JP7519965B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

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

A technology is disclosed that accepts information about the item to be auctioned and the starting price of the auction, references information about the past bidding history of the item, and if it determines that the accepted starting price is too high, instructs the seller to change the starting price.

JP 2003-316975 A

However, the above conventional technology merely changes the starting price of the auction depending on the price of similar products. In electronic commerce, product information, including the listing title, can be freely set, but sales can vary greatly depending on what is included in the product information. Therefore, if the product information could be changed to something more appropriate than the current product information, sales can be expected to increase.

This application was made in consideration of the above, and aims to automatically change to more appropriate product information in electronic commerce.

The information processing device of the present application is characterized by comprising an aggregation unit that aggregates the attributes of buyers who purchase products listed for sale on electronic commerce and the time of purchase, aggregates the sales of the product for each attribute and time of purchase of the product by each buyer who purchased the product, and accumulates the sales of the product and product information at the time of sale, and a modification unit that uses the accumulated data as learning data to construct a model, and when a new user accesses the purchasing page for the product , uses the model to infer product information according to the user's attributes and the time of access, and automatically changes at least one of the text data and image data related to the product other than the transaction price included in the product information posted on the purchasing page for the product.

According to one aspect of the embodiment, product information can be automatically changed to more appropriate product information for electronic commerce.

FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. FIG. 2 is an explanatory diagram showing an outline of a processing method for automatically changing product information according to user attributes and time. FIG. 3 is an explanatory diagram showing an overview of the commodity exhibition prediction system. FIG. 4 is an explanatory diagram showing an overview of the process for automatically gathering exhibitors and holding a fair. FIG. 5 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. FIG. 6 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. FIG. 7 is a diagram illustrating an example of the configuration of an information providing device according to an embodiment. FIG. 8 is a diagram illustrating an example of the user information database. FIG. 9 is a diagram illustrating an example of the history information database. FIG. 10 is a diagram showing an example of the product information database. FIG. 11 is a flowchart showing a processing procedure according to the embodiment. FIG. 12 is a diagram illustrating an example of a hardware configuration.

Below, the information processing device, information processing method, and information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, information processing method, and information processing program according to the present application are not limited to these embodiments. In addition, the same components in the following embodiments will be denoted by the same reference numerals, and duplicated descriptions will be omitted.

[1. Overview of information processing method]
First, an overview of an information processing method performed by an information processing device according to an embodiment will be described with reference to Fig. 1. Fig. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. Note that Fig. 1 will be described by taking as an example a case where a change to a more appropriate listing title is proposed in electronic commerce (EC).

As shown in FIG. 1, the information processing system 1 includes a terminal device 10 and an information providing device 100. The terminal device 10 and the information providing device 100 are connected to each other via a network N (see FIG. 5) in a wired or wireless manner so as to be able to communicate with each other. In this embodiment, the terminal device 10 cooperates with the information providing device 100.

The terminal device 10 is a smart device such as a smartphone or tablet used by a user U, and is a mobile terminal device capable of communicating with any server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). The terminal device 10 has a screen such as a liquid crystal display with touch panel functions, and accepts various operations on displayed data such as content, such as tapping, sliding, scrolling, etc., performed by the user U with a finger or a stylus. An operation performed on an area of the screen where content is displayed may be considered to be an operation on the content. The terminal device 10 may be not only a smart device, but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

The information providing device 100 is an information processing device that cooperates with the terminal device 10 of each user U and provides API (Application Programming Interface) services for various applications (hereinafter, apps) and various data to the terminal device 10 of each user U, and is realized by a server device, a cloud system, etc.

The information providing device 100 may also be an information processing device that provides some kind of web service online to the terminal device 10 of each user U. For example, the information providing device 100 may provide services such as Internet connection, search services, SNS (Social Networking Service), electronic commerce (EC), electronic payment, online games, online banking, online trading, accommodation and ticket reservations, video and music distribution, news, maps, route searches, route guidance, line information, operation information, and weather forecasts as web services. In practice, the information providing device 100 may cooperate with various servers that provide the above-mentioned web services and act as an intermediary for the web services or be responsible for processing the web services.

The information providing device 100 can acquire user information about the user U. For example, the information providing device 100 acquires information about the attributes of the user U, such as the gender, age, and residential area of the user U. The information providing device 100 then stores and manages the information about the attributes of the user U together with identification information (such as a user ID) indicating the user U.

The information providing device 100 also acquires various types of history information (log data) indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID, etc. For example, the information providing device 100 acquires a location history, which is a history of the location and date and time of the user U, from the terminal device 10. The information providing device 100 also acquires a search history, which is a history of search queries entered by the user U, from a search server (search engine). The information providing device 100 also acquires a browsing history, which is a history of content viewed by the user U, from a content server. The information providing device 100 also acquires a purchase history (payment history), which is a history of the product purchases and payment processing of the user U, from an electronic commerce server or a payment processing server. The information providing device 100 may also acquire a listing history, which is a history of listings on the marketplace by the user U, and a sales history, from an electronic commerce server or a payment processing server. In addition, the information providing device 100 acquires a posting history, which is a history of posts made by the user U, from a posting server that provides a word-of-mouth posting service or an SNS server.

[1-1. Product name change recommendation on EC]
In a first embodiment of the present application, the information providing device 100 predicts sales of an item that is to be listed/being listed before and after changing the title based on the relationship between the listing title (heading) given to the item listed on an electronic commerce (EC) site/app and the sales of the item, and suggests a recommended title based on the prediction result.

Note that a product is an item (property) owned by a user and can be offered for sale on an EC site/app. In other words, a product is merely one example of a trading subject. The listing title also includes the product name, a catchy copy, a catch phrase, etc.

As shown in FIG. 1, the information providing device 100 accepts product listing registrations for EC sites/applications (malls, shops, auctions, flea markets, etc.) from the terminal devices 10 of each user U via a network N (see FIG. 5) (step S1).

Next, the information providing device 100 tallies the sales of each product listed by each user U (step S2).

Next, the information providing device 100 accepts a request to change the listing title of a product from user U who wishes to change the listing title of a product currently being sold (step S3).

Next, the information providing device 100 tallyes up the change in sales before and after the product listing title is changed (step S4).

At this time, the information providing device 100 calculates the change in sales due to the change in the listing title as a sales ratio to the total sales of the EC site/app on that day so that it is not affected by the sales of the entire EC site/app. In other words, the information providing device 100 converts the sales change into a ratio so that it is not affected by the sales of the entire EC site/app. In addition, the information providing device 100 normalizes the sales so that it is not affected by sales, etc.

For example, the information providing device 100 may take into consideration the possibility that the change in the listing title is not the main factor behind the change in sales, and may carry out the following processing (1) or (2).
(1) When a sale or the like is being held across all services/categories, the information providing device 100 normalizes the sales based on the sales change trend of products in the same category.
(2) The information providing device 100 normalizes the sales change based on the sales of a specific store/product (for the same category) on the day when the same campaign was implemented on the same day when a sale or advertisement was implemented only for the specific store/product. For this purpose, a service campaign master or the like is required.

Then, the information providing device 100 compiles and stores data on the number of products containing the same word after the change (competitiveness), attributes of the purchaser, etc., in sets. For example, for each product listed on an EC site/app, the information providing device 100 compiles and stores data on the change in sales before and after changing the listing title including the product name, the number of products containing the same word after the change (competitiveness), and attributes of the purchaser, etc., in sets.

Next, the information providing device 100 performs machine learning based on the accumulated data to estimate, for each product, a listing title that will lead to increased sales of the product (step S5).

Then, the information providing device 100 proposes, via the network N (see FIG. 5), to the terminal device 10 of the user U who is currently listing the product or who plans to list the product, to change the listing title (step S6). Note that, when the user U inputs a new listing title on the screen for registering the product for listing, the information providing device 100 may propose to the terminal device 10 of the user U to change the listing title of the product to a more preferable one.

At this time, the information providing device 100 uses the accumulated data as learning data to build a model, and uses the model to infer a more preferable listing title and changes in sales when the listing title is changed. For example, the information providing device 100 builds a model using "word" x "attribute" x "number of competing products" x "change in number of purchasers" x "change in number of views", and uses the model to infer a more preferable listing title and changes in sales when the listing title is changed.

In this embodiment, the information providing device 100 presents candidates for the listing title after the current product has been changed, and the degree (proportion, amount) and possibility of sales improvement if the listing title is changed, based on the change in sales before and after changing the listing title of an item with similar buyer attributes, and recommends changing the listing title. In other words, the information providing device 100 presents how much sales are likely to change if the listing title of the current product is changed, based on the change in sales before and after changing the listing title of an item with similar buyer attributes, and recommends changing the listing title.

The information providing device 100 may also compile and store the changes in sales before and after a change in the search tag, as with the listing title. Furthermore, the information providing device 100 may also compile and store the changes in sales before and after a change in the product description. That is, the information providing device 100 compiles and stores the changes in sales before and after a change in text data such as the listing title, search tag, and/or product description.

In addition, if sales suddenly increase when the image of a product is changed, the information providing device 100 also compiles and accumulates the change in sales before and after the change in the image of the product. The information providing device 100 then analyzes the pattern of images of products whose sales have increased after the change, and also suggests how to take images that will sell (photography method, examples/samples). For example, the information providing device 100 analyzes the color, design, layout, etc. of image data of products whose sales have increased, predicts how to take images that will sell, and suggests how to take images that will sell.

For example, the information providing device 100 grasps the change in sales before and after a change is made to the listing-related data (text data and image data related to the product) including the listing title of each product listed on an EC site/app (mall, shop, auction, flea market, etc.), and suggests changing the listing-related data to a more favorable one.

In addition, the information providing device 100 compiles and accumulates the changes in sales before and after changes to the listing title, search tags, images, etc. for each time period, such as the season, day of the week, or time of day. The information providing device 100 then suggests changing the listing title, search tags, images, etc. to ones that will sell, depending on the time period, such as the season, day of the week, or time of day.

The seasons are not limited to the four seasons such as spring, summer, autumn, and winter, but also include Golden Week, the rainy season, mountain/sea openings, Obon and New Year's, school entrance/graduation seasons, etc. Seasonal events such as the occurrence/warning periods for heat stroke and hay fever are also included. The days of the week are not limited to the seven days of the week, but may be divided into weekdays/Saturdays, Sundays, and holidays (holidays), etc. The time periods are not limited to periods between certain times (for example, 8 o'clock, 8:00-9:00, etc.), but may be divided into morning/afternoon/night (or morning/noon/evening/night), etc.

[1-2. Automatically change product information according to user attributes and time]
In the second embodiment of the present application, the information providing device 100 automatically changes product information regarding sales of products exhibited on an EC site/app in accordance with characteristics and trends of each period, such as season, day of the week, time of day, etc. Fig. 2 is an explanatory diagram showing an overview of a processing method for automatically changing product information in accordance with user attributes and the period.

As shown in FIG. 2, the information providing device 100 receives a request for purchase (order) of a product listed on the EC site/app or payment information from the terminal device 10 of a user U who is a purchaser of the product via the network N (see FIG. 5) (step S11).

Next, the information providing device 100 acquires and tallys up information on the attributes of the user U who purchased the product (step S12). For example, the information providing device 100 acquires and tally up information on the attributes of the user U who purchased the product, such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes.

Next, the information providing device 100 acquires and tallys information relating to the attributes of the product purchased by user U (step S13). For example, the information providing device 100 acquires and tallys information relating to the code, product name, price, size/dimensions, weight, specifications, etc., as information relating to the attributes of the product purchased by user U. In addition, the information providing device 100 may acquire and tally information relating to the brand or category of the product, the target of the product (the attributes of users expected to be the target/buyer), etc. In the case of an auction, the information providing device 100 may acquire and tally information relating to the starting price and the final winning bid price.

Next, the information providing device 100 acquires and tallys information regarding the quantity of products purchased by the user U (step S14). For example, the information providing device 100 acquires and tallys information regarding the number of products purchased by the user U. The information providing device 100 may also acquire and tally information regarding the number of products (number of items) purchased simultaneously by the user U.

Next, the information providing device 100 acquires and tallys up information about the time when the user U purchased the product (step S15). For example, the information providing device 100 acquires and tallys up information about the time when the user U purchased the product, such as the season, day of the week, or time of day.

Next, the information providing device 100 tally up the sales of the product for each attribute and time of each user U who purchased the product, and accumulates the sales of the product and the product information at the time of sale (step S16). For example, the information providing device 100 tally up and accumulates data related to each of the above acquired information, the sales of the product, and the product information in sets.

Next, when a new user U accesses the purchasing page for the product, the information providing device 100 automatically changes the product information displayed on the purchasing page for the product according to the attributes of the user U and the time of access (step S17).

At this time, the information providing device 100 constructs a model using the accumulated data as learning data, and uses the model to infer and automatically change the product information to be posted on the purchasing page for the product. For example, the information providing device 100 infers and automatically changes product information appropriate to the attributes and time of access of user U based on the attributes and time of access of user U.

For example, the information providing device 100 changes the product title, search tags, images and/or product descriptions, etc. to those that correspond to the attributes of the user U, such as age, sex, occupation (student/company employee/civil servant/freelance), etc. Furthermore, when the user U accesses the information providing device 100 in the morning, the information providing device 100 changes the product title, search tags, images and/or product descriptions, etc. to those for the morning, and when the user U accesses the information providing device 100 in the evening, the information providing device 100 changes the product title, search tags, images and/or product descriptions, etc. to those for the evening. Note that morning/evening product information is prepared for each attribute of the user U.

Next, the information providing device 100 provides the product information posted on the purchasing page of the product to the terminal device 10 of the new user U who accessed the purchasing page of the product via the network N (see FIG. 5) (step S18). The user U then browses the provided product information, and if he or she wishes to purchase the product, performs an operation to purchase the product (transition to step S11).

In this way, the information providing device 100 automatically changes the product information depending on the attributes and time of the accessing user. For example, the information providing device 100 changes the text data and/or image data related to the product being sold on the EC site/app depending on the attributes and time of the accessing user. In this case, the information providing device 100 registers multiple pieces of text data and image data, and switches between them depending on the attributes and time of the accessing user.

Furthermore, the information providing device 100 may change the price range of the product depending on the attributes and time of the accessing user. The information providing device 100 may also change the appealing points of the product depending on the attributes and time of the accessing user.

In addition, the information providing device 100 may estimate the season or time of day when a product will sell well for a user with a particular attribute, select keywords and images that appeal to the user according to the number of items desired to be sold (target number), and change the listing-related data (text data and image data related to the product) including the listing title of the product.

The information providing device 100 may also estimate products that compete with the product being sold (competing products) and select a time period for changing the product information so that the product information is changed at the same time as the competing products or so that the product information is changed to avoid the competing products.

If the information providing device 100 sees an increase in sales as a result of changing the product information, it can continue to learn and continuously improve the accuracy of its inferences.

For example, the information providing device 100 constructs a model using "target (user attributes)" x "product type" x "price" x "time period (season, day of the week, time period)" x "target quantity" x "product information (keywords, images)" and the like, and automatically changes the product information according to the attributes and time period of the accessing user.

[1-3. Listing Prediction System]
In the third embodiment of the present application, the information providing device 100 analyzes product information in electronic commerce to predict the timing when a specific product will be put up for sale on an EC site/application, and provides information on the predicted timing to a purchaser. Fig. 3 is an explanatory diagram showing an overview of the selling prediction system.

Usually, consumers do not know when a particular product will be put up for sale on an EC site/app. In addition, consumers who are heavy users predict for themselves when a particular product will be put up for sale on an EC site/app based on experience or the like. Therefore, the information providing device 100 analyzes product information to predict when a particular product will be put up for sale on an EC site/app, and provides information regarding the timing of when the product will be put up for sale to those who wish to purchase the product or potential consumers who are likely to purchase the product.

As shown in FIG. 3, the information providing device 100 receives a request from the user U's terminal device 10 via the network N (see FIG. 5) to list a product owned by the user U on an EC site/app (step S21).

Next, the information providing device 100 acquires and compiles information on the attributes of the user U who has put up the product (step S22). For example, the information providing device 100 acquires and compiles information on the attributes of the user U who has put up the product, such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes.

Next, the information providing device 100 acquires and tallys up information related to the attributes of the product listed by the user U (step S23). For example, the information providing device 100 acquires and tally up information related to the attributes of the product listed by the user U, such as the brand, category, size, and target users of the product.

Next, the information providing device 100 acquires and tallys up information related to the time when the user U put up the product (step S24). For example, the information providing device 100 acquires and tallys up information related to the time when the user U put up the product, such as the season, day of the week, or time of day.

The information providing device 100 then tallies up the period (cycle) from when user U purchases a product on the EC site/app to when he or she sells it (step S25). That is, the information providing device 100 tallies up the period from when user U acquires a product on the EC site/app to when he or she puts it up for sale. For example, the information providing device 100 obtains the time when user U purchases (acquires) a product from user U's purchase history, and tallies up the period from when user U purchases (acquires) the product to when he or she receives a request to put the product up for sale.

At this time, the information providing device 100 may tally up the period for each attribute of the user U who is the seller and each attribute of the product. The information providing device 100 may also tally up the period for each EC site/app on which the user U has listed the product.

Next, the information providing device 100 estimates the timing to put up for sale based on the attributes of the user U, the attributes of the product, and the period (cycle) from purchase to sale of the product (step S26). For example, the information providing device 100 predicts the time to put up for sale (time to sell) the product based on the attributes of the product and the seasonality of the product. The information providing device 100 also predicts the timing to put up for sale at a flea market based on the period during which the product sold well on an EC site/app and the cycle of selling/replacing the product (cycle of letting go of purchased products).

In addition, the information providing device 100 may predict the timing of listing a product based on the product's life cycle. In addition, the information providing device 100 may predict the timing of listing an old model product based on the planned timing of market launch of a new model product.

Next, the information providing device 100 provides information regarding the predicted timing of listing the product to the terminal device 10 of the user U via the network N (see FIG. 5) (step S27).

For example, when a predetermined period of time has passed since a user U purchased product XX on an EC site/app and the product selling/replacement cycle (the cycle for letting go of a purchased product) has arrived, the information providing device 100 provides a message such as "Would you like to list product XX" to the terminal device 10 of user U, who may become a seller.

At this time, the information providing device 100 may set a threshold/lower limit value for the timing of listing depending on the type of product. For example, in the case of a durable consumer product such as an electrical appliance or furniture, the information providing device 100 may limit the provision of information regarding the timing of listing the product only when a predetermined period (for example, one month) has passed since the user U purchased the product. There are few opportunities or users who will sell a durable consumer product that they have just purchased in a short period of time, and it may not leave a good impression on the user U if we suggest selling a durable consumer product that we have just purchased in a short period of time (such as immediate sale). In addition, there is also a purpose to prevent resale. In addition, if it is a product that many users will sell in a short period of time, there is no need to encourage listing, and it is considered that a large number of products are listed and there is a surplus of products. In addition, if the predetermined period has not yet passed since the user U purchased the product, the information providing device 100 may provide information regarding the timing of listing the product after the predetermined period has passed.

In addition, the information providing device 100 provides a message such as "Product XX is expected to be listed around XX" to the terminal device 10 of a person who wishes to purchase the product or a potential consumer who is likely to purchase the product a predetermined period before the predicted listing timing.

[1-4. Automatically gather exhibitors and hold a fair on EC]
In a fourth embodiment of the present application, the information providing device 100 analyzes supply and demand fluctuations of products put up for sale on an EC site/app and recommends appropriate listing timing to sellers, thereby automatically gathering sellers on the EC site/app to hold a fair. The fair may be a sale (seasonal bargain sale, time sale with limited time/quantity, etc.), a campaign, an event, etc. FIG. 4 is an explanatory diagram showing an overview of the process of automatically gathering sellers to hold a fair.

Normally, sellers do not know when they will be able to sell. Therefore, the information providing device 100 analyzes past supply and demand fluctuations for products similar to the product to be put up for sale, estimates when demand for the product will increase, and suggests an appropriate time to put the product up for sale to the seller. In addition, if a seller is already putting up a product for sale, the information providing device 100 notifies the seller of the time when demand for the product is expected to increase. This allows sellers to automatically gather together and hold a fair.

As shown in FIG. 4, the information providing device 100 receives a request for purchase (order) of a product listed on the EC site/app or payment information from the terminal device 10 of a user U who is a purchaser of the product via the network N (see FIG. 5) (step S31).

Next, the information providing device 100 acquires and tallys up information about the attributes of the user U who purchased the product (step S32). For example, the information providing device 100 acquires and tally up information about the attributes of the user U who purchased the product, such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes.

Next, the information providing device 100 acquires and tallys information relating to the attributes of the product purchased by user U (step S33). For example, the information providing device 100 acquires and tallys information relating to the code, product name, price, size/dimensions, weight, specifications, etc., as information relating to the attributes of the product purchased by user U. In addition, the information providing device 100 may acquire and tally information relating to the brand or category of the product, the target of the product (the attributes of users expected to be the target/buyer), etc. In the case of an auction, the information providing device 100 may acquire and tally information relating to the starting price and the final winning bid price.

Next, the information providing device 100 acquires and tallys information regarding the quantity of products purchased by the user U (step S34). For example, the information providing device 100 acquires and tallys information regarding the number of products purchased by the user U. The information providing device 100 may also acquire and tally information regarding the number of products (number of items) purchased simultaneously by the user U.

Next, the information providing device 100 acquires and tallys up information about the time when the user U purchased the product (step S35). For example, the information providing device 100 acquires and tallys up information about the time when the user U purchased the product, such as the season, day of the week, or time of day.

Next, the information providing device 100 tally up the product sales for each attribute and time period of each user U who purchased the product, and accumulates the product sales (step S36). For example, the information providing device 100 tally up and accumulates data relating to each of the acquired information and product sales as a set.

Next, the information providing device 100 estimates the users U who will be the targets of the fair and the time when the fair will be held, based on the attributes of each user U who purchased the product and sales according to the time (step S37).

Next, the information providing device 100 provides information regarding the timing of the fair to the terminal device 10 of the user U who is the target of the fair via the network N (see Figure 5) (step S38).

For example, the information providing device 100 provides a message such as "A fair is scheduled to be held around XX. Would you like to participate?" to the terminal device 10 of a user U who is expected to participate in the fair via the network N (see FIG. 5).

At this time, the information providing device 100 may provide a message such as "A fair will be held around XX. Would you like to put up your products for sale" to the terminal device 10 of the user U who is a potential seller via the network N (see FIG. 5).

In addition, the information providing device 100 may provide a message such as "A fair is planned to be held around XX. Your desired product is likely to be on sale" to the terminal device 10 of a user U who is interested in the products featured in the fair and is expected to make a purchase, via the network N (see FIG. 5).

In this way, the information providing device 100 estimates the demand (need) for each product in electronic commerce, determines which products are likely to sell, and publishes special features for those products. The information providing device 100 looks at the balance of supply and demand for each product, and in order to gather sellers of products that are expected to see an increase in sales from among the changing categories, provides messages such as "Let's sell this!" to the owners of the products, and with the consent of the owners of the products, automatically holds a fair.

Since consumers are more sensitive to other EC sites/apps than to flea markets, the information providing device 100 collects and analyzes supply and demand fluctuations for each product on other EC sites/apps, and holds a fair at the flea market in advance.

For example, in transactions between individuals at flea markets, auctions, and the like, the quantities traded are small and the products are constantly changing, making it difficult to accumulate sufficient information. However, the information providing device 100 provides a wide range of services, including malls and shopping, in addition to flea markets and auctions, and can track the continuous transactions of the same product at online malls, shopping sites, and the like, thereby accumulating sufficient information in a comprehensive manner.

2. Example of information processing system configuration
Next, a configuration of an information processing system 1 including an information providing device 100 according to an embodiment will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of a configuration of the information processing system 1 according to an embodiment. As shown in Fig. 5, the information processing system 1 according to an embodiment includes a terminal device 10 and an information providing device 100. These various devices are connected to each other via a network N so as to be able to communicate with each other by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Furthermore, the number of devices included in the information processing system 1 shown in FIG. 5 is not limited to that shown. For example, in FIG. 5, only one terminal device 10 is shown to simplify the illustration, but this is merely an example and is not limiting, and there may be two or more devices.

The terminal device 10 is an information processing device used by a user U. For example, the terminal device 10 is a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game console or AV equipment with a communication function, a car navigation system, a wearable device such as a smart watch or a head-mounted display, smart glasses, etc.

In addition, the terminal device 10 can connect to the network N via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: 5th generation mobile communication system), or via short-range wireless communication such as Bluetooth (registered trademark) or wireless LAN (Local Area Network), and communicate with the information providing device 100.

The information providing device 100 is, for example, a PC, a server device, a mainframe, a workstation, etc. The information providing device 100 may be realized by cloud computing.

3. Example of terminal device configuration
Next, the configuration of the terminal device 10 will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the configuration of the terminal device 10. As shown in Fig. 6, the terminal device 10 includes a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40.

(Communication unit 11)
The communication unit 11 is connected to a network N (see FIG. 5 ) by wire or wirelessly, and transmits and receives information to and from the information providing device 100 via the network N. For example, the communication unit 11 is realized by a network interface card (NIC), an antenna, or the like.

(Display unit 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic electro-luminescent display (OLED). The display unit 12 is also a touch panel display, but is not limited to this.

(Input unit 13)
The input unit 13 is an input device that accepts various operations from the user U. For example, the input unit 13 has buttons for inputting characters, numbers, and the like. The input unit 13 may be an input/output port (I/O port) or a Universal Serial Bus (USB) port, and the like. In addition, when the display unit 12 is a touch panel display, a part of the display unit 12 functions as the input unit 13. In addition, the input unit 13 may be a microphone that accepts voice input from the user U, and the like. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives signals (radio waves) transmitted from satellites of a GPS (Global Positioning System), and acquires position information (e.g., latitude and longitude) indicating the current position of the terminal device 10 based on the received signals. That is, the positioning unit 14 measures the position of the terminal device 10. Note that the GPS is merely an example of a GNSS (Global Navigation Satellite System).

The positioning unit 14 can also measure the position using various methods other than GPS. For example, the positioning unit 14 may measure the position using various communication functions of the terminal device 10 as an auxiliary positioning means for position correction, etc., as described below.

(Wi-Fi positioning)
For example, the positioning unit 14 uses the Wi-Fi (registered trademark) communication function of the terminal device 10 or a communication network provided by each communication company to measure the position of the terminal device 10. Specifically, the positioning unit 14 performs Wi-Fi communication or the like and measures the distance to a nearby base station or access point to measure the position of the terminal device 10.

(Beacon positioning)
Furthermore, the positioning unit 14 may measure the position by using a Bluetooth (registered trademark) function of the terminal device 10. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting to a beacon transmitter connected by the Bluetooth (registered trademark) function.

(geomagnetic positioning)
In addition, the positioning unit 14 locates the position of the terminal device 10 based on a geomagnetic pattern of a structure that has been measured in advance and a geomagnetic sensor provided in the terminal device 10 .

(RFID positioning)
Furthermore, for example, if the terminal device 10 has a function of an RFID (Radio Frequency Identification) tag equivalent to a contactless IC card used at station ticket gates, stores, etc., or has a function of reading an RFID tag, the location of use is recorded together with information on a payment or the like made by the terminal device 10. The positioning unit 14 may obtain such information to measure the location of the terminal device 10. Furthermore, the location may be measured by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

If necessary, the positioning unit 14 may use one or a combination of the positioning means described above to determine the position of the terminal device 10.

(Sensor unit 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. The connection may be wired or wireless. For example, the sensors may be detection devices other than the terminal device 10, such as wearable devices and wireless devices. In the example shown in FIG. 6, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, an air pressure sensor 23, a temperature sensor 24, a sound sensor 25, a light sensor 26, a magnetic sensor 27, and an image sensor (camera) 28.

Note that the above-mentioned sensors 21 to 28 are merely examples and are not limiting. In other words, the sensor unit 20 may be configured to include some of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of the sensors 21 to 28.

The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects the physical movement of the terminal device 10, such as the direction of movement, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects the physical movement of the terminal device 10, such as the tilt in three axial directions, based on the angular velocity of the terminal device 10. The air pressure sensor 23 detects, for example, the air pressure around the terminal device 10.

Since the terminal device 10 is equipped with the above-mentioned acceleration sensor 21, gyro sensor 22, air pressure sensor 23, etc., it is possible to determine the position of the terminal device 10 using technology such as Pedestrian Dead-Reckoning (PDR) that utilizes these sensors 21 to 23. This makes it possible to obtain indoor position information that is difficult to obtain using positioning systems such as GPS.

For example, the number of steps, walking speed, and distance walked can be calculated using a pedometer that uses the acceleration sensor 21. In addition, the gyro sensor 22 can be used to know the user U's direction of travel, line of sight, and body inclination. In addition, the air pressure detected by the air pressure sensor 23 can be used to know the altitude and floor on which the user U's terminal device 10 is located.

The air temperature sensor 24 detects, for example, the air temperature around the terminal device 10. The sound sensor 25 detects, for example, sound around the terminal device 10. The light sensor 26 detects the illuminance around the terminal device 10. The magnetic sensor 27 detects, for example, the geomagnetism around the terminal device 10. The image sensor 28 captures an image around the terminal device 10.

The above-mentioned air pressure sensor 23, temperature sensor 24, sound sensor 25, light sensor 26, and image sensor 28 can detect the environment and situation around the terminal device 10 by detecting air pressure, temperature, sound, and illuminance, and capturing images of the surroundings. In addition, it becomes possible to improve the accuracy of the location information of the terminal device 10 based on the environment and situation around the terminal device 10.

(Control unit 30)
The control unit 30 includes, for example, a microcomputer having a central processing unit (CPU), a read only memory (ROM), a RAM, an input/output port, and various other circuits. The control unit 30 may also be configured with hardware such as an integrated circuit, for example, an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The control unit 30 includes a transmission unit 31, a reception unit 32, and a processing unit 33.

(Transmitter 31)
The transmission unit 31 can transmit, for example, various information input by the user U using the input unit 13, various information detected by each sensor 21 to 28 mounted on or connected to the terminal device 10, and location information of the terminal device 10 measured by the positioning unit 14 to the information providing device 100 via the communication unit 11.

(Receiving unit 32)
The receiving unit 32 can receive various information provided by the information providing device 100 and requests for various information from the information providing device 100 via the communication unit 11 .

(Processing Unit 33)
The processing unit 33 controls the entire terminal device 10, including the display unit 12, etc. For example, the processing unit 33 can output various pieces of information transmitted by the transmission unit 31 and various pieces of information received by the reception unit 32 from the information providing device 100 to the display unit 12 for display.

(Memory unit 40)
The storage unit 40 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk drive (HDD), a solid state drive (SSD), an optical disk, etc. Various programs and various data are stored in the storage unit 40.

4. Example of the configuration of the information providing device
Next, a configuration of the information providing device 100 according to the embodiment will be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of the configuration of the information providing device 100 according to the embodiment. As shown in Fig. 7, the information providing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(Communication unit 110)
The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is also connected to a network N (see FIG. 5) in a wired or wireless manner.

(Memory unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a HDD, an SSD, an optical disk, etc. As shown in FIG. 7 , the storage unit 120 has a user information database 121, a history information database 122, and a product information database 123 .

(User Information Database 121)
The user information database 121 stores user information related to the user U. For example, the user information database 121 stores various information such as attributes of the user U. Fig. 8 is a diagram showing an example of the user information database 121. In the example shown in Fig. 8, the user information database 121 has items such as "User ID (Identifier)", "Age", "Gender", "Home", "Workplace", and "Interests".

"User ID" indicates identification information for identifying user U. Note that "user ID" may be contact information for user U (telephone number, email address, etc.) or may be identification information for identifying user U's terminal device 10.

Furthermore, "age" indicates the age of user U identified by the user ID. Note that "age" may be information indicating the specific age of user U (e.g., 35 years old) or information indicating the generation of user U (e.g., 30s). Alternatively, "age" may be information indicating user U's date of birth or information indicating user U's generation (e.g., born in the 1980s). Furthermore, "gender" indicates the gender of user U identified by the user ID.

"Home" indicates the location information of the home of user U, which is identified by the user ID. In the example shown in FIG. 8, "Home" is illustrated as an abstract code such as "LC11", but it may also be latitude and longitude information, etc. For example, "Home" may also be the name of a region or an address.

"Workplace" indicates the location information of the workplace (school in the case of a student) of user U identified by the user ID. In the example shown in FIG. 8, "workplace" is illustrated as an abstract code such as "LC12", but it may also be latitude and longitude information, etc. For example, "workplace" may also be the name of a region or an address.

Furthermore, "interests" indicate the interests of user U identified by the user ID. In other words, "interests" indicate subjects in which user U identified by the user ID is highly interested. For example, "interests" may be search queries (keywords) entered by user U into a search engine. Note that, although one "interest" is illustrated for each user U in the example shown in FIG. 8, there may be multiple "interests."

For example, in the example shown in FIG. 8, the age of user U identified by user ID "U1" is "20s" and the gender is "male." Furthermore, for example, user U identified by user ID "U1" indicates that his/her home address is "LC11." Furthermore, for example, user U identified by user ID "U1" indicates that his/her workplace is "LC12." Furthermore, for example, user U identified by user ID "U1" indicates that he/she is interested in "sports."

In the example shown in FIG. 8, abstract values such as "U1", "LC11", and "LC12" are used to illustrate the data, but it is assumed that concrete information such as character strings and numerical values is stored in "U1", "LC11", and "LC12". In the following figures relating to other information, abstract values may also be illustrated.

The user information database 121 may store various information according to the purpose, not limited to the above. For example, the user information database 121 may store various information related to the terminal device 10 of the user U. The user information database 121 may also store information related to the attributes of the user U, such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes. For example, the user information database 121 may store information such as name, family structure, place of origin (hometown), occupation, job title, income, qualifications, type of residence (detached house, apartment, etc.), whether or not the user has a car, commuting time, commuting route, commuter pass section (station, line, etc.), frequently used station (other than the nearest station to home or workplace), extracurricular activities (location, time period, etc.), hobbies, interests, and lifestyle.

(History information database 122)
The history information database 122 stores various information related to history information (log data) indicating the behavior of the user U. Fig. 9 is a diagram showing an example of the history information database 122. In the example shown in Fig. 9, the history information database 122 has items such as "user ID", "location history", "search history", "browsing history", "purchase history", and "posting history".

"User ID" refers to identification information for identifying user U. "Location history" refers to location history, which is a history of user U's location and movements. "Search history" refers to search history, which is a history of search queries entered by user U. "Browse history" refers to browse history, which is a history of content viewed by user U. "Purchase history" refers to purchase history, which is a history of purchases made by user U. "Post history" refers to posting history, which is a history of posts made by user U. "Post history" may include questions about user U's possessions.

For example, in the example shown in FIG. 9, user U identified by user ID "U1" moved as shown in "location history #1," searched as shown in "search history #1," viewed content as shown in "browsing history #1," purchased specific products at specific stores as shown in "purchase history #1," and posted as shown in "posting history."

In the example shown in FIG. 9, abstract values such as "U1", "Location History #1", "Search History #1", "Browse History #1", "Purchase History #1", and "Post History #1" are used for illustration, but it is assumed that specific information such as character strings and numerical values is stored in "U1", "Location History #1", "Search History #1", "Browse History #1", "Purchase History #1", and "Post History #1".

The history information database 122 is not limited to the above, and may store various information depending on the purpose. For example, the history information database 122 may store the usage history of a specific service by the user U. The history information database 122 may also store the history of the user U's visit to a physical store or the history of the user U's visit to a facility. The history information database 122 may also store the payment history of payments (electronic payments) made using the user U's terminal device 10.

(Product information database 123)
The product information database 123 stores various information related to history information (log data) indicating the behavior of the user U. Fig. 10 is a diagram showing an example of the product information database 123. In the example shown in Fig. 10, the product information database 123 has items such as "product ID", "listing title", "product attributes", "seller attributes", "purchasing demographic", and "listing timing".

"Product ID" indicates identification information for identifying a product. For example, the product ID indicates a product code, product name, etc. "Listing title" indicates the listing title of a product listed on an EC site/app. "Product attributes" indicates the attributes of a product listed on an EC site/app. "Seller attributes" indicates the attributes of a seller who listed a product on an EC site/app. "Purchaser demographic" indicates the purchasing demographic of a product listed on an EC site/app. "Listing timing" indicates the appropriate timing for listing a product on an EC site/app.

For example, in the example shown in Figure 10, a product identified by product ID "product #A" is listed on the EC site/app with "listing title #A" and "product attribute #A", the attribute of the main seller of the product is "seller attribute #A", the attribute of the main purchaser of the product is "buyer demographic #A", and it is preferable to list the product at the "listing timing".

In the example shown in FIG. 10, abstract values such as "Product #A", "Listing title #A", "Product attribute #A", "Seller attribute #A", "Buying demographic #A" and "Listing timing #A" are used for illustration, however, specific information such as character strings or numerical values is stored in "Product #A", "Listing title #A", "Product attribute #A", "Seller attribute #A", "Buying demographic #A" and "Listing timing #A".

The product information database 123 may store various information according to the purpose, not limited to the above. For example, the product information database 123 may store identification information indicating the EC site/app on which the product is listed. The product information database 123 may also store the time period, such as the season, day of the week, or time of day, when product sales change. The product information database 123 may also store the period (cycle) from when a user U purchases a product on the EC site/app to when he or she sells it.

(Control unit 130)
Returning to Fig. 7, the description will be continued. The control unit 130 is a controller, and is realized by, for example, a central processing unit (CPU), a micro processing unit (MPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or the like, executing various programs (corresponding to an example of an information processing program) stored in a storage device inside the information providing device 100 using a storage area such as a RAM as a working area. In the example shown in Fig. 7, the control unit 130 has an acquisition unit 131, a counting unit 132, an estimation unit 133, a change unit 134, and a provision unit 135.

(Acquisition unit 131)
The acquisition unit 131 acquires a search query input by the user U. For example, when the user U inputs a search query into a search engine or the like to perform a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110.

The acquisition unit 131 also acquires user information about the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information (such as a user ID) indicating the user U, location information of the user U, attribute information of the user U, and the like from the terminal device 10 of the user U. The acquisition unit 131 may also acquire identification information indicating the user U, attribute information of the user U, and the like when registering the user U. Then, the acquisition unit 131 registers the user information in the user information database 121 of the storage unit 120.

The acquisition unit 131 also acquires various types of history information (log data) indicating the behavior of the user U via the communication unit 110. For example, the acquisition unit 131 acquires various types of history information indicating the behavior of the user U from the terminal device 10 of the user U, or from various servers, etc. based on the user ID, etc. Then, the acquisition unit 131 registers the various types of history information in the history information database 122 of the storage unit 120.

In this embodiment, the acquisition unit 131 acquires information about the attributes of a user U who has listed/purchased a product on an EC site/app. For example, the acquisition unit 131 acquires information about attributes such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes of the user U who has listed/purchased the product.

The acquisition unit 131 also acquires information regarding the attributes of the product purchased by the user U. For example, the acquisition unit 131 acquires information regarding the attributes of the product purchased by the user U, such as the code, product name, price, size/dimensions, weight, and specifications. In addition, the acquisition unit 131 may acquire information regarding the brand and category of the product, the target of the product (the attributes of users expected to be the target/purchasing demographic), and the like. In the case of an auction, the acquisition unit 131 may acquire information regarding the starting price and the final winning bid price.

The acquisition unit 131 also acquires information regarding the quantity of products purchased by the user U. For example, the acquisition unit 131 acquires information regarding the number of products purchased by the user U. The acquisition unit 131 may also acquire information regarding the number of products (number of items) purchased simultaneously by the user U.

The acquisition unit 131 also acquires information regarding the time when the user U purchased the product. For example, the acquisition unit 131 acquires information regarding the time, such as the season, day of the week, or time period, when the user U purchased the product.

(Counting unit 132)
The tallying unit 132 tallys up the attributes of products being offered for sale in electronic commerce, the attributes of the purchasers, and the time of purchase. At this time, the tallying unit 132 tallys up information relating to the attributes of the users U who purchased the products. The tallying unit 132 also tallys up information relating to the attributes of the products purchased by the users U. The tallying unit 132 also tallys up information relating to the quantity of products purchased by the users U. The tallying unit 132 also tallys up information relating to the time when the users U purchased the products. The tallying unit 132 then tallys up the sales of the products for each attribute and time of each user U who purchased the product.

The aggregation unit 132 also aggregates the period (cycle) from when user U purchases a product on the EC site/app to when he or she sells it. That is, the aggregation unit 132 aggregates the period from when user U obtains a product on the EC site/app to when he or she puts it up for sale. For example, the aggregation unit 132 obtains the time when user U purchased (obtained) the product from user U's purchase history, and aggregates the period from when user U purchased (obtained) the product to when he or she received a request to put the product up for sale.

At this time, the aggregation unit 132 may aggregate the period for each attribute of the user U who is the seller and each attribute of the product. The aggregation unit 132 may also aggregate for the EC site/app on which the user U has listed the product.

The aggregation unit 132 also aggregates the sales of each product listed by each user U. For example, the aggregation unit 132 aggregates the change in sales before and after changing the listing title of the product. At this time, the aggregation unit 132 may aggregate a set of data related to the number of products containing the same word after the change (competitiveness), attributes of the purchaser, etc. For example, the aggregation unit 132 aggregates a set of data related to the change in sales before and after changing the listing title including the product name, the number of products containing the same word after the change (competitiveness), attributes of the purchaser, etc. for each product listed on the EC site/app.

The aggregation unit 132 may aggregate the change in sales before and after a change in the search tag, as with the listing title. Furthermore, the aggregation unit 132 may also aggregate the change in sales before and after a change in the product description. That is, the aggregation unit 132 may aggregate the change in sales before and after a change in text data such as the listing title, search tag, and/or product description. Furthermore, if sales suddenly increase when the product image is changed, the aggregation unit 132 also aggregates the change in sales before and after the product image is changed.

(Estimation unit 133)
The estimation unit 133 estimates sales before and after changing the listing title of the item being put up for sale, based on the relationship between the listing title and sales of the item previously put up for sale in electronic commerce. For example, the estimation unit 133 estimates sales before and after changing the product description of the item being put up for sale, based on the relationship between the product description and sales of the item previously put up for sale in electronic commerce. The estimation unit 133 also estimates sales before and after changing the search tag of the item being put up for sale, based on the relationship between the search tag of the item previously put up for sale in electronic commerce and sales. The estimation unit 133 also estimates sales before and after changing the image data of the item being put up for sale, based on the relationship between the image data of the item previously put up for sale in electronic commerce and sales.

In addition, the estimation unit 133 estimates competing products based on the attributes of the products being offered for sale in electronic commerce, the attributes of the purchaser, and the time of purchase.

The estimation unit 133 also analyzes product information of products being offered for sale on electronic commerce to estimate the timing at which the products will be offered for sale. For example, the estimation unit 133 analyzes the period from purchase to sale of a product offered for sale on electronic commerce to estimate the timing at which the product may be offered for sale. The estimation unit 133 also analyzes the time when sales of a product offered for sale on electronic commerce change to estimate the timing suitable for offering the product for sale.

In addition, the estimation unit 133 analyzes product information of products being listed on the online shopping mall and estimates the timing at which the products will be listed in person-to-person transactions.

The estimation unit 133 also analyzes the supply and demand fluctuations of products offered for sale in electronic commerce to estimate the timing of a product fair and the participants of the fair. For example, the estimation unit 133 analyzes the supply and demand fluctuations of products offered for sale in electronic commerce to estimate the timing of a product fair and the exhibitors of the products. The estimation unit 133 also analyzes the supply and demand fluctuations of products offered for sale in electronic commerce to estimate the timing of a product fair and the purchasers of the products.

In addition, the estimation unit 133 analyzes the supply and demand fluctuations of products offered for sale in electronic commerce, and estimates potential sellers of products and the timing of product listing.

The estimation unit 133 also analyzes the supply and demand fluctuations of products offered for e-commerce to estimate products that are expected to see an increase in sales, and estimates the timing of fairs to be held for the estimated products and the exhibitors of the products.

In addition, the estimation unit 133 analyzes the supply and demand fluctuations of products offered on the online shopping mall, and estimates the timing of product fairs and the exhibitors of the products in person-to-person transactions.

(Change unit 134)
The change unit 134 automatically changes the product information according to the characteristics of each period regarding the sales of the product being offered for sale in electronic commerce, based on the results of compilation regarding the attributes of the product being offered for sale in electronic commerce, the attributes of the purchaser, and the timing of purchase.

For example, the modification unit 134 automatically modifies the product information in accordance with seasonal characteristics related to sales of products listed on electronic commerce, based on the results of aggregation related to the attributes of products listed on electronic commerce, the attributes of the purchaser, and the time of purchase. The modification unit 134 also automatically modifies the product information in accordance with characteristics for each day of the week related to sales of products listed on electronic commerce, based on the results of aggregation related to the attributes of products listed on electronic commerce, the attributes of the purchaser, and the time of purchase. The modification unit 134 also automatically modifies the product information in accordance with characteristics for each time period related to sales of products listed on electronic commerce, based on the results of aggregation related to the attributes of products listed on electronic commerce, the attributes of the purchaser, and the time of purchase.

In addition, the modification unit 134 automatically modifies the product information according to the attributes of the products being offered for sale in electronic commerce, the attributes of the purchaser, and the characteristics of each purchase period, based on the results of the aggregation regarding the attributes of the products being offered for sale in electronic commerce, the attributes of the purchaser, and the purchase period.

For example, the change unit 134 automatically changes the price of the product in accordance with the characteristics of each period of sales of the product being offered for sale on electronic commerce, based on the results of an aggregation of the attributes of the product being offered for sale on electronic commerce, the attributes of the purchaser, and the timing of the purchase.

In addition, the change unit 134 automatically changes the selling points of the product in accordance with the characteristics of each period of sales of the product being offered for sale on electronic commerce, based on the results of the aggregation of the attributes of the product being offered for sale on electronic commerce, the attributes of the purchaser, and the timing of the purchase.

In addition, the change unit 134 automatically changes the product information according to the product information of the estimated competing product.

(Providing Unit 135)
The providing unit 135 proposes a recommended listing title based on the estimated results of sales before and after the change to the listing title of the item being listed. For example, the providing unit 135 proposes a change to the product name included in the listing title of the item being listed based on the estimated results of sales before and after the change to the listing title of the item being listed. The providing unit 135 also proposes a change to the catch phrase included in the listing title of the item being listed based on the estimated results of sales before and after the change to the listing title of the item being listed.

In addition, the providing unit 135 proposes a recommended product description based on the estimated results of sales before and after the change to the product description of the product being listed. In addition, the providing unit 135 proposes a recommended search tag based on the estimated results of sales before and after the change to the search tag of the product being listed.

The providing unit 135 also suggests a recommended way to take image data based on the estimated results of sales before and after the change to the image data of the product being listed. For example, the providing unit 135 suggests a recommended change to the color of the image data based on the estimated results of sales before and after the change to the image data of the product being listed. The providing unit 135 also suggests a recommended change to the layout of the image data based on the estimated results of sales before and after the change to the image data of the product being listed.

In addition, the provision unit 135 analyzes product information of products being offered for sale in electronic commerce and provides the estimated listing timing to those who wish to purchase the products.

For example, the providing unit 135 analyzes the period from purchase to sale of a product offered for sale on an electronic commerce site, and provides a message to a prospective purchaser of the product, informing them that the product may be offered for sale at the estimated listing time, a predetermined period of time before the estimated listing time.

In addition, the providing unit 135 analyzes the period from purchase to sale of a product offered for sale on an electronic commerce site, and provides a message encouraging a potential seller of the product to offer the product at the estimated listing time a predetermined period of time before the estimated listing time.

In addition, the providing unit 135 analyzes product information of products being offered for sale in electronic commerce and provides the estimated listing timing to potential sellers of the products. For example, the providing unit 135 provides a message encouraging potential sellers of the products to list their products at the estimated listing timing, a predetermined period of time prior to the estimated listing timing, to the potential sellers of the products.

In addition, the estimation unit 133 analyzes the attributes of the product offered for sale in electronic commerce, the attributes of the seller of the product, the purchasing demographic of the product, the period from purchase to sale of the product, and the time when sales of the product change, to estimate the best timing to offer the product for sale.

For example, the providing unit 135 analyzes the purchasing demographic of the product, the period from purchase to sale of the product, and the time when sales of the product change, and provides a message encouraging a potential seller of the product to list the product at the estimated listing timing a predetermined period of time before the estimated listing timing (a suitable listing timing for listing the product).

In addition, the providing unit 135 analyzes the period from purchase to sale of the product and the time when the sales of the product change, and provides a message to a prospective purchaser of the product, a predetermined period of time before the estimated listing timing (a suitable listing timing for listing the product), informing the purchaser that the product may be listed at the estimated listing timing.

In addition, the providing unit 135 analyzes product information of products being offered for sale on the online shopping mall and provides the estimated timing of the product being offered for sale in person-to-person transactions to those who wish to purchase the product.

The providing unit 135 also provides participants with the timing of the product fair, and automatically gathers participants around the time of the product fair to hold the fair. For example, the providing unit 135 provides sellers with the timing of the product fair, and automatically gathers sellers around the time of the product fair to hold the fair. The providing unit 135 also provides purchasers with the timing of the product fair, and automatically gathers purchasers around the time of the product fair to hold the fair.

In addition, the provision unit 135 analyzes the supply and demand fluctuations of products offered for sale in electronic commerce and provides the estimated timing of product listing to potential product sellers.

In addition, the providing unit 135 provides a message encouraging a potential seller of a product to exhibit a product at the product fair a predetermined period of time before the product fair is held. In addition, the providing unit 135 provides a message encouraging participation in the product fair to a person who wishes to purchase a product a predetermined period of time before the product fair is held.

In addition, the providing unit 135 analyzes the supply and demand fluctuations of products offered in the online shopping mall and provides participants with the estimated timing of product fairs in person-to-person transactions, and automatically gathers participants at the timing of the product fair to hold the fair.

5. Processing Procedure
Next, a processing procedure performed by the information providing device 100 according to the embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the information providing device 100.

As shown in FIG. 11, the aggregation unit 132 of the information providing device 100 aggregates information regarding the attributes of user U who has listed/purchased an item on the EC site/app, which information is acquired by the acquisition unit 131 (step S101).

Next, the aggregation unit 132 of the information providing device 100 aggregates information regarding the attributes of the products listed/purchased on the EC site/app acquired by the acquisition unit 131 (step S102).

Next, the aggregation unit 132 of the information providing device 100 aggregates information related to the purchase time (time when the product was purchased) of the product on the EC site/app acquired by the acquisition unit 131 (step S103).

Next, the aggregation unit 132 of the information providing device 100 aggregates information regarding sales of each product on the EC site/app (step S104).

Next, the aggregation unit 132 of the information providing device 100 aggregates information regarding changes in sales before and after changing the listing title, etc., of each product on the EC site/app (step S105). For example, the aggregation unit 132 aggregates changes in sales before and after changing the listing title, search tag, product description, image data, etc. of the product.

Next, the estimation unit 133 of the information providing device 100 estimates recommended listing titles, etc., based on the tabulation results (step S106). That is, the estimation unit 133 estimates listing titles, etc., that are expected to increase sales compared to the current level, based on the tabulation results.

Next, the change unit 134 of the information providing device 100 automatically changes the product information according to the characteristics of each period of sales of the product being offered for sale in electronic commerce, based on the aggregated results regarding the attributes of the product being offered for sale on the EC site/app, the attributes of the purchaser, and the timing of the purchase (step S107).

Next, the estimation unit 133 of the information providing device 100 estimates the timing of listing, the users U who will be the targets of the fair, and the time when the fair will be held based on the attributes of the users U who listed/purchased the item on the EC site/app, the attributes of the item, the period (cycle) from purchase to sale of the item, and fluctuations in supply and demand for the item (step S108).

Then, the providing unit 135 of the information providing device 100 provides information on the recommended listing title, the listing timing, and the fair timing to the terminal device 10 of the user U who is the seller or the person planning to sell the product, via the communication unit 110 (step S109). The providing unit 135 may also suggest a setting to automatically change the product information (setting to allow automatic changes to product information). The providing unit 135 also provides information on the seller's listing timing and the fair timing to the terminal device 10 of the user U who may purchase the product, via the communication unit 110.

6. Modifications
The terminal device 10 and the information providing device 100 described above may be implemented in various different forms other than the above embodiment. Therefore, modifications of the embodiment will be described below.

In the above embodiment, some or all of the processing performed by the information providing device 100 may actually be performed by the terminal device 10. For example, the processing may be completed in a stand-alone manner (by the terminal device 10 alone). In this case, the terminal device 10 is assumed to have the functions of the information providing device 100 in the above embodiment. Also, in the above embodiment, since the terminal device 10 is linked to the information providing device 100, from the perspective of the user U, it appears that the processing of the information providing device 100 is also being performed by the terminal device 10. In other words, from another perspective, it can also be said that the terminal device 10 is equipped with the information providing device 100.

In the above embodiment, the information providing device 100 may appropriately combine product name change recommendations in the EC, automatic changes to product information according to user attributes and time, an item listing prediction system, and holding a fair by automatically gathering sellers in the EC, depending on settings made by the user U, etc. For example, the information providing device 100 may perform all of the processes simultaneously, or may perform them selectively.

7. Effects
As described above, the information processing device (information providing device 100) according to the present application includes an aggregation unit 132 that aggregates attributes of products listed on electronic commerce, attributes of purchasers, and the timing of purchases, and a change unit 134 that automatically changes product information according to the characteristics of each period related to sales of the products listed on electronic commerce based on the aggregation results.

For example, the change unit 134 automatically changes the product information based on the aggregation results in accordance with seasonal characteristics related to sales of products listed for sale in electronic commerce.

Alternatively, the change unit 134 automatically changes the product information according to the characteristics of each day of the week related to sales of products listed for electronic commerce based on the aggregation results.

Alternatively, the modification unit 134 automatically modifies the product information based on the aggregation results according to the characteristics of each time period regarding sales of products being offered for e-commerce.

In addition, the modification unit 134 automatically modifies the product information based on the aggregation results according to the attributes of the product being offered for sale in electronic commerce, the attributes of the purchaser, and the characteristics of each purchase period.

In addition, the change unit 134 automatically changes the price of the product based on the aggregation results, depending on the characteristics of each period of sales of the product being offered for electronic commerce.

In addition, the change unit 134 automatically changes the selling points of the product based on the aggregation results, according to the characteristics of each period of sales of the product being offered for electronic commerce.

The information processing device according to the present application further includes an estimation unit 133 that estimates competing products based on the attributes of the product being offered for sale in electronic commerce, the attributes of the purchaser, and the time of purchase. The change unit 134 automatically changes the product information according to the product information of the estimated competing product.

By using any one or a combination of the above processes, the information processing device according to the present application can automatically change the product information to be more appropriate for electronic commerce.

8. Hardware Configuration
Moreover, the terminal device 10 and the information providing device 100 according to the above-described embodiment are realized by a computer 1000 having a configuration as shown in Fig. 12, for example. The information providing device 100 will be described below as an example. Fig. 12 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are connected by a bus 1090.

The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The arithmetic device 1030 is realized, for example, by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that primarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), a HDD (Hard Disk Drive), a SSD (Solid State Drive), a flash memory, or the like. The secondary storage device 1050 may be an internal storage device or an external storage device. The secondary storage device 1050 may be a removable storage medium such as a USB (Universal Serial Bus) memory or a SD (Secure Digital) memory card. The secondary storage device 1050 may be a cloud storage device (online storage device), a NAS (Network Attached Storage), a file server, or the like.

The output I/F 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a display, projector, printer, etc., and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (registered trademark) (High Definition Multimedia Interface). The input I/F 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, keypad, button, scanner, etc., and is realized by a USB, etc.

In addition, the output I/F 1060 and the input I/F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

In addition, the output device 1010 and the input device 1020 may be integrated, such as a touch panel. In this case, the output I/F 1060 and the input I/F 1070 may also be integrated as an input/output I/F.

The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

The network I/F 1080 receives data from other devices via the network N and sends it to the computing device 1030, and also transmits data generated by the computing device 1030 to other devices via the network N.

The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output I/F 1060 and the input I/F 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

For example, when the computer 1000 functions as the information providing device 100, the arithmetic unit 1030 of the computer 1000 executes a program loaded onto the primary storage device 1040 to realize the functions of the control unit 130. The arithmetic unit 1030 of the computer 1000 may also load a program acquired from another device via the network I/F 1080 onto the primary storage device 1040 and execute the loaded program. The arithmetic unit 1030 of the computer 1000 may also cooperate with other devices via the network I/F 1080 and use the functions and data of a program by calling them from other programs of the other devices.

[9. Other]
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. The above-described components include those that a person skilled in the art can easily imagine, those that are substantially the same, and those that are within the so-called equivalent range. Furthermore, the above-described components can be appropriately combined. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments.

Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

For example, the information providing device 100 described above may be realized by multiple server computers, and depending on the functions, the configuration can be flexibly changed, such as by calling an external platform using an API (Application Programming Interface) or network computing.

The above-described embodiments and variations can be combined as appropriate to the extent that they do not cause inconsistencies in the processing content.

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

REFERENCE SIGNS LIST 1 Information processing system 10 Terminal device 100 Information providing device 110 Communication unit 120 Storage unit 121 User information database 122 History information database 123 Product information database 130 Control unit 131 Acquisition unit 132 Counting unit 133 Estimation unit 134 Change unit 135 Provision unit

Claims (10)

a counting unit that counts attributes of purchasers who have purchased products being offered for sale on electronic commerce and the time of purchase, counts sales of the products for each attribute and time of purchaser who purchased the products, and accumulates the sales of the products and product information at the time of sale;
a modification unit that constructs a model using the accumulated data as learning data, and when a new user accesses a purchasing page for the product, uses the model to infer product information according to the attributes of the user and the time of access, and automatically modifies at least one of the text data and image data related to the product, other than the transaction price, included in the product information posted on the purchasing page for the product;
An information processing device comprising: the tabulation unit tabulates sales of the products being offered for sale in electronic commerce by attributes of each purchaser who purchased the products and by the season, day of the week, or time period in which the products were purchased, and accumulates the sales of the products and product information at the time of the sales;
The information processing device according to claim 1, characterized in that, when a new user accesses the purchasing page for the product, the modification unit automatically modifies at least one of the text data and image data related to the product, other than the transaction price, contained in the product information posted on the purchasing page for the product, depending on the attributes of the user and the season, day of the week, or time of access. The information processing device according to claim 1 or 2, characterized in that, when a new user accesses the purchasing page for the product, the change unit automatically changes the product title included in the product information posted on the purchasing page for the product in accordance with the attributes of the user and the time of access. The information processing device of any one of claims 1 to 3, characterized in that when a new user accesses a product purchasing page, the change unit automatically changes the price of the product included in the product information posted on the product purchasing page, depending on the attributes of the user and the time of access. The information processing device described in any one of claims 1 to 4, characterized in that when a new user accesses a product purchasing page, the change unit automatically changes the product's appeal points contained in the product information posted on the product purchasing page, depending on the attributes of the user and the time of access. The information processing device of any one of claims 1 to 5, characterized in that the modification unit uses the model to predict a period when a product will sell well to users with specific attributes, selects at least one of keywords and images that appeal to the users, and automatically modifies at least one of text data and image data related to the product other than the transaction price included in the product information posted on the purchasing page for the product at the predicted period . The information processing device according to any one of claims 1 to 6, characterized in that when changing product information posted on a product purchasing page, the change unit changes the product title, search tag, image or product description according to the age, gender and occupation of the user accessing the page. The information processing device according to any one of claims 1 to 7, characterized in that, when changing the product information posted on the product purchasing page, the change unit changes the product title, search tags, images or product description to morning ones when the user accesses the page in the morning , and changes the product title, search tags, images or product description to evening ones when the user accesses the page in the evening. An information processing method executed by an information processing device,
a counting step of counting attributes of purchasers who have purchased products being offered for sale on electronic commerce and the time of purchase, counting sales of the products for each attribute of the purchaser who purchased the products and for each time of purchase, and accumulating the sales of the products and product information at the time of sale;
a modification step of constructing a model using the accumulated data as learning data, and when a new user accesses a purchasing page for the product , inferring product information according to the attributes of the user and the time of access using the model, and automatically modifying at least one of the text data and image data related to the product, other than the transaction price, included in the product information posted on the purchasing page for the product;
13. An information processing method comprising: a counting step of counting attributes of purchasers who have purchased products being offered for sale on electronic commerce and the timing of the purchases, counting sales of the products for each attribute of the purchaser who purchased the products and for each timing of the purchases, and storing the sales of the products and product information at the time of the sales;
a modification procedure for constructing a model using the accumulated data as learning data, and when a new user accesses a purchasing page for the product , inferring product information according to the attributes of the user and the time of access using the model, and automatically modifying at least one of the text data and image data relating to the product, other than the transaction price, included in the product information posted on the purchasing page for the product;
An information processing program for causing a computer to execute the above.

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