JP2024172061A - Device for determining item to recommend, method for determining item to recommend, and program for determining item to recommend - Google Patents

Abstract

The present invention makes it possible to reduce the operational burden placed on customers when recommending products.
[Solution] The recommended product determination device includes a visit history acquisition means for acquiring a visit history regarding places visited by a customer, a candidate product extraction means for extracting candidate products corresponding to the visited places from corresponding product information in which a product is associated with a place that a purchaser of the product is likely to visit, a determination means for determining whether the candidate product should be recommended to the customer based on criteria regarding the visit history, and a transmission means for transmitting recommended product information regarding the recommended products that the customer can refer to.
[Selected figure] Figure 2

Description

The present disclosure relates to a recommended product determination device, a recommended product determination method, and a recommended product determination program.

A sales company proposes recommended products to customers on an EC (Electronic Commerce) site. When deciding on recommended products, for example, information about the customer's wish list or the customer's browsing history may be used.

Patent document 1 describes an invention related to a product ordering system that creates information on provisionally ordered products based on a customer's wish list.

International Publication No. 2019/008619

For example, determining recommended products based on information about a customer's wish list or a customer's browsing history may require customer interaction.

One of the objectives of the present disclosure is to provide a recommended product determination device, a recommended product determination method, and a recommended product determination program that can reduce the operational effort required by customers when recommending products.

To solve the above-mentioned problems, the recommended product determination device disclosed herein includes a visit history acquisition means for acquiring a visit history related to places visited by a customer, a candidate product extraction means for extracting candidate products corresponding to the visited places from corresponding product information in which products are associated with places that purchasers of the products are likely to visit, a determination means for determining whether the candidate products should be recommended to the customer based on criteria related to the visit history, and a transmission means for transmitting recommended product information that can be referenced by the customer.

In order to solve the above-mentioned problems, the recommended product determination method disclosed herein acquires a visit history of places visited by a customer, extracts candidate products corresponding to the visited places from corresponding product information that associates products with places that purchasers of the products are likely to visit, determines whether the candidate products should be recommended to the customer based on criteria related to the visit history, and transmits recommended product information that can be referenced by the customer.

To solve the above-mentioned problems, the recommended product determination program disclosed herein causes a computer to execute the following processes: acquire a visit history of places visited by a customer, extract candidate products corresponding to the visited places from corresponding product information that associates products with places that purchasers of the products are likely to visit, determine whether the candidate products should be recommended to the customer based on criteria related to the visit history, and transmit recommended product information that can be referenced by the customer.

According to the present disclosure, it is possible to reduce the operational effort required by customers when recommending products.

1 is a block diagram showing an example of the configuration of a recommended product determination system according to the present invention. 1 is a block diagram showing a configuration of a recommended product determination device according to the present invention. FIG. 2 is a diagram showing an example of a visit history regarding places visited by a customer according to the present invention. 11A and 11B are diagrams showing examples of corresponding product information and criteria according to the present invention. FIG. 4 is a diagram showing an example of a screen displayed on a customer terminal of the recommended product determination system according to the present invention. 4 is a flowchart showing a processing operation of the customer monitoring support device according to the present invention. 1 is a block diagram showing a configuration of a recommended product determination device according to the present invention. FIG. 11 is a diagram showing an example of conditions set for each product according to the present invention. 4 is a flowchart showing a processing operation of the customer monitoring support device according to the present invention. 1 is a diagram illustrating an example of a hardware configuration of a recommended product determination device according to the present invention.

[First embodiment]
An example of the configuration of a recommended product determination system including a recommended product determination device 11 according to the present disclosure will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the configuration of a recommended product determination system. The recommended product determination system includes the recommended product determination device 11, a mobile terminal 91, and a database 92. With reference to Fig. 1, the recommended product determination device 11, the mobile terminal 91, and the database 92 are connected via a network N1.

The mobile terminal 91 is a mobile terminal carried by a customer. The mobile terminal 91 is, for example, a smartphone. The customer can browse the EC site using the mobile terminal 91. The number of mobile terminals 91 included in the recommended product determination system is not limited to one. The recommended product determination system may include multiple mobile terminals 91.

The database 92 stores information used by the recommended product determination device 11. For example, information related to the customer's visit history, corresponding product information, and information related to the customer's attributes. The number of databases 92 is not limited to one. Each piece of information may be stored in a different database 92. The database 92 may be one of the components included in the recommended product determination device 11, or may be provided separately from the recommended product determination device 11.

Next, the recommended product determination device 11 will be described with reference to FIG. 2. FIG. 2 is a block diagram showing the configuration of the recommended product determination device. The recommended product determination device 11 includes a visit history acquisition unit 111, a candidate product extraction unit 112, a determination unit 113, and a transmission unit 114. The visit history acquisition unit 111 acquires a visit history related to places visited by a customer. The candidate product extraction unit 112 then extracts candidate products corresponding to the visited places from corresponding product information in which products are associated with places that a purchaser of the products may visit. The determination unit 113 determines whether the candidate products should be recommended to the customer as recommended products based on criteria related to the visit history. The transmission unit 114 then transmits recommended product information that can be referenced by the customer.

The visit history acquisition unit 111 is one aspect of a visit history acquisition means for acquiring a visit history regarding places visited by a customer. The visit history acquisition unit 111 acquires a visit history regarding places actually visited by a customer.

Here, a place in this disclosure refers to a facility or area that a customer visits. Examples of places include sports facilities, stores, leisure facilities, and tourist spots. Examples of sports facilities include stadiums, gymnasiums, baseball fields, and swimming facilities. Examples of stores include restaurants such as izakayas or cafes. Examples of leisure facilities include campsites, athletic facilities, parks, and beaches. Examples of tourist spots include shrines or theme parks. Tourist spots may also include tourist areas that indicate a certain range. For example, the bookshop district of Jimbocho or Chinatown in Yokohama. And places also include natural environments such as mountains, rivers, or lakes. The facilities or areas included in a place are not limited to the above.

The visited locations acquired by the visit history acquisition unit 111 are the locations among the above locations that the customer has actually visited. The visit history for the visited locations is a criterion indicating that the customer has visited the visited locations many times. The visit history for the visited locations is, for example, the frequency of visits to the visited locations and the duration of stay at the visited locations. The visit frequency is expressed, for example, twice a month or once a week. The duration of stay is expressed in minutes, for example, 1 hour and 24 minutes. The duration of stay may also be expressed in a predetermined unit of time, such as 1.5 hours, 2 hours, or 2.5 hours. The visit history may also include the total number of visits to the visited locations.

The visit history acquisition unit 111 can acquire visit history regarding visited locations from, for example, a mobile terminal 91 carried by the customer. The mobile terminal 91 can detect visited locations from location information. For example, the mobile terminal 91 acquires location information at regular intervals. The mobile terminal 91 can detect a location corresponding to the location information as a location visited by the customer. Furthermore, the mobile terminal 91 can calculate the stay time at a visited location from changes in the location information acquired at regular intervals. The mobile terminal 91 then stores the visited locations of the customer together with the date and time of visit in a database 92. The database 92 is provided inside or outside the mobile terminal 91.

The mobile terminal 91 can then calculate the frequency of visits to the visited places using the information on the visited places and the visit dates and times stored in the database 92. The mobile terminal 91 can also calculate the total number of visits using the information on the visited places and the visit dates and times stored in the database 92.

The mobile terminal 91 transmits the detected visited places and the visit history related to the visited places to the visit history acquisition unit 111. The visit history acquisition unit 111 then acquires the visited places and the visit history related to the visited places. In this case, the visit history acquisition unit 111 acquires the visit history each time the visit history is calculated by the mobile terminal 91.

The visit history acquisition unit 111 may acquire the visit history from the above-mentioned database 92. The mobile terminal 91 stores the visit history in the database 92 together with information on the visited location and the visit date and time. The visit history acquisition unit 111 then acquires the visit history from the database 92. In this case, the visit history acquisition unit 111 can acquire the visit history at any timing. For example, the visit history acquisition unit 111 can acquire the visit history at a preset time. In addition, the visit history acquisition unit 111 can acquire the visit history when the number of visit histories stored in the database 92 exceeds a predetermined number.

Furthermore, the visit acquisition means 111 may acquire location information from the mobile terminal 91. Then, the visit history acquisition unit 111 acquires the visited location and visit history from the location information. Specifically, the visit history acquisition means 111 can detect the location corresponding to the location information as a location visited by the customer. Furthermore, the visit history acquisition unit 111 can calculate the stay time at the visited location from changes in the location information. Then, the visit history acquisition unit 111 can calculate the frequency of visits to the visited location using the information on the visited location and the visit date and time stored in the database 92.

Here, an example of a visit history acquired by the visit history acquisition unit 111 is shown. FIG. 3 is an example of a visit history related to places visited by a customer. The visit history shown in FIG. 3 is an example of a visit history acquired by the visit history acquisition unit 111 from the database 92. The visit history acquired by the visit history acquisition unit 111 includes "Izakaya B" and "C Town Bookstore District" as information on the visited places. The visit history also includes information on the stay time and visit frequency as visit history related to the visited places. Referring to FIG. 3, the visit history related to "Izakaya B" includes information on the stay time of "2 hours" and the visit frequency of "2 times/week". The visit history related to "C Town Bookstore District" also includes information on the stay time of "30 minutes" and the visit frequency of "2 times/year".

The visit history acquisition unit 111 may acquire the visit history based on the history registered for each location. The history registered for each location is the visit history collected by each store or district. For example, it is the history of entering and leaving a facility or the purchase history at a store. The history registered for each location may be stored in the mobile terminal 91. The history registered for each location may also be stored in the database 92. The history registered for each location may each be stored in a different database 92. Then, the visit history acquisition unit 111 acquires the visit history from the mobile terminal 91 or the database 92.

The candidate product extraction unit 112 is one aspect of a candidate product extraction means that extracts candidate products corresponding to a visited location from corresponding product information in which a product is associated with a location that a purchaser of the product may visit. First, the corresponding product information is information in which each location is associated with a product. Here, the locations included in the corresponding product information are locations that a purchaser of the product may visit. Specific examples of locations are as described above. Then, the products included in the corresponding product information are products that are connected to the characteristics specific to the location to which the product is associated. Therefore, visitors to the location included in the corresponding product information are considered to be people who may purchase the product associated with the location. A product category may be associated with a location. Examples of categories include alcohol, beer, books, novels, or sweets. Products associated with a location are not limited to these. Also, the corresponding product information may associate multiple products or product categories with one location.

The corresponding product information that has been set in advance is stored in a database 92 that is provided inside or outside the recommended product determination device 11. When the corresponding product information is stored in the database 92, the candidate product extraction unit 112 acquires the corresponding product information from the database 92.

The corresponding product information will be described with reference to FIG. 4. FIG. 4 is an example of the corresponding product information and the criteria described below. The corresponding product information shown in FIG. 4 associates a product with a location that a purchaser of the product may visit. For example, "Sports goods" and "Cheering goods" are associated with "Stadium A." Visitors to Stadium A are likely to buy sports goods. Also, visitors to Stadium A are likely to support the sports team that plays at the stadium. Therefore, visitors to Stadium A are likely to purchase cheering goods. Therefore, as shown in FIG. 4, the corresponding product information may associate multiple products ("Sports goods" and "Cheering goods") with one location ("Stadium A").

In addition, in the corresponding product information shown in Figure 4, "Izakaya B," "C Town Bookstore District," "Cafe D," and "E Theater" are each associated with products that are related to the characteristics of the location.

Then, the candidate product extraction unit 112 extracts candidate products corresponding to the visited location from the corresponding product information. In other words, the candidate product extraction unit 112 extracts products corresponding to the visited locations visited by the customer in the visit history acquired by the visit history acquisition unit 111 as candidate products. Products associated with the visited location in the corresponding product information are candidate products.

Now, with reference to Figures 3 and 4, an example of candidate product extraction will be described. The customer's visit history shown in Figure 3 includes "Izakaya B" and "C Town Bookstore District" as visited locations. First, by referring to the corresponding product information, "alcohol" is set as the product corresponding to "Izakaya B". Furthermore, "books" are set as the product corresponding to "C Town Bookstore District". Therefore, the candidate product extraction unit 112 extracts "alcohol" and "books" as candidate products.

The determination unit 113 is one aspect of a determination means that determines whether a candidate product is to be recommended to a customer based on criteria related to the visit history. First, the criteria related to the visit history are criteria that indicate that a customer visits a location frequently. They are used to determine whether a candidate product is to be recommended. If the visit history of a customer satisfies the criteria, the determination unit 113 determines that the candidate product is to be recommended. Then, the criteria related to the visit history are set in advance for each product. Then, the criteria related to the visit history are set based on the visit history of customers who are likely to purchase a product corresponding to the location. In other words, if the visit history of a customer satisfies the criteria, the customer may be likely to purchase the product.

The content of the criteria will be explained in detail. First, the criteria regarding the visit history are specifically set for the duration of stay or the frequency of visits. The criteria regarding the visit history may be set for both the duration of stay and the frequency of visits. Furthermore, the criteria regarding the visit history may be set for a visit history different from the duration of stay and the visit history. The criteria regarding the visit history may be set for the total number of visits, for example.

The criteria for the visit history are set, for example, as a threshold value, and represent that a customer visits a location a lot. For example, a case where the criteria for the frequency of visits is twice a month will be described. When a criterion for the frequency of visits is set, and the visit history is three times a month, the visit history meets the criteria. On the other hand, when the visit history is once a month, the visit history does not meet the criteria. Criteria for the duration of stay will also be described. As an example, the criterion for the duration of stay is one hour. In this case, if the duration of stay in the visit history is less than one hour, the visit history does not meet the criterion for the duration of stay. On the other hand, if the duration of stay is two hours, the visit history meets the criterion for the duration of stay. A threshold value may also be set for the total number of visits as a criterion for the duration of stay.

The criteria for visit history may be set within a predetermined range. A specific example is a criteria for visit history of 2-4 times per month. An example of a specific range for stay time is 2-3 hours.

Additionally, the criteria for the visit history may be set with respect to changes in the visit history over time. A change in the visit history is, for example, an increase or decrease in the frequency of visits. Specifically, the criteria for the visit history is that the frequency of visits has more than doubled within a specified period of time. Changes in the visit history also include changes in the duration of stay. Specifically, the criteria for the visit history is that the duration of stay has more than doubled within a specified period of time.

When using a change in visit history as the criterion, the visit history acquisition unit 111 acquires from the database 92 the latest visit history and the visit history from a predetermined period of time that are stored in the database 92. The determination unit 113 then calculates the change in visit history from the latest visit history and the visit history from a predetermined period of time ago. The determination unit 113 can then use the criterion regarding the change in visit frequency to determine whether to set the candidate product as a recommended product.

Here, we will explain the case where multiple criteria are set. As an example, we will explain the case where the criteria are set for thresholds of stay time and visit frequency. The determination unit 113 may determine that a product is a candidate product when the stay time and visit frequency satisfy the criteria. Furthermore, the determination unit 113 may determine that a product is a candidate product when either the stay time or the visit frequency satisfies the criteria.

When multiple products are associated with one location, different criteria may be set for each product. Also, when multiple products are associated with one location, the same criteria may be set for all products.

Figure 4 shows an example of corresponding product information and criteria. The corresponding product information is as described above. Referring to Figure 4, criteria are set for products corresponding to each location. In Figure 4, the stay time and visit frequency are set as criteria. However, criteria related to visit history may be set for the criteria related to stay time, but not for the criteria related to visit frequency. Also, criteria related to visit history may be set for the criteria related to visit frequency, but not for the criteria related to stay time. Furthermore, criteria related to visit history may be set for visit history different from stay time and visit frequency.

Referring to Figure 4, two products are associated with each of "Stadium A" and "Café D." The two products associated with "Stadium A" have different standards. On the other hand, the two products associated with "Café D" have the same standards.

Now, a specific example will be described further with reference to Figures 3 and 4. The visit history acquisition unit 111 and the candidate product extraction unit 112 have been described above. In this example, the determination unit 113 determines that a product is a candidate product when the stay time and visit frequency satisfy the criteria.

As already explained, the candidate product extraction unit 112 extracts "alcohol" and "books" as candidate products. The determination unit 113 determines whether "alcohol" and "books" should be recommended products. Here, referring to the criteria in FIG. 4, the criteria for "alcohol" are a stay time of "1 hour" and a visit frequency of "1 time/week". The visit history corresponding to "alcohol" is a stay time of "2 hours" and a visit frequency of "2 times/week". In this case, the visit history satisfies the criteria. Therefore, the determination unit 113 determines that "alcohol" should be a recommended product.

On the other hand, the criteria for "books" are a stay time of "1 hour" and a visit frequency of "once a week." And the visit history corresponding to "books" has a stay time of "30 minutes" and a visit frequency of "twice a year." In this case, the visit history does not satisfy the criteria. Therefore, the determination unit 113 determines that "books" is not a recommended product.

The transmission unit 114 is one aspect of a transmission means for transmitting recommended product information that can be referenced by a customer. The recommended product information is information related to the recommended product. Details of the recommended product information will be described later. The transmission unit 114 transmits the recommended product information for the product determined by the determination unit 113 to be a recommended product in a format that can be referenced by the customer. Specifically, the transmission unit 114 may transmit a notification including the recommended product information to the mobile terminal 91. The destination of the notification transmitted by the transmission unit 114 is not limited to the mobile terminal 91. The transmission unit 114 transmits the recommended product information related to the recommended product to a terminal that can be confirmed by the customer. The transmission unit 114 may also transmit the recommended product information to be displayed on the EC site. For example, the customer browses the EC site using the mobile terminal 91. At this time, the mobile terminal 91 displays a screen of the EC site including the recommended product information. As a result, the customer can confirm the recommended product information.

The recommended product information may include, for example, the product name, price, a photo of the product, size, or number of items in stock. The recommended product information may also include information about the location associated with the recommended product, i.e., the location visited by the customer.

The case where a category is set as a product will also be described. The transmission unit 114 transmits recommended product information of a product that belongs to a category determined to be a recommended product in a format that can be referenced by the customer.

Figure 5 is a diagram showing an example of a screen displayed on a customer terminal. Figure 5 shows an example of an EC site displayed on a mobile terminal 91 as an example of displaying information about recommended products that a customer can refer to. Figure 5 shows an example of a case where the determination unit 113 has determined that "alcohol" is a recommended product. The determination unit 113 determines that the product category "alcohol" is to be a recommended product. Information about products that belong to the product category "alcohol" is then displayed on the screen. The product name, price, and photo of each product are displayed as information about the product.

Furthermore, "alcohol" is a product associated with "Izakaya B." Therefore, "For those who frequent Izakaya B!" is displayed as information related to the place "Izakaya B" visited by the customer. Furthermore, when the determination unit 113 determines that a product category is a recommended product, a button for transitioning to a screen where a list of products belonging to that category can be viewed may be displayed. In the example of FIG. 5, when the customer presses "Click here for category page," the screen display transitions to a screen where a list of products belonging to that category can be viewed.

The display of the EC site shown in FIG. 5 is an example, and the display content is not limited to this. The display of the EC site may have any display content and format that allows customers to refer to information about recommended products.

The transmission unit 114 transmits the recommended product information at the timing when the determination unit 113 makes a determination. Alternatively, the transmission unit 114 may transmit the recommended product information at the timing when a predetermined time has elapsed since the determination unit 113 determined that a product is a recommended product. The predetermined time is any time, for example, 30 minutes or one day later. The timing when the transmission unit 114 transmits the recommended product is not limited to the above timing.

Next, the operation of the recommended product determination device 11 will be described with reference to FIG. 6. FIG. 6 is a flowchart showing the operation of the recommended product determination device 11.

First, in step S101, the visit history acquisition unit 111 acquires a visit history relating to the places visited by the customer. Then, in step S102, the candidate product extraction unit 112 extracts candidate products corresponding to the visited places from the corresponding product information.

In step S103, the determination unit 113 determines whether to recommend the candidate product to the customer based on criteria related to the visit history. If the visit history meets the criteria, there may be a high possibility that the visitor will purchase the product. Then, in step S104, the transmission unit 114 transmits information about the recommended product that can be referenced by the customer.

The recommended product determination device 11 in this embodiment extracts candidate products corresponding to visited locations from corresponding product information that associates products with locations that purchasers of the products are likely to visit. The recommended product determination device 11 then determines whether to recommend the candidate products to the customer based on criteria related to the visit history. At this time, if the visit history meets the criteria, there may be a high possibility that the visitor will purchase the product. With this configuration, the recommended product determination device 11 can reduce the effort required for the customer to perform operations when recommending products.

The customer effort involved in recommending a product is, for example, the action of the customer adding a product on an EC site to a wish list. Another example of the customer effort is the action of browsing products displayed on an EC site. When recommending products based on a customer's wish list or browsing history, the above tasks or actions may be required.

However, the recommended product determination device 11 of the present invention extracts candidate products corresponding to the visited location from the corresponding product information. Then, the recommended product determination device 11 determines whether to recommend the candidate products based on the visit history. Therefore, it is possible to reduce the work or actions that are troublesome for the customer.

Furthermore, the recommended product determination device 11 extracts candidate products from corresponding product information in which a product is associated with a location that a purchaser of the product may visit, and determines whether the candidate product is to be a recommended product. With this configuration, the recommended product determination device 11 can provide the customer with information on products that match the characteristics of the customer. In the corresponding product information, the location and the product are associated. This product is a product that is related to the location and may be purchased by visitors to the location. In other words, it is a product that is connected to the characteristics of each location. And, the location visited by the customer may represent the characteristics of the customer. The customer's characteristics are, for example, hobbies, habits, or preferences. Therefore, by setting the product corresponding to the location visited by the customer as a candidate product, it is possible to set a product that matches the customer's characteristics as a candidate product. As a result, the recommended product determination device 11 can transmit information on the product that matches the customer's characteristics as a recommended product. In other words, the recommended product determination device 11 can provide the customer with information on products that match the customer's characteristics.

In addition, in the recommended product determination device 11 in this embodiment, the visit history acquisition unit 111 acquires a visit history regarding the places visited by the customer. Here, the visit history includes information regarding the frequency of visits to the places visited by the customer, or information regarding the stay time at the places visited. Then, in the recommended product determination device 11, the determination unit 113 determines whether the candidate product is to be recommended to the customer as a recommended product. At this time, the determination unit 113 determines that the candidate product is to be recommended as a recommended product if the visit frequency or stay time meets the criteria. The visit frequency or stay time of the customer may represent the characteristics of the customer. As described above, the customer's characteristics are, for example, hobbies, habits, or preferences. Specifically, a customer whose hobby is watching sports may frequently go to a stadium. Also, a customer who likes alcohol may stay in an izakaya for a long time. Therefore, the recommended product determination device 11 can determine whether the candidate product is to be recommended to the customer by using the customer's visit frequency or stay time, and determine that a product that matches the customer's characteristics is a recommended product. In other words, the recommended product determination device 11 can provide customers with information about products that match their characteristics.

In the present embodiment, the recommended product determination device 11 determines whether the candidate product is to be recommended to the customer by the determination unit 113 based on criteria. Here, the criteria include a threshold value for the frequency of visits or the duration of stay. Then, the recommended product determination device 11 determines that the candidate product is a recommended product when the frequency of visits or the duration of stay exceeds the threshold value. By setting a threshold value as the criteria, the determination unit 113 can quantitatively determine the relevance between the product and the customer.

In addition, the recommended product determination device 11 in this embodiment determines whether a candidate product should be recommended to a customer based on criteria that differ for each product. A customer is considered to visit a certain location frequently, and the frequency of visits varies depending on the location. Also, the length of stay that a customer is considered to stay in a certain location for a long time varies depending on the location. Therefore, the recommended product determination device 11 determines a candidate product should be recommended to a customer based on criteria that differ for each product, and an appropriate determination is made for each product. As a result, the recommended product determination device 11 is able to transmit information on appropriate recommended products to the customer.

In the present embodiment, the recommended product determination device 11 extracts multiple products as candidate products when multiple products are associated with a place that corresponds to a visited place. The recommended product determination device 11 then determines whether the determination unit 113 will recommend each of the candidate products to the customer. At this time, the determination unit 113 determines whether to recommend each of the candidate products based on a criterion related to the visit history that differs for each candidate product. With this configuration, the recommended product determination device 11 can transmit information on appropriate recommended products to the customer. For example, when multiple products are associated with one location, visitors to a stadium include visitors who are playing a game themselves and visitors who come to watch a game held at the stadium. Products that are highly related to both of them may differ. And the frequency of visits and duration of stay at the stadium for both of them may differ. Therefore, the recommended product determination device 11 can provide the customer with information on products that match the customer's characteristics by determining whether each of the candidate products is recommended to the customer based on a criterion that differs for each candidate product.

Second Embodiment
Next, a second embodiment of the present disclosure will be described. Below, the description of the second embodiment will be omitted to the extent that the description of the second embodiment is not unclear.

Fig. 7 is a block diagram showing the configuration of the recommended product determination device 11 of the present disclosure. Referring to Fig. 7, compared to the recommended product determination device 11, the recommended product determination device 21 further includes a customer information acquisition unit 215 and a priority order determination unit 216. The transmission unit 214 transmits information about the recommended products that can be referenced by the customer based on the priority order.

The customer information acquisition unit 215 is one aspect of a customer information acquisition means for acquiring customer information, which is information relating to the attributes of a customer. The customer information acquisition unit 215 acquires information registered in advance by the customer. The information registered in advance is information relating to the attributes of the customer. Information relating to the attributes of the customer includes, for example, age, sex, family structure, occupation, or area of residence.

The customer inputs information about attributes, for example, on the member registration page of an EC site. The input information about the customer's attributes is stored in database 92. Then, the customer information acquisition unit 215 acquires the information stored in database 92.

Information regarding customer attributes may be stored in the mobile terminal 91. In this case, the customer information acquisition unit 215 acquires information regarding customer attributes from the mobile terminal 91.

The priority determination unit 216 is one aspect of a priority determination means for determining the priority of recommended products based on the conditions for each product related to attributes and customer information. First, the customer information is information related to the attributes of the customer acquired by the customer information acquisition unit 215. The conditions for each product are related to a tendency common to customers who purchase the product. For each product, there are restrictions or a predetermined tendency of customers who purchase the product. For example, the age of customers who purchase alcohol is 20 years or older. There is also a tendency that customers who purchase sweets tend to be mostly women. Therefore, conditions are set in advance based on the restrictions or tendencies of customers for each product. The conditions are set for the attributes. Therefore, if the attributes of a customer satisfy the conditions of a recommended product, it is considered that the customer is likely to purchase the recommended product. Therefore, the priority determination unit 216 determines the priority of recommended products based on the conditions for each product related to attributes and customer information. Here, the condition for each product related to attributes may be one or more. In the following description, it is assumed that there are multiple conditions for each product related to attributes.

The conditions for each product related to attributes are stored in a database 92 provided inside or outside the recommended product determination device 11. The priority determination unit 216 then acquires the conditions from the database 92. The attributes for which conditions are set include, for example, age, sex, family structure, occupation, or residential area. Conditions are set for one or more attributes for each recommended product.

Conditions related to age include conditions expressed by age group, such as "20s". Conditions may also be set with a specific age threshold or range, such as "20 years old or older" or "20 to 35 years old". Furthermore, when the condition is "ALL", customers of any age meet the condition. Conditions related to gender include, for example, "female" or "male". Furthermore, when the criterion is "ALL", customers of any gender meet the condition. Conditions related to family structure include, for example, "family", "single", or "couple". For "family", the number of children or their ages may be set. Furthermore, the number of generations may be set, such as "three-generation family". Conditions related to occupation include, for example, the type of job, industry, working style, working hours, or days of the week on which holidays are taken. Furthermore, the range of the residential area is appropriately set for conditions related to residential area. Conditions related to residential area may be set by city, ward, town, or village, such as "Yokohama City". Furthermore, conditions related to residential area may be set by region, such as "Kanto region". Furthermore, it may be set on a prefecture-by-prefecture basis, such as "Kanagawa Prefecture." The size of the residential area used as the standard varies depending on the location. In other words, for locations visited by customers from all over the country, the standard can be set on a regional basis, for example. On the other hand, for locations visited mainly by residents of the prefecture, the standard can be set on a city, ward, town, or village basis.

With reference to Figure 8, an example of conditions for each product related to attributes will be described. Figure 8 is an example of conditions set for each product. With reference to Figure 8, the attributes for which conditions are set are age and gender. The attributes for which conditions are set are not limited to these. Conditions are set for each product. The conditions differ for each product.

The priority determination unit 216 will now explain how it determines the priority of recommended products based on the conditions for each product related to attributes and customer information. First, a case will now be described where the determination unit 213 has determined that multiple candidate products are recommended products. The priority determination unit 216 calculates the number of attributes that satisfy the conditions among the attributes registered by the customer for each recommended product. The priority determination unit 216 then determines a high priority for a recommended product that has a larger number of registered attributes that satisfy the conditions. If there are recommended products that have the same number of attributes that satisfy the conditions, the priority determination unit 216 determines that the priorities of these products are the same. The priority determination unit 216 may also determine the priority based on, for example, the prices of recommended products that have the same number of attributes that satisfy the conditions. If there is only one recommended product, the priority determination unit 216 can set the priority of that product to the highest.

In addition, the conditions for each product related to an attribute may be weighted for each attribute. In other words, the priority determination unit 216 can also determine the priority of recommended products based on the conditions weighted for each attribute and customer information. As a specific example of weighting, a case will be described in which a score is assigned to each attribute included in the conditions for each product related to an attribute. In other words, the score represents the weight. The score is set, for example, based on the attribute tendencies of purchasers of the recommended products. The priority determination unit 216 then calculates the sum of the scores for each product. The priority is then determined in descending order of the sum of the scores.

The score assigned to each attribute may be the same for all products. Also, the score assigned to each attribute may differ for each product. The scores assigned to each attribute are explained in detail below.

Take the example of a case where product X and product Y are determined to be recommended products. At this time, conditions related to age and gender are set for each recommended product. First, a score is assigned to each attribute, and an example of the scores when the scores are the same for all products will be described. The score for each attribute is set according to the importance of the attribute. For example, age is an important attribute, and gender is an unimportant attribute. For product X, if the customer information satisfies the age condition, the score is 3, and if the gender condition is satisfied, the score is 1. For product Y, if the customer information satisfies the age condition, the score is 3, and if the gender condition is satisfied, the score is 1. Since the scores for the important attributes are higher than the scores for the unimportant attributes, when the priority order determination unit 216 calculates the total score for the products, the importance of the attributes is reflected in the total score value.

On the other hand, a case where a score is assigned to each attribute and the score differs for each product will be described. The tendency of the attributes of the purchaser may differ for each product. When the tendency of the attributes of the purchaser differs for each product, the importance of the attributes differs for each product. Therefore, by assigning different scores to each attribute for each product, the priority determination unit 216 can determine a priority that reflects the importance of the attributes that differ for each product. An example of a score assigned to each attribute and the score differs for each product will be described. For example, for product X, if the customer information satisfies the age condition, the score is 3, and if the gender condition is satisfied, the score is 1. For product X, for product Y, if the customer information satisfies the age condition, the score is 1, and if the gender condition is satisfied, the score is 2.

The transmission unit 214 transmits information about the recommended products that can be referenced by the customer, based on the priority order determined by the priority order determination unit 216. The transmission unit 214 is capable of preferentially transmitting information about products with high priority orders. For example, the transmission unit 214 may transmit to the mobile terminal 91 a notification including recommended product information about the recommended product with the highest priority order. The transmission unit 214 may also transmit to the mobile terminal 91 a notification including information about products with priority orders up to a predetermined rank. The transmission unit 214 may also transmit information about the product with the highest priority order as product information to be displayed on the EC site. The transmission unit 214 may also transmit information about products with priority orders up to a predetermined rank.

The transmission unit 214 may also store information about the products determined by the determination unit 213 to be recommended products in the database 92 together with the customer information of the customer. The transmission unit 214 may transmit all recommended product information stored in the database 92 based on priority. The transmission unit 214 may transmit recommended product information about recommended products up to a predetermined priority among the recommended products stored in the database 92.

In addition, information about the recommended product may be transmitted when the customer revisits a visited location associated with a product determined by the determination unit 213 to be a recommended product. The transmission unit 214 may transmit information about the recommended product when a visited location in the visit history acquired by the visit history acquisition unit 211 matches a visited location of the recommended product stored in the database 92.

Next, the operation of the recommended product determination device 21 will be described with reference to FIG. 9. In comparison with the operation of the recommended product determination device 11 shown in FIG. 6, the operations from step S101 to step S103 and the operations from step S201 to step S203 are the same.

In step S204, the customer information acquisition unit 215 acquires customer information, which is information about the attributes of the customer. Then, in step S205, the priority determination unit 216 determines the priority of the recommended products based on the conditions for each product related to the attributes and the customer information.

In step S206, the transmission unit 214 transmits information about the recommended products that can be referenced by the customer based on the priorities determined by the priority determination unit 216.

In the flowchart shown in FIG. 9, the order of step S204 does not matter. It is sufficient that the acquisition of customer information in step S204 is performed before step S205. For example, step S204 may be performed in parallel with step S201. Also, step S204 may be performed between step S201 and step S202.

The recommended product determination device 21 in this embodiment acquires customer information, which is information related to the attributes of a customer. The recommended product determination device 21 then determines the priority order of recommended products based on the conditions for each product related to the attributes and the customer information. The recommended product determination device 21 then transmits information about the recommended products that the customer can refer to, based on the priority order. With this configuration, the recommended product determination device 21 can increase the priority order of products that match the attributes of a customer. The recommended product determination device 21 then transmits information about the recommended products based on the priority order. As a result, the customer can view information about products that match the attributes. For the seller of the product, since product information is transmitted to customers with matching attributes, there may be a higher possibility that the product will be purchased. In other words, the recommended product determination device 21 can increase purchasing opportunities.

In the present embodiment, the recommended product determination device 21 has a customer information acquisition unit 215 that acquires customer information, which is information about customer attributes including age, sex, family structure, occupation, or residential area. Then, the priority determination unit 216 of the recommended product determination device 21 determines the priority of recommended products based on the conditions set for at least one of the attributes and the customer information. By setting conditions for the attributes, it is possible to transmit information about recommended products that match the customer's attributes. In other words, the customer can learn information about products that match the attributes. Furthermore, if a customer's attributes satisfy the conditions, there may be a high possibility that the customer will purchase the recommended product. This can increase purchasing opportunities for the product seller.

In the present embodiment, the priority determination unit 216 of the recommended product determination device 21 determines a high priority for recommended products that, among the registered attributes, have many attributes that satisfy the conditions. This configuration allows customers to preferentially learn about information about products that match more attributes. It also enables product sellers to provide customers with information about recommended products that are more suited to the customer's attributes. This allows product sellers to expand purchasing opportunities.

In the present embodiment, the priority determination unit 216 of the recommended product determination device 21 determines the priority of the recommended products based on the weight of the attribute that satisfies the condition. Here, the condition is weighted for each attribute. For example, regarding the weighting for each attribute, the seller of the product can set a high score for the attribute that he/she values. Then, the priority determination unit 216 calculates the sum of the scores and determines the priority. Therefore, the priority of the recommended product that satisfies the condition of the attribute with a high score may be determined to be high. Therefore, by weighting the condition for each attribute, the seller's intention can be reflected in the determination of the priority of the recommended products. As a specific example, a case will be described in which it is important for the seller that the product meets the criteria related to age due to its characteristics. In this example, the seller can increase the score of the criteria related to age. As a result, the seller's intention to attach importance to age is reflected in the priority determined by the priority determination unit 216. In other words, it is possible to provide information on recommended products to customers with attributes desired by the seller.

[Hardware configuration example]
10 is a diagram showing an example of a hardware configuration of the recommended item determination device 31 according to the present disclosure. The recommended item determination device 31 is realized by a computer.

The recommended product determination device 31 includes a processor 311, a ROM (Read Only Memory) 312, a RAM (Random Access Memory) 313, a storage device 314 such as a hard disk for storing programs, an input/output interface 315 for inputting and outputting data, and a communication interface 316 for network connection. Each component is connected via a bus 317.

The processor 311 runs an operating system to control the entire computer. Examples of the processor 311 include a CPU (Central Processing Unit), a DSP (Digital Signal Processor), and a GPU (Graphics Processing Unit). The processor loads programs stored in, for example, the ROM 312 or the storage device 314. The processor 311 then executes each process coded in the program. The processor 311 may execute the processes or instructions in the illustrated flowchart based on the program.

ROM 312 stores application programs, programs related to each embodiment, etc. In addition, RAM 313 is used as a work area for processor 311.

The storage device 314 may be, for example, a semiconductor memory such as a flash memory, or a hard disk driver (HDD). The storage device 314 stores, for example, an operating system (OS) program, application programs, programs according to each embodiment, etc.

The input/output interface 315 is connected to peripheral devices (not shown). The connection method may be wired or wireless. Peripheral devices include, for example, a display as an output device.

The communication interface 316 is connected to a communication network (not shown) such as a LAN (Local Network) or a WAN (Wide Area Network) via a wireless or wired communication line. Note that the communication network may be composed of multiple communication networks. This allows the computer to be connected to an external device via the communication network.

A part or all of the above-described embodiments can be described as follows. However, a part or all of the above-described embodiments are not limited to the following.

(Appendix 1)
A visit history acquisition means for acquiring a visit history regarding places visited by a customer;
A candidate product extraction means for extracting candidate products corresponding to the places to be visited from corresponding product information in which a product is associated with a place that a purchaser of the product may visit;
a determination means for determining whether the candidate product should be recommended to the customer based on a criterion related to the visit history;
a transmitting means for transmitting information about the recommended product that can be referenced by the customer;
A recommended product determination device comprising:

(Appendix 2)
A customer information acquisition means for acquiring customer information which is information regarding attributes of a customer;
a priority order determining means for determining a priority order of the recommended products based on the conditions for each product related to the attributes and the customer information;
Further equipped with
The recommended product determination device according to claim 1, wherein the transmitting means transmits the information based on the priority order.

(Appendix 3)
The attributes include age, sex, family structure, occupation, or residential area;
The recommended product determination device according to claim 2, wherein the condition is set for at least one of the attributes.

(Appendix 4)
The recommended product determination device according to claim 3, wherein the priority order determination means determines a higher priority order for the recommended products having a larger number of the attributes that satisfy the condition among the registered attributes.

(Appendix 5)
The conditions of the recommended products are weighted for each of the attributes,
The recommended product determination device according to claim 3, wherein the priority order determination means determines the priority order of the recommended products based on the weights of the attributes that satisfy the condition.

(Appendix 6)
the candidate product extraction means extracts, when a plurality of products are associated with the location corresponding to the visited location in the corresponding product information, the plurality of products as the candidate products;
The recommended product determination device according to claim 1, wherein the determination means determines whether or not each of the candidate products should be a recommended product to be recommended to the customer based on the criterion that differs for each of the candidate products.

(Appendix 7)
The visit history includes information regarding a frequency of visits to the visit location by the customer or information regarding a duration of stay at the visit location;
The recommended product determination device according to any one of claims 1 to 6, wherein the determination means determines whether to recommend the candidate product to the customer as a recommended product when the visit frequency or the stay time satisfies the criterion.

(Appendix 8)
The criteria include a threshold value for the frequency of visits or the duration of stay,
The recommended product determination device according to claim 7, wherein the determination means determines that the candidate product is the recommended product when the visit frequency or the stay time exceeds the threshold value.

(Appendix 9)
The recommended product determination device according to any one of claims 1 to 8, wherein the determination criterion is to determine whether the candidate product is to be a recommended product to be recommended to the customer based on a criterion that differs for each of the products.

(Appendix 10)
Obtaining a visit history regarding the places visited by the customer,
extracting candidate products corresponding to the places to be visited from corresponding product information in which the products are associated with the places that the purchaser of the products may visit;
determining whether to recommend the candidate product to the customer based on criteria related to the visit history;
Transmitting information about the recommended products that can be referenced by the customer;
How to determine recommended products.

(Appendix 11)
On the computer,
Obtaining a visit history regarding the places visited by the customer,
extracting candidate products corresponding to the places to be visited from corresponding product information in which the products are associated with the places that the purchaser of the products may visit;
determining whether to recommend the candidate product to the customer based on criteria related to the visit history;
Transmitting information about the recommended products that can be referenced by the customer;
A recommended product determination program that executes processing.

REFERENCE SIGNS LIST 11, 21, 31 Recommended product determination device 111, 211 Visit history acquisition unit 112, 212 Candidate product extraction unit 113, 213 Determination unit 114, 214 Transmission unit 215 Customer information acquisition unit 216 Priority order determination unit 311 Processor 312 ROM
313 RAM
314 Storage device 315 Input/output interface 316 Communication interface 317 Bus

Claims (10)

A visit history acquisition means for acquiring a visit history regarding places visited by a customer;
a candidate product extraction means for extracting candidate products corresponding to the places to be visited from corresponding product information in which the products are associated with the places to be visited by a purchaser of the products;
a determination means for determining whether the candidate product should be recommended to the customer based on a criterion related to the visit history;
a transmitting means for transmitting recommended product information that can be referred to by the customer when the determining means determines that the candidate product is the recommended product;
A recommended product determination device comprising: A customer information acquisition means for acquiring customer information which is information regarding attributes of the customer;
a priority order determining means for determining a priority order of the recommended products based on the conditions for each product related to the attributes and the customer information;
Further equipped with
The recommended item determination device according to claim 1 , wherein the transmitting means transmits the recommended item information based on the priority order. The attributes include at least one of age, sex, family structure, occupation, and residential area;
The recommended product determination device according to claim 2 , wherein the condition is set for at least one of the attributes. The recommended product determination device according to claim 3 , wherein the priority order determination means determines a higher priority order for the recommended products having a larger number of the attributes that satisfy the condition among the registered attributes. The conditions of the recommended products are weighted for each of the attributes,
The recommended product determination device according to claim 3 , wherein the priority order determination means determines the priority order of the recommended products based on weights of the attributes that satisfy the condition. the candidate product extraction means extracts, when a plurality of products are associated with the location corresponding to the visited location in the corresponding product information, the plurality of products as the candidate products;
The recommended product determination device according to claim 1 , wherein the determination means determines whether each of the candidate products is to be a recommended product to be recommended to the customer based on the criterion that differs for each of the candidate products. The visit history includes information regarding a frequency of visits to the visit location by the customer or information regarding a duration of stay at the visit location;
The recommended product determination device according to claim 1 , wherein the determination means determines whether the candidate product is to be a recommended product to be recommended to the customer when the visit frequency or the stay time satisfies the criterion. The criteria include a threshold value for the frequency of visits or the duration of stay,
The recommended product determination device according to claim 7 , wherein the determination means determines the candidate product to be the recommended product when the visit frequency or the stay time exceeds the threshold value. Obtaining a visit history regarding the places visited by the customer,
extracting candidate products corresponding to the places to be visited from corresponding product information in which the products are associated with the places that the purchaser of the products may visit;
determining whether to recommend the candidate product to the customer based on criteria related to the visit history;
Transmitting recommended product information that can be referenced by the customer regarding the recommended products;
How to determine recommended products. On the computer,
Obtaining a visit history regarding the places visited by the customer,
extracting candidate products corresponding to the places to be visited from corresponding product information in which the products are associated with the places that the purchaser of the products may visit;
determining whether to recommend the candidate product to the customer based on criteria related to the visit history;
Transmitting recommended product information that can be referenced by the customer regarding the recommended products;
A recommended product determination program that executes processing.

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