Merchandise recommendation device, method, and program

Abstract

To provide a merchandise recommendation device that allows a customer to easily find merchandise suitable for the customer from among the merchandise sold in a store.SOLUTION: A merchandise recommendation device comprises an identification unit, an acquisition unit, a specification unit, and an output unit. The identification unit identifies a customer who visits a store. The acquisition unit acquires information of owned merchandise owned by the identified customer. The specification unit specifies, from among selling merchandise sold in the store, selling merchandise in which a combination of wearing feeling when the selling merchandise and the owned merchandise are worn in combination matches a combination condition of the wearing feeling favored by the customer. The output unit outputs information of the identified selling merchandise as recommendation merchandise information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a product recommendation device and the like. [Background technology]

[0002] When shopping for clothing, there are technologies that deliver content to customers to encourage them to purchase products. For example, the technology disclosed in Patent Document 1 displays when a consumer uses an accessory or piece of clothing that the consumer picked up from a display shelf. Also, for example, the technology disclosed in Patent Document 1 displays combinations or coordination information of the product picked up by the consumer with other products. Also, for example, the technology disclosed in Patent Document 2 recommends products to customers using personal colors. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-045454 [Patent Document 2] Japanese Patent Application Laid-Open No. 2006-089883 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when shopping for clothing in a physical 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.

[0005] An example of an objective of the present disclosure is to provide a product recommendation device or the like that makes it easier for customers to find products that suit them from products sold in a store. [Means for solving the problem]

[0006] 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 owned products owned by the identified customer; an identification means for identifying, from the products sold in the store, products for sale that, when combined with the owned products, meet predetermined combination conditions based on the acquired information on the owned products; and an output means for outputting information on the identified products for sale as recommended product information for the customer to wear, wherein the predetermined combination conditions include a combination condition of the customer's preferred wearing feel, and the identification means identifies, from the products for sale in the store, products for sale that, when worn in combination with the owned products, meet the combination condition of the customer's preferred wearing feel.

[0007] In one aspect of the present disclosure, a method includes a computer executing a process in which it identifies a customer who visits a store, acquires information about products owned by the identified customer, and, based on the acquired information about the owned products, identifies products sold at the store that, when combined with the owned products, meet predetermined combination conditions, and outputs information about the identified products as recommended product information for the customer to wear, wherein the predetermined combination conditions include a combination condition of the customer's preferred wearing feel, and the identification process identifies products sold at the store that, when worn in combination with the owned products, meet the customer's preferred wearing feel combination condition.

[0008] A program in one aspect of the present disclosure causes a computer to execute a process of identifying a customer who visits a store, acquiring information on owned products owned by the identified customer, identifying from the products sold at the store those products for sale that, when combined with the owned products, meet predetermined combination conditions based on the acquired information on the owned products, and outputting information on the identified products for sale as recommended product information for the customer to wear, wherein the predetermined combination conditions include a combination condition of the customer's preferred wearing feel, and the identification process identifies from the products sold at the store those products for sale that, when worn in combination with the owned products, meet the customer's preferred combination condition of the wearing feel. [Effects of the Invention]

[0009] According to the present disclosure, it is possible to make it easier for customers to find products suitable for them from the products sold in a store. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram illustrating a configuration example of a product recommendation device according to the first embodiment. [Figure 2] FIG. 2 is a flowchart illustrating an operation example of the product recommendation device according to the first embodiment. [Figure 3] FIG. 3 is an explanatory diagram illustrating a configuration example of a system according to the second embodiment. [Figure 4] FIG. 4 is a block diagram illustrating a configuration example of a system according to the second embodiment. [Figure 5] FIG. 5 is an explanatory diagram showing an example of the customer identification DB. [Figure 6] FIG. 6 is an explanatory diagram illustrating an example of the owned product DB. [Figure 7] FIG. 7 is an explanatory diagram showing an example of the sales product DB. [Figure 8] FIG. 8 is an explanatory diagram showing an example of a combination condition. [Figure 9]FIG. 9 is an explanatory diagram showing an example of the process from combination to output. [Figure 10] FIG. 10 is an explanatory diagram showing an example of outputting in ascending order of total amount. [Figure 11] FIG. 11 is a flowchart illustrating an operation example of the product recommendation device according to the second embodiment. [Figure 12] FIG. 12 is a flowchart showing an example of the identification process in FIG. [Figure 13] FIG. 13 is a flowchart showing an example of the output process in FIG. [Figure 14] FIG. 14 is an explanatory diagram illustrating an example of the hardware configuration of the system. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, with reference to the drawings, embodiments of a product recommendation device, an information processing method, and a program according to the present disclosure will be described in detail. However, the disclosed technology is not limited to the embodiments.

[0012] (Embodiment 1) FIG. 1 is a block diagram showing an example of the configuration of a product recommendation device according to a first embodiment. The product recommendation device 10 recommends products sold in a store to customers who visit the store. Here, the store is not particularly limited. For example, the store may be a store that sells clothing and accessories. Alternatively, the store may be, for example, a commercial facility that is a collection of multiple stores.

[0013] The product recommendation device 10 recommends products for sale to customers who visit a store. In FIG. 1, the product recommendation device 10 includes a recognition unit 101, an acquisition unit 102, a specification unit 103, and an output unit 104.

[0014] The identification unit 101 identifies a customer who visits a 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, and may include face, fingerprint, vein, iris, and voiceprint. Specifically, the identification unit 101 may perform biometric authentication on a customer who visits the store near the store entrance. Alternatively, for example, if an image capture device is capable of capturing images of the store at all times, the image capture device captures an image of a customer who visits the store. The identification unit 101 may then extract facial data of the customer from the image. The facial data may be, for example, image data of the customer's facial area or feature quantities of the customer's facial area. The identification unit 101 may then match the extracted facial data with facial data previously stored in a storage unit. This allows the identification unit 101 to identify the customer without the customer having to perform any additional operations. Alternatively, the identification unit 101 may identify the customer by reading a point card with 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. Furthermore, the identification unit 101 may 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.

[0015] The acquisition unit 102 acquires information about products owned by the identified customer. The owned products include products previously purchased by the customer and products previously inherited by the customer. There is no particular limitation on the location where the customer owns the products. Hereinafter, the information about the owned products will be 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 the storage unit or a terminal device owned by the customer. The owned product information may be registered in the storage unit or a terminal device owned by the customer based on, for example, the customer's product purchase history. The owned product information may also be information about products sold within a predetermined period. The owned product information may also be information about products similar to the products owned by the customer.

[0016] The identification unit 103 identifies, from among the products sold in the store based on the owned product information, products whose combination with the owned product satisfies a predetermined combination condition. The predetermined combination condition is not particularly limited. For example, details of the predetermined combination condition will be described in the second embodiment.

[0017] The output unit 104 outputs information about the sales products identified based on the predetermined combination of conditions as recommended product information. The information about the sales products 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 the customer's terminal device. More specifically, the output unit 104 may output an email or electronic message presenting the recommended product information to the customer's terminal device. Furthermore, the output unit 104 may 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.

[0018] 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 owned products owned by the customer (step S102).

[0019] Then, the identifying unit 103 identifies, from among the products sold in the store, products whose combination with the owned products meets a predetermined combination condition (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 in the store (step S104). After step S104, the product recommendation device 10 ends the operation of the flow.

[0020] Next, the effects of the first embodiment will be described. The product recommendation device 10 recommends to a customer, when the combination of the customer's owned products and the sold products meets a predetermined combination condition. This allows the product recommendation device 10 to recommend a sold product that is suitable for the owned products of the customer who visited the store. Therefore, the product recommendation device 10 can make it easier for customers who visited the actual store to find the most suitable product.

[0021] (Embodiment 2) Next, a second embodiment will be described in detail with reference to the drawings. Below, explanations of the second embodiment that overlap with the above explanations will be omitted to the extent that the explanation of the second embodiment is not unclear. Furthermore, in the second embodiment, the customer identification method is not particularly limited, as explained in the first embodiment. In the second embodiment, a method using an image will be explained as an example of a customer identification method.

[0022] FIG. 3 is an explanatory diagram illustrating 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 via, for example, a communication network. The imaging device 22 is installed in, for example, a store. A plurality of imaging devices 22 may be installed, such as imaging devices 22-1 and 22-2. In FIG. 3, the terminal device 21 is a device owned by a customer. The terminal device 21 may be installed in the store. Alternatively, the terminal device 21 may be owned by a store clerk. The imaging device 22, for example, captures an image for identifying a customer who visits the store. The product recommendation device 20 outputs recommended products to the customer who visits the store. Furthermore, the terminal device 21 displays the recommended products output from the product recommendation device 20 on a display unit for the customer. Alternatively, the terminal device 21 notifies the customer of the recommended sales products output from the product recommendation device 20 by email, electronic message, or voice. In Fig. 3, when outputting recommended sales 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, display on a display device or print on a printer in the store.

[0023] 4 is a block diagram showing an example of the configuration of a system according to the second embodiment. In FIG. 4, the system 2 includes a product recommendation device 20, a terminal device 21, and an imaging device 22.

[0024] 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 the 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 multiple imaging devices 22, such as imaging devices 22-1 to 22-n, where n is a positive integer greater than or equal to 1.

[0025] The terminal device 21 is, for example, a device owned by a customer (example of FIG. 3), a device owned by a store clerk, 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 recommended sales information at the timing when an instruction is received from a customer via the terminal device 21. Alternatively, the product recommendation device 20 may output recommended sales products to the terminal device 21 as a push notification. Although an example in which there is one customer is shown in FIGS. 3 and 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 device.

[0026] 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 classification unit 201, an owned product acquisition unit 202 (acquisition unit), a behavior analysis unit 206, an identification unit 203, an output unit 204, and a storage unit 210. The product recommendation device 20 newly adds the image acquisition unit 205, the behavior analysis unit 206, and the storage unit 210 to the product recommendation device 20 according to embodiment 1. The classification unit 201, the owned product acquisition unit 202, the identification unit 203, and the output unit 204 have the functions of the classification unit 101, the acquisition unit 102, the identification unit 103, and the output unit 104 described in embodiment 1, respectively.

[0027] 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 for processing by 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 sold product DB 213, and a combination condition 214. The storage contents of the storage unit 210 in FIG. 4 are one 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.

[0028] As will be described in detail later with reference to an example hardware configuration in FIG. 14, the product recommendation device 20 loads a program including various commands for realizing each functional unit into the storage unit 210 and executes the program. The type of storage unit 210 is not limited. For example, the storage unit 210 may be a read-only memory (ROM), a random access memory (RAM), a semiconductor memory, a hard disk drive (HDD), or a solid state drive (SSD). Alternatively, the storage unit 210 may be a combination of these.

[0029] 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.

[0030] FIG. 5 is an explanatory diagram showing an example of the customer identification DB 211. For example, the customer identification DB 211 associates, for each customer, customer ID (Identification) information, customer name information, facial feature information, contact information, and other information related to the 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 a facial image of the customer. Instead of the feature, facial image data may be associated with the customer ID information. The notification destination is, for example, the number or email address of the customer's terminal device 21 to which an electronic message is sent when notifying the customer.

[0031] Here, in order to explain the method of identifying customers using facial features as an example, an example has been described in which information on the facial features of customers is included in the customer identification DB 211. For this reason, the contents stored in the customer identification DB 211 can be changed in various ways depending on the method of identifying customers.

[0032] Furthermore, the customer identification DB211 may not include all of the information shown in the figure. The customer identification DB211 may include other information not shown. For example, the customer identification DB211 may include information on the physical characteristics of each customer, such as information on the customer's body type, such as the customer's height and weight. The customer identification DB211 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 the owned product DB212.

[0033] FIG. 6 is an explanatory diagram showing an example of the owned product DB212. The owned product DB212 is owned product information for each customer. The owned product information includes attribute values ​​of multiple attributes of the owned products. In the owned product DB212, for example, a customer ID, a product name, a product ID, and attributes are associated with each customer. In FIG. 6, the attributes of the owned product are type, size, dimensions, image, pattern, style, wearability, and material. In addition, the owned product DB212 may associate the name or identifier of the product's manufacturer and the name or identifier of the distributor with the owned product. For example, various data may be registered in the owned product DB212 based on the sales history of each customer. Alternatively, various data may be registered in the owned product DB212 in advance by the customer. The owned product information is each piece of information associated with a customer ID. In other words, the owned product information is a record for each row in the owned product DB212.

[0034] 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.

[0035] The product name is the product name of a product owned by the customer. The product ID is an identifier for a 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, the types include T-shirts, dress shirts, blouses, tank tops, cardigans, knits, and hoodies. In the case of bottoms, the types include jeans (pants), wide pants, tapered pants, chinos, flared skirts, tight skirts, pencil skirts, and wrap skirts. Other types of clothing include various types of dresses, various types of jackets, and various types of coats. Types also include types of jewelry such as rings and necklaces, types of shoes, types of bags, and types of hats.

[0036] The color is the color of the owned product. There is no particular limitation on the method of expressing the color. The size is the size of the owned product. There is no particular limitation on the method of expressing the size. For example, the size may be expressed as S (Small), M (Medium), L (Large), or F (Free), or as 7, 9, or 11. The dimensions are the dimensions of the owned product. There is no particular limitation on the method of expressing the dimensions. Examples of dimensions include numerical values ​​such as the length of a garment or the length of a waist portion of a garment provided by a manufacturer or retailer. Alternatively, the dimensions may be numerical values ​​such as the length of a garment actually measured by a customer. The image is, for example, data of an image of the owned product. The image here may be data linked to a storage device in which the image is saved. The image may be obtained, for example, from the manufacturer of the owned product, a retail store, or the Internet. Alternatively, the image may be an image captured by the customer. The pattern is, for example, the pattern (design) of the owned product. The pattern may be, for example, a picture applied to the surface of clothing, jewelry, or the like. The type of pattern is not particularly limited. For example, patterns include point patterns with symbols such as hearts and stars, animal patterns, polka dot patterns, and striped patterns.

[0037] The style may be, 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 fit may be, for example, the feeling when wearing the owned product. Examples of the fit may include tight, loose, fitted, long length, short length, loose waist, loose neck, etc. The fit may be specified by the customer. Alternatively, the fit may be provided in advance by the manufacturer or retailer. The fit may be determined by the product recommendation device 20 from various information. For example, the fit may be determined based on the material of the owned product. The fit may be determined based on the length of the owned product. The fit may be determined based on the shape of the owned product extracted from an image of the owned product. The fit may be determined based on an image of the customer or a store clerk wearing the owned product and the customer's or store clerk's body shape. The material may be, for example, the material of the owned product. For example, the material may be cotton, polyester, nylon, etc. The material may also be expressed as 50% cotton or 50% polyester.

[0038] The owned product DB 212 may include other information not shown. For example, the owned product DB 212 may include information such as washing instructions provided by manufacturers, distributors, or stores. Furthermore, the owned product DB 212 may not include all of the information shown in the figure.

[0039] Fig. 7 is an explanatory diagram showing an example of the sales product DB 213. For example, the sales product DB 213 associates product ID information, product name information, and product attribute values ​​for each product sold in a store. In Fig. 7, the attributes of a sales product include color, size, dimensions, stock quantity, image, price, pattern, style, fit, and material.

[0040] The product ID is an identifier for the product for sale. The product name is the name of the product for sale. The color is the color of the product for sale. The size is the size of the product for sale. There are no particular limitations on how sizes are expressed. Sizes are expressed, for example, as S, M, L, F, or as 7, 9, or 11. The dimensions are the dimensions of the owned product. Examples of dimensions include numerical values ​​such as the length of the garment or the length of the waist of clothing provided by the manufacturer, retailer, or store. The stock quantity is the number of products for sale in stock at the store. The image is, for example, image data of the owned product. As shown in the figure, the size, dimensions, and stock quantity information may be associated by color.

[0041] The price is the price of the product for sale. 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 product for sale. 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, examples of the fit include tight, loose, and fitted. The fit may be specified by the customer who purchased the product or a store clerk. Alternatively, the fit may be provided in advance by the manufacturer or retailer. 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. For example, the others may be other features of the product for sale or examples of use of the product for sale. Furthermore, the sales product DB 213 may not include all of the information shown in the figure, and may include other information not shown.

[0042] 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. There are no particular limitations on the method of defining the combination condition 214. The combination condition 214 may be, for example, a conditional expression.

[0043] The combination condition 214 may be determined by, for example, attribute values ​​of product attributes. As shown in FIG. 8, attributes of the combination condition 214 include color, color combination, pattern, pattern combination, style, wearability, and material. In FIG. 8, attribute values ​​are shown below each attribute. The combination condition 214 shown in FIG. 8 may include only some of the multiple attributes. Furthermore, the combination condition 214 may include other attributes not shown. The attribute value of each attribute in the combination condition 214 may be preferred. Furthermore, the attribute value of each attribute in the combination condition 214 may be unpreferable. Furthermore, for example, the attribute value of an attribute to be 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.

[0044] If each attribute relates to a preference, the combination condition 214 may be, for example, that the combination of the sales product and the owned product includes a preference, or that the combination of the sales product and the owned product is a preference.

[0045] Furthermore, when each attribute relates to something that is not preferred, the combination condition 214 may be, for example, that the combination of the sales product and the owned product does not include something that is not preferred. Alternatively, the combination condition 214 may be, for example, that the combination of the sales product and the owned product is not a combination that is not preferred.

[0046] 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 recommends. 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 a combination of a product for sale and a product owned. The color may also be a disliked color. For example, the disliked color may be a color 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 a combination of a product for sale and a product owned.

[0047] The color combination may be a preferred color combination. The preferred color combination may be, for example, a color combination of a top, bottoms, hat, and shoes. The preferred color combination may be, for example, a color combination that includes 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 a sales product and a personal item. For example, if the combination of black and white is preferred, a combination of a sales product and a personal item in which one of the products is black and the other is white satisfies the combination condition 214. Alternatively, the color combination may be a disliked color combination. In the case of an disliked color combination, the combination condition 214 may be a combination of a sales product and a personal item that is not a disliked color combination. For example, if the combination of white and yellow is not preferred, a combination of a sales product and a personal item in which one of the products is white and the other is yellow does not satisfies the combination condition 214.

[0048] Returning to the explanation of Fig. 4, each functional unit will be described. As explained in the first embodiment, there is no particular limitation on the method of identification by the identification unit 201. In the second embodiment, a method using an image will be explained as an example of a method of identifying a customer by the identification unit 201.

[0049] The image acquisition unit 205 acquires, for example, an image captured by the imaging device 22. The image here may be a moving image.

[0050] 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. Then, the identification unit 201 may identify the customer by, for example, matching information on the extracted facial features with information on each facial feature stored in the customer identification DB 211. For example, the identification unit 201 acquires customer ID information associated with the matching facial feature information.

[0051] 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 customer ID information, for example, from the owned product DB 212. The owned product information of the customer is each piece of information (row-oriented records) associated with the customer ID information in the owned product DB 212.

[0052] 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 sales products sold in the store. For example, the combination condition 214 may be as shown in FIG. 8. The combination condition 214 may also 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.

[0053] Furthermore, the identification unit 203 may identify a sales product where a combination of an attribute value of an attribute of the sales product and an attribute value of an attribute of the 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 case where the favorite color combination is a white top and a red bottom. In this case, the identification unit 203 identifies a sales product where the combination of the sales product and the owned product is a white top and a red bottom.

[0054] Also, consider an example in which the combination condition 214 is to exclude combinations 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 products for sale, products for sale that do not have the same pattern when combined with a owned product. For example, if the product for sale is a polka dot skirt and the owned product is a plain dress shirt, the patterns are not the same, so the identification unit 203 identifies the polka dot skirt.

[0055] Also, take an example where the combination condition 214 is a combination of preferred fit. If the combination of preferred fit is "tight tops and loose bottoms," the identification unit 203 identifies, from the sales products, a sales product where the combination of the fit of the sales product and the fit of the owned product is "tight tops and loose bottoms." For example, if the type of sales product is a shirt that fits loosely and the type of owned product is a skirt that fits loosely, the top is not tight, and therefore the combination of the sales product and the owned product does not match the combination condition 214. On the other hand, if the type of sales product is a shirt that fits tightly and the type of owned product is a skirt that fits tightly, then the combination of the sales product and the owned product matches the combination condition 214. Therefore, the identification unit 203 identifies the sales product as a tight shirt.

[0056] Further, although not shown, a case will be taken as an example where the combination condition 214 is whether or not the product has been featured in a magazine. If the product has been featured in a magazine, the identification unit 203 may identify, among the products for sale, a product for sale that is currently featured in the magazine in combination with the owned product. In such a case, information on combinations including the products for sale that have been featured in the magazine during a predetermined period is stored in advance in the storage unit 210 as coordination information. Alternatively, the 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.

[0057] The combination condition 214 may also be determined based on the attributes of the products shown in Fig. 8 and whether or not they have been featured in a magazine. For example, the combination condition 214 may be a combination of a preferred wearing feel and being featured in a magazine.

[0058] 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, from among the products on sale, products on sale 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 products that can be frequently worn 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.

[0059] Furthermore, for example, the identification unit 203 may identify a recommended product from among products corresponding to the customer's behavior in the store. Examples of products corresponding to the customer's behavior in the store include products picked up by the customer, products looked at by the customer for a predetermined period of time or more, and products similar thereto. 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 images acquired by the image acquisition unit 205. The behavior analysis unit 206 may also identify a product that the customer has gazed at for a predetermined period of time or more from images acquired by the image acquisition unit 205. The predetermined period of time may be specified by the customer, a user of the product recommendation device 20, or a store clerk. Then, the identification unit 203 may identify a recommended product from among the products identified by the behavior analysis unit 206. This allows the product recommendation device 20 to recommend a product suitable for the customer from among products that the customer was interested in when visiting the store or products similar to those products.

[0060] Next, the processing by the output unit 204 will be described. The output unit 204 outputs sales product information of the identified sales product to the customer as recommended product information. 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. For example, the output unit 204 may display the recommended product information on a display device of the customer's terminal device 21. 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 by push notification. The output unit 204 may output the recommended product information at the timing specified by the customer.

[0061] There are no particular limitations on the specific output contents. For example, the output unit 204 may output an image of a combination that matches the combination condition 214. Furthermore, the output unit 204 may output, for example, the product name of a product for sale. Furthermore, the output unit 204 may output, for example, the product price, 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.

[0062] Here, an example of processing by the identification unit 203 and the output unit 204 will be described using FIG. 9. FIG. 9 is an explanatory diagram showing an example from combination to output. In FIG. 9, for example, the sales products are sales product "A001", sales product "A002", sales product "A003", and sales product "A010". Here, for example, sales product "A001" indicates a sales product identified by the product ID "A001". Sales product "A001", sales product "A002", and sales product "A003" are skirts with different patterns and different lengths. Sales product "A010" is a polka dot hat. In FIG. 9, for example, owned products are owned product "B001" and owned product "B002". Here, for example, owned product "B001" indicates a owned product identified by the product ID "B001". It is a shirt with a different pattern from owned product "B001" and owned product "B002". Therefore, there are six possible combinations of a product for sale and a product owned. The combination condition 214 may be, for example, an outfit published in magazine X. For example, the combination of product for sale "A001" and product owned "B001" is the only outfit published in magazine X. The identification unit 203 then identifies the product for sale "A001." The output unit 204 then outputs information about the product for sale "A001" as recommended product information. In FIG. 9, the output unit 204 displays on the customer's terminal device 21 the name and price of the product for sale "A001," and the fact that it is featured in magazine X.

[0063] 4, the output unit 204 may output the recommended product information to the customer in a predetermined output order. Also, the output unit 204 may narrow down the recommended product information to be output.

[0064] For example, the output unit 204 outputs the recommended product information in order according to the number of combinations that satisfy the combination condition 214. The order according to the number of combinations may be, for example, order according to the number of combinations with the largest number of combinations, order according to the smallest number of combinations, or order according to the number of combinations closest to a 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 satisfy the combination condition 214: a combination of the product for sale "A001" and an owned product "B001," and a combination of the product for sale "A001" and an owned product "B002." On the other hand, for the product for sale "A002," one combination of the product for sale "A002" and an owned product "B001" satisfies the combination condition 214. In this case, the output unit 204 outputs the recommended product information in the order of the product for sale "A001" to the product for sale "A002." For example, the customer or the store clerk may be able to switch on the screen of the terminal device 21 between sorting in descending order of the number of combinations, sorting in descending order of the number of combinations, and sorting in descending order of the number of combinations closest to a specified number.

[0065] Furthermore, the output unit 204 outputs, as recommended product information, sales product information for sales products for which the number of combinations that satisfy 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 depending on the customer, the age group of the customer, etc. 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 for 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 for the sales product "A002" as recommended product information. The predetermined number may also be set to be equal to or less than the second predetermined number described above.

[0066] Furthermore, the output unit 204 outputs the recommended product information in order according to the number of sales products in the combination that satisfies the combination condition 214. Examples of the order according to the number of sales products include the order of the largest number of sales products, the order of the smallest number of sales products, and the order of the number of sales products closest to a specified number. In the case of the order of the largest number of sales products, the product recommendation device 20 can recommend sales products in order of the number of sales products that are most likely to be newly purchased. Furthermore, the order according to the number of sales products may be fixed, whether it is the order of the largest number of sales products, the order of the smallest number of sales products, or the order of the number of sales products closest to a 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 currently featured in magazine X. For example, a combination of a sales product "A001" and an owned product "B001" is currently featured in magazine X. In this case, the number of sales products in the combination is 1. For example, a combination of sales product "A002", owned product "B001", and sales product "A010" is currently being featured in magazine X. In this case, the number of sales products in this combination is 2. When sorting in descending order of 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".

[0067] Furthermore, the output unit 204 outputs the recommended product information in order according to the total price of the sales products in the combination that satisfies the combination condition 214. The order according to the total price of the sales products may be from highest to lowest total price or from lowest to highest total price. Furthermore, the order of highest to lowest price may be specified by a customer, a store clerk, or a user of the product recommendation device 20. Specifically, for example, the order of highest to lowest price may be input or switched on the screen of the terminal device 21. Here, the combination condition 214 is assumed to be 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 magazine X does not include any other sales products in the combination 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, magazine X includes a sales product "A010" that is a hat in the combination. In this case, the total price of the combined products is the total price of the product "A001" and the product "A010." When the total price of the products is sorted in ascending order, the output unit 204 outputs the recommended product information in the order of product "A001" and product "A002."

[0068] FIG. 10 is an explanatory diagram showing an example of outputting the total amounts in ascending order. The total amount of the items for sale in a combination of a sales item "A001" and an owned item "B001" is 3,900 yen, the price of the sales item "A001." The total amount of the items for sale in a combination of a sales item "A002," a sales item "A010," and an owned item "B001" is 8,000 yen, the total price of the sales item "A010" and the price of the sales item "A002." In FIG. 10, the items are output in descending order, and the combination of the sales item "A001" and the owned item "B001" is displayed first on the customer's terminal device 21. Then, the combination of the sales item "A002," the sales item "A010," and the owned item "B001" is displayed second on the customer's terminal device 21. For example, the order between highest and lowest total amounts may be switchable on the screen of the terminal device 21.

[0069] 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 using a budget range of 3,000 to 7,000 yen. In FIG. 10, the total amount of sales products in the combination of sales product "A002," sales product "A010," and owned product "B001" is 8,000 yen, which is outside the budget range. Therefore, the output unit 204 does not output information about sales product "A002" and sales product "A010" as recommended product information. Furthermore, the output unit 204 may output recommended product information in order of the total amount of sales products in a combination whose total amount is within the budget range.

[0070] 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 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.

[0071] 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 output sales products that are a predetermined color with priority. This allows the product recommendation device 20 to recommend sales products that are coordinated to make the most of the products owned and that better suit the customer's preferences.

[0072] Furthermore, the output unit 204 may combine the above-described output order and output narrowing method. For example, the output unit 204 may output recommended product information in descending order of the number of combinations and the total amount of sales products in the combinations. For example, the output unit 204 may output recommended product information in descending order of the number of combinations and the total amount of sales products in the combinations that are within the budget range.

[0073] 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). Note that in detail in 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.

[0074] Fig. 12 is a flowchart 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 items according to the customer's behavior (step S212). Examples of sales items according to the customer's behavior include sales items picked up by the customer, sales items on which the customer's gaze is directed for a predetermined period of time or more, and sales items similar to the product picked up by the customer.

[0075] Next, the identifying unit 203 identifies, from the extracted sales products, sales products whose combination with the owned products 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.

[0076] FIG. 13 is a flowchart 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, as described above, 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. 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.

[0077] 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 on-sale 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 make it easier for customers to find products that suit them from the on-sale products sold in the store.

[0078] Furthermore, the product recommendation device 20 outputs recommended product information in order according to the number of combinations that match a predetermined combination condition. This allows the product recommendation device 20 to recommend to the customer products that have more combination patterns with owned products and products for sale. Therefore, the product recommendation device 20 can recommend products for sale that are more suitable for the customer.

[0079] Furthermore, the product recommendation device 20 outputs, as recommended product information, sales product information for sales products that have a predetermined number or more of combinations that meet predetermined combination conditions. This allows the product recommendation device 20 to recommend to the customer sales products that are frequently worn with owned products and sales products. Therefore, the product recommendation device 20 can recommend sales products that are more suitable for the customer.

[0080] Furthermore, 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, an outfit that includes many sales products. Therefore, the product recommendation device 20 can output sales products so that customers will purchase more sales products.

[0081] Furthermore, the product recommendation device 20 outputs recommended product information in order according to the total price of the products for sale in combinations that meet predetermined combination conditions. This allows the product recommendation device 20 to support customers in selecting products for sale according to their budget. Furthermore, 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.

[0082] 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 matches the 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.

[0083] Furthermore, the product recommendation device 20 identifies products for sale that match a predetermined combination condition when combined with owned products from products for sale according to the customer's behavior in the store. This allows the product recommendation device 20 to recommend products from products for sale 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 them from products for sale in the store.

[0084] Furthermore, the product recommendation device 20 identifies, from among the products sold in the store, products for which the combination of the attribute values ​​of the attributes of the product for sale and the attribute values ​​of the attributes of the owned products meets a predetermined combination condition. As described above, the attributes include the color, pattern, fit, fashion style, or material of the product. In this way, the product recommendation device 20 can, for example, make it easier for the customer to find a product that suits them based on the combination of product attributes.

[0085] 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 using the products the customer owns. Therefore, the product recommendation device 20 can make it easier for customers who visit a store to find products that suit them.

[0086] 14 is an explanatory diagram showing an example of the 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.

[0087] 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.

[0088] The CPU 301 controls the entire product recommendation device 30. For example, the CPU 301 may run an OS (Operating System) to control the entire product recommendation device 30. The CPU 301 may have multiple cores.

[0089] The product recommendation device 30 has, for example, a ROM 302, a RAM 303, and a storage device 304 as storage units. Examples of the storage device 304 include semiconductor memory such as a flash memory, an 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.

[0090] 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 all of the product recommendation device 30. Then, the CPU 301 may execute the processes or instructions in the illustrated flowchart based on the program.

[0091] The communication interface 305 is connected to a communication network 310 such as a LAN (Local Area Network) or WAN (Wide Area Network) via a wireless or wired communication line. This allows the product recommendation device 30 to be connected to external devices and external computers via 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 also controls the input and output of data from the external devices and external computers.

[0092] 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 programs and data from a recording medium attached to the drive device to the RAM 303. Examples of recording media include optical disks, flexible disks, magneto-optical disks, and USB (Universal Serial Bus) memories. Furthermore, for example, the product recommendation device 30 may have input devices such as a keyboard and a mouse. The product recommendation device 30 may have output devices such as a printer and a display.

[0093] 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 embodiment 2 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.

[0094] 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 storage units. Examples of the storage device 314 include semiconductor memory such as flash memory, HDDs, and SSDs. For example, the storage device 314 stores an OS program and application programs. Alternatively, the ROM 312 stores application programs. The RAM 313 is used as a work area for the CPU 311.

[0095] 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 all of the terminal device 31. Then, the CPU 311 may execute the processes or instructions in the illustrated flowchart based on the program.

[0096] 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 external devices and external computers 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 devices and external computers. The input / output device 317 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.

[0097] 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 and store them in the RAM 313. Examples of recording media include optical disks, flexible disks, magneto-optical disks, and USB (Universal Serial Bus) memories. For example, the terminal device 31 may also have input devices such as a keyboard and a mouse. The terminal device 31 may also have an output device such as a printer. The terminal device 31 is not particularly limited to a smartphone, a mobile phone, a tablet device, a PC (Personal Computer), and the like.

[0098] 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. The components are connected by a bus 323. The communication interface 322 is connected to a communication network 310 such as a LAN or a WAN via, for example, a wireless or wired communication line. The camera 321 has a function capable of capturing images. The camera 321 may also be capable of capturing moving images. 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.

[0099] This concludes the description of the hardware configuration of the system 3. There are various modified examples of the method for 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 a single computer and program.

[0100] Furthermore, some or all of the components of the product recommendation devices 10 and 20 may be realized by circuits for specific applications. Also, some or all of the product recommendation devices 10 and 20 may be realized by general-purpose circuits including a processor such as an FPGA (Field Programmable Gate Array). Also, some or all of the product recommendation devices 10 and 20 may be realized by a combination of circuits for specific applications, a combination of general-purpose circuits, or a combination of circuits for specific applications and general-purpose circuits. 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.

[0101] Furthermore, when some or all of the components of each device are realized by a plurality of computers or circuits, the plurality of computers or circuits may be centrally located or distributed.

[0102] 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 a communication network 310.

[0103] The functions of each of the components of the product recommendation devices 10 and 20 in each embodiment described above may be realized by hardware, such as a product recommendation device 30 of a computer shown in Fig. 14. Alternatively, each component may be realized by a computer device or firmware based on program control.

[0104] Although the present disclosure has been described above with reference to various embodiments, the present disclosure is not limited to the above embodiments. The configuration and details of each of the present disclosures may include embodiments to which various modifications that would be apparent to those skilled in the art are applied within the scope of the present disclosure. The present disclosure may also include embodiments in which the details described herein are appropriately combined or substituted as necessary. For example, details described using a particular embodiment may also be applied to other embodiments to the extent that no contradiction occurs. For example, although multiple operations are described in sequence in the form of a flowchart, the order of the descriptions does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations may be changed as long as it does not interfere with the content.

[0105] Some or all of the above-described embodiments can be described as follows: However, some or all of the above-described embodiments are not limited to the following.

[0106] (Appendix 1) an identification means for identifying customers who visit the store; an acquisition means for acquiring information on the products owned by the identified customer; a specifying means for specifying, from among the products sold in the store, products that, when combined with the owned products, satisfy a predetermined combination condition, based on the acquired information on the owned products; an output means for outputting information on the identified sales product as recommended product information; A product recommendation device comprising:

[0107] (Appendix 2) the output means outputs the recommended product information in an order according to the number of combinations that match the predetermined combination condition. 1. A product recommendation device as described in Appendix 1.

[0108] (Appendix 3) the output means outputs, as the recommended product information, information on the sales products for which the number of the combinations that meet the predetermined combination conditions is equal to or greater than a predetermined number. 10. A product recommendation device as described in appendix 1 or 2.

[0109] (Appendix 4) the output means outputs the recommended product information in order according to the number of the sales products in the combination that meets the predetermined combination condition. 4. A product recommendation device according to any one of claims 1 to 3.

[0110] (Appendix 5) the output means outputs the recommended product information in order according to the total amount of the sales products in the combinations that meet the predetermined combination conditions. 5. A product recommendation device according to any one of appendices 1 to 4.

[0111] (Appendix 6) the output means outputs, as the recommended product information, information on the sales products in the combination that matches the predetermined combination condition and whose total price is within a budget range, among the identified sales products; 6. A product recommendation device according to any one of appendices 1 to 5.

[0112] (Appendix 7) the specifying means specifies a sales product whose combination with the owned product satisfies the predetermined combination condition from sales products corresponding to the customer's behavior in the store; 7. A product recommendation device according to any one of appendices 1 to 6.

[0113] (Appendix 8) the information on the owned product includes attribute values ​​of the attributes of the owned product; the specifying means specifies, from the merchandise sold in the store, a merchandise in which a combination of an attribute value of the merchandise and an attribute value of the owned merchandise meets the predetermined combination condition; 8. A product recommendation device according to any one of claims 1 to 7.

[0114] (Appendix 9) The predetermined combination condition is specified by the customer. 9. A product recommendation device according to any one of appendices 1 to 8.

[0115] (Appendix 10) Identify customers who visit your store, Acquire information on products owned by the identified customer; Identifying, from among the products sold in the store, products that, when combined with the owned product, meet a predetermined combination condition based on the acquired information on the owned product; The information on the identified sales product is output as recommended product information. method.

[0116] (Appendix 11) On the computer, Identify customers who visit your store, Acquire information on products owned by the identified customer; Identifying, from among the products sold in the store, products that, when combined with the owned product, meet a predetermined combination condition based on the acquired information on the owned product; The information on the identified sales product is output as recommended product information. A program that executes a process.

[0117] 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. [Explanation of symbols]

[0118] 2,3 System 10, 20, 30 Product Recommendation Device 101,201 Identification unit 102 Acquisition Department 103,203 Specific part 104,204 Output section 202 Owned Product Acquisition Department 205 Image acquisition unit 206 Behavior Analysis Department 210 Storage section 211 Customer identification DB 212 Owned product DB 213 Sales Product DB

Claims

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 product information for the customer to wear; Equipped with The predetermined combination conditions include a combination condition of a wearing feel preferred by the customer, The specifying means specifies a sales product from the sales products sold at the store, the combination of the wearing feel of the sales product when worn in combination with the owned product matches a combination condition of the wearing feel preferred by the customer. Product recommendation device.

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. The product recommendation device according to claim 1 .

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. The product recommendation device according to claim 1 or 2.

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. The product recommendation device according to any one of claims 1 to 3.

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. The product recommendation device according to any one of claims 1 to 4.

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; The product recommendation device according to any one of claims 1 to 5.

7. 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; outputting information on the identified sales item as recommended item information for the customer to wear; Execute the process, The predetermined combination conditions include a combination condition of a wearing feel preferred by the customer, In the process of identifying, from the sales products sold at the store, a sales product is identified that satisfies a combination condition of the customer's preferred wearing feel when the sales product is combined with the owned product and worn. method.

8. 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; outputting information on the identified sales item as recommended item information for the customer to wear; Execute the process, The predetermined combination conditions include a combination condition of a wearing feel preferred by the customer, In the process of identifying, from the sales products sold at the store, a sales product is identified that satisfies a combination condition of the customer's preferred wearing feel when the sales product is combined with the owned product and worn. program.

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