advertisements are distributed to mobile devices 23 located within each specified area 26. Therefore, advertisements can be distributed to potential customers at a time when it is convenient for them to use the distribution store. Further, a reference price for advertisement distribution is set based on information regarding each specified area 26. Therefore, it is possible to set a standard price according to advertising effectiveness. Furthermore, since the user 24 can obtain benefits by using the distribution store after receiving the advertisement, his or her desire to purchase increases. Therefore, the effectiveness of distributed advertisements can be increased.

(2) Based on the number of mobile devices 23 located within each specified area 26, the number of potential customers within each specified area 26 can be estimated. Therefore, the standard price can be determined depending on the number of potential customers.

(3) The number of potential customers may not include the number of users 24 residing within each specified area 26. In this way, even in areas with high population density, it is possible to set an appropriate standard price with floating users as the advertising target. This setting is possible because there is a customer database accumulated by the payment service.

(4) The information regarding each specified area 26 may include at least one of campaign information, user attribute information, attribute information of each distribution store, or weather information of each specified area. Based on this information, a standard price for advertisement distribution can be set.

(5) By setting a standard price based on the time slot for distributing advertisements, it is possible to distribute advertisements at a time slot that takes into account the behavioral patterns of potential customers.
(6) Advertising effectiveness can be increased by limiting the number of distributions per user or by limiting the number of distributions per time period. As a result, an appropriate standard price can be set according to advertising effectiveness. Further, by distributing a limited number of advertisements to the user 24, the user 24 is not bothered by frequent advertisement distribution. As a result, the user 24's attention to the advertisement increases, so that the effectiveness of the advertisement can be enhanced.

(7) A standard price can be set based on the output results of a machine learning model. In this case, an appropriate standard price can be calculated based on past performance.
(8) A distribution store can be determined based on bids from one or more distribution-desiring stores. In this case, the distribution store and advertising price can be efficiently determined by having one or more distribution-desiring stores compete on price.

(9) An advertisement for a store 22 located within a specified area 26 is distributed to the user 24 who has entered the specified area 26. Since the distribution store is located near the current location of the user 24, the user 24 can easily access the store 22, resulting in higher advertising effectiveness. Further, advertisements can be effectively distributed according to the behavior pattern of the user 24.

(10) The mobile devices 23 of the users 24 residing within each specified area 26 can be excluded from the distribution target of advertisements to the specified area 26. This setting is possible because there is a customer database accumulated by the payment service. By selecting distribution targets in this manner, resident users are not bothered by frequent advertisement distribution. Further, by distributing advertisements to floating users who reside outside each specified area 26, the distribution store has an opportunity to acquire new customers who visit from outside the specified area 26.

(11) Based on the time zone associated with each distribution store, advertisements regarding the distribution store can be distributed during the time period that includes the current time. This allows each distribution store to distribute advertisements in a timely manner according to the time slot when customers are expected to visit the store. Furthermore, since the user 24 can receive advertisements in accordance with the hours of use of the store 22, convenience is enhanced. As a result, advertising effectiveness can be further enhanced.

(12) If an expiration date for granting the benefit is set, the user 24 who received the notification attempts to use the distribution store within the expiration date in order to obtain the benefit. Therefore, the effectiveness of advertising can be demonstrated early.

(13) If the mobile device 23 to which the advertisement was distributed moves out of the corresponding specified area 26, the user 24 can be excluded from the benefit. In this case, the user 24 who received the advertisement attempts to use the distribution store while within each specified area 26 in order to obtain the benefit. Therefore, the effectiveness of advertising can be demonstrated early.

This embodiment can be implemented with the following modifications. This embodiment and the following modified examples can be implemented in combination with each other within a technically consistent range.
- The standard price may be set based on statistically obtained dynamic demographic trends.

- The method for determining distribution stores is not limited to bidding, but may also be based on individual purchase applications. For example, when a local government implements a campaign targeting its administrative area, it can purchase advertisements through a contract that does not involve bidding.

- The distribution store may be located outside the prescribed area 26 where advertisements are distributed. For example, an advertisement for a store 22 whose nearest station is any station on the railway line may be distributed to users 24 who have entered a plurality of prescribed areas 26 centered around each station on the railway line.

Aspects understood based on the above embodiment and modification examples are listed below.
[1] A system for advertising distribution according to one aspect of the present disclosure includes:
a location acquisition device configured to identify one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
a pricing device configured to set a reference price for distributing an advertisement to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
an advertisement acceptance device configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price; ,
a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas;
a benefit granting device configured to grant a benefit to the user when the user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement;
Equipped with

[2] The reference price is set based on the number of potential customers within each of the specified areas, and the number of potential customers is calculated based on the number of mobile devices located within each of the specified areas. The system according to [1] above.

[3] The number of potential customers is a number obtained by excluding at least the number of users residing within each specified area from the number of users existing within each specified area. system.

[4] Among the above [1] to [3], the setting information includes at least one of campaign information, user attribute information, attribute information of each distribution store, or weather information of each specified area. The system described in any of the above.

[5] The system according to any one of [1] to [4] above, wherein the reference price is set based on at least a time period in which the advertisement is distributed.
[6] The system according to any one of [1] to [5] above, wherein the reference price is set based on at least a limit number for limiting the number of advertisements distributed per user.

[7] The system according to [6] above, wherein the limit number is set for each time period.
[8] The system according to any one of [1] to [7] above, wherein the reference price is set based on an output result of a machine learning model.

[9] The advertisement acceptance device according to any one of [1] to [8] above, wherein the advertisement acceptance device is configured to determine the distribution store based on bids from the one or more distribution desired stores. system.

[10] The system according to any one of [1] to [9] above, wherein the distribution store is a store located within each of the specified areas to which the advertisement is distributed.
[11] The mobile device of the user residing within each specified area is configured to be excluded from the distribution target of the advertisement to the specified area, The system described.

[12] The distribution device is configured to distribute the advertisement regarding the distribution store in the time zone including the current time based on the time zone associated with each distribution store, 1] to [11].

[13] The benefit granting device is configured to grant the benefit when the user uses the distribution store within a valid period after distributing the advertisement, [1] to [12] above. ] The system described in any of the following.

[14] The benefit granting device is configured to exclude the user from receiving the benefit if the mobile device to which the advertisement has been distributed moves out of the corresponding defined area. 1] to [13].

[15] A method for advertising distribution according to one aspect of the present disclosure includes:
identifying one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
setting a reference price for distributing advertisements to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
determining one or more distribution stores from the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price;
distributing the advertisement to one or more of the mobile devices located within each of the prescribed areas;
When a user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement, providing a benefit to the user;
Including executing.

[16] A program for advertising distribution according to one aspect of the present disclosure is configured to include, on one or more computers,
identifying one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
setting a reference price for distributing advertisements to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
determining one or more distribution stores from the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price;
distributing the advertisement to one or more of the mobile devices located within each of the prescribed areas;
When a user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement, providing a benefit to the user;
A program to run.

[17] A computer-readable medium according to one aspect of the present disclosure is configured to allow one or more computers to:
identifying one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
setting a reference price for distributing advertisements to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
determining one or more distribution stores from the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price;
distributing the advertisement to one or more of the mobile devices located within each of the prescribed areas;
When a user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement, providing a benefit to the user;
The program to run this is recorded.

DESCRIPTION OF SYMBOLS 11...System, 12...Price setting device, 13...Advertisement reception device, 14...Distribution device, 15...Benefit giving device, 16...Location acquisition device, 17...Payment device, 20...Network, 21...Store terminal, 23...Mobile Equipment, 24...User, 25...Map data, 26...Specified area, 27...Large facility, 28...Residence, 31...Processor, 32...Memory, 34...Input device, 35...Output device, 36...Storage, 37...Communication bus, 38...application, 39...database, 60...machine learning device.

Claims (18)

a location acquisition device configured to identify one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
a pricing device configured to set a reference price for distributing an advertisement to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
an advertisement acceptance device configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price; ,
a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas;
a benefit granting device configured to grant a benefit to the user when the user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement;
Equipped with
The standard price is set based on the number of potential customers within each specified area,
The system for advertising distribution, wherein the number of potential customers is a number obtained by excluding at least the number of users residing in each specified area from the number of users existing in each specified area . a location acquisition device configured to identify one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
a pricing device configured to set a reference price for distributing an advertisement to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
an advertisement acceptance device configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price; ,
a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas;
a benefit granting device configured to grant a benefit to the user when the user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement;
Equipped with
The system for advertising distribution, wherein the reference price is set based on at least a limit number for limiting the number of advertisements distributed per user . a location acquisition device configured to identify one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
a pricing device configured to set a reference price for distributing an advertisement to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
an advertisement acceptance device configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price; ,
a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas;
a benefit granting device configured to grant a benefit to the user when the user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement;
Equipped with
The reference price is set based on at least a limit number for limiting the number of advertisements distributed per user,
A system for advertising distribution in which the limit number is set for each time period . a location acquisition device configured to identify one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
a pricing device configured to set a reference price for distributing an advertisement to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
an advertisement acceptance device configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price; ,
a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas;
a benefit granting device configured to grant a benefit to the user when the user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement;
Equipped with
A system for advertising distribution, wherein the mobile devices of the users residing within each of the specified areas are excluded from distribution targets for the advertisements to the specified areas . a location acquisition device configured to identify one or more mobile devices located within one or more defined areas based on location information of the one or more mobile devices;
a pricing device configured to set a reference price for distributing an advertisement to at least one of the one or more mobile devices based on setting information associated with each of the prescribed areas;
an advertisement acceptance device configured to determine one or more distribution stores from among the one or more distribution desired stores based on the purchase application for the advertisement received from the one or more distribution desired stores and the reference price; ,
a distribution device configured to distribute the advertisement to one or more of the mobile devices located within each of the prescribed areas;
a benefit granting device configured to grant a benefit to the user when the user of the mobile device that has received the advertisement uses the distribution store that is the distributor of the advertisement;
Equipped with
The benefit granting device is configured to exclude the user from the benefit if the mobile device to which the advertisement has been distributed moves out of the corresponding prescribed area. system. The reference price is set based on the number of potential customers in each of the specified areas, and the number of potential customers is calculated based on the number of mobile devices located in each of the specified areas.
A system according to any one of claims 1 to 5 . The reference price is set based on the number of potential customers within each of the specified areas, and the number of potential customers is determined from the number of users who reside within each of the specified areas at least. is the number excluding the number of users,
A system according to any one of claims 2 to 5. The setting information includes at least one of campaign information, user attribute information, attribute information of each distribution store, or weather information of each specified area.
A system according to any one of claims 1 to 5 . The reference price is set based on at least a time period in which the advertisement is distributed.
A system according to any one of claims 1 to 5 . The reference price is set based on at least a limit number for limiting the number of advertisements distributed per user.
A system according to any one of claims 1, 4 and 5 . The limit number is set for each time period,
The system according to claim 10 . The reference price is set based on the output result of the machine learning model,
A system according to any one of claims 1 to 5 . The advertisement acceptance device is configured to determine the distribution store based on bids from the one or more distribution desired stores.
A system according to any one of claims 1 to 5 . The distribution store is a store located within each of the specified areas where the advertisement is distributed.
A system according to any one of claims 1 to 5 . The mobile devices of the users residing within each of the defined areas are configured to be excluded from distribution of the advertisement to the defined areas;
The system according to any one of claims 1 to 3 and 5 . The distribution device is configured to distribute the advertisement regarding the distribution store in the time period that includes the current time based on the time zone associated with each distribution store.
A system according to any one of claims 1 to 5 . The benefit granting device is configured to grant the benefit when the user uses the distribution store within a valid period after distributing the advertisement.
A system according to any one of claims 1 to 5 . The benefit granting device is configured to exclude the user from receiving the benefit if the mobile device to which the advertisement was distributed moves out of the corresponding defined area;
A system according to any one of claims 1 to 4 .

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