JP7231485B2 - Information processing device, information processing method and information processing program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

Conventionally, there has been known a technique for saving the trouble of restaurant and site operators regarding payment of customer referral fees when a restaurant visits a restaurant by making a reservation through a gourmet site. For example, a technology is known in which a site operator bills a restaurant for a customer referral fee reduced according to the number of customer referral cancellations.

JP 2017-033263 A

However, with the conventional technology described above, it is not always possible to appropriately accept bids from business operators that operate targets with limited capacity, such as stores. For example, the conventional technology described above is merely a technology for calculating a customer referral fee according to the number of cancellations.

The present application has been made in view of the above, and aims to appropriately accept bids from business operators that operate targets with limited capacity.

In the information processing device according to the present application, when a predetermined condition regarding customer referral of a user to a target with limited capacity is satisfied, the first business operator managing the target is different from the first business operator. It is characterized by comprising a reception unit that receives a bid from the first business operator for paying a reward to the second business operator.

According to one aspect of the embodiments, it is possible to appropriately accept bids from business operators that operate targets with limited capacity.

FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 2 is a diagram illustrating an example of information processing according to the embodiment; FIG. 3 is a diagram illustrating a configuration example of an information processing system according to the embodiment; FIG. 4 is a diagram illustrating a configuration example of a terminal device according to the embodiment; FIG. 5 is a diagram illustrating a configuration example of a provider device according to the embodiment; FIG. 6 is a diagram illustrating a configuration example of an information processing apparatus according to the embodiment; FIG. 7 is a diagram illustrating an example of a customer referral related information storage unit according to the embodiment; 8 is a diagram illustrating an example of a first model storage unit according to the embodiment; FIG. 9 is a diagram illustrating an example of a bid information storage unit according to the embodiment; FIG. 10 is a diagram illustrating an example of a ranking determination information storage unit according to the embodiment; FIG. 11 is a diagram illustrating an example of a second model storage unit according to the embodiment; FIG. 12 is a diagram illustrating an example of a provided information storage unit according to the embodiment; FIG. 13 is a diagram illustrating an example of a user information storage unit according to the embodiment; FIG. 14 is a diagram illustrating an example of a business operator information storage unit according to the embodiment; FIG. FIG. 15 is a flowchart illustrating an example of information processing according to the embodiment; FIG. 16 is a flowchart illustrating an example of information processing according to the embodiment; 17 is a flowchart illustrating an example of information processing according to the embodiment; FIG. 18 is a flowchart illustrating an example of information processing according to the embodiment; FIG. 19 is a flowchart illustrating an example of information processing according to the embodiment; FIG. FIG. 20 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing apparatus.

Embodiments for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Also, in each of the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

(embodiment)
[1. Example of information processing]
First, an example of information processing according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 1 shows an example in which information processing according to an embodiment is executed by an information processing apparatus 100 . In the examples of FIGS. 1 and 2, a store (store) is described as an example of a target with limited capacity, but any target can be used as long as it has a limited capacity. There may be. For example, the target may be a predetermined mobile object such as a taxi or a private car. For example, the target may be public transportation such as trains and buses. For example, the target may be a predetermined space such as a conference room or event venue where events, activities, seminars, and the like are held. For example, the target may be a predetermined space such as a free-address office, an Internet cafe, a capsule hotel, or a hotel. The capacity is not limited to a spatial limit, and may be limited to the number of participants such as the number of participants. Also, the capacity is not limited to the number of people, but may be a space capacity limitation such as the number of chairs or the number of seats. In addition, the object to be stored for the target whose capacity is limited is not limited to a person, and may be an object or the like. For example, the object may be a storage space for a moving object related to physical distribution, such as a truck bed. Also, the object here may be a variety of objects such as an empty house, an empty room, an empty warehouse, a suitcase, a bag, a coin-operated locker, a coin-operated laundry, a massage chair, and the like. Note that the above is only an example, and the processing described later may be performed on various objects that have limited capacity and to which the following information processing can be applied.

FIG. 1 shows a case in which the information processing device 100 receives a bid amount bid by a store regarding customer referrals (case of business operator CM3). It should be noted that, as in the cases of the businesses CM1 and CM2 shown in FIG. 1, the information processing device 100 may receive a bid amount from the store that requested information for assisting the bidding on customer referrals. For example, the information for assisting a bid regarding customer referrals is information regarding the degree of customer referrals according to the remuneration (remuneration amount). In this case, the information processing device 100 provides information for assisting bids for referrals. Hereinafter, the information for assisting the bidding for customer referrals will be referred to as bidding assist information as appropriate. In addition, information related to customer referrals by a user (user) is appropriately referred to as customer referral related information. FIG. 1 shows a case where the degree of customer referral is calculated based on the customer referral related information of the store that requested the bid assist information. An example of information processing according to the embodiment will be described below with reference to FIG.

The information processing device 100 receives a request for bid assist information transmitted by the business operator CM1 via the business operator device 20-1 (step 101). The business operator CM1 shown in FIG. 1 is a business operator having a predetermined relationship with the store SP1. For example, the business operator CM1 is a business operator that operates (manages) the store SP1. Hereinafter, a business operator having a predetermined relationship with a store will be referred to as a first business operator as appropriate. In FIG. 1, the store SP1 is an izakaya. Hereinafter, the store may be read as a business operator (first business operator). For example, store SP1 may be read as business operator CM1. In step S101, the information processing apparatus 100 receives a request for bid assist information and acquires customer referral related information of the store SP1. For example, the information processing apparatus 100 may acquire the customer referral related information transmitted from the business operator apparatus 20-1, or may acquire the customer referral related information stored in a predetermined storage unit. The customer referral related information may include information (conditions) specified (requested) by the store.

The customer referral related information may include any information as long as it is information specified by the store. For example, the customer referral related information includes user attributes (for example, demographic attributes) specified by the store, whether or not the user uses the store (whether or not the user is a repeater), the time zone, and the user's arrival time. It may also include information to indicate. As a specific example, if a store wants to attract women in their twenties, the store may designate an attribute such as "twenties: female" as the customer referral related information. Also, when it is desired to acquire new users who do not use the store, the store may designate an attribute such as "new user" as the customer referral related information. Also, if it is desired to attract customers during the lunch time from 13:00 to 14:00, a condition regarding a time period such as "13:00 to 14:00" may be specified as the customer referral related information. Further, if it is desired to attract customers who can come to the store within 10 minutes from the current time, a condition regarding the user's arrival time such as "within 10 minutes from the current time" may be specified as the customer referral related information.

The customer referral related information may include the situation regarding the fullness of the store. Here, the situation regarding full occupancy may be the vacant seat situation of the store. Specifically, the situation regarding fullness may be the number of vacant seats in the store, such as "15 seats available", or the congestion rate in the store, such as "10% vacant". It may be indicated by an expression. For example, the customer referral related information may include the situation regarding the fullness of the store for each day of the week or for each time period. Further, the customer referral related information may include information specified by the store and the situation regarding the fullness of the store. Further, the customer referral related information may include information designated by the store according to the situation regarding the fullness of the store.

The information processing device 100 acquires a predetermined function related to customer referrals. For example, the information processing device 100 acquires a predetermined function stored in a predetermined storage unit. For example, the information processing device 100 acquires a function corresponding to a reward as a predetermined function related to customer referrals. Note that the predetermined function may be a model that outputs a score. For example, the predetermined function may be a model that calculates a score by inputting a reward. The information processing apparatus 100 uses a model related to customer referral (hereinafter referred to as “first model M1” as appropriate) to calculate a score indicating an index related to customer referral (step S102). In FIG. 1, the information processing device 100 calculates the degree of referral according to the reward. Here, the degree of customer referral is the degree to which a predetermined condition regarding customer referral of the user is satisfied. That is, the degree of customer referral is the degree to which a reward for customer referral can be received. Note that the degree calculated by the information processing apparatus 100 may be a probability. The information processing device 100 calculates the degree of customer referral when the reward is input to the first model M1. Equation (1) shown below is an example of the predetermined function shown in FIG. In the example of FIG. 1, the first model M1 corresponds to Equation (1) below. The predetermined function shown in FIG. 1 may calculate the score according to multiple factors. That is, the predetermined function shown in FIG. 1 is a model that outputs the degree of referral. Specifically, the predetermined function shown in FIG. 1 is a model that outputs the degree of customer referral by inputting customer referral related information.

x1, x2, . . . , xn shown in Equation (1) are elements for calculating the score. The element shown in Formula (1) is customer referral related information. The elements shown in the formula (1) are remuneration, information specified by the store, the situation regarding the fullness of the store, information held by the external server, and the like. Here, x1 shown in the formula (1) corresponds to the reward, x2 corresponds to the information specified by the store, x3 corresponds to the situation regarding the fullness of the store, and x4 corresponds to the information held by the external server. shall be Also, the information specified by the store x2 is, for example, the attributes of the user, the presence or absence of use, and the time zone. Expression (1) may also include each element corresponding to a user's attribute specified by the store, the presence or absence of use specified by the store, and the time period specified by the store. The information held by the x4 external server is, for example, information on users around the store, information on the environment around the store (for example, weather), and information on evaluation of the store. Expression (1) may also include elements corresponding to each piece of information held by the external server.

In FIG. 1, when the information processing apparatus 100 inputs a reward of 50 yen to the first model M1, the probability X% is calculated (step S102-1). Further, the information processing apparatus 100 calculates the probability Y % when the reward of 100 yen is input to the first model M1 (step S102-2). Further, the information processing apparatus 100 calculates the probability Z % when the reward of 200 yen is input to the first model M1 (step S102-3). Note that FIG. 1 shows a case where the information processing apparatus 100 calculates the probability of customer referral using the first model M1 stored in a predetermined storage unit. A first model M1 may be generated or learned that outputs Note that a process of generating or learning the first model M1 by the information processing apparatus 100 will be described later.

The reward is a success fee paid to the customer referral. The remuneration is paid to a business operator that provides a predetermined web service (hereinafter referred to as a "second business operator" as appropriate) when predetermined conditions are met. Specifically, the remuneration is paid from the first business operator that operates the store to the second business operator that has performed an action that contributes to the referral of users to the store. That is, the reward is paid when the information processing device 100 determines that the second business operator has performed an action that contributes to the customer referral to the store. Note that the information indicating the remuneration is appropriately called remuneration information. Also, processing for payment of remuneration will be described later with reference to FIG.

The information processing apparatus 100 generates a graph GR1 based on the first model M1 (step S103). For example, the information processing device 100 generates a graph GR1 indicating the degree of customer referral according to reward. The information processing device 100 may use the graph GR1 as the bid assist information. Although the example shown in FIG. 1 shows the case where the information processing device 100 generates the graph GR1, the information processing device 100 may generate any information as long as it assists the bidding of the store. good. For example, the information processing device 100 may generate a table (list) showing the association between the remuneration and the degree of referral. The information processing device 100 may use the generated information as bid assist information.

The information processing device 100 provides bid assist information (step S104). In the example of FIG. 1, the information processing device 100 transmits the graph GR1 to the provider device 20-1. As a result, the information processing apparatus 100 can develop attractive customer-attracting activities according to the degree of customer referral for the store.

The information processing device 100 receives the bid information of the bid by the business operator CM1 via the business operator device 20-1 (step S105). The information processing device 100 receives bid information regarding customer referrals per person bid by the business operator CM1. FIG. 1 shows that business operator CM1 has bid 100 yen for customer referrals. It should be noted that the bid amount (100 yen) that the business operator CM1 bids for the customer referral is the amount of remuneration to be paid to the second business operator when a predetermined condition regarding the customer referral is satisfied.

Similarly, the information processing device 100 receives a request for bid assist information transmitted by the business operator CM2 via the business operator device 20-2 (step 106). In addition, the business operator CM2 shown in FIG. 1 is the first business operator having a predetermined relationship with the store SP2. For example, the business operator CM2 is the first business operator that operates the store SP2. In FIG. 1, the store SP2 is a bakery. In addition, below, shop SP2 may be read as business operator CM2 suitably. In step S106, the information processing apparatus 100 receives the request for bid assist information and acquires the customer referral related information of the store SP2. For example, the information processing apparatus 100 may acquire the customer referral related information transmitted from the business operator apparatus 20-2, or may acquire the customer referral related information stored in a predetermined storage unit.

The information processing device 100 provides bid assist information corresponding to the store SP2 based on the same processing as steps S102 and S103 (step S107). Specifically, the information processing device 100 generates the first model M1 corresponding to the store SP2 based on the customer referral related information of the store SP2, and converts the information generated based on the first model M1 into the bid assist information. Provide as The information processing device 100 transmits the bid assist information corresponding to the store SP2 to the business operator device 20-2.

The information processing device 100 receives the bid information of the bid by the business operator CM2 via the business operator device 20-2 (step S108). The information processing device 100 receives bid information regarding customer referrals per person bid by the business operator CM2. FIG. 1 shows that business operator CM2 has bid 200 yen for referrals. It should be noted that the bid amount (200 yen) that the business operator CM2 bids for the customer referral is the amount of remuneration to be paid to the second business operator when a predetermined condition regarding the customer referral is satisfied.

FIG. 1 shows a case where, unlike the companies CM1 and CM2, the company CM3 does not request the bid assist information. In this case, the information processing device 100 does not accept a request for bid assist information from the business operator CM3 via the business operator device 20-3. Further, the information processing device 100 does not have to transmit the bid assist information corresponding to the store SP3 to the business operator device 20-3. In addition, the business operator CM3 shown in FIG. 1 is the first business operator having a predetermined relationship with the store SP3. For example, the business operator CM3 is the first business operator that operates the store SP3. In FIG. 1, the store SP3 is a restaurant. In addition, below, shop SP3 may be read as business operator CM3 suitably.

The information processing device 100 receives the bid information of the bid by the business operator CM3 via the business operator device 20-3 (step S109). The information processing device 100 receives bid information regarding customer referrals per person bid by the business operator CM3. FIG. 1 shows that business operator CM3 has bid 150 yen for customer referrals. It should be noted that the bid amount (150 yen) that the business operator CM3 bids for the customer referral is the amount of remuneration to be paid to the second business operator when a predetermined condition regarding the customer referral is satisfied.

It is assumed that there is no relationship between the order of the processing of steps S101 through S105 regarding the store SP1, the processing of steps S106 through S108 regarding the store SP2, and the processing of step S109 regarding the store SP3.

In the example shown in FIG. 1, the information processing apparatus 100 receives bids from businesses CM1 to CM3, but the number of first businesses that receive bids is not limited. That is, the information processing device 100 may receive bid information transmitted from three or more first business operators.

In the example of FIG. 1, the stores operated by the first business operator are food-related stores such as a pub (store SP1), a bakery (store SP2), and a restaurant (store SP3). Bids may be accepted from stores belonging to other categories. For example, the information processing device 100 may receive bids from a first business operator that operates a store related to housing such as a hotel or private lodging.

The remuneration may be the amount of remuneration paid for one customer referral, or may be the remuneration amount paid for a plurality of customer referrals. For example, a reward of 50 yen for inputting into the first model M1 may be the amount of reward paid for customer referrals per person.

The bid amount may be the bid amount for one customer referral, or may be the bid amount for a plurality of customer referrals. For example, the bid of 100 yen bid by the business operator CM1 may be the amount of the bid for customer referrals per person.

[2. Example of information processing]
Next, an example of information processing according to the embodiment will be described using FIG. FIG. 2 is a diagram illustrating an example of information processing according to the embodiment; FIG. 2 shows an example in which information processing according to the embodiment is executed by the information processing apparatus 100 . The example of FIG. 2 shows a case where the user U1 is a user (hereinafter also referred to as a "target user") who is the target of customer referral to the store. Note that the target user may be appropriately determined (selected), for example, a user who uses a predetermined web service such as a web service provided by the information processing apparatus 100, a user who can acquire position information, or the like. .

FIG. 2 shows a case where the information to be provided to the target user is determined based on the bid amount that the store bids on the referral. In FIG. 2 , the information processing device 100 determines the order (ranking) of the stores that have made bids regarding customer referrals. Specifically, the information processing device 100 determines the order of stores corresponding to the target user. In FIG. 2, the information used to determine the order of the stores is appropriately referred to as the order determination information. An example of information processing according to the embodiment will be described below with reference to FIG. The map MP1 indicates the positional relationship among the store SP1, the store SP2, the store SP3, and the user U1. Map MP1 indicates that user U1 has moved to store SP3 after the process of step S207.

The information processing device 100 acquires user information regarding the user U1 via the terminal device 10-1 (step S201). In FIG. 2, the information processing device 100 acquires the location information of the user U1. For example, the information processing device 100 acquires location information of the user U1 located within a predetermined range from the store.

The information processing apparatus 100 acquires ranking determination information (step S202). In the example shown in FIG. 1, the information processing apparatus 100 acquires the ranking information stored in the ranking information storage unit 124. However, the information processing apparatus 100 acquires the ranking information transmitted from the external server. good too. Here, the ranking determination information is predetermined information. For example, the ranking determination information may be information predetermined for each store, or information commonly determined for each store. For example, the order determination information may be information (conditions) specified in advance by the store, or may be information (conditions) determined by the information processing apparatus 100 . The ranking determination information may be any information as long as it is information used to rank the shops corresponding to the target user.

The ranking information may include information (conditions) regarding target users. Specifically, the ranking determination information may include information on target users to whom the store requests customer referrals. For example, the ranking information includes the attributes of the target user (for example, demographic attributes), the action history of the target user, whether or not the target user uses the store (whether or not the target user is a repeater), and the location of the target user. information, information indicating the distance between the target user and the store, and the like. For example, the information processing apparatus 100 may acquire information about the attribute of the target user such as "twenties: female". For example, the information processing apparatus 100 may acquire information related to the action history of the target user such as "access to the restaurant information site is 10 times or more". For example, the information processing apparatus 100 may acquire information regarding whether or not the target user uses the store, such as "use of store". For example, the information processing apparatus 100 may acquire information regarding the target user's location information such as "around AA station" or "within BB". For example, the information processing apparatus 100 may acquire information about the distance between the target user and the store, such as "the distance from the store is within 100 meters".

The ranking determination information may include the situation regarding the fullness of the store. Here, the status regarding fullness may be the reservation status of the store. Note that the reservation status of the store may be the current reservation status or the future reservation status. For example, the reservation status of a store may be a real-time reservation status, a reservation status after one second, or a reservation status after one month. For example, the order determination information may include a reservation status including a time period such as "18:00 to 19:00: many reservations". In addition, the reservation status may be the number of reservations such as "10 reservations", or the reservation congestion rate such as "reservation rate 90%" or "9 seats reserved out of 10 seats in the store". However, it may be indicated by another expression. The ranking information may also include the price range of the store. Note that the price range of the store may be a price range for each day of the week or for each time period. Also, the ranking determination information may include store evaluations. Note that the evaluation of the store may be an evaluation by a user who has used the store.

The information processing device 100 acquires a predetermined function related to customer referrals. The information processing device 100 acquires a predetermined function different from the first model M1. The information processing apparatus 100 acquires a predetermined function that does not include rewards as input information. For example, the information processing device 100 acquires a function corresponding to the ranking determination information. The information processing device 100 calculates a first score used for ranking stores. Note that the first score is a score calculated for each store. Here, the first score is a score indicating the probability of customer referrals by the target user. For example, the first score may be a score that indicates the probability that the target user will perform an action that will benefit the first business operator (the business operator that manages the store). Specifically, the first score may be a score indicating the probability that the target user will come to the store. Also, the predetermined function may be a model that outputs the first score. For example, the predetermined function may be a model that calculates the first score by inputting ranking determination information. Hereinafter, the model that outputs (calculates) the first score will be referred to as a "second model M2" as appropriate. Equation (2) shown below is an example of the predetermined function shown in FIG. In the example of FIG. 2, the second model M2 corresponds to Equation (2) below. The predetermined function shown in FIG. 2 may calculate the score according to multiple factors.

y1, y2, . . . , yn shown in Equation (2) are elements for calculating the score. The elements shown in formula (2) are information for ranking. The elements shown in the formula (2) are information on the target user, the situation regarding the fullness of the store, the price range of the store, the evaluation of the store, the information held by the outside, and the like. Here, y1 shown in equation (2) corresponds to the information about the target user, y2 corresponds to the situation regarding the fullness of the store, y3 corresponds to the price range of the store, y4 corresponds to the evaluation of the store, It is assumed that y5 corresponds to information held externally. The information about the target user of y1 is, for example, the attribute of the target user and the distance between the target user and the store. For example, Expression (2) may include elements corresponding to the attributes of the target user and the distance between the target user and the store. Moreover, the situation regarding the fullness of the store of y2 is, for example, the vacant seat situation of the store or the reservation situation of the store. For example, Expression (2) may include elements corresponding to the vacant seat status of the store and the reservation status of the store. The information held by the external server of y4 is, for example, information on users around the store, information on the environment around the store (for example, weather), and information on evaluation of the store. Expression (2) may also include elements corresponding to each piece of information held by the external server.

In FIG. 2, when the information processing apparatus 100 inputs the ranking determination information corresponding to the store SP1, the information processing apparatus 100 calculates the first score "SC1" (step S203-1). Further, when the information for determining the ranking corresponding to the store SP2 is input, the information processing apparatus 100 calculates the first score "SC2" (step S203-2). Further, when the information for determining the ranking corresponding to the store SP3 is input, the information processing apparatus 100 calculates the first score "SC3" (step S203-3). Note that FIG. 2 shows the case where the information processing apparatus 100 calculates the first score used for ranking the shops using the second model M2 stored in the predetermined storage unit. may generate or learn a second model M2 that outputs a first score for use in ranking stores. Note that the processing by which the information processing apparatus 100 generates or learns the second model M2 will be described later.

The information processing device 100 calculates a second score used for ranking shops based on the first score and the remuneration information (step S204). Note that the second score is a score calculated for each store. Specifically, the second score is the score that determines the order of the stores. Here, the second score is a score related to customer referrals of the target user. For example, the second score is a score based on the bid amount and the probability that the target user will come. In the example shown in FIG. 2, the information processing device 100 calculates the second score based on the first score and the bid price of the store. Note that the second score may be calculated based on any function as long as it is a score calculated based on the first score and remuneration information. For example, the information processing device 100 may calculate the second score by multiplying the first score by the bid price of the store. In FIG. 2, for example, the information processing device 100 calculates the second score of "25" for the store SP1 based on the bid amount of "100 yen" for the store SP1 and the first score "SC1". . Note that the example of FIG. 2 shows the case where the information processing apparatus 100 generates the table SL1 showing the bid amount of the store, the first score, and the second score for each store ID. is not limited to the example shown in Further, the information processing apparatus 100 does not have to generate the table SL1.

The information processing apparatus 100 determines the order of the shops based on the calculated second score (step S205). The information processing device 100 determines the order of stores to be provided to the user U1 based on the second score. For example, the information processing apparatus 100 determines the ranking of each shop so that the higher the second score value, the higher the ranking. That is, the information processing apparatus 100 determines the order of each store so that the store with a higher second score value is preferentially provided with information to the target user. In FIG. 2, the information processing apparatus 100 determines the shop SP3 with the highest second score as the first rank. In addition, the information processing apparatus 100 determines the store SP1 having the second highest second score as the second rank. The information processing apparatus 100 then determines information to be provided to the user U1 (step S206). In FIG. 2, the information processing device 100 determines to provide information on the store SP3 with the highest second score. In the example shown in FIG. 2, the information processing apparatus 100 shows an example in which the information about the store with the highest second score is provided, but the example is not limited to that shown in FIG. For example, the information processing device 100 may determine to provide information on shops up to a predetermined rank. Although the example in FIG. 2 shows the case where the information processing apparatus 100 generates the table RK1 showing the order of stores in descending order of the second score, the example is not limited to that shown in FIG. Further, the information processing apparatus 100 does not need to generate the table RK1.

The information processing device 100 provides the user U1 with the information of the store that has been determined to provide (step S207). In FIG. 2, the information processing device 100 provides information on the store SP3 with the highest second score. Specifically, the information processing device 100 provides store information as an example of a service related to sending customers to the store. For example, the information processing device 100 provides information that attracts the target user to the store. As a specific example, the information processing device 100 may provide information to the effect that "store SP3 is advantageous" or "store SP3 is on sale". For example, the information processing apparatus 100 may provide information including a condition such as "Discount if payment is made by 19:00" or "Discount if you visit the store by 18:00 and complete payment by 19:00." good.

The information processing apparatus 100 acquires predetermined information regarding customer referrals (step S208). The information processing device 100 acquires predetermined information transmitted from the terminal device 10 . The information processing apparatus 100 acquires predetermined information regarding the behavior of the target user with respect to the provided store information. For example, the information processing apparatus 100 acquires position information of the target user. For example, the information processing device 100 acquires information indicating the distance between the target user and the store. In the example of FIG. 2, the information processing device 100 acquires information indicating the distance between the user U1 and the store SP3.

The information processing apparatus 100 determines whether or not the predetermined information acquired in step S208 satisfies a predetermined condition regarding customer referral (step S209). For example, the information processing device 100 determines whether or not the target user has taken an action that benefits the first business operator (the business operator who manages the store). Specifically, the information processing device 100 determines whether or not the target user has come to the store. The information processing apparatus 100 determines whether or not to charge (claim) the first business operator who has made a bid. When the information processing apparatus 100 determines that the predetermined condition regarding customer referral is satisfied, the information processing apparatus 100 determines to charge the first business operator who has made a bid. When the information processing apparatus 100 determines to charge, the information processing apparatus 100 executes processing related to charging. Note that the billing process may include transmission of information about billing.

The information processing device 100 charges the provider CM3 (step S210). For example, the information processing device 100 transmits billing information (billing information) to the business CM3.

Note that there is no relationship between the processing in step S201 for acquiring user information and the processing in steps S202 to S206 for calculating the second score. For example, the information processing apparatus 100 may perform the process of step S201 after the process of step S206.

[3. Variation of processing]
(3-1. Acquisition of location information)
It is assumed that the position information of the terminal device 10 is detected by GPS (Global Positioning System) built into the terminal device 10, for example. The information processing device 100 acquires the target user's location information via the GPS of the terminal device 10 . That is, the information processing device 100 acquires the position information acquired via the GPS of the terminal device 10 as the target user's position information. On the other hand, it is assumed that the store location information is indicated by, for example, the store address. The information processing device 100 acquires the location information of the store from a predetermined storage unit. The information processing apparatus 100 acquires the store address stored in the business operator information storage unit 128 as the store location information. The information processing apparatus 100 may acquire the address of the store acquired from the external server as the location information of the store.

(3-2. Judgment of customer referral by location)
The information processing device 100 determines whether the target user has visited the store based on the location of the target user and the location of the store. The information processing apparatus 100 determines that the target user has visited the store when the distance between the target user and the store is within a predetermined threshold value (for example, within 1 m). In the example of FIG. 1, the information processing apparatus 100 determines that the user U1 has visited the store SP3 because the distance between the user U1 and the store SP3 is within the predetermined threshold. As a result, the information processing apparatus 100 determines that the user U1, who is the target user, has visited the store SP3 to which the information has been provided, and thus satisfies the predetermined condition regarding customer referral. The information processing device 100 charges the bid amount of "150 yen" that the business operator CM3 of the shop SP3 bids to the business operator CM3 as a reward for referring the user U1 to the shop SP3.

(3-3. Judgment of referral by authentication)
The information processing device 100 determines whether the target user has visited the store based on the information detected by the sensor installed in the store. For example, the information processing apparatus 100 determines whether the target user has visited the store based on authentication (for example, face authentication, fingerprint authentication, etc.) by an authentication apparatus installed in the store. For example, when information detected by an authentication device installed in a store matches information registered in a predetermined web service such as a web service provided by the information providing device 50, the information processing device 100 It is determined that the target user has visited the store.

(3-4. Distribution of coupons)
In the embodiment, the case where the information processing apparatus 100 provides store information as an example of a service related to customer referral to the store has been described. The information processing device 100 may provide a coupon related to customer referral as an example of a service related to customer referral to a store. For example, coupons are perks that benefit the target user. For example, a coupon is a privilege that can be used at a store. For example, a coupon may be a privilege that can be used at a store when a predetermined condition is met. For example, the coupon may be a privilege including conditions such as being valid for settlement by a predetermined time. For example, the coupon may be a benefit including a condition that the coupon is valid if the target user performs an operation (tap, click, etc.) to make a payment by a predetermined time. In this case, the first score calculated by the information processing device 100 may be a score indicating the probability that the target user will perform a predetermined action with respect to the information provided by the second operator. Specifically, the first score calculated by the information processing device 100 may be a score indicating the probability that the target user will select the coupon provided by the second business operator.

(3-5. Various methods of providing services)
The information processing apparatus 100 may provide services related to customer referrals using a predetermined notification method (for example, push notification, etc.). The information processing device 100 may provide advertising content as a service related to customer referrals. For example, the information processing apparatus 100 may provide advertising content to be displayed in a predetermined area (for example, an advertising area) included in a predetermined web service as a customer referral service.

(3-6. Judgment of remuneration by settlement)
In the embodiment, it is assumed that a reward is paid when the target user comes to the store as a predetermined condition regarding customer referral. Here, as a predetermined condition regarding customer referral, a reward may be paid when the target user makes a predetermined payment. Specifically, the reward may be paid when the target user makes a payment at the store using the coupon provided by the second business operator. In this case, the information processing device 100 may determine whether the target user has performed a predetermined action using the coupon provided by the second business operator.

(3-7. Variations of customer referrals)
In the embodiment, the case where the customer referral is to visit a store has been described as an example. Any movement is possible. Customer referrals to targets with limited capacity are not limited to the movement of people, but may be the movement of goods and the like. As a specific example, sending customers to a target with limited capacity may be participation in a predetermined space such as a conference room or event venue where events, activities, seminars, etc. are held. . In addition, if the object with limited capacity is an object such as a storage space for a moving object related to logistics such as a truck bed, sending customers to the object with limited capacity is transport (carrying). There may be.

(3-8. Variation of the first operator)
The first business operator is not limited to the business operator that operates the target with limited capacity, but any business operator that has a predetermined relationship with the target with limited capacity. good too. For example, the first operator may be an operator that provides a subject with limited capacity. As a specific example, if the target with limited capacity is a predetermined space such as a conference room or event venue where events, activities, seminars, etc. are held, the first business operator It may be a business operator that provides a predetermined space such as a room or an event venue. Also, the first business operator may be a business operator that handles objects with limited capacity. To give a specific example, if the object with limited capacity is the space for accommodating mobile objects related to physical distribution, such as a truck bed, the first business operator is a business that handles the accommodation space for mobile objects related to physical distribution. may be a person.

[4. Configuration of information processing system]
The information processing system 1 shown in FIG. 3 will be described. As shown in FIG. 3 , the information processing system 1 includes a terminal device 10 , an operator device 20 and an information processing device 100 . The terminal device 10, the business operator device 20, and the information processing device 100 are communicably connected by wire or wirelessly via a predetermined communication network (network N). FIG. 3 is a diagram illustrating a configuration example of an information processing system according to the embodiment; The information processing system 1 shown in FIG. 3 may include a plurality of terminal devices 10, a plurality of provider devices 20, and a plurality of information processing devices 100. FIG.

The terminal device 10 is an information processing device used by a user (target user). The terminal device 10 may be any device as long as it can implement the processing in the embodiments. The terminal device 10 may be a device such as a smart phone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. The example shown in FIG. 2 shows a case where the terminal device 10 is a smart phone. The terminal device 10-1 is a terminal device used by the user U1. Moreover, the terminal device 10 may detect various sensor information by various sensors other than a GPS sensor or the like.

The business operator device 20 is an information processing device used by the first business operator. The provider device 20 may be any device as long as it can implement the processing in the embodiment. Also, the business operator device 20 may be a device such as a smart phone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, or a PDA. The examples shown in FIGS. 1 and 2 show the case where the business operator device 20 is a notebook PC. The provider device 20-1 is a provider device used by the provider CM1. The provider device 20-2 is a provider device used by the provider CM2. The provider device 20-3 is a provider device used by the provider CM3. Further, the business operator device 20 may detect various sensor information using various sensors other than the GPS sensor or the like.

The information processing device 100 is used to calculate the degree of customer referral based on store information. Further, the information processing device 100 is used to receive bids on customer referrals from stores. Further, the information processing device 100 is used to determine the order of stores that have submitted bids for customer referrals. The information processing device 100 is, for example, an information processing device such as a PC or a WS (Work Station), and performs processing based on information transmitted from the terminal device 10 and the business operator device 20 via the network N. For example, the information processing device 100 performs processing based on user information transmitted from the terminal device 10 . For example, the information processing device 100 performs processing based on bid information transmitted from the business operator device 20 .

[5. Configuration of terminal device]
Next, the configuration of the terminal device 10 according to the embodiment will be described using FIG. FIG. 4 is a diagram showing a configuration example of the terminal device 10 according to the embodiment. As shown in FIG. 4 , the terminal device 10 has a communication section 11 , an input section 12 , an output section 13 and a control section 14 .

(Communication unit 11)
The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 11 is connected to a predetermined network N by wire or wirelessly, and transmits and receives information to and from the information processing apparatus 100 via the predetermined network N.

(Input unit 12)
The input unit 12 receives various operations from a user (target user). In the example shown in FIG. 2, various operations from user U1 are accepted. For example, the input unit 12 may receive various operations from the user through the display surface using a touch panel function. The input unit 12 may also receive various operations from buttons provided on the terminal device 10 or from a keyboard or mouse connected to the terminal device 10 . For example, the input unit 12 receives various operations from the user on information transmitted from the information processing apparatus 100 . For example, the input unit 12 receives an operation for making a reservation to visit a store determined by the information processing device 100 . For example, the input unit 12 receives an operation not to reserve a visit to the store determined by the information processing apparatus 100 or an operation to close the provided information.

(Output unit 13)
The output unit 13 is a display screen of a tablet terminal realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various information. Also, the output unit 13 outputs information transmitted from the information processing apparatus 100 . For example, the output unit 13 outputs information on the store determined by the information processing device 100 . In the example shown in FIG. 2, the output unit 13 outputs information about the store SP3. For example, the output unit 13 outputs information including services related to sending customers to stores.

(control unit 14)
The control unit 14 is, for example, a controller, and a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like stores various programs stored in a storage device inside the terminal device 10 into a RAM (Random Access Memory). ) as a work area. For example, the various programs include application programs installed in the terminal device 10 . For example, the various programs include an application program for displaying information transmitted from the information processing apparatus 100 . Also, the control unit 14 is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 4, the control unit 14 has a transmitting unit 141 and a receiving unit 142, and implements or executes the information processing operation described below.

(transmitting unit 141)
The transmission unit 141 provides various types of information to an external information processing device. The transmission unit 141 transmits various types of information to an external information processing device. For example, the transmission unit 141 transmits various information to other information processing devices such as the information processing device 100 . The transmission unit 141 transmits various information stored in a predetermined storage unit. The transmission unit 141 transmits various information acquired from the external server. The transmission unit 141 transmits various information detected by the sensor. The transmission unit 141 transmits various information detected by the sensor built into the terminal device 10 . The transmitter 141 transmits user information. The transmitting unit 141 transmits user position information. Also, the transmission unit 141 may transmit various information executed via an application installed in the terminal device 10 .

(Receiver 142)
The receiving unit 142 receives various information. The receiving unit 142 receives various information from an external information processing device. The receiving unit 142 receives various information from other information processing devices such as the information processing device 100 . For example, the receiving unit 142 receives information on the store determined by the information processing device 100 . The receiving unit 142 receives store information regarding customer referrals. The receiving unit 142 receives information including services related to customer referrals to stores.

[6. Configuration of operator device]
Next, the configuration of the business operator device 20 according to the embodiment will be described with reference to FIG. FIG. 5 is a diagram showing a configuration example of the business operator device 20 according to the embodiment. As shown in FIG. 5 , the provider device 20 has a communication section 21 , an input section 22 , an output section 23 and a control section 24 .

(Communication unit 21)
The communication unit 21 is implemented by, for example, a NIC. The communication unit 21 is connected to a predetermined network N by wire or wirelessly, and transmits and receives information to and from the information processing apparatus 100 via the predetermined network N.

(Input unit 22)
The input unit 22 receives various operations from the first operator. In the example shown in FIG. 1, various operations are accepted from businesses CM1 to CM3. For example, the input unit 22 may receive various operations from the first operator through the display surface using a touch panel function. Further, the input unit 22 may receive various operations from buttons provided on the operator device 20 or from a keyboard or mouse connected to the operator device 20 . For example, the input unit 22 receives a bid from the first business operator regarding customer referrals. For example, the input unit 22 receives transmission of a request for bid assist information regarding customer referrals. For example, the input unit 22 receives the setting of information (conditions) specified by the first business operator regarding customer referrals.

(Output unit 23)
The output unit 23 is, for example, a display screen of a tablet terminal realized by a liquid crystal display, an organic EL display, or the like, and is a display device for displaying various information. Also, the output unit 23 outputs information transmitted from the information processing apparatus 100 . For example, the output unit 23 outputs bid assist information regarding customer referrals. For example, the output unit 23 outputs information regarding the degree of customer referral calculated by the information processing device 100 . In the example shown in FIG. 1, the output unit 23 may output a graph GR1 regarding referrals. In addition, the output unit 23 outputs billing information regarding customer referrals.

(control unit 24)
The control unit 24 is, for example, a controller, and is implemented by executing various programs stored in a storage device inside the business operator apparatus 20 using a RAM as a work area by means of a CPU, MPU, or the like. For example, these various programs include application programs installed in the business operator device 20 . For example, the various programs include an application program for transmitting bid information regarding referrals to the information processing apparatus 100 . Also, the control unit 24 is implemented by an integrated circuit such as an ASIC or FPGA, for example.

As shown in FIG. 5, the control unit 24 has a transmitting unit 241 and a receiving unit 242, and implements or executes the information processing operation described below.

(transmitting unit 241)
The transmission unit 241 provides various types of information to an external information processing device. The transmission unit 241 transmits various types of information to an external information processing device. For example, the transmission unit 241 transmits various information to other information processing devices such as the information processing device 100 .

The transmission unit 241 transmits a request for bid assist information regarding customer referrals. The transmission unit 241 transmits information (conditions) specified by the first business operator regarding customer referrals. The transmitting unit 241 transmits the customer referral related information specified by the first business operator regarding the customer referral.

The transmission unit 241 transmits bid information regarding customer referrals. The transmitting unit 241 may transmit bid information based on bid assist information.

(Receiver 242)
The receiving unit 242 receives various information. The receiving unit 242 receives various information from an external information processing device. The receiving unit 242 receives various information from other information processing devices such as the information processing device 100 .

The receiving unit 242 receives bid assist information. The receiving unit 242 receives information about the degree of customer referral. For example, the receiving unit 242 receives information about the degree of customer referral according to the reward. In the example shown in FIG. 1, the receiving unit 242 may receive a graph GR1 regarding referrals.

The receiving unit 242 receives billing information regarding customer referrals. The receiving unit 242 receives billing information based on a bid made by the first business operator.

[7. Configuration of Information Processing Device]
Next, the configuration of the information processing apparatus 100 according to the embodiment will be described using FIG. FIG. 6 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 6, the information processing apparatus 100 has a communication section 110, a storage section 120, and a control section . The information processing apparatus 100 has an input unit (for example, a keyboard, a mouse, etc.) that receives various operations from the administrator of the information processing apparatus 100, and a display unit (for example, a liquid crystal display, etc.) for displaying various information. You may

(Communication unit 110)
The communication unit 110 is implemented by, for example, a NIC. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information between the terminal device 10 and the business operator device 20 via the network N.

(storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM or flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 6, the storage unit 120 includes a customer referral related information storage unit 121, a first model storage unit 122, a bid information storage unit 123, a ranking determination information storage unit 124, and a second model storage unit. 125 , provided information storage unit 126 , user information storage unit 127 , and business operator information storage unit 128 .

The customer referral related information storage unit 121 stores customer referral related information. The customer referral related information storage unit 121 stores information related to customer referral specified by the store. The customer referral related information storage unit 121 stores information indicating the situation regarding the fullness of the store. Here, FIG. 7 shows an example of the customer referral related information storage unit 121 according to the embodiment. As shown in FIG. 7, the customer referral related information storage unit 121 has items such as "customer referral ID", "store ID", "enterprise ID", and "customer referral related information".

“Customer referral ID” indicates identification information for identifying customer referral related information. "Store ID" indicates identification information for identifying a store. For example, FIG. 7 shows that store SP1 is a store that has specified customer referral related information corresponding to customer referral SK1. “Business ID” indicates identification information for identifying the first business. For example, FIG. 7 shows that the business operator CM1 is the first business operator that operates the store SP1.

"Customer referral related information" indicates customer referral related information. The "customer referral related information" further includes items such as "customer referral request" and "customer referral full". "Customer referral request" indicates information (conditions) specified by the store regarding customer referral. The “customer referral request” indicates, for example, user information specified by the store regarding customer referral (eg, user attributes, whether or not the user uses the store), time zone, and user arrival time conditions. In the example shown in FIG. 7, conceptual information such as "customer referral request #11" and "customer referral request #12" is stored in "customer referral request". Data (for example, a conditional expression) indicating the information obtained is stored. If there is no information specified by the store, information such as "none" or "NULL" may be stored in the "customer referral request". To give a specific example, "customer referral request #11" included in the customer referral request corresponding to the customer referral ID "SK1" is "sex: female", "customer referral request #12" is "age: 20 ~ 30” may be stored, and information such as “none” may be stored after “customer referral request #13”. In addition, "customer delivery full" indicates the situation regarding the fullness of the store. For example, "customer referral full" indicates the status of the store being fully occupied when the store designates customer referral information. In the example shown in FIG. 7, conceptual information such as "customer referral full #1" and "customer referral full #2" is stored in "customer referral full". Data indicating the number of vacant seats in the store (for example, vacant seat rate) is stored.

The first model storage unit 122 stores information about the first model M1. The first model storage unit 122 stores information about the first model M1 for calculating a score indicating an index of customer referrals. Here, FIG. 8 shows an example of the first model storage unit 122 according to the embodiment. As shown in FIG. 8, the first model storage unit 122 has items such as "first model ID" and "first model (calculation formula)".

"First model ID" indicates identification information for identifying the first model M1. "First model (calculation formula)" indicates a calculation formula for the first model M1. In the example shown in FIG. 8, conceptual information such as "first model #1" and "first model #2" is stored in "first model (calculation formula)". , where the function data is stored. For example, the function of formula (1) is stored in "first model (calculation formula)".

The bid information storage unit 123 stores bid information. The bid information storage unit 123 stores bid information of each first business operator bidding on customer referrals. Here, FIG. 9 shows an example of the bid information storage unit 123 according to the embodiment. As shown in FIG. 9, the bid information storage unit 123 has items such as "bid ID", "store ID", "company ID", and "bid information".

"Bid ID" indicates identification information for identifying bid information. "Store ID" indicates identification information for identifying a store. For example, FIG. 9 shows that store SP1 is the store that submitted the bid corresponding to bid NS1. “Business ID” indicates identification information for identifying the first business. “Customer referral ID” indicates identification information for identifying customer referral related information. "Bid information" indicates the bid information for which the first business operator made a bid. Specifically, the bid amount is stored in the "bid information". For example, FIG. 9 shows that the business operator CM1 has bid 100 yen for customer referral SK1. Further, FIG. 9 shows that the business operator CM2 has bid 200 yen for the customer referral of the customer referral SK2.

The ranking information storage unit 124 stores ranking information. The ranking determination information storage unit 124 stores information related to customer referrals specified by the store. Specifically, the ranking determination information storage unit 124 stores information (conditions) regarding the target users of customer referrals requested by the store. The ranking determination information storage unit 124 stores information indicating the situation regarding the fullness of the store. Specifically, the ranking determination information storage unit 124 stores information indicating the reservation status of the store. Here, FIG. 10 shows an example of the ranking determination information storage unit 124 according to the embodiment. As shown in FIG. 10, the ranking determination information storage unit 124 has items such as "ranking ID", "shop ID", "enterprise ID", and "ranking information".

“Ranking ID” indicates identification information for identifying ranking information. "Store ID" indicates identification information for identifying a store. For example, FIG. 10 shows that the store SP1 is the store that specified the ranking determination information corresponding to the ranking determination JK1. “Business ID” indicates identification information for identifying the first business.

"Information for ranking determination" indicates information for ranking determination. The "ranking information" further has items such as "ranking request" and "ranking full". "Ranking request" indicates information (conditions) specified by the store regarding the target user. "Ranking request" indicates, for example, the attributes of the target user, the action history, whether or not the store is used, and the conditions related to the location information. In the example shown in FIG. 10, conceptual information such as "ranking request #11" and "ranking request #12" is stored in "ranking request". Denoting data (for example, a conditional expression) is stored. If there is no information specified by the store, information such as "none" or "NULL" may be stored in the "order request". To give a specific example, “ranking request #11” included in the ranking request corresponding to the ranking determination ID “JK1” includes “gender: female” and “ranking request #12” includes “age: 20 to 30”. Information such as "none" may be stored after "rank request #13".

"Ranked full" indicates the current status of full vacancies. In the example shown in FIG. 10, conceptual information such as "rank full #1" and "rank full #2" is stored in "rank full". Data indicating the number is stored. "Reservation Status" indicates the future status of store vacancies. Specifically, the "reservation status" stores information indicating the reservation status regarding full occupancy. In the example shown in FIG. 10, conceptual information such as "reservation #1" and "reservation #2" is stored in "reservation status". Data indicating the number (for example, reservation rate) is stored.

The "price range" indicates the price range of the transaction object (product) offered at the store. The "price range" may indicate the price range from the lowest price to the highest price of the transaction object offered at the store, or may indicate the average price range. Further, the "price range" may store a predetermined price, or may store a price range. In the example shown in FIG. 10, conceptual information such as "price #1" and "price #2" is stored in the "price range", but actually data indicating the price is stored. be done.

"Evaluation" indicates the evaluation of the store. For example, "evaluation" indicates the evaluation by the user who used the store. In addition, any information may be stored in the "evaluation" as long as it is information indicating an index of evaluation. For example, "evaluation" may store characters indicating evaluations such as "good", "average", and "bad", or may store symbols indicating evaluations such as "A", "B", and "C". Alternatively, evaluation numerical values such as "4", "3", and "2" may be stored. The example shown in FIG. 10 shows an example in which conceptual information such as "evaluation #1" and "evaluation #2" is stored in "evaluation".

The second model storage unit 125 stores information about the second model M2. The second model storage unit 125 stores information about the second model M2 for calculating the first score used for ranking the stores. For example, the second model storage unit 125 stores information about the second model M2 for calculating the probability of customer referrals of the target user. Here, FIG. 11 shows an example of the second model storage unit 125 according to the embodiment. As shown in FIG. 11, the second model storage unit 125 has items such as "second model ID" and "second model (calculation formula)".

"Second model ID" indicates identification information for identifying the second model M2. "Second model (calculation formula)" indicates a calculation formula for the second model M2. In the example shown in FIG. 11, conceptual information such as "second model #1" and "second model #2" is stored in "second model (calculation formula)". , where the function data is stored. For example, the function of formula (2) is stored in the "second model (calculation formula)".

The provided information storage unit 126 stores information determined to be provided to the target user (hereinafter referred to as "provided information" as appropriate). The provided information storage unit 126 stores information determined to be transmitted to the terminal device 10 of the target user. The provided information storage unit 126 stores information related to the customer referral service. Here, FIG. 12 shows an example of the provided information storage unit 126 according to the embodiment. As shown in FIG. 12, the provided information storage unit 126 has items such as "provided ID", "user ID", and "provided information".

"Provision ID" indicates identification information for identifying the provision information. "User ID" indicates identification information for identifying the target user. "Provided information" indicates provided information. For example, the "provided information" stores information about the store determined to be provided to the target user. For example, in the "provided information", information on a plurality of stores is stored as information on stores. In the example shown in FIG. 12, conceptual information such as "store information #1" and "store information #2" is stored in "store information", but in reality, store names, store advertisements, and so on are stored. , URL (Universal Resource Locator) of the store, and data indicating the location of the store (for example, map information). In addition, information on coupons related to the store may be stored in the "provided information". For example, the "provided information" may store, as information on coupons, information on a plurality of coupons corresponding to each store. In addition, the "provided information" may store conditions related to the use of coupons. Alternatively, the "provided information" may store a condition regarding the behavior of the target user. In practice, data indicating the content of coupon discounts and conditional expressions for using coupons may be stored in the “provided information”.

The user information storage unit 127 stores user information indicating information about a user (target user). Here, FIG. 13 shows an example of the user information storage unit 127 according to the embodiment. As shown in FIG. 13, the user information storage unit 127 has items such as "user ID", "terminal ID", "sex", "age", "place of residence", and "whether shop is used".

"User ID" indicates identification information for identifying a user. "Terminal ID" indicates identification information for identifying the terminal device used by the user. "Gender" indicates the gender of the user. "Age" indicates the age of the user. "Residence" indicates information about the user's address. In the example shown in FIG. 13, an example is shown in which conceptual information such as "residence #1" and "residence #2" is stored in "residence". data is stored. “Store use/non-use” indicates whether or not each store is used by the user. Information indicating whether or not a user uses a plurality of stores may be stored in the "store use/non-use" field. In the example shown in FIG. 13 , conceptual information such as “usage #1” and “use #2” is stored in “use of shop”. (for example, "store SP1: use available") is stored.

The business operator information storage unit 128 stores business operator information indicating information about the first business operator. Here, FIG. 14 shows an example of the business operator information storage unit 128 according to the embodiment. As shown in FIG. 14, the business operator information storage unit 128 stores "business operator ID", "business operator device ID", "store ID", "specialty", "store location", "price range", and "evaluation". It has items such as

“Business ID” indicates identification information for identifying the first business. "Operator device ID" indicates identification information for identifying the operator apparatus used by the first operator. For example, FIG. 14 shows that the operator device 20-1 is the operator device used by the operator CM1. "Store ID" indicates identification information for identifying a store. For example, FIG. 14 shows that the store SP1 is operated by the business operator CM1. "Specialty" indicates the attribute of the store. "Store location" indicates information about the address of the store. In the example shown in FIG. 14, conceptual information such as "store location #1" and "store location #2" is stored in "store location". data is stored.

The "price range" indicates the price range of the transaction object (product) offered at the store. The "price range" may indicate the price range from the lowest price to the highest price of the transaction object offered at the store, or may indicate the average price range. Further, the "price range" may store a predetermined price, or may store a price range. In the example shown in FIG. 14, conceptual information such as "price #1" and "price #2" is stored in the "price range", but in reality, data indicating the price is stored. be done.

"Evaluation" indicates the evaluation of the store. For example, "evaluation" indicates the evaluation by the user who used the store. In addition, any information may be stored in the "evaluation" as long as it is information indicating an index of evaluation. For example, "evaluation" may store symbols indicating evaluations such as "good", "average", "bad", "A", "B", and "C", or "4", " Numerical values such as "3" and "2" may be stored. In the example shown in FIG. 14, conceptual information such as "evaluation #1" and "evaluation #2" is stored in "evaluation".

(control unit 130)
The control unit 130 is a controller, and is realized by, for example, executing various programs stored in a storage device inside the information processing apparatus 100 using a RAM as a work area by a CPU, MPU, or the like. Also, the control unit 130 is a controller, and is implemented by an integrated circuit such as an ASIC or FPGA, for example.

As shown in FIG. 6, the control unit 130 includes an acquisition unit 131, a reception unit 132, a generation unit 133, a calculation unit 134, a determination unit 135, a provision unit 136, a determination unit 137, and a charging unit 138. and implements or performs the information processing operations described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 6, and may be another configuration as long as it performs information processing described later.

(Acquisition unit 131)
Acquisition unit 131 acquires various types of information. Acquisition unit 131 acquires various types of information from an external information processing device. The acquisition unit 131 acquires various types of information from other information processing devices such as the terminal device 10 and the business operator device 20 .

Acquisition unit 131 acquires various types of information from storage unit 120 . The acquisition unit 131 stores the customer referral related information storage unit 121, the first model storage unit 122, the bid information storage unit 123, the ranking information storage unit 124, the second model storage unit 125, the provided information storage unit 126, and the user information storage unit. Various information is acquired from the unit 127 and the business operator information storage unit 128 .

The acquisition unit 131 stores the acquired various information in the storage unit 120 . The acquisition unit 131 stores the customer referral related information storage unit 121, the first model storage unit 122, the bid information storage unit 123, the ranking information storage unit 124, the second model storage unit 125, the provided information storage unit 126, and the user information storage unit. Various information is stored in the unit 127 and the business operator information storage unit 128 .

Acquisition unit 131 acquires various types of information received, generated, calculated, determined, and determined by other functional configurations.

The acquisition unit 131 acquires a request for bid assist information. The acquisition unit 131 acquires a request for bid assist information transmitted by the first business operator via the business device 20 . The acquisition unit 131 acquires customer referral related information. The acquiring unit 131 acquires customer referral related information transmitted by the first business operator via the business operator device 20 . For example, the acquisition unit 131 acquires customer referral related information including information (conditions) specified by the store. For example, the acquisition unit 131 acquires the customer referral related information including the situation regarding the fullness of the store.

Acquisition unit 131 acquires a predetermined function. The acquisition unit 131 acquires the first model M1. For example, the acquisition unit 131 may acquire the first model M1 stored in the first model storage unit 122 or the first model M1 generated by the generation unit 133 . Also, the acquisition unit 131 acquires the second model M2. For example, the acquisition unit 131 may acquire the second model M2 stored in the second model storage unit 125 or may acquire the second model M2 generated by the generation unit 133 .

The acquisition unit 131 acquires bid information. The acquisition unit 131 acquires bid information of a store bidding on customer referrals. The acquisition unit 131 acquires the bid information transmitted by the first business operator via the business operator device 20 . In other words, the acquisition unit 131 acquires remuneration information. Specifically, the acquisition unit 131 acquires remuneration information paid by the first business operator who operates the store to the second business operator who has performed an action that contributes to the referral of the user to the store.

The acquisition unit 131 acquires ranking information. Acquire ranking information including information (conditions) specified by the store. For example, the acquisition unit 131 acquires ranking information including information about target users. For example, the acquisition unit 131 acquires ranking determination information including a situation regarding full occupancy of the store. For example, the acquisition unit 131 acquires ranking determination information including the reservation status of the store. For example, the acquisition unit 131 acquires ranking determination information including the price range of the store. For example, the acquisition unit 131 acquires ranking determination information including store evaluations.

The acquisition unit 131 acquires position information of a user (target user). For example, the acquisition unit 131 acquires position information transmitted from the terminal device 10 . Also, the acquisition unit 131 acquires the location information of the first business operator. For example, the acquisition unit 131 acquires information about the address of the store stored in the business operator information storage unit 128 .

(Reception unit 132)
The reception unit 132 receives various types of information. The reception unit 132 receives various types of information from an external information processing device. The receiving unit 132 receives various types of information from other information processing devices such as the terminal device 10 . Note that the reception unit 132 may be part of the acquisition unit 131 .

The receiving unit 132 stores the received various information in the storage unit 120 . For example, the reception unit 132 stores various information in the bid information storage unit 123 .

The reception unit 132 receives bids from the first business operator. The reception unit 132 accepts a bid from the first business operator for the first business operator who operates the store to pay a reward to the second business operator who has performed an action that contributes to the referral of the user to the store. accept.

(Generating unit 133)
The generation unit 133 generates various types of information. The generation unit 133 stores the generated various information in the storage unit 120 . For example, the generation unit 133 stores various information in the first model storage unit 122 and the second model storage unit 125 .

The generation unit 133 generates various types of information based on various types of information acquired, received, calculated, and determined by other functional configurations.

The generation unit 133 generates a model. The generation unit 133 generates a model for causing a computer to output index values. The generator 133 generates the first model M1. The generation unit 133 generates a first model M1 corresponding to the customer referral related information. When the reward (input information) is input to the first model M1, the generation unit 133 generates the first model M1 that outputs the degree of referral (output information). In the example of FIG. 1, the generation unit 133 generates the first model M1 that outputs a probability of X% when a reward of 50 yen is input.

The generator 133 learns the first model M1. The generation unit 133 learns the first model M1 based on the information about the reward and the information about the degree of referral. Specifically, the generation unit 133 generates the first model M1 learned by using the target user who came to the store as correct data. For example, the generation unit 133 generates the first model M1 learned to output "100" as the degree of the target user's visit to the store when the target user inputs a reward for coming to the store. For example, the generation unit 133 generates the first model M1 that has been learned to output "0" as the degree to which the target user does not come to the store when the reward for the target user not to come to the store is input. do.

The generator 133 generates the second model M2. The generator 133 generates the second model M2 according to the ranking determination information. The generation unit 133 inputs the store ranking information to the second model M2, and generates the second model M2 that outputs a first score indicating the degree of customer referral of the target user. In the example of FIG. 2, the generation unit 133 generates the second model M2 that outputs the first score SC1 when the ranking determination information of the store SP1 is input.

The generator 133 learns the second model M2. The generation unit 133 learns the second model M2 based on the ranking determination information and the degree of customer referral of the target user. Specifically, the generation unit 133 generates the second model M2 learned by using the target user who came to the store as correct data. For example, the generating unit 133 generates the second model M2 that has learned to output "100" as the degree of visit of the target user to the store when the target user's visit to the store is inputted with the ranking determination information. Generate. For example, the generation unit 133 learns to output "0" as the degree to which the target user does not come to the store when the ranking determination information for the case where the target user does not come to the store is input. Generate M2.

(Calculation unit 134)
The calculator 134 calculates various types of information. The calculation unit 134 calculates various information from the storage unit 120 . For example, the calculation unit 134 calculates various information from the first model storage unit 122 and the second model storage unit 125 .

The calculation unit 134 calculates various types of information acquired, received, generated, and determined by other functional configurations.

The calculation unit 134 calculates a score indicating an index related to customer referrals. For example, the calculation unit 134 calculates a score related to customer referral based on the customer referral related information and a predetermined function. For example, the calculation unit 134 calculates a score related to customer referral based on the customer referral related information and the first model M1. For example, the calculation unit 134 calculates the degree (probability) of referrals.

The calculation unit 134 calculates a first score used for ranking stores. For example, the calculator 134 calculates the first score based on the ranking determination information and a predetermined function. For example, the calculator 134 calculates the first score based on the ranking determination information and the second model M2. The calculation unit 134 also calculates a second score used for ranking the stores. For example, the calculator 134 calculates the second score based on the first score and the remuneration information.

(Determination unit 135)
The determination unit 135 determines various types of information. The determination unit 135 stores the determined various information in the storage unit 120 . For example, the determination unit 135 stores various information in the provided information storage unit 126 .

The determination unit 135 determines various types of information acquired, received, generated, and calculated by other functional configurations.

The determination unit 135 determines the order of stores. The determination unit 135 determines the order of the stores that are the target of providing information to the target user. The determining unit 135 determines the order of the stores based on the reward information and the order determination information. The determination unit 135 determines the order of stores based on the second score calculated by the calculation unit 134 .

(Providing unit 136)
The providing unit 136 provides various types of information to an external information processing device. The providing unit 136 transmits various types of information to an external information processing device. The providing unit 136 notifies various information to an external information processing device. For example, the providing unit 136 provides various information to other information processing devices such as the terminal device 10 .

The providing unit 136 provides various information from the storage unit 120 . The providing unit 136 provides various information from the provided information storage unit 126 .

The providing unit 136 provides various types of information obtained, received, generated, calculated, and determined by other functional configurations.

The providing unit 136 provides bid assist information. For example, the providing unit 136 provides bid assist information based on the first model M1 generated by the generating unit 133 . For example, the providing unit 136 provides information indicating the degree of customer referral according to the reward.

The providing unit 136 provides (distributes) services related to customer referrals to stores. For example, the providing unit 136 provides information on stores. For example, the providing unit 136 provides advertisements regarding stores. For example, the providing unit 136 provides coupons (privileges) related to stores.

The providing unit 136 provides billing information (billing information). The provision unit 136 provides billing information to the first business operator who has made a bid according to the determination result of the determination unit 137 .

(Determination unit 137)
The determination unit 137 determines various types of information. The determination unit 137 determines a predetermined condition regarding customer referrals. The determination unit 137 determines whether or not the target user has performed an action that satisfies a predetermined condition regarding referrals. For example, the determination unit 137 determines whether or not the target user has taken an action that benefits the first business operator (the business operator who manages the store). For example, the determination unit 137 determines whether the target user has come to the store.

(charging unit 138)
The billing unit 138 bills the first business operator who has made a bid for the bid amount related to customer referrals. Billing unit 138 executes billing when a predetermined condition is satisfied. Charging unit 138 performs charging according to the determination result of determination unit 137 .

[8. Information processing flow]
Next, the procedure of information processing by the information processing system 1 according to the embodiment will be described with reference to FIGS. 15 to 19. FIG. 15 to 19 are flowcharts showing procedures of information processing by the information processing system 1 according to the embodiment.

As shown in FIG. 15, the information processing apparatus 100 acquires customer referral related information (step S301). The information processing apparatus 100 calculates a score indicating an index related to customer referral by inputting a predetermined function to the acquired customer referral related information (step S302).

As shown in FIG. 16, the information processing device 100 determines whether a request for bid assist information has been received (step S401). If the request for bid assist information has not been received (step S401; NO), the information processing apparatus 100 waits until the request for bid assist information is received. On the other hand, when receiving a request for bid assist information (step S401; YES), the information processing apparatus 100 generates bid assist information indicating the degree of customer referral according to the reward (step S402). The information processing device 100 provides the generated bid assist information to the first business operator (step S403).

As shown in FIG. 17, the information processing device 100 determines whether or not a customer referral bid has been received from the first business operator (step S501). The information processing device 100 terminates the information processing when the customer referral bid is not received from the first business operator (step S501; NO). On the other hand, when the information processing device 100 receives a customer referral bid from the first business operator (step S501; YES), the information processing device 100 stores information on the bid from the first business operator in the storage unit (step S502).

As shown in FIG. 18, the information processing apparatus 100 acquires ranking determination information from the storage unit (step S601). The information processing apparatus 100 calculates a first score used for ranking stores (step S602). The information processing apparatus 100 calculates a second score based on the calculated first score and the reward information (step S603). The information processing apparatus 100 determines the rank of the store according to the calculated second score (step S604). The information processing apparatus 100 determines the information of the target store to be provided to the target user according to the determined ranking of the store (step S605). The information processing apparatus 100 provides the target user with information on the determined store (step S606).

As shown in FIG. 19, the information processing apparatus 100 determines whether the target user has performed an action that satisfies a predetermined condition regarding referrals (step S701). When the information processing apparatus 100 determines that the target user has not performed an action that satisfies the predetermined condition regarding customer referrals (step S701; NO), the information processing ends. On the other hand, when the information processing apparatus 100 determines that the target user has performed an action that satisfies the predetermined condition regarding customer referral (step S701; YES), the information processing apparatus 100 charges the first business operator who made the bid (step S702).

[9. effect〕
As described above, the information processing device 100 according to the embodiment has the reception unit 132 . When the reception unit 132 satisfies a predetermined condition regarding the customer referral of the user to the target whose capacity is limited, the first business operator managing the target is transferred to a second business operator different from the first business operator. Bids are accepted from the first operator for paying the fee.

As a result, the information processing apparatus 100 according to the embodiment can appropriately accept bids from businesses that operate targets with limited capacity. In addition, the information processing apparatus 100 can appropriately pay a reward corresponding to the user's referral to a target with limited capacity. In addition, since the information processing apparatus 100 can send customers according to the bid amount specified by the target side, it is possible to develop attractive customer-attracting activities for the target side.

Further, the accepting unit 132 accepts a bid indicating the value of the remuneration to be paid by the first business operator to the second business operator when a predetermined condition is satisfied.

Thereby, the information processing apparatus 100 according to the embodiment can refer customers according to the bid amount specified by the target side.

In addition, the reception unit 132 receives a bid from the first business operator for paying a reward to the second business operator that has performed an action that contributes to the user referral to the target.

As a result, the information processing apparatus 100 according to the embodiment can appropriately pay the reward corresponding to the user's customer referral to the target to the second company that has performed the customer referral desired by the first company. .

In addition, the reception unit 132 receives a bid from the first business operator for paying a reward to the second business operator who has provided the user with information about the target.

As a result, the information processing apparatus 100 according to the embodiment can appropriately pay to the second business operator who has provided the information desired by the first business operator a reward corresponding to the referral of the user to the target. .

In addition, the reception unit 132 receives the first operator's compensation for the first operator's payment to the second operator when the user performs a predetermined action in response to the information provided by the second operator. Accept bids from businesses.

As a result, the information processing apparatus 100 according to the embodiment appropriately pays a reward corresponding to the referral of the user to the target to the second business operator who provided the information for promoting the improvement of the referral of the user to the target. can be done.

In addition, the reception unit 132 receives a bid from the first business operator for paying a reward to the second business operator who distributed the coupon related to the target to the user.

As a result, the information processing apparatus 100 according to the embodiment appropriately pays a reward corresponding to the referral of the user to the target to the second business operator who provided the information for promoting the improvement of the referral of the user to the target. can be done.

In addition, the reception unit 132 receives a bid from the first business operator for the first business operator to pay a reward to the second business operator when the user selects the coupon.

Thereby, the information processing apparatus 100 according to the embodiment can appropriately pay a reward corresponding to the user referral to the target.

In addition, the reception unit 132 receives a bid from the first business operator for the first business operator to pay a reward to the second business operator when the user performs an action that leads to the profit of the first business operator. accept.

Thereby, the information processing apparatus 100 according to the embodiment can appropriately pay a reward corresponding to the user referral to the target.

The reception unit 132 also receives a bid from the first business operator for the first business operator to pay a reward to the second business operator when the user visits the target store.

As a result, the information processing apparatus 100 according to the embodiment can appropriately pay a reward corresponding to the referral of the user to the target store.

The information processing apparatus 100 according to the embodiment also has a providing unit 136 that provides services related to the bids received by the receiving unit 132 .

As a result, the information processing apparatus 100 according to the embodiment can stimulate the user's curiosity about the target according to the service to be provided, thereby promoting the improvement of customer referrals to the target.

In addition, the providing unit 136 provides a service related to referral of the user to the target.

As a result, the information processing apparatus 100 according to the embodiment can stimulate the user's curiosity about the target, and thus can promote the improvement of customer referrals to the target.

In addition, the providing unit 136 provides the user with information about the target.

As a result, the information processing apparatus 100 according to the embodiment can stimulate the user's curiosity about the target, and thus can promote the improvement of customer referrals to the target.

Also, the providing unit 136 distributes a coupon related to the target to the user.

As a result, the information processing apparatus 100 according to the embodiment can stimulate the user's curiosity about the target, and thus can promote the improvement of customer referrals to the target.

[10. Hardware configuration]
Also, the terminal device 10, the business operator device 20, and the information processing device 100 according to the above-described embodiments are implemented by, for example, a computer 1000 configured as shown in FIG. FIG. 20 is a hardware configuration diagram showing an example of a computer that implements the functions of the terminal device 10, the business operator device 20, and the information processing device 100. As shown in FIG. Computer 1000 has CPU 1100 , RAM 1200 , ROM 1300 , HDD 1400 , communication interface (I/F) 1500 , input/output interface (I/F) 1600 and media interface (I/F) 1700 .

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

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. Communication interface 1500 receives data from another device via a predetermined communication network, sends the data to CPU 1100, and transmits data generated by CPU 1100 to another device via a predetermined communication network.

The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, through an input/output interface 1600 . CPU 1100 acquires data from an input device via input/output interface 1600 . CPU 1100 also outputs the generated data to an output device via input/output interface 1600 .

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

For example, when the computer 1000 functions as the terminal device 10, the business operator device 20, and the information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes a program loaded on the RAM 1200 to control the control unit 14, 24 and 130 functions. CPU 1100 of computer 1000 reads these programs from recording medium 1800 and executes them, but as another example, these programs may be obtained from another device via a predetermined communication network.

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

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

Further, the embodiments described above can be appropriately combined within a range that does not contradict the processing contents.

As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to carry out the invention in other forms with modifications.

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

1 information processing system 10 terminal device 20 business operator device 100 information processing device 110 communication unit 120 storage unit 121 customer referral related information storage unit 122 first model storage unit 123 bid information storage unit 124 order determination information storage unit 125 second model Storage unit 126 Provided information storage unit 127 User information storage unit 128 Business operator information storage unit 130 Control unit 131 Acquisition unit 132 Reception unit 133 Generation unit 134 Calculation unit 135 Determination unit 136 Provision unit 137 Judgment unit 138 Accounting unit N Network

Claims (13)

a providing unit that provides the user with information about targets whose customer referral score of the target user is equal to or higher than a predetermined threshold among a plurality of targets with limited capacity;
an acquisition unit that acquires position information of the user and position information of the target;
a determination unit that determines whether the user has visited the target based on the position information of the user and the position information of the target ;
When the determination unit determines that the user has visited the target , the first business operator who manages the target pays a reward to a second business operator different from the first business operator , and a reception unit that receives a bid from the first business operator. The reception unit
2. The bid indicating the value of the remuneration to be paid by the first business operator to the second business operator is accepted when the determination unit determines that the user has visited the target . The information processing device according to . The reception unit
accepting said bid from said first business operator for paying said reward to said second business operator who has performed an action that contributes to said customer referral of said user to said target. 3. The information processing apparatus according to claim 1 or 2. The reception unit
4. The method according to any one of claims 1 to 3, wherein said bid is received from said first business operator for paying said remuneration to said second business operator who has provided said user with information about said object. 1. The information processing apparatus according to 1. The reception unit
When the user performs a predetermined action with respect to the information provided by the second business operator, the first business operator pays the second business operator a reward. 5. The information processing apparatus according to claim 4, wherein a bid is accepted from. The reception unit
Claim 4 or Claim 5, wherein said bid is received from said first business operator for paying said reward to said second business operator who has distributed a coupon relating to said object to said user. The information processing device described. The reception unit
7. The method according to claim 6, wherein when the user selects the coupon, a bid is received from the first business operator for the first business operator to pay the second business operator a reward. information processing equipment. The acquisition unit
Acquiring the location information of the user and the location information of the target store,
The determination unit is
Determining whether the user has visited the store based on the location information of the user and the location information of the store ,
The reception unit
When the determining unit determines that the user has visited the store , the first business operator makes a bid for paying a reward to the second business operator. 8. The information processing apparatus according to any one of claims 1 to 7, characterized by receiving. The providing unit
further providing services related to the bid received by the receiving unit;
The information processing apparatus according to any one of claims 1 to 8, characterized by: The providing unit
10. The information processing apparatus according to any one of claims 1 to 9, wherein the information processing apparatus provides a service related to the customer referral of the user to the target. The providing unit
11. The information processing apparatus according to any one of claims 1 to 10, wherein a coupon relating to said object is distributed to said user. A computer-executed information processing method comprising:
a providing step of providing information to a user about targets whose customer referral score of the target user is equal to or higher than a predetermined threshold among a plurality of targets whose capacity is limited;
an obtaining step of obtaining location information of the user and location information of the target;
a determination step of determining whether or not the user has visited the target based on the location information of the user and the location information of the target ;
When the determination step determines that the user has visited the target , the first business operator who operates the target pays a reward to a second business operator different from the first business operator , and a receiving step of receiving a bid from the first business operator. A provision procedure for providing information to a user about a target user whose score regarding customer referrals of the target user is equal to or higher than a predetermined threshold among a plurality of targets whose capacity is limited;
an acquisition procedure for acquiring location information of the user and location information of the target;
a determination procedure for determining whether or not the user has visited the target based on the position information of the user and the position information of the target ;
When it is determined by the determination procedure that the user has visited the target , the first business operator who operates the target pays a reward to a second business operator different from the first business operator , an acceptance procedure for accepting a bid from the first business operator, and an information processing program characterized by causing a computer to execute these.

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