JP7632474B2 - Product recommendation device - Google Patents

Description

The present disclosure relates to a product recommendation device and the like.

In the case of shopping for clothing, there are techniques for delivering content to customers to induce them to purchase products. For example, the technique disclosed in Patent Document 1 displays when a consumer uses an accessory or piece of clothing that the consumer picked up in front of a product display shelf. In another technique disclosed in Patent Document 1, for example, combinations or coordination information of the product picked up by the consumer with other products is displayed. In another technique disclosed in Patent Document 2, for example, a personal color is used to recommend products to a customer.

JP 2018-045454 A JP 2006-089883 A

However, when shopping for clothing at an actual store, customers may find it difficult to find a product that suits them. For example, in Patent Document 1, the state of use of the product or coordination information is displayed to the customer, but it is difficult for the customer to determine which product is actually suitable for them from among multiple products.

One example of an objective of the present disclosure is to provide a product recommendation device or the like that makes it easier for a customer to find a product that suits him or her from among products sold in a store.

A product recommendation device in one aspect of the present disclosure includes an identification means for identifying a customer who visits a store, an acquisition means for acquiring information on products owned by the identified customer, an identification means for identifying, from products sold in the store, products whose combination with the owned products meets predetermined combination conditions based on the acquired information on the owned products, and an output means for outputting information on the identified products as recommended product information.

A method in one aspect of the present disclosure identifies a customer who visits a store, obtains information on products owned by the identified customer, and based on the obtained information on the owned products, identifies products for sale at the store that match predetermined combination conditions when combined with the owned products, and outputs information on the identified products for sale as recommended product information.

A recording medium in one aspect of the present disclosure non-temporarily records a program that causes a computer to execute a process of identifying a customer who visits a store, acquiring information on products owned by the identified customer, identifying products sold at the store that, based on the acquired information on the owned products, match a predetermined combination condition when combined with the owned products, and outputting information on the identified products as recommended product information.

According to the present disclosure, it is possible to facilitate a customer to find a product suitable for the customer from among the products sold in a store.

FIG. 1 is a block diagram illustrating a configuration example of a product recommendation device according to the first embodiment. FIG. 2 is a flowchart illustrating an operation example of the product recommendation device according to the first embodiment. FIG. 3 is an explanatory diagram illustrating a configuration example of a system according to the second embodiment. FIG. 4 is a block diagram illustrating a configuration example of a system according to the second embodiment. FIG. 5 is an explanatory diagram illustrating an example of the customer identification DB. FIG. 6 is an explanatory diagram illustrating an example of the owned product DB. FIG. 7 is an explanatory diagram illustrating an example of a sales item DB. FIG. 8 is an explanatory diagram showing an example of a combination condition. FIG. 9 is an explanatory diagram showing an example of a process from combination to output. FIG. 10 is an explanatory diagram showing an example of outputting total amounts in ascending order. FIG. 11 is a flowchart illustrating an operation example of the product recommendation device according to the second embodiment. FIG. 12 is a flowchart showing an example of the specification process in FIG. FIG. 13 is a flowchart showing an example of the output process in FIG. FIG. 14 is an explanatory diagram illustrating an example of a hardware configuration of the system.

Hereinafter, embodiments of a product recommendation device, an information processing method, and a program according to the present disclosure will be described in detail with reference to the drawings. The disclosed technology is not limited to the embodiments.

(Embodiment 1)
FIG. 1 is a block diagram showing a configuration example of a product recommendation device according to a first embodiment. The product recommendation device 10 recommends products sold in a store to a customer who visits the store. Here, the store is not particularly limited. For example, the store is a store that sells clothing accessories. In addition, the store may be, for example, a commercial facility that is a collection of multiple stores.

The product recommendation device 10 recommends products for sale to customers who visit a store. In FIG. 1 , the product recommendation device 10 includes an identification unit 101, an acquisition unit 102, a specification unit 103, and an output unit 104.

The identification unit 101 identifies a customer who visits the store. The identification method is not particularly limited. The identification unit 101 may identify the customer by performing biometric authentication when the customer visits the store. The type of biometric authentication is not particularly limited to face, fingerprint, vein, iris, voiceprint, and the like. Specifically, the identification unit 101 may perform biometric authentication on the customer who visits the store near the entrance of the store, for example. Alternatively, for example, when the inside of the store can be imaged at all times by an imaging device, the imaging device images the customer who visits the store. Then, the identification unit 101 may extract face data of the customer from the image. The face data is, for example, image data of the face part of the customer or a feature amount of the face part of the customer. Then, the identification unit 101 may match the extracted face data with face data stored in advance in the storage unit. This allows the identification unit 101 to identify the customer without the customer performing a new operation or the like. Also, the identification unit 101 may identify the customer by reading the point card by a predetermined device when the customer visits the store. Alternatively, the identification unit 101 may identify a customer by reading, with a predetermined device, information unique to each customer that is displayed on the screen of a display device of the customer's terminal device when the customer visits the store. The identification unit 101 may also identify a customer based on information from the terminal device by wirelessly communicating with the customer's terminal device using a beacon device or the like.

The acquisition unit 102 acquires information on the owned products owned by the identified customer. The owned products are products that the customer has previously purchased or that the customer has previously inherited. There is no particular limitation as to where the customer owns the owned products. Here, the information on the owned products is hereinafter referred to as owned product information. The owned product information is stored in advance in a storage unit accessible by the product recommendation device 10, for example. The storage unit may be a storage unit connected to the internal bus of the product recommendation device 10, or a storage unit of a device accessible by the product recommendation device 10 via a network. The owned product information may be registered in advance by the customer in, for example, the storage unit or a terminal device owned by the customer. The owned product information may be registered in, for example, the storage unit or a terminal device owned by the customer based on the purchase history of products for each customer. The owned product information may also be information on owned products sold within a predetermined period. The owned product information may also be information on products similar to the products owned by the customer.

The identification unit 103 identifies a sales product that matches a predetermined combination condition when combined with the owned product from among the sales products sold in the store based on the owned product information. The predetermined combination condition is not particularly limited. For example, details of the predetermined combination condition will be described in the second embodiment.

The output unit 104 outputs information on the sales items identified based on the predetermined combination conditions as recommended product information. The information on the sales items is hereinafter referred to as sales product information. The output method is not particularly limited. For example, the output unit 104 may output the recommended product information to a customer's terminal device. More specifically, the output unit 104 outputs an email or an electronic message presenting the recommended product information to the customer's terminal device. The output unit 104 may also output the recommended product information to a display device in a store, for example, and the display device may display the recommended product information, thereby outputting the recommended product information to the customer. The output unit 104 may output the recommended product information by, for example, printing the recommended product information to be provided to the customer.

2 is a flowchart showing an example of an operation of the product recommendation device 10 according to the first embodiment. Here, the processing results of each step by the product recommendation device 10 in FIG. 2 are stored in a storage unit such as a storage unit that the product recommendation device 10 can access. The identification unit 101 identifies a customer (step S101). Next, the acquisition unit 102 acquires owned product information of products owned by the customer (step S102).

Then, the identification unit 103 identifies products that meet a predetermined combination condition when combined with the owned products among the products sold in the store (step S103). The output unit 104 outputs the product information of the identified products as product recommendation information to the customer terminal or a display device of the store (step S104). After step S104, the product recommendation device 10 ends the operation of the flow.

Next, the effects of the first embodiment will be described. The product recommendation device 10 recommends to a customer, a sales product whose combination of the customer's owned products and sales products meets a predetermined combination condition. This allows the product recommendation device 10 to recommend sales products that are suitable for the owned products of the customer who visits the store. Therefore, the product recommendation device 10 can facilitate customers who visit an actual store to find the most suitable product.

(Embodiment 2)
Next, the second embodiment will be described in detail with reference to the drawings. Below, the description of the second embodiment will be omitted for the content that overlaps with the above description, so long as the description of the second embodiment is not unclear. Furthermore, in the second embodiment, the customer identification method is not particularly limited as described in the first embodiment. In the second embodiment, a method using an image will be described as an example of a customer identification method.

FIG. 3 is an explanatory diagram showing a configuration example of a system according to the second embodiment. In FIG. 3, the system includes a product recommendation device 20, a terminal device 21, and an imaging device 22. The product recommendation device 20, the imaging device 22, and the terminal device 21 can be connected, for example, via a communication network or the like. The imaging device 22 is installed, for example, in a store. A plurality of imaging devices 22 may be installed, such as imaging devices 22-1 to 22-2. In FIG. 3, the terminal device 21 is a device owned by a customer. The terminal device 21 may be a device installed in a store. Alternatively, the terminal device 21 may be a device owned by a salesperson. The imaging device 22, for example, captures an image for identifying a customer who has visited the store. The product recommendation device 20 outputs a sales-recommended product to a customer who has visited the store. In addition, the terminal device 21 displays, for example, the sales-recommended product output from the product recommendation device 20 on a display unit to the customer. Alternatively, the terminal device 21 notifies the customer of the recommended products output from the product recommendation device 20 by email, electronic message, or voice. In Fig. 3, when outputting the recommended products to the customer, the product recommendation device 20 may output to an output device instead of the customer's terminal device 21, for example, to a display device or to print on a printer in the store.

4 is a block diagram showing a configuration example of a system according to the embodiment 2. In FIG. 4, the system 2 includes a product recommendation device 20, a terminal device 21, and an imaging device 22.

The imaging device 22 captures images or moving images. The imaging device 22 may capture images in response to an instruction from the product recommendation device 20. Alternatively, the imaging device 22 may constantly capture images inside the store. Then, the imaging device 22 may transmit images to the product recommendation device 20 or a storage device in response to an instruction from the product recommendation device 20. When capturing images inside the store, the imaging device 22 captures images of customers who visit the store. As shown in FIG. 4, there may be a plurality of imaging devices 22, such as imaging devices 22-1 to 22-n, where n is a positive integer equal to or greater than 1.

The terminal device 21 is, for example, a device owned by a customer (example of FIG. 3), a device owned by a salesperson, or a device installed in a store. In the second embodiment, as an example, the product recommendation device 20 may output recommended product information to the terminal device 21. The product recommendation device 20 may output sales recommendation information at the timing when an instruction is given by a customer via the terminal device 21. Alternatively, the product recommendation device 20 may output sales recommended products to the terminal device 21 like a push notification. Although an example in which there is one customer is given in FIG. 3 and FIG. 4, when there are multiple customers in the store, there may be as many terminal devices 21 as there are customers. Furthermore, the terminal device 21 and the product recommendation device 20 may be the same.

The product recommendation device 20 has the functions of the product recommendation device 10 described in embodiment 1. The product recommendation device 20 has an image acquisition unit 205, a discrimination unit 201, an owned product acquisition unit 202 (acquisition unit), a behavior analysis unit 206, a specification unit 203, an output unit 204, and a storage unit 210. The product recommendation device 20 is newly added with the image acquisition unit 205, the behavior analysis unit 206, and the storage unit 210 from the product recommendation device 20 according to embodiment 1. The discrimination unit 201, the owned product acquisition unit 202, the specification unit 203, and the output unit 204 have the functions of the discrimination unit 101, the acquisition unit 102, the specification unit 103, and the output unit 104 described in embodiment 1, respectively.

First, the storage unit 210 stores the processing results of each function of the product recommendation device 20. The storage unit 210 also stores data used in the processing of each unit. In Fig. 4, the storage unit 210 stores, as storage contents, for example, a customer identification DB (database) 211, an owned product DB 212, a sales product DB 213, and a combination condition 214. The storage contents of the storage unit 210 in Fig. 4 are only an example. For example, these various pieces of information may be stored in the storage unit 210 of another device (for example, a storage device) connected to the product recommendation device 20 via a communication network or the like.

Although a detailed description will be given of an example of a hardware configuration in FIG. 14 described later, the product recommendation device 20 loads a program including various commands for implementing each functional unit into the storage unit 210 and executes the program. The type of the storage unit 210 is not limited. For example, the storage unit 210 may be a ROM (Read Only Memory), a RAM (Random Access Memory), a semiconductor memory, a HDD (Hard Disk Drive), a SSD (Solid State Drive), or the like.
Furthermore, the storage unit 210 may be a combination of these.

Next, an example of the customer identification DB 211, the owned product DB 212, the sold product DB 213, and the combination condition 214 will be described.

FIG. 5 is an explanatory diagram showing an example of the customer identification DB 211. In the customer identification DB 211, for example, customer ID (Identification) information, customer name information, facial feature information, contact information, and other information related to the customer are associated with each customer. The customer ID is an identifier for identifying the customer. The customer name is the name of the customer. The facial feature is the facial feature of the customer extracted from an image of the customer's face. Instead of the feature, facial image data may be associated with the customer ID information. The notification destination is, for example, the number and email address of the customer's terminal device 21 to which an electronic message is sent when notifying the customer.

In this example, in order to explain the method of identifying a customer using facial features, an example has been described in which information on the facial features of the customer is included in customer identification DB 211. For this reason, the contents stored in customer identification DB 211 can be changed in various ways depending on the method of identifying a customer.

Furthermore, customer identification DB 211 may not include some of the information shown in the figure. Customer identification DB 211 may include other information not shown. For example, customer identification DB 211 may include information on the physical characteristics of customers, such as information on the customer's body type, such as the customer's height and weight, for each customer. Customer identification DB 211 may also include information on the customer's general clothing size and information on the customer's clothing size when purchasing a specific manufacturer. Such customer information may also be included in owned product DB 212.

FIG. 6 is an explanatory diagram showing an example of the owned product DB 212. The owned product DB 212 is owned product information for each customer. The owned product information includes attribute values of multiple attributes of the owned product. For example, the owned product DB 212 associates a customer ID, a product name, a product ID, and attributes for each customer. In FIG. 6, the attributes of the owned product are type, size, dimensions, image, pattern, style, wearing comfort, and material. In addition, the owned product DB 212 may associate the name or identifier of the product's manufacturer and the name or identifier of the sales manufacturer with the owned product. For example, the owned product DB 212 may register various data based on the sales history of each customer. Alternatively, the owned product DB 212 may register various data in advance by the customer. The owned product information is each piece of information associated with a customer ID. That is, the owned product information is a record for each row in the owned product DB 212.

The customer ID is an identifier for identifying a customer. The customer ID here is the same as the customer ID shown in Fig. 5. The owned product DB 212 and the customer identification DB 211 are associated with each other by the customer ID. Note that the customer identification DB 211 and the owned product DB 212 may be the same DB.

The product name is the product name of the product owned by the customer. The product ID is an identifier of the product owned by the customer. The type is, for example, the type of the product owned. The type here is not particularly limited. For example, the type may be a broad classification of clothing such as tops and bottoms. Alternatively, the type here may be more specifically classified by tops and bottoms. For example, in the case of tops of clothing, the types are T-shirts, Y-shirts, blouses, tank tops, cardigans, knits, and hoodies. In the case of bottoms of clothing, the types include jeans (pants), wide pants, tapered pants, chino pants, flare skirts, tight skirts, pencil skirts, and wrap skirts. Other types of clothing include types of dresses, types of jackets, and types of coats. Types also include types of jewelry such as rings and necklaces, types of shoes, types of bags, and types of hats.

The color is the color of the owned product. The method of expressing the color is not particularly limited. The size is the size of the owned product. The method of expressing the size is not particularly limited. The size is expressed, for example, by the sizes S (Small), M (Medium), L (Large), and F (Free), or the sizes 7, 9, and 11. The dimension is the dimension of the owned product. The method of expressing the dimension is not particularly limited. The dimension may be, for example, a numerical value such as the length of the clothes or the length of the waist part of the clothes provided by the manufacturer or the sales manufacturer. Alternatively, the dimension may be a numerical value such as the length actually measured by the customer. The image is, for example, data of an image of the owned product. The image here may be data of a link destination of a storage device in which the image is stored. The image may be, for example, acquired from the manufacturer of the owned product, a store that is a sales destination, or the Internet. Alternatively, the image may be an image captured by the customer. The pattern is, for example, a pattern (design) of the owned product. The pattern may be, for example, a picture applied to the surface of clothes, jewelry, or the like. The type of pattern is not particularly limited, and examples of the pattern include point patterns with symbols such as hearts and stars, animal patterns, polka dot patterns, and stripe patterns.

The style is, for example, the style of the owned product. There is no particular limitation on the style. For example, the style may be a place, situation, or coordinated atmosphere in which the owned product is expected to be used, such as casual, formal, office, or wedding. The wearing feel may be, for example, the feeling when wearing the owned product. Examples of the wearing feel include tight, loose, fit, long length, short length, loose waist circumference, loose neck circumference, and the like. The wearing feel may be specified by the customer. Alternatively, the wearing feel may be provided in advance by a manufacturer or a sales manufacturer. The wearing feel may be determined from various information by the product recommendation device 20. For example, the wearing feel may be determined based on the material of the owned product. The wearing feel may be determined based on the length of the owned product. The wearing feel may be determined based on the shape of the owned product extracted from an image of the owned product. The wearing feel may be determined based on an image of the customer or an image of a store clerk wearing the owned product and the body type of the customer or the body type of the store clerk. The material is, for example, the material of the owned product. For example, the material may be cotton, polyester, nylon, etc. The material may be expressed as 50% cotton or 50% polyester.

The owned product DB 212 may include other information not shown. For example, the owned product DB 212 may include information provided by a manufacturer, a distributor, or a store, such as a washing method. Also, the owned product DB 212 may not include some of the information shown in the figure.

Fig. 7 is an explanatory diagram showing an example of the sales item DB 213. For example, the sales item DB 213 associates item ID information, item name information, and attribute values of item attributes for each item sold in a store. In Fig. 7, the attributes of the sales item include color, size, dimensions, number in stock, image, price, pattern, style, fit, and material.

The product ID is an identifier for the product being sold. The product name is the name of the product being sold. The color is the color of the product being sold. The size is the size of the product being sold. There is no particular limitation on the way in which sizes are expressed. Sizes are expressed, for example, as S, M, L, and F, or as sizes 7, 9, and 11. The dimensions are the dimensions of the product owned. The dimensions include, for example, numerical values such as the length of the garment or the length of the waist of the garment provided by the manufacturer, retailer, or store. The number in stock is the number of products being sold in the store. The image is, for example, data on an image of the product owned. As shown in the figure, the size, dimensions, and number in stock information may be associated by color.

The price is the price of the product for sale. As the price, multiple prices may be registered, such as a price including consumption tax and a price excluding consumption tax. The pattern is the pattern of the product for sale. The pattern may be the same as the pattern in the owned product DB 212. The style is the style of the owned product. The style may be the same as the style in the owned product DB 212. The fit may be, for example, the feeling when wearing the product for sale. As described above, the fit may be tight, loose, or fit. The fit may be specified by a customer or a store clerk who purchased the product for sale. Alternatively, the fit may be provided in advance by a manufacturing manufacturer or a sales manufacturer. Alternatively, the fit may be determined based on the material of the product for sale. The fit may be determined based on the length of the product for sale. The fit may be determined based on the shape of the product for sale extracted from an image of the product for sale. The material is, for example, the material of the product for sale. The material may be the same as the material in the owned product DB 212. The others are not particularly limited. The others are, for example, other features of the product for sale or examples of use of the product for sale. In addition, the sales item DB 213 may not include some of the information shown in the figure. In addition, the sales item DB 213 may include other information that is not shown in the figure.

Fig. 8 is an explanatory diagram showing an example of the combination condition 214. In Fig. 8, for ease of understanding, the combination condition 214 is expressed like a database. The method of defining the combination condition 21 is not particularly limited. The combination condition 214 may be, for example, a conditional expression.

The combination condition 214 may be determined by, for example, attribute values of attributes of the products. As shown in FIG. 8, attributes of the combination condition 214 include color, color combination, pattern, pattern combination, style, wearing comfort, and material. In FIG. 8, attribute values are shown under each attribute. The combination condition 214 shown in FIG. 8 may include only some of the multiple attributes. The combination condition 214 may also include other attributes not shown. The attribute value of each attribute in the combination condition 214 may be preferable. The attribute value of each attribute in the combination condition 214 may also be unpreferable. For example, the attribute value of which attribute is used as the combination condition 214 may be set by a customer, a store clerk, a user of the product recommendation device 20, or an administrator of the product recommendation device 20.

If each attribute is related to a preference, the combination condition 214 may be, for example, that the combination of the sale product and the owned product includes a preference, or that the combination of the sale product and the owned product is a preference combination.

In addition, when each attribute relates to something that is not preferred, the combination condition 214 may be, for example, that the combination of the sale item and the owned item does not include something that is not preferred, or that the combination of the sale item and the owned item is not a combination that is not preferred.

Taking color as an example, the color may be a favorite color. For example, the favorite color may be a color that the customer likes or a color that the sales clerk wants to recommend. The favorite color may also be a trendy color, etc. In the case of a favorite color, for example, the combination condition 214 is that the favorite color is included in the combination of the sale product and the owned product. The color may also be a disliked color. For example, the disliked color may be that the customer does not like or a color that the sales clerk does not recommend. In the case of a disliked color, for example, the combination condition 214 is that the disliked color is not included in the combination of the sale product and the owned product.

The color combination may be a preferred color combination. The preferred color combination may be, for example, a color combination of tops, bottoms, hats, and shoes. The preferred color combination may be, for example, a trendy color in any of the tops, bottoms, hats, or shoes. For example, in the case of a preferred color combination, the combination condition 214 may be a preferred color combination of the sold product and the owned product. For example, if the combination of black and white is preferred, a combination of the sold product and the owned product in which one of the products is black and the other is white matches the combination condition 214. The color combination may also be a non-preferred color combination. In the case of a non-preferred color combination, the combination condition 214 may be that the sold product and the owned product are not a non-preferred color combination. For example, if the combination of white and yellow is not preferred, a combination of the sold product and the owned product in which one of the products is white and the other is yellow does not match the combination condition 214.

Returning to the explanation of Fig. 4, each functional unit will be explained. As explained in the first embodiment, the identification method by the identification unit 201 is not particularly limited. In the second embodiment, an example of a method of identifying a customer by the identification unit 201 will be explained using an image.

The image acquisition unit 205 acquires, for example, an image captured by the imaging device 22. The image here may be a moving image.

The identification unit 201 identifies a customer by identifying a person's face from a captured image. Specifically, the identification unit 201 extracts facial features from the image, for example. The identification unit 201 may then identify the customer by, for example, matching information on the extracted facial features with information on the facial features of each face stored in the customer identification DB 211. For example, the identification unit 201 obtains information on a customer ID associated with the information on the matched facial features.

Next, the owned product acquisition unit 202 acquires owned product information of the identified customer. Specifically, the owned product acquisition unit 202 acquires the owned product information of the customer based on the information of the customer ID from the owned product DB 212, for example. The owned product information of the customer is each piece of information (row-oriented records) associated with the information of the customer ID in the owned product DB 212.

The identification unit 203 identifies a sales product whose combination with the owned product matches the combination condition 214 based on the acquired owned product information. The identified sales product becomes a recommended sales product. The identification unit 203 identifies the recommended sales product from the sales products sold in the store. For example, the combination condition 214 may be as shown in FIG. 8. The combination condition 214 may be specified by the customer. Therefore, the combination condition 214 can be changed in various ways. The sales product information is acquired from the sales product DB 213 described above.

Furthermore, the identifying unit 203 may identify a sales product in which a combination of an attribute value of an attribute of the sales product and an attribute value of an attribute of an owned product matches the combination condition 214. As shown in FIG. 8, the attributes used in the combination condition 214 are, for example, as shown in FIG. 8. Take a favorite color combination as an example. Take a favorite color combination of a white top and a red bottom. In this case, the identifying unit 203 identifies a sales product in which the top is white and the bottom is red in the combination of the sales product and the owned product.

Also, a case will be taken as an example in which the combination condition 214 does not include a combination of patterns that are not preferred. When the attribute value of the combination of patterns that are not preferred is "same pattern," the identification unit 203 identifies, from the sold products, a sold product and a owned product that do not have the same pattern. For example, a combination in which the sold product is a skirt with a polka dot pattern and the owned product is a plain Y-shirt is not the same pattern, so the identification unit 203 identifies the skirt with a polka dot pattern.

Also, a case where the combination condition 214 is a combination of preferred fit will be taken as an example. When the preferred combination of fit is "tight tops and loose bottoms", the identification unit 203 identifies a sales product from among the sales products that has a combination of the fit of the sales product and the fit of the owned product that is "tight tops and loose bottoms". For example, if the type of the sales product is a shirt and has a loose fit, and the type of the owned product is a skirt and has a loose fit, the combination of the sales product and the owned product does not match the combination condition 214 because the top is not tight. On the other hand, for example, if the type of the sales product is a shirt and has a tight fit, and the type of the owned product is a skirt and has a tight fit, the combination of the sales product and the owned product matches the combination condition 214. For this reason, the identification unit 203 identifies a sales product that is a tight shirt.

Also, although not shown, a case where the combination condition 214 is whether or not the product is featured in a magazine will be taken as an example. If the product is featured in a magazine, the identification unit 203 may identify, among the products for sale, a product for sale that is featured in a magazine in combination with the owned product. In such a case, information on combinations including the products for sale that were featured in a magazine during a predetermined period of time is stored in the storage unit 210 in advance as coordination information. Alternatively, magazine publication information may be acquired via a communication network. Furthermore, the identification unit 203 may identify, for example, a product for sale that is featured in a specified magazine in a combination of the product for sale and the owned product. The magazine may be specified by a customer, a store clerk, a user of the product recommendation device 20, or an administrator of the product recommendation device 20.

The combination condition 214 may be determined based on the attributes of the products shown in Fig. 8 and whether or not the products have been featured in a magazine. For example, the combination condition 214 may be a combination of a preferred fit and being featured in a magazine.

Furthermore, the combination condition 214 may be determined, for example, by whether the number of combinations is equal to or greater than a second predetermined number. Specifically, the identification unit 203 identifies, for example, among the sales products, sales products that have a second predetermined number or more of combinations with the owned products. This allows the product recommendation device 20 to recommend to the customer sales products that are often worn together with the owned products. The second predetermined number can be set, for example, by the customer, a store clerk, a user of the product recommendation device 20, or an administrator of the product recommendation device 20. The second predetermined number can be changed in various ways depending on the customer or the age group of the customer.

Also, for example, the identification unit 203 may identify a recommended product from among products corresponding to the behavior of the customer in the store. Examples of products corresponding to the behavior of the customer in the store include products picked up by the customer, products looked at by the customer for a predetermined time or more, or products similar to these. Specifically, for example, the behavior analysis unit 206 may analyze the behavior of the identified customer. The behavior analysis unit 206 may identify a product picked up by the customer from the image acquired from the image acquisition unit 205. Also, the behavior analysis unit 206 may identify a product to which the customer has been looking for a predetermined time or more from the image acquired from the image acquisition unit 205. The predetermined time may be specified by the customer, the user of the product recommendation device 20, or the store clerk. Then, the identification unit 203 may identify a recommended product from among the products identified by the behavior analysis unit 206. As a result, the product recommendation device 20 can recommend a product that suits the customer from the product in which the customer was interested when visiting the store or products similar to the product.

Next, the process by the output unit 204 will be described. The output unit 204 outputs the sales product information of the identified sales product to the customer as recommended product information. In addition, the sales product information is acquired from the above-mentioned sales product DB 213. As described above, the output method is not particularly limited. For example, the output unit 204 may output the recommended product information to the customer's terminal device 21 using an email, an electronic message, or the like. In addition, the output unit 204 may display the recommended product information on the display device of the customer's terminal device 21. In addition, the output unit 204 may output the recommended product information to an output device installed in the store. The timing of output is not particularly limited. The output unit 204 may output the recommended product information at the timing when the recommended product information is identified from the product recommendation device 20, such as a push notification. In addition, the output unit 204 may output the recommended product information at the timing specified by the customer.

There is no particular limitation on the specific output contents. For example, the output unit 204 may output an image of a combination that matches the combination condition 214. The output unit 204 may also output, for example, the product name of a product for sale. The output unit 204 may also output, for example, the price of the product, the number of products in stock at the store, and the like, in addition to the product name and product image of the product for sale.

Here, an example of the processing of the specification unit 203 and the output unit 204 will be described with reference to FIG. 9. FIG. 9 is an explanatory diagram showing an example from combination to output. In FIG. 9, for example, the products for sale are a product for sale "A001", a product for sale "A002", a product for sale "A003", and a product for sale "A010". Here, for example, the product for sale "A001" indicates a product for sale identified by the product ID "A001". The product for sale "A001", the product for sale "A002", and the product for sale "A003" are skirts with different patterns and different lengths. The product for sale "A010" is a hat with a polka dot pattern. In FIG. 9, for example, the owned products are a product for sale "B001" and a product for sale "B002". Here, for example, the owned product "B001" indicates a product for sale identified by the product ID "B001". The owned product "B001" is a shirt with a different pattern from the owned product "B001" and the owned product "B002". Therefore, there are six combinations of the sale item and the owned item. The combination condition 214 may be, for example, an outfit published in magazine X. For example, the combination of the sale item "A001" and the owned item "B001" is the only outfit published in magazine X. The identification unit 203 then identifies the sale item "A001". The output unit 204 then outputs information about the sale item "A001" as recommended product information. In FIG. 9, the output unit 204 causes the customer's terminal device 21 to display the name and price of the sale item "A001", and the fact that it is being published in magazine X.

4, the output unit 204 may output the recommended product information to the customer in a predetermined output order. The output unit 204 may also narrow down the recommended product information to be output.

For example, the output unit 204 outputs the recommended product information in an order according to the number of combinations that meet the combination condition 214. The order according to the number of combinations may be, for example, an order according to the number of combinations that is the largest, the smallest, or the closest to the specified number. An example will be described in which the identification unit 203 identifies a product for sale "A001" and a product for sale "A002". For the product for sale "A001", two combinations, a combination of the product for sale "A001" and the owned product "B001" and a combination of the product for sale "A001" and the owned product "B002", meet the combination condition 214. On the other hand, for the product for sale "A002", one combination of the product for sale "A002" and the owned product "B001" meets the combination condition 214. In such a case, the output unit 204 outputs the recommended product information in the order from the product for sale "A001" to the product for sale "A002". For example, a customer or a store clerk may be able to switch on the screen of the terminal device 21 between sorting by the largest number of combinations, sorting by the smallest number of combinations, and sorting by the number of combinations closest to a specified number.

In addition, the output unit 204 outputs, as recommended product information, sales product information of sales products for which the number of combinations that match the combination condition 214 is equal to or greater than a predetermined number. The predetermined number can be set by a customer, a store clerk, a user of the product recommendation device 20, or an administrator of the product recommendation device 20. Specifically, for example, the predetermined number may be input on the screen of the terminal device 21. The predetermined number can be changed in various ways depending on the customer or the age group of the customer. In the above example, there are two combinations for the sales product "A001". There is one combination for the sales product "A002". When the predetermined number is 2, the output unit 204 outputs the sales product information of the sales product "A001" as recommended product information. On the other hand, when the predetermined number is 2, the output unit 204 does not output the sales product information of the sales product "A002" as recommended product information. In addition, the predetermined number may be set to be equal to or less than the above-mentioned second predetermined number.

Moreover, the output unit 204 outputs the recommended product information in an order according to the number of sales products in the combination that meets the combination condition 214. The order according to the number of sales products can be the order of the number of sales products that is the largest, the order of the number of sales products that is the smallest, or the order of the number of sales products that is close to the specified number. In the case of the order of the number of sales products that is the largest, the product recommendation device 20 can recommend the sales products in the order of the number of sales products that are newly purchased. Moreover, the order according to the number of sales products may be fixed among the order of the number of sales products that is the largest, the order of the number of sales products that is the smallest, or the order of the number of sales products that is close to the specified number. Alternatively, these orders may be specified by a customer, a store clerk, or a user of the product recommendation device 20. Specifically, for example, these orders may be switchable on the screen of the terminal device 21. Here, the combination condition 214 is a combination that is being published in magazine X. For example, a combination of a sales product "A001" and an owned product "B001" is being published in magazine X. In this case, the number of sales products in the combination is 1. For example, a combination of a sales product "A002", a owned product "B001", and a sales product "A010" is being published in magazine X. In this case, the number of sales products in this combination is 2. When sorting by the number of sales products, the output unit 204 outputs the recommended product information in the order of sales product "A002" and sales product "A001".

Moreover, the output unit 204 outputs the recommended product information in an order according to the total price of the sales products in the combination that meets the combination condition 214. The order according to the total price of the sales products is the highest total price or the lowest total price. Moreover, the highest or lowest price order may be specified by a customer, a store clerk, or a user of the product recommendation device 20. Specifically, for example, the highest or lowest price order may be input or switched on the screen of the terminal device 21. Here, the combination condition 214 is a combination currently being published in magazine X. For example, a combination of a sales product "A001" that is a skirt and a owned product "B001" that is a shirt is currently being published in magazine X, but the combination in magazine X does not include any sales products other than the sales product "A001". In this case, the total price of the sales products in the combination is the price of the sales product "A001". For example, a combination of a sales product "A002" that is a skirt and a owned product "B001" that is a shirt is currently being published in magazine X. Furthermore, the combination in magazine X includes a sales product "A010" that is a hat. In this case, the total price of the sales items in the combination is the total price of the sales item “A001” and the sales item “A010.” In the case of ascending order of total price of the sales items, the output unit 204 outputs the recommended item information in the order of sales item “A001” and sales item “A002.”

FIG. 10 is an explanatory diagram showing an example of output in ascending order of total amount. The total amount of the sold products in a combination of a sold product "A001" and a owned product "B001" is 3,900 yen, the amount of the sold product "A001". The total amount of the sold products in a combination of a sold product "A002", a sold product "A010", and a owned product "B001" is 8,000 yen, the total amount of the sold product "A010" and the sold product "A002". In FIG. 10, the products are output in descending order, and the combination of the sold product "A001" and the owned product "B001" is displayed first on the customer's terminal device 21. Then, the combination of the sold product "A002", the sold product "A010", and the owned product "B001" is displayed second on the customer's terminal device 21. For example, the total amount may be switched between high and low on the screen of the terminal device 21.

Returning to the explanation of FIG. 4, the output unit 204 may output, as recommended product information, sales products among the identified sales products in a combination that matches the combination condition 214 and whose total amount is within the budget range. An example will be explained in which the budget range is 3,000 yen to 7,000 yen. The total amount of sales products in the combination of sales product "A002", sales product "A010", and owned product "B001" in FIG. 10 is 8,000 yen, which is not within the budget range. Therefore, the output unit 204 does not output information on sales product "A002" and sales product "A010" as recommended product information. In addition, the output unit 204 may output recommended product information in an order according to the total amount of sales products in a combination in which the total amount of sales products is within the budget range.

Furthermore, the output unit 204 may output the recommended product information in order according to the number of owned products that match the combination condition 214. The order according to the number of owned products may be, for example, in order of the number of owned products that match the combination condition 214. This allows the product recommendation device 20 to recommend sales products that can be coordinated to make the most of the owned products. Alternatively, the order according to the number of owned products may be, for example, in order of the number of owned products that match the combination condition 214 that is the least. Furthermore, the order of most or least may be selectable by the customer, a store clerk, or a user of the product recommendation device 20 as appropriate.

Furthermore, the output unit 204 may output the recommended product information in an order according to the attribute values of the attributes of the sales products in the combination that matches the combination condition 214. For example, the output unit 204 may preferentially output sales products that are a predetermined color. This allows the product recommendation device 20 to recommend sales products that are coordinated to make the most of the owned products and that better suit the customer's preferences.

Furthermore, the output unit 204 may combine the above-mentioned output order and the output narrowing method. For example, the output unit 204 may output the recommended product information in the order of the number of combinations that is the largest and the total amount of the sold products in the combinations is lowest. For example, the output unit 204 may output the recommended product information in the order of the number of combinations that is the largest and the total amount of the sold products in the combinations is within the budget range.

FIG. 11 is a flowchart showing an example of an operation of the product recommendation device 20 according to the second embodiment. Here, for example, the processing results of each step by the product recommendation device 20 in FIG. 2 are stored in the storage unit 210 or a storage unit accessible by the product recommendation device 20. The image acquisition unit 205 acquires a customer image (step S201). Next, the identification unit 201 identifies the customer from the acquired customer image (step S202). Then, the owned product acquisition unit 202 acquires owned product information (step S203). The identification unit 203 and the behavior analysis unit 206 perform identification processing (step S204). In addition, in the details of step S204, the behavior analysis unit 206 and the output unit 204 perform output processing (step S205). After step S205, the product recommendation device 20 ends the operation of the flow.

Fig. 12 is a flow chart showing an example of the identification process (step S204) in Fig. 11. The behavior analysis unit 206 tracks the behavior of the identified customer for a certain period of time (step S211). Then, the behavior analysis unit 206 extracts sales products according to the customer's behavior (step S212). Examples of sales products according to the customer's behavior include sales products picked up by the customer, sales products on which the customer's gaze is directed for a predetermined period of time or more, and sales products similar to the products picked up by the customer.

Next, the identifying unit 203 identifies, from the extracted sales products, a sales product whose combination with the owned product matches the combination condition 214 (step S213). Then, after step S213, the product recommendation device 20 returns to the original flow. That is, after step S213, the product recommendation device 20 proceeds to step S205 in FIG. 11.

Fig. 13 is a flow chart showing an example of the output process (step S205) in Fig. 11. The product recommendation device 20 determines the order in which the identified sales products are output as recommended sales products (step S221). The output order can be changed in various ways. For example, the output order may be an order according to the total amount of the combination, an order according to the number of combinations, or an order according to the number of sales products in the combination, as described above. Next, the product recommendation device 20 outputs information on the recommended sales products to the terminal device 21 or the like in the determined order (step S222). After step S222, the product recommendation device 20 ends the operation of the flow.

Next, the effects of the second embodiment will be described. The product recommendation device 20 outputs, as recommended product information, information on sales products in which the combination of the owned products of a customer who visits the store and the sales products meets a predetermined combination condition. This allows the product recommendation device 20 to recommend sales products that are suitable for the owned products of the customer who visits the store. Therefore, the product recommendation device 20 can facilitate the customer to find a product that is suitable for the customer from the sales products sold in the store.

In addition, the product recommendation device 20 outputs the recommended product information in order according to the number of combinations that meet a predetermined combination condition. This allows the product recommendation device 20 to recommend to the customer sales products that have more combination patterns with owned products and sales products. Therefore, the product recommendation device 20 can recommend sales products that are more suitable for the customer.

In addition, the product recommendation device 20 outputs, as recommended product information, sales product information of sales products that have a predetermined number or more of combinations that match a predetermined combination condition. This allows the product recommendation device 20 to recommend to the customer sales products that are often worn in combination with owned products and sales products. Therefore, the product recommendation device 20 can recommend sales products that are more suitable for the customer.

In addition, the product recommendation device 20 outputs recommended product information in order according to the number of sales products in a combination that meets a predetermined combination condition. This allows the product recommendation device 20 to recommend, for example, a coordination that includes many sales products. Therefore, the product recommendation device 20 can output sales products so that customers will purchase more sales products.

In addition, the product recommendation device 20 outputs recommended product information in order according to the total price of the products in a combination that meets a predetermined combination condition. This allows the product recommendation device 20 to support the customer in selecting products according to the customer's budget. In addition, when outputting recommended product information in order of lowest total price, the product recommendation device 20 can output to the customer a coordination that is suitable for the customer and has a low total price.

Furthermore, the product recommendation device 20 outputs, as recommended product information, sales product information of sales products whose total value is within the budget range in a combination that meets a predetermined combination condition 214 among the identified sales products. This allows the product recommendation device 20 to recommend sales products that can be purchased within the budget range and coordination that includes the sales products.

In addition, the product recommendation device 20 identifies a sales product that matches a predetermined combination condition when combined with an owned product from among sales products according to the customer's behavior in the store. This allows the product recommendation device 20 to recommend products from sales products that match the interests of the customer who visited the store, for example. Therefore, the product recommendation device 20 can make it easier for the customer to find a product that suits the customer from among the sales products sold in the store.

In addition, the product recommendation device 20 identifies a product for sale that satisfies a predetermined combination condition between the attribute value of the attribute of the product for sale and the attribute value of the attribute of the owned product from among the products for sale in the store. As described above, the attribute may be the color, pattern, wearing comfort, fashion style, or material of the product. In this way, the product recommendation device 20 can facilitate the customer to find a product suitable for the customer according to the combination of product attributes, for example.

The predetermined combination condition may be specified by the customer, for example. This allows the product recommendation device 20 to recommend products for sale that can be coordinated according to the customer's preferences with the products owned by the customer. Therefore, the product recommendation device 20 can make it easier for customers who visit a store to find products that suit them.

14 is an explanatory diagram showing an example of a hardware configuration of the system. The system 3 includes, for example, a product recommendation device 30, a terminal device 31, and an imaging device 32. First, a case where the product recommendation devices 10 and 20 according to the first and second embodiments are realized by a computer will be described. The product recommendation device 30 is an example where the product recommendation devices 10 and 20 described in the first and second embodiments are realized by a computer.

The product recommendation device 30 includes a CPU (Central Processing Unit) 301, a ROM 302, a RAM 303, a storage device 304, and a communication interface 305. Each component is connected to each other via a bus 306.

The CPU 301 controls the entire product recommendation device 30. For example, the CPU 301 may operate an OS (Operating System) to control the entire product recommendation device 30. The CPU 301 may have multiple cores.

The product recommendation device 30 has, for example, a ROM 302, a RAM 303, and a storage device 304 as a storage unit. Examples of the storage device 304 include a semiconductor memory such as a flash memory, a HDD, and an SSD. For example, the storage device 304 stores an OS program, an application program, and various programs according to the first and second embodiments. Alternatively, the ROM 302 stores an application program. The ROM 302 may also store the programs according to the first and second embodiments. The RAM 303 is used as a work area for the CPU 301.

Furthermore, the CPU 301 loads a program stored in the storage device 304 or the ROM 302. Then, the CPU 301 executes each process coded in the program. The CPU 301 may also download various programs via the communication network 310. The CPU 301 functions as a part or the whole of the product recommendation device 30. Then, the CPU 301 may execute the processes or instructions in the illustrated flowchart based on the program.

The communication interface 305 is connected to a communication network 310 such as a LAN (Local Area Network) or a WAN (Wide Area Network) through a wireless or wired communication line. As a result, the product recommendation device 30 is connected to an external device and an external computer through the communication network 310. The communication interface 305 serves as an interface between the communication network 310 and the inside of the product recommendation device 30. The communication interface 305 controls input and output of data from the external device and the external computer.

However, the hardware configuration of the product recommendation device 30 shown in FIG. 14 is an example, and other components may be added, or some components may not be included. For example, the product recommendation device 30 may have a drive device. The CPU 301 may read out the program and data from a recording medium attached to the drive device to the RAM 303. Examples of the recording medium include an optical disk, a flexible disk, a magneto-optical disk, and a USB (Universal Serial Bus) memory. For example, the product recommendation device 30 may also have input devices such as a keyboard and a mouse. The product recommendation device 30 may also have output devices such as a printer and a display.

Next, the hardware configuration of the terminal device 31 described in each embodiment will be described. The terminal device 31 is an example in which the terminal device 21 described in the second embodiment is realized by a computer. The terminal device 31 has, for example, a CPU 311, a ROM 312, a RAM 313, a storage device 314, a communication interface 315, and an input/output device 317. Each component is connected to each other via a bus 316.

The CPU 311 controls the entire terminal device 31. The terminal device 31 has a ROM 312, a RAM 313, and a storage device 314 as a storage unit. Examples of the storage device 314 include a semiconductor memory such as a flash memory, a HDD, and an SSD. For example, the storage device 314 stores an OS program and an application program. Alternatively, the ROM 312 stores an application program. The RAM 313 is used as a work area for the CPU 311.

Furthermore, the CPU 311 loads programs stored in the storage device 314 or the ROM 312. Then, the CPU 311 executes each process coded in the program. The CPU 311 may also download various programs via the communication network 310. The CPU 311 functions as a part or the whole of the terminal device 31. Then, the CPU 311 may execute processes or instructions in the illustrated flowchart based on the program.

The communication interface 315 is connected to a communication network 310 such as a LAN or WAN via a wireless or wired communication line. As a result, the terminal device 31 is connected to an external device and an external computer via the communication network 310. The communication interface 315 serves as an interface between the communication network 310 and the inside of the terminal device 31. The communication interface 315 controls the input and output of data from the external device and the external computer. The input/output device 317 also accepts inputs made by customer operations. The input/output device 317 also outputs data. The input/output device 317 is, for example, a touch panel display.

The hardware configuration of the terminal device 31 shown in FIG. 14 is an example. Components other than those shown in FIG. 14 may be added, or some components may not be included. For example, the terminal device 31 may have a drive device. The CPU 311 may read programs and data from a recording medium attached to the drive device to the RAM 313. Examples of the recording medium include an optical disk, a flexible disk, a magneto-optical disk, and a USB (Universal Serial Bus) memory. For example, the terminal device 31 may have an input device such as a keyboard or a mouse. The terminal device 31 may have an output device such as a printer. The terminal device 31 is not particularly limited to, for example, a smartphone, a mobile phone, a tablet device, or a PC (Personal Computer).

Next, an example of the hardware configuration of the imaging device 32 will be described. The imaging device 32 corresponds to the imaging device 22 described in the second embodiment. The imaging device 32 has a camera 321 and a communication interface 322. Each component is connected by a bus 323. The communication interface 322 is connected to a communication network 310 such as a LAN or a WAN through a wireless or wired communication line. The camera 321 has a function capable of capturing an image. The camera 321 may also be capable of capturing a moving image. As described above, a plurality of imaging devices 32 may be provided. The hardware configuration of the imaging device 32 is an example. Components other than those shown in FIG. 14 may be added.

This concludes the description of the hardware configuration of the system 3. There are various modified examples of the method of realizing the product recommendation devices 10 and 20 described in the first and second embodiments. For example, the product recommendation devices 10 and 20 may be realized by any combination of different computers and programs for each component. Furthermore, multiple components included in each device may be realized by any combination of one computer and program.

Also, a part or all of each component of the product recommendation device 10, 20 may be realized by a circuit for a specific application. Also, a part or all of the product recommendation device 10, 20 may be realized by a general-purpose circuit including a processor such as an FPGA (Field Programmable Gate Array). Also, a part or all of the product recommendation device 10, 20 may be realized by a combination of circuits for a specific application, a combination of general-purpose circuits, or a combination of circuits for a specific application and a general-purpose circuit. Also, these circuits may be a single integrated circuit. Or, these circuits may be divided into multiple integrated circuits. And, the multiple integrated circuits may be configured by being connected via a bus or the like.

Furthermore, when some or all of the components of each device are realized by multiple computers or circuits, the multiple computers or circuits may be arranged in a centralized or distributed manner.

The information processing method described in each embodiment is realized by execution by the product recommendation device 10, 20. Also, the information processing method is realized by execution of a prepared program by a computer such as the product recommendation device. The program described in each embodiment is recorded on a computer-readable recording medium such as an HDD, SSD, flexible disk, optical disk, flexible disk, magneto-optical disk, or USB memory. Then, the program is executed by being read from the recording medium by the computer. Also, the program may be distributed via the communication network 310.

The components of the product recommendation devices 10 and 20 in the above-described embodiments may be realized by hardware, such as a product recommendation device 30 of a computer shown in Fig. 14. Alternatively, the components may be realized by a computer device or firmware based on program control.

Although the present disclosure has been described above with reference to each embodiment, the present disclosure is not limited to the above embodiment. The configuration and details of each of the present disclosures may include embodiments to which various modifications that a person skilled in the art may understand within the scope of the present disclosure are applied. The present disclosure may include embodiments in which the matters described in this specification are appropriately combined or replaced as necessary. For example, matters described using a specific embodiment may also be applied to other embodiments to the extent that no contradiction occurs. For example, although multiple operations are described in order in the form of a flowchart, the order of description does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations can be changed to the extent that the content is not impaired.

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

(Appendix 1)
An identification means for identifying a customer who visits the store;
An acquisition means for acquiring information on products owned by the identified customer;
a specifying means for specifying, from among sales products sold at the store, a sales product that matches a predetermined combination condition when combined with the owned product based on the acquired information on the owned product;
an output means for outputting information on the identified sales item as recommended item information;
A product recommendation device comprising:

(Appendix 2)
the output means outputs the recommended product information in an order according to the number of the combinations that meet the predetermined combination condition.
2. The product recommendation device of claim 1.

(Appendix 3)
the output means outputs, as the recommended product information, information on the sales products in which the number of the combinations that meet the predetermined combination condition is equal to or greater than a predetermined number.
3. The product recommendation device according to claim 1 or 2.

(Appendix 4)
the output means outputs the recommended product information in an order according to the number of the sales products in the combination that meets the predetermined combination condition.
4. The product recommendation device according to claim 1 .

(Appendix 5)
the output means outputs the recommended product information in order according to the total price of the sales products in the combinations that meet the predetermined combination condition.
5. The product recommendation device according to any one of claims 1 to 4.

(Appendix 6)
the output means outputs, as the recommended product information, information on sales products in the combination that meets the predetermined combination condition and has a total price within a budget range, among the identified sales products;
6. The product recommendation device according to any one of claims 1 to 5.

(Appendix 7)
the specifying means specifies a sales item, the combination of which with the owned item satisfies the predetermined combination condition, from sales items corresponding to the behavior of the customer in the store;
7. The product recommendation device according to any one of claims 1 to 6.

(Appendix 8)
The information on the owned product includes attribute values of attributes of the owned product,
the specifying means specifies, from the sales products sold in the store, a sales product in which a combination of an attribute value of the sales product and an attribute value of the owned product meets the predetermined combination condition;
8. The product recommendation device according to any one of claims 1 to 7.

(Appendix 9)
The predetermined combination condition is specified by the customer.
9. The product recommendation device according to any one of claims 1 to 8.

(Appendix 10)
Identify customers who visit your store,
Acquire information on products owned by the identified customer;
Identifying a sales item that satisfies a predetermined combination condition when combined with the owned product from among sales items sold at the store based on the acquired information on the owned product;
and outputting information on the identified sales item as recommended item information.

(Appendix 11)
On the computer,
Identify customers who visit your store,
Acquire information on products owned by the identified customer;
Identifying a sales item that satisfies a predetermined combination condition when combined with the owned product from among sales items sold at the store based on the acquired information on the owned product;
and outputting information on the identified sales item as recommended item information.

This application claims priority based on Japanese Patent Application No. 2020-180992, filed on October 29, 2020, the disclosure of which is incorporated herein in its entirety.

2, 3 System 10, 20, 30 Product recommendation device 101, 201 Identification unit 102 Acquisition unit 103, 203 Identification unit 104, 204 Output unit 202 Owned product acquisition unit 205 Image acquisition unit 206 Behavior analysis unit 210 Storage unit 211 Customer identification DB
212 Owned Product DB
213 Sales product DB

Claims (9)

An identification means for identifying a customer who visits the store;
An acquisition means for acquiring information on products owned by the identified customer;
a specifying means for specifying, from among sales products sold at the store, a sales product that matches a predetermined combination condition when combined with the owned product based on the acquired information on the owned product;
an output means for outputting information on the identified sales item as recommended product information for the customer to wear;
Equipped with
The predetermined combination condition includes a condition that the combination is a combination of items that are being worn in a magazine,
The identification means identifies, from the products sold at the store, a product whose combination of the product and the owned product is a combination of the product that is featured in the magazine.
Product recommendation device. the output means outputs the recommended product information in an order according to the number of the combinations that meet the predetermined combination condition.
The product recommendation device according to claim 1 . the output means outputs, as the recommended product information, information on the sales products in which the number of the combinations that meet the predetermined combination condition is equal to or greater than a predetermined number.
The product recommendation device according to claim 1 or 2 . the output means outputs the recommended product information in an order according to the number of the sales products in the combination that meets the predetermined combination condition.
The product recommendation device according to any one of claims 1 to 3 . the output means outputs the recommended product information in order according to the total price of the sales products in the combinations that meet the predetermined combination condition.
The product recommendation device according to any one of claims 1 to 4 . the output means outputs, as the recommended product information, information on sales products in the combination that meets the predetermined combination condition and has a total price within a budget range, among the identified sales products;
The product recommendation device according to any one of claims 1 to 5 . the specifying means specifies a sales item, the combination of which with the owned item satisfies the predetermined combination condition, from sales items corresponding to the behavior of the customer in the store;
The product recommendation device according to any one of claims 1 to 6 . The information on the owned product includes attribute values of attributes of the owned product,
the specifying means specifies, from the sales products sold in the store, a sales product in which a combination of an attribute value of the sales product and an attribute value of the owned product meets the predetermined combination condition;
The product recommendation device according to any one of claims 1 to 7 . The predetermined combination condition is specified by the customer.
The product recommendation device according to any one of claims 1 to 8 .

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