Information processing apparatus, information processing method, and information processing program

Abstract

To provide an information processor capable of recommending a commodity and its size matched with the desire of a user by adding body shape information to the interest and idea of the user about the commodity to be sold on a Web site by an electronic commerce agent such as Internet sales, and personalizing an electronic commerce site.SOLUTION: The system includes a user information acquisition unit configured to acquire user information including a type of a product desired by a user and user body information of the user via a user terminal, a product information acquisition unit configured to acquire stock quantity, color, size, and type of the product as product information for each product sold on a website of an electronic commerce business operator, a matching unit configured to generate, as recommendation information, coordinate information indicating a state in which the product is worn by a wearer as a subject together with a product group, the coordinate information corresponding to the user based on the stock quantity, color, size, and type of the product, and an output unit configured to output the recommendation information to the user terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program, and more particularly to a device, a method, and a program for recommending products that match the tastes, preferences, and body shape of a user. [Background technology]

[0002] In recent years, services provided by e-commerce businesses, such as those selling online, on their websites have become widespread. A technology has been proposed that presents appropriate recommended sizes to users browsing a website when they purchase clothing (clothing, footwear, etc.) (see Patent Document 1, etc.).

[0003] Conventionally, there have been many websites for clothing. Therefore, users can browse products on their favorite brand websites or sales sites that sell various brand products, and purchase the selected products through e-commerce without visiting a physical store. However, although users can check product sizes (e.g., S, M, L) on websites, they cannot try on products as they can in physical stores. This can lead to situations where users try on products after purchasing them only to find that they do not fit properly. A solution to this problem was needed.

[0004] As an example of this type of technology, Patent Document 1 discloses a technology that acquires a database in which measurements of each part of a product used in virtual fitting and measurements of each part of a purchaser's body are registered, and also acquires measurements of the size of each part of the product and each part of the purchaser's body, and compares these to determine how well the product will fit the purchaser. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-134470 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technology of Patent Document 1 requires that measurements of each part of the product and each part of the purchaser's body be registered in advance, and the more products are handled, the more complicated the preparation becomes. Furthermore, there is no perspective on recommending products and sizes suitable for users by comprehensively taking into account both the user's tastes and preferences and the user's body shape. Today, designs are becoming more diverse, and even the same size varies depending on the brand. Therefore, without comprehensively taking these factors into consideration, it is difficult to recommend products and sizes that ultimately match the user's desires.

[0007] The present invention has been made in consideration of the above points, and provides an information processing device, information processing method, and information processing program that can recommend products and sizes that match the user's desires by adding body shape information to the user's tastes and preferences for products sold on websites by e-commerce businesses such as internet retailers, thereby realizing personalization of e-commerce sites (making individual proposals for each user), thereby building relationships between users and staff such as store clerks and promoting product purchases based on suggestions from staff and staff coordination. [Means for solving the problem]

[0008] That is, the information processing device of the embodiment is characterized by comprising: a user information acquisition unit that acquires the type of product desired by the user and user information including the user's body shape information via a user terminal; a product information acquisition unit that acquires the stock quantity, color, size, and type of the product for each product sold on the website of an e-commerce operator as product information; a matching unit that matches the user information and product information for the type of product desired by the user based on the stock quantity, color, size, and type of the product, and generates coordination information as recommendation information together with a group of products, presenting a wearer wearing the product as a subject; and an output unit that outputs the recommendation information to the user terminal.

[0009] Furthermore, in the information processing device, the recommendation information may be such that a group of products that fall within a predetermined range based on a numerical value set in the user's body shape information is extracted.

[0010] Furthermore, in an information processing device, in addition to the group of products extracted corresponding to the user, recommended information may also include products other than the type of product desired by the user that correspond to the user's body shape information and be extracted and added to the group of products.

[0011] Furthermore, in the information processing device, the recommendation information may include coordination information that presents the product group together with how the product is worn, and the information processing device may be provided with a coordination information storage unit that stores the coordination information.

[0012] Furthermore, in the information processing device, the coordinate information may include coordinated body shape information of a wearer wearing the product.

[0013] Furthermore, in the information processing device, the matching unit may extract an image of a wearer wearing the product based on the user information and coordinated body shape information. [Effects of the Invention]

[0014] The information processing device of the present invention comprises a user information acquisition unit that acquires, via a user terminal, the type of product desired by a user and user information including the user's body shape information; a product information acquisition unit that acquires, for each product sold on the website of an e-commerce operator, the stock quantity, color, size, and type of the product as product information; a matching unit that, for the type of product desired by the user, matches the user information and product information to the user based on the stock quantity, color, size, and type of the product, and generates coordination information as recommendation information together with a group of products, in which a wearer of the product is presented as a subject wearing the product; and an output unit that outputs the recommendation information to the user terminal.Therefore, for products sold on the website of an e-commerce operator, such as an internet retailer, the information processing device can recommend products and sizes that match the user's preferences by adding body shape information to the user's tastes and preferences, thereby realizing personalization of the e-commerce site, and thereby making it possible to build relationships between users and staff such as store clerks, and to promote product purchases based on suggestions from the user and staff coordination.

[0015] Furthermore, in the information processing method and the information processing program, similar to the information processing device, for products sold on websites by e-commerce businesses such as internet retailers, body shape information is added to the user's tastes and preferences to recommend products and sizes that match the user's desires, thereby realizing personalization of the e-commerce site, and thereby making it possible to build relationships between users and staff such as store clerks and promote product purchases based on suggestions from staff and coordination by staff. [Brief explanation of the drawings]

[0016] [Figure 1] FIG. 1 is a schematic diagram illustrating a configuration of an information processing apparatus according to an embodiment. [Figure 2] FIG. 2 is a block diagram showing functional units of the information processing apparatus; [Figure 3] 10 is an example of a display on the website of an e-commerce business. [Figure 4] 10 is an example of a display on the website of an e-commerce business. [Figure 5]10 is an example of a display on the website of an e-commerce business. [Figure 6] 10 is a display example of a website of an e-commerce business according to another embodiment. [Figure 7] 1 is a flowchart illustrating an information processing method according to an embodiment. [Figure 8] 10 is a flowchart illustrating an information processing method according to another embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0017] The information processing device, information processing system, information processing method, and information processing program of the embodiments are devices, methods, and programs for promoting the sales of products and services sold on websites (Internet sites) operated by electronic commerce operators (E-commerce operators), and further proposing measures to increase the purchasing motivation of users viewing the websites.

[0018] A user (customer) browses a website operated by an e-commerce business operator, and when the user finds a product they want on that website, the payment procedure for the purchase is carried out, and the transaction of the product between the e-commerce business operator and the user is completed. However, when the product arrives at the user's home, it may not necessarily be the size, shape, or color that the user desired.

[0019] This is due to the fact that users purchase products on websites without visiting a physical store to see the actual product. In addition, especially with clothing, if a purchase is made based solely on the user's height and weight data, the product may not fit the user's body shape. This can result in future lost business opportunities due to e-commerce operators being unable to fully meet the product requirements of users. Therefore, by matching (matching or matching) a user's detailed body shape information and preferences with products from the beginning, users can purchase products that are the size, shape, and color they desire and expect, and even suit their preferences. In other words, the information processing device, etc. (device, method, program) of the embodiments can be positioned as a technology for reducing user dissatisfaction when purchasing on an e-commerce operator's website and for suggesting products that better suit the user's preferences.

[0020] The configuration of an information processing device 1 according to an embodiment is shown in the schematic diagram of Fig. 1. In terms of hardware, the information processing device 1 is configured by a computer 100 (processing unit), and is internally equipped with processing elements such as a CPU and a GPU, and storage elements such as a ROM, a RAM, a HDD, and an SSD. The information processing device 1 may be implemented using various electronic computers (computing resources), such as a personal computer (PC), a mainframe, a workstation, a cloud computing system, a tablet terminal, a smartphone, etc. An information processing method is realized in terms of software by an information processing program loaded into a main memory, etc.

[0021] 1, the information processing device 1 is connected to a wired or wireless line such as an Internet line 2. A user 3 (customer) who purchases a product can access a website 12 of an e-commerce business operator 10 from a terminal device 4 owned by the user 3 via the Internet line 2.

[0022] The computer 100 of the information processing device 1 is connected to an internet line 2, thereby forming an information processing system 1S. The computer 100 in the information processing system 1S and the computer 100 in the information processing device 1 have a common configuration, and will be described below as the information processing device 1. The computer 100 in the information processing device 1 may be provided as equipment associated with the e-commerce business operator 10, or may be provided in an independent business operator separate from the e-commerce business operator 10. In the illustration, the computer 100 is provided inside the e-commerce business operator 10.

[0023] When each functional unit of the information processing device 1 (information processing system 1S) in FIG. 1 is implemented by software, the computer 100 of the information processing device 1 executes instructions of a program, which is software that implements each function. The recording medium that stores this program can be a "non-transitory tangible medium," such as a CD, DVD, semiconductor memory, or programmable logic circuit. The program may also be supplied to the computer 100 of the information processing device 1 (information processing system 1S) via any transmission medium (such as a communication network or broadcast waves) that can transmit the program.

[0024] FIG. 2 is a block diagram showing the functional units of the information processing device 1 (information processing system 1S). The computer 100 is provided with a user information acquisition unit 101, a product information acquisition unit 102, a coordinate information storage unit 103, a matching unit 104, and an output unit 105. It is also provided with a related content output unit 106 that corresponds to the processing of FIG. 6 described below. The coordinate information storage unit 103 uses storage elements such as ROM, RAM, HDD, and SSD. The output unit 105 is a known display, monitor, etc. Furthermore, the computer 100 of the information processing device 1 (information processing system 1S) is provided with processing elements such as a CPU and GPU.

[0025] The user information acquisition unit 101 acquires user information including the type of product desired by the user and the user's body shape information via the user terminal. In the embodiment, the products are assumed to be clothing, shoes, cosmetics, various accessories, and jewelry, since the preferences of users (customers, purchasers) vary, and beverages and food may also be included in the products. In the embodiment, clothing will be described.

[0026] The user's body shape information includes information about the user's height, weight, age, and sex, as well as information about a bone structure diagnosis. The reason for using information about a bone structure diagnosis is that a user's body shape is not determined solely by height and weight, but there are various body shapes such as thin and stocky, and taking the results of a bone structure diagnosis into account will result in more accurate body shape information.

[0027] According to the Skeleton Diagnosis Analyst Association, there are three types of types based on bone structure, particularly for women: straight, wave, and natural. Straight types have a three-dimensional, well-defined figure with a pronounced muscular figure and a somewhat upper-body center of gravity, so clothing with a thick, firm texture and simple designs is selected. Wave types are characterized by a thin, delicate body with soft curves, so clothing with a thin, soft texture and decorative designs is selected. Natural types have a stylish body with little visible muscle or fat, large, thick bones, prominent joints, and an overall rectangular frame, so clothing with a dry or washed-out texture and loose designs is selected.

[0028] Men are classified into three types: the standard A type, the Y type with a large difference between chest and waist circumference, and the B type with a small difference between chest and waist circumference.

[0029] The user information acquisition unit 101 acquires the contact information of the user 3 as user information from the terminal device 4 owned by the user 3. The contact information of the user 3 is unique information that identifies the user 3 and allows the e-commerce business operator 10 to notify the user, such as the user's name, address, telephone number, email address, and social media account. These items that constitute the personal information of the user 3 are items that the user 3 is required to input when first purchasing a product from the e-commerce business operator 10, and are appropriately managed and stored by the e-commerce business operator 10.

[0030] Furthermore, the user information includes information about the body shape of the user 3. The body shape information is information that the user 3 entered when he or she previously purchased a product from the e-commerce business operator 10, and if the product is clothing, it is a size such as S, M, L, or 7, 9, 11, etc., and if the product is shoes, it is a size such as 23.5 cm.

[0031] That is, the user information includes a purchase history unique to the user 3 that is generated by linking the products that the user 3 previously purchased from the e-commerce business operator 10 with the information that the user entered when purchasing the products. Of course, in addition to this, the user information may also include the color and price of the products that the user entered (selected) when purchasing the products from the e-commerce business operator 10 in the past.

[0032] The product information acquisition unit 102 acquires the product information such as the stock quantity, price, color, size, and type for each product sold on the website 12 of the e-commerce operator 10 as attributes of the product.

[0033] Product attributes are items that serve as indicators for classifying products, and in the case of clothing in particular, the main product attributes are the inventory quantity that the e-commerce business operator 10 can handle, the price (price range) of the product, the color of the product, the size of the product, and the type of the product. Other information such as whether the product is second-hand or discounted, whether there are scratches or stains, etc. may also be added as product attributes. The e-commerce business operator 10 classifies the products it sells based on these product attributes, particularly clothing attributes, and uploads and manages product photos and product attributes on website 12.

[0034] The coordinate information storage unit 103 stores information about the user 3, information about products, information about staff, and information about coordination. The staff here refers to sales clerks at an apparel store, etc. Information about the user 3 is stored in a user body shape database 1031, information about products in a brand body database 1032, information about staff in a staff body shape database 1033, and information about coordination in a coordinate database 1034.

[0035] For example, the height, weight, age, sex, and brand size of the user may be stored in the user body shape database 1031. The brand size may be, for example, S, M, L, LL, etc., or may be 7, 9, 11, 13, etc.

[0036] The brand body database 1032 may store, for example, product names, sizes, stock status, etc. Product names may be, for example, T-shirts, blouses, sweaters, hoodies, jackets, coats, pants, skirts, shoes, sandals, etc. Sizes may be, as described above, S, M, L, LL, etc., or may be 7, 9, 11, 13, etc. Stock status may be, for example, in stock, low in stock, out of stock, etc.

[0037] The staff body shape database 1033 may store, for example, the height, weight, age, sex, brand, registered items, etc. of all staff members belonging to each store. For example, height may be stored as around 150 cm, weight as around 45 kg, and age as around 30 years old. For example, famous domestic and international brand names may be stored. Registered items may be product names handled by the store, such as T-shirts, blouses, sweaters, hoodies, jackets, coats, pants, skirts, shoes, sandals, etc.

[0038] The coordinate database 1034 may store information such as the height, weight, age, sex, brand, and registered item of the staff member who wears the product that will be recommended by the matching unit 104 (described later). For example, the staff member who matches a user who is a 28-year-old woman who is 150 cm tall and weighs 45 kg and who likes light-colored shirts may be staff member A who is wearing a shirt from company Z. Information may be stored in each database by providing photos of the subject from affiliated stores, or by automatically acquiring the information from affiliated stores using a crawler in the information processing device 1 (information processing system 1S). The subject is the staff member who wears the product that will be recommended, and the staff member may be, for example, a sales clerk at an apparel store.

[0039] The matching unit 104 matches user information and product information for the type of product desired by the user based on the product's stock quantity, color, size, and type, and generates coordination information as recommendation information together with a group of products, in which a subject is presented wearing the product. The matching unit 104 uses natural language processing by the computer 100 to analyze linguistic information such as the user's height, weight, and the color, size, and type of the desired product, and generates the coordination information as recommendation information together with the group of products. The matching unit 104 may use image processing in addition to natural language processing. The "group of products" may be one product or two or more products.

[0040] The recommendation information may include a group of products that fall within a predetermined range of the values ​​set in the user's body shape information. The predetermined range refers to a range that is plus or minus a certain amount of the user's height, weight, etc. For example, if the user's height is 150 cm, the predetermined range would be within 2 cm of that, i.e., 148 cm to 152 cm. If the user's weight is 50 kg, the predetermined range would be within 2 kg of that, i.e., 48 kg to 52 kg. This extracts a group of products that suit people with heights and weights similar to the user's height and weight, broadening the user's product selection options.

[0041] In addition to the product group extracted corresponding to the user, the recommendation information may also extract products other than the type of product desired by the user that correspond to the user's body shape information and add them to the product group. For example, if the user only wants a top, bottoms that go with the top may also be suggested according to the user's body shape. This allows other product groups that match the product desired by the user to be extracted, making it possible to suggest products outside the user's range of preferences, thereby expanding the fun of fashion combinations.

[0042] Examples of types of matching include clothing matching, size matching, staff body shape matching, and staff preference matching.

[0043] Clothing matching is a matching method that matches clothing items that suit the tastes and preferences of user 3. For example, a down jacket is recommended for a user who likes down jackets, a trench coat is recommended for a user who likes trench coats, a T-shirt is recommended for a user who likes T-shirts, and an aloha shirt is recommended for a user who likes aloha shirts. Figure 3 shows the screen that displays the recommendation information.

[0044] Size matching is a matching method that matches clothing items that fit the age, sex, and body shape of user 3. For example, if the user is a woman who is 150 cm tall, weighs 45 kg, and is around 30 years old, clothing items that fit a woman who is 150 cm tall, weighs 45 kg, and is around 30 years old are matched based on the information stored in the brand body database 1032. Figure 3 shows the screen that displays the recommendation information.

[0045] Staff body shape matching is a matching method that matches a staff member who matches the age, gender, and body shape of the user 3. For example, if the user is a woman who is 150 cm tall, weighs 45 kg, and is around 30 years old, a wearer with similar height, weight, and age is selected. The selection is made by selecting an apparel store clerk whose height, weight, and age are within a predetermined range of the user's body shape information. "Within the predetermined range" refers to a certain amount of the user's height, weight, etc. For example, if the user's height is 150 cm, the predetermined range would be plus or minus 2 cm, i.e., 148 cm to 152 cm. If the user's weight is 50 kg, the predetermined range would be plus or minus 2 kg, i.e., 48 kg to 52 kg. For example, a female staff member who is 149 cm tall, weighs 46 kg, and is 29 years old is recommended as a wearer. Figure 4 shows a screen displaying the recommendation information.

[0046] Staff preference matching is a matching method for recommending staff members with similar hobbies and tastes to the user, and for example, for a user who likes sportswear, staff members who also like sportswear are extracted from the information accumulated in the coordinate database 1034 and recommended to the user, for a user who likes rockwear, staff members who also like rockwear are extracted from the information accumulated in the coordinate database 1034 and recommended to the user, and for a user who likes natural clothing, staff members who also like natural clothing are extracted from the information accumulated in the coordinate database 1034 and recommended to the user. Specifically, for example, for a user who likes Major League Baseball, staff members wearing uniform T-shirts with the Anaheim Angels' jersey number on them are extracted and recommended, for example, for a user who likes the Rolling Stones, a Rolling Stones T-shirt or leather jacket with a tongue-out mouth mark is recommended, and for a user who likes natural clothing, clothes made from natural materials such as linen, cotton, denim, etc. are recommended. For example, for a user who likes to wear a sleeveless top over a striped shirt and a long skirt, recommendations could be made for a similar combination of a sleeveless top over a striped shirt and a long skirt, but in different colors. For a user who likes to wear a short skirt over trousers, recommendations could be made for a similar combination of a short skirt over trousers, but in different colors. Figure 4 shows a screen displaying recommendation information for the latter example. Suggestions from staff can also be included in the recommendation information.

[0047] The output unit 105 transmits various types of clothing, which are products proposed as recommendation information generated by the matching unit 104, to the terminal device 4 of the user 3. The output unit 105 performs image processing on the information generated by the matching unit 104 using the computer 100, and outputs the various types of clothing, which are products proposed as recommendation information, as images. Figures 3 to 5 are display examples.

[0048] The related content output unit 106 outputs related videos or posts (see FIG. 6 ) other than the recommendation information generated by matching in the matching step. For example, as shown in FIG. 6 , this includes videos introducing the recommendation information output as images, or introductory posts on social media. For example, a travel feature page, a women's feature page, and a children's clothing feature page may be output based on the user's preferences. Specifically, for a user who likes Okinawa, a special feature on Okinawa travel along with recommendations for Kariyushi wear may be output, and for a user who likes Hawaii, a special feature on Hawaii travel along with recommendations for aloha shirts may be output. For example, a special feature on subdued yet cute clothing may be output for women in their late twenties or older. For example, a special feature on clothing featuring children's anime or special effects characters may be output for parents with children up to about 10 years old. In FIG. 6 , clicking the circled portion of the right-pointing triangle in the center plays the video. This outputs recommendation information using images and audio, deepening the user's understanding of the product group.

[0049] The information processing method and information processing program of the embodiment will now be described with reference to the flowchart of Fig. 7. The information processing method of the embodiment is executed by the computer 100 (matching unit 104) of the information processing device 1 of the embodiment based on the information processing program (see Figs. 1 and 2). The information processing program of the embodiment causes the computer 100 of the information processing device 1 to realize a user information acquisition function, a product information acquisition function, a coordinate information accumulation function, a matching function, and an output function. Each function overlaps with the description of the information processing device 1 of the embodiment described above, so details will be omitted.

[0050] 7 shows the flow of an information processing method according to an embodiment, and includes various steps such as a user information acquisition step (S1), a product information acquisition step (S2), a coordinate information accumulation step (S3), a matching step (S4), and an output step (S5). In addition, the information processing method also includes various steps (not shown) necessary as needed, such as storing and retrieving matching results, other matching, input, output, and storage.

[0051] The user information acquisition function acquires the contact information of the user 3 as user information from the terminal device 4 owned by the user 3 (S1; user information acquisition step). The product information acquisition function acquires the inventory quantity, price, color, and size of each product as information on the products sold on the website 12 of the e-commerce operator 10 (S2; product information acquisition step).

[0052] The coordinate information accumulation function accumulates coordinate information that shows how the products are worn together with the product group included in the recommendation information (S3; coordinate information accumulation step). The coordinate information is, for example, a photo of an apparel salesperson.

[0053] The matching function generates recommendation information by matching the user information and product information for the type of product desired by the user 3 based on the product's stock quantity, color, size, and type (S4; matching step). The output function transmits the recommendation information generated in the matching step to the terminal device 4 of the user 3 (S5; output step).

[0054] The flowchart in Figure 8 shows the flow of another information processing method of the embodiment, which is a form that realizes a related content output function. This form includes various steps such as a user information acquisition step (S1), a product information acquisition step (S2), a coordinate information accumulation step (S3), a matching step (S4), an output step (S5), and a related content output step (S6). In addition, the information processing method also includes various necessary steps (not shown) such as storing and retrieving matching results, other calculations, input, output, and storage.

[0055] In the flowchart of Figure 8, a related content output step of the related content output function is added. The related content output function outputs related videos or posts other than the recommendation information generated by matching in the matching step (S6; related content output step). The other functions and steps are the same as those in the flowchart of Figure 7.

[0056] The information processing program of the embodiment can be implemented using, for example, scripting languages ​​such as ActionScript, JavaScript (registered trademark), Python, and Ruby, or compiler languages ​​such as C, C++, C#, Objective-C, Swift, and Java (registered trademark). [Explanation of symbols]

[0057] 1. Information processing equipment 1S Information Processing System 2. Internet connection 3 users 4. Terminal equipment 10. E-commerce operators 12 websites 100 computers 101 User information acquisition unit 102 Product information acquisition department 103 Coordination Information Storage Unit 104 Matching Section 105 Output section 106 Related Content Output Unit 1031 User Body Shape Database 1032 Brand Body Database 1033 Staff Body Shape Database 1034 Coordinate Database

Claims

1. a user information acquisition unit that acquires, via a user terminal, user information including a type of product desired by a user who is a purchaser and body shape information of the user; a product information acquisition unit that acquires product information, such as inventory quantity, color, size, and type, for each product sold on the website of the e-commerce business; a matching unit that generates, as recommendation information together with a group of products, coordination information that presents a wearer wearing the products as a subject by matching the user information and the product information for the type of product desired by the user based on the stock quantity, color, size, and type of the products; and an output unit that outputs the recommendation information to the user terminal.

2. The information processing device according to claim 1 , wherein the recommendation information extracts a group of products that fall within a predetermined range based on a numerical value set in the user's body shape information.

3. The information processing device described in claim 1, wherein the recommendation information is added to the group of products extracted corresponding to the user, and products other than the type of product desired by the user that correspond to the user's body shape information are extracted and added to the group of products.

4. The information processing device according to claim 1 , further comprising a coordinate information storage unit that stores the coordinate information.

5. The information processing device according to claim 4 , wherein the coordinate information includes coordinated body shape information of a wearer wearing the product.

6. The information processing device according to claim 5 , wherein the matching unit extracts an image of a wearer wearing the product based on the user information and the coordinated body shape information.

7. The computer a user information acquisition step of acquiring user information including a type of product desired by the user and body shape information of the user via the user terminal; a product information acquisition step of acquiring product information, such as inventory quantity, color, size, and type, for each product sold on the website of the e-commerce business; a matching step of generating, as recommendation information together with a group of products, coordination information that corresponds the user information and the product information to the user based on the inventory quantity, color, size, and type of the product, and presents a wearer wearing the product as a subject; an output step of outputting the recommendation information to the user terminal; An information processing method that performs the above.

8. On the computer, a user information acquisition function that acquires user information including the type of product desired by the user and body shape information of the user via the user terminal; a product information acquisition function that acquires product information such as inventory quantity, color, size, and type for each product sold on the website of the e-commerce business; a matching function that generates, as recommendation information together with a group of products, coordination information that corresponds the user information and the product information to the user based on the inventory quantity, color, size, and type of the product, and presents a wearer wearing the product as a subject; and an output function for outputting the recommendation information to the user terminal; A non-transitory computer-readable medium storing a program for executing the above.

Images