JP7419303B2 - 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.

It accepts information regarding the product to be auctioned and the price at which the auction should be started, refers to information including past winning bids for the product, and if it is determined that the accepted starting price is relatively high, the auction starts. A technique has been disclosed for instructing sellers to change their starting prices.

Japanese Patent Application Publication No. 2003-316975

However, in the above-mentioned conventional technology, the starting price of the auction is simply changed according to the prices of similar products. In electronic commerce, listing titles including product names can be freely set, but sales can vary greatly depending on what is included in the listing title. Therefore, if the listing title can be changed to a more appropriate listing title than the current listing title, an increase in sales can be expected.

This application was made in view of the above, and the purpose is to propose a change to a more appropriate exhibition title in electronic commerce.

The information processing device according to the present application includes a tabulation unit that tabulates and accumulates changes in sales before and after the listing title has been changed for products that have been put up for sale in the past in electronic and electronic commerce; The estimation unit includes an estimating unit that estimates sales before and after changing the listing title, and a providing unit that proposes recommended listing titles based on the estimation results , and the estimating unit uses the accumulated results as learning data to model The system is characterized by constructing a model and using the model to infer a more preferable listing title and a change in sales when changing the listing title .

According to one aspect of the embodiment, it is possible to propose a change to a more appropriate listing title in 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 overview 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 listing prediction system. FIG. 4 is an explanatory diagram showing an overview of processing when automatically gathering exhibitors and holding a fair. FIG. 5 is a diagram illustrating a configuration example of an information processing system according to an embodiment. FIG. 6 is a diagram illustrating a configuration example of a terminal device according to the embodiment. FIG. 7 is a diagram illustrating a configuration example of an information providing apparatus according to an embodiment. FIG. 8 is a diagram showing an example of a user information database. FIG. 9 is a diagram showing an example of a history information database. FIG. 10 is a diagram showing an example of a product information database. FIG. 11 is a flowchart showing the processing procedure according to the embodiment. FIG. 12 is a diagram showing an example of the hardware configuration.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. In addition, in the following embodiments, the same parts are given the same reference numerals, and redundant explanations will be omitted.

[1. Overview of information processing method]
First, with reference to FIG. 1, an overview of an information processing method performed by an information processing apparatus according to an embodiment will be described. FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. In addition, in FIG. 1, a case will be described as an example in which 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) so that they can communicate with each other by wire or wirelessly. 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 a tablet used by a user U (user), and can communicate with any server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). This is a mobile terminal device that can perform Further, the terminal device 10 has a screen such as a liquid crystal display, which has a touch panel function, and displays data such as content through a tap operation, a slide operation, a scroll operation, etc. from the user U using a finger or a stylus. Accepts various operations on. Note that an operation performed on an area of the screen where content is displayed may be an operation on the content. Further, 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 cooperates with the terminal device 10 of each user U, and provides API (Application Programming Interface) services for various applications (hereinafter referred to as applications), etc., to the terminal device 10 of each user U, and various It is an information processing device that provides data, and is realized by a server device, a cloud system, etc.

Further, the information providing device 100 may 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 provides web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce (EC), electronic payment, online games, online banking, online trading, accommodation and ticket reservations. , video/music distribution, news, maps, route searches, route guidance, route information, operation information, weather forecasts, and other services may be provided. In reality, the information providing apparatus 100 may cooperate with various servers that provide the above-mentioned Web services, mediate the Web services, or may be in charge of processing the Web services.

Note that the information providing device 100 can acquire user information regarding the user U. For example, the information providing device 100 acquires information regarding attributes of the user U, such as the user's U's gender, age, and area of residence. Then, the information providing device 100 stores and manages information regarding attributes of the user U along with identification information indicating the user U (user ID, etc.).

Further, the information providing device 100 acquires various kinds 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 or the like. For example, the information providing device 100 acquires a location history, which is a history of the user U's location, date and time, from the terminal device 10. The information providing device 100 also acquires a search history, which is a history of search queries input by the user U, from a search server (search engine). The information providing device 100 also acquires a viewing history, which is a history of content viewed by the user U, from the content server. Further, the information providing device 100 acquires a purchase history (payment history) that is a history of product purchases and payment processing by the user U from the electronic commerce server and the payment processing server. Further, the information providing device 100 may acquire the listing history and the sales history, which are the listing history of the user U on the marketplace, from the electronic commerce server or the payment server. The information providing device 100 also acquires a posting history, which is a history of postings by the user U, from a posting server or SNS server that provides a word-of-mouth posting service.

[1-1. Product name change recommendation on EC]
In the first embodiment of the present application, the information providing device 100 determines the relationship between the listing title (headline) attached to a product listed on an electronic commerce (EC) site/app and the sales of the product. The system predicts the sales before and after changing the title of the product scheduled to be listed or currently on sale based on the above, and proposes a recommended title based on the prediction results.

Note that the product is an item (property) owned by the user, and is an item that can be put up for sale on the EC site/app. In other words, products are just one example of a transaction target. In addition, the exhibition title includes the product name, catchphrase, catchphrase, etc.

As shown in FIG. 1, the information providing device 100 sends products from the terminal device 10 of each user U to an EC site/app (mall, shop, auction, flea market, etc.) via the network N (see FIG. 5). (Step S1).

Subsequently, the information providing device 100 totals the sales of each product exhibited by each user U (step S2).

Subsequently, the information providing device 100 receives a request to change the listing title of the product from the user U who wishes to change the listing title of the product being put up for sale (step S3).

Subsequently, the information providing device 100 tallies changes in sales before and after changing the listing title of the product (step S4).

At this time, the information providing device 100 calculates the sales change due to the change in the exhibition title as a percentage of the total sales of the EC site/app on the day so as not to be influenced by the sales of the entire EC site/app. That is, the information providing device 100 converts sales changes into percentages so as not to be influenced by sales of the entire EC site/app. Further, the information providing device 100 normalizes sales so as not to be influenced by sales or the like.

For example, the information providing apparatus 100 processes as described in (1) and (2) below in consideration of the possibility that a change in the exhibited title is not the main cause of a change in sales.
(1) If the information providing device 100 is having a sale for the entire service/category, it normalizes the sale based on the sales change trend of products in the same category.
(2) The information providing device 100 normalizes a day when only a specific store/product is running a sale or advertising based on the change in sales (in the same category) when a similar measure was being implemented on the same day. For this purpose, a service policy master etc. is required.

Then, the information providing device 100 aggregates and accumulates data regarding the number of products that include the same word after the change (competitiveness), buyer attributes, etc. in sets. For example, for each product listed on an EC site/app, the information providing device 100 can calculate changes 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 the number of buyers. Data related to attributes, etc. are aggregated and accumulated in sets (sets).

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

Subsequently, the information providing device 100 proposes a change in the listing title to the terminal device 10 of the user U who is listing the product or planning to list the product via the network N (see FIG. 5) (step S6). . Note that when the user U inputs a new listing title on the product listing registration screen, the information providing device 100 sends a message to the terminal device 10 of the user U to change the listing title of the item more preferably. You may also suggest.

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

In the present embodiment, the information providing device 100 changes the candidate listing title of the current product after the change and the listing title based on changes in sales before and after changing the listing title of products with similar buyer attributes. It presents the degree (rate, amount) and possibility of sales improvement if the product is changed, and recommends changing the listing title. That is, the information providing device 100 determines how much sales are likely to change if the listing title of the current product is changed, based on changes in sales before and after changing the listing title of products with similar buyer attributes. Recommend changing the listing title.

Note that the information providing device 100 may aggregate and accumulate changes in sales before and after the change in the search tag, similarly to the exhibition title. Furthermore, the information providing device 100 may also aggregate and accumulate changes in sales before and after changes in product descriptions. That is, the information providing device 100 aggregates and accumulates sales changes before and after changes in text data such as exhibition titles, search tags, and/or product descriptions.

Furthermore, if sales suddenly increase when the product image is changed, the information providing device 100 also aggregates and accumulates the changes in sales before and after the product image is changed. The information providing device 100 then analyzes the pattern of images of products whose sales have improved after the change, and also suggests how to take images that will sell (photography methods, examples/samples). For example, the information providing device 100 analyzes the color tone, design, layout, etc. of image data of products with improved sales, estimates how to take an image that will sell, and makes a proposal on how to take an image that will sell.

For example, the information providing device 100 provides exhibition-related data (text data and image data related to the product) including the product exhibition title for each product listed on an EC site/app (mall, shop, auction, flea market, etc.). Understand changes in sales before and after the change in sales, and suggest changes to more desirable listing-related data.

Further, the information providing device 100 aggregates and accumulates changes in sales before and after changes in exhibition titles, search tags, images, etc., for each period such as season, day of the week, and time of day. Then, the information providing device 100 proposes changes to selling listing titles, search tags, images, etc., depending on the season, day of the week, time of day, etc.

Note that the seasons are not limited to the four seasons such as spring, summer, fall, and winter, but also include Golden Week, rainy season, mountain/sea season, Obon, New Year, school entrance/graduation season, etc. It also includes seasonal events such as heatstroke and hay fever outbreaks/warning periods. Furthermore, the days of the week are not limited to the seven days of the week, but may be divided into weekdays, weekends, holidays (holidays), and the like. In addition, the time period is not limited to between a certain time (for example, 8 o'clock, 8:00 to 9:00, etc.), but also morning/afternoon/night (or morning/noon/evening/night). etc. may be used.

[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 provides product information regarding sales of products listed on an EC site/app according to characteristics and trends of each period such as season, day of the week, and time of day. change. FIG. 2 is an explanatory diagram showing an overview of a processing method for automatically changing product information according to user attributes and time.

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

Subsequently, the information providing device 100 acquires and totals information regarding the attributes of the user U who purchased the product (step S12). For example, the information providing device 100 may provide information on the demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. Acquire and aggregate information regarding attributes such as attributes).

Subsequently, the information providing device 100 acquires and totals information regarding the attributes of the products purchased by the user U (step S13). For example, the information providing device 100 acquires and totals information regarding codes, product names, prices, sizes/dimensions, weights, standards, etc. as information regarding the attributes of the products purchased by the user U. In addition, the information providing device 100 may acquire and aggregate information regarding the brand and category of the product, the target of the product (attributes of users expected to be the target/purchasing group), and the like. Note that in the case of an auction, the information providing apparatus 100 may acquire and total information regarding the starting price and the final winning bid price.

Subsequently, the information providing device 100 acquires and totals information regarding the quantity of products purchased by the user U (step S14). For example, the information providing device 100 acquires and totals information regarding the number of products purchased by the user U. Further, the information providing device 100 may acquire and total information regarding the number of products (number of items) that the user U has purchased at the same time.

Subsequently, the information providing device 100 acquires and totals information regarding the time when the user U purchased the product (step S15). For example, the information providing device 100 acquires and aggregates information regarding the season, day of the week, time zone, etc. when the user U purchased the product.

Next, the information providing device 100 aggregates product sales for each attribute and time of each user U who purchased the product, and accumulates product sales and product information at the time of sale (step S16). . For example, the information providing device 100 aggregates and accumulates data related to each of the acquired information, product sales, and product information as a set.

Subsequently, when a new user U accesses the purchase page for the product, the information providing device 100 displays information that is posted on the purchase page for the product according to the attributes of the user U and the time of access. The product information is automatically changed (step S17).

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

For example, the information providing device 100 changes the product title, search tag, image, and/or product description, etc. according to the user U's attributes such as age, gender, and occupation (student/company employee/civil servant/freelance). do. In addition, the information providing device 100 changes the product title, search tag, image, and/or product description, etc. for the morning when the user U accesses in the morning, and changes it to the product title, search tag, image, and/or product description, etc. Change the product title, search tag, image, and/or product description, etc. It is assumed that product information for morning use/evening use is prepared for each attribute of user U.

Subsequently, the information providing device 100 sends the information posted on the purchase page of the product to the terminal device 10 of the new user U who has accessed the purchase page of the product via the network N (see FIG. 5). Product information is provided (step S18). Then, the user U views the provided product information and performs an operation for purchasing the product when purchasing the product (proceeding to step S11).

In this way, the information providing device 100 automatically changes product information according to the attributes and timing of the accessing user. For example, the information providing device 100 changes text data and/or image data regarding products being exhibited on the EC site/app according to the attributes and time zone of the accessing user. At this time, the information providing apparatus 100 registers a plurality of text data and image data, and switches them according to the attribute and time zone of the accessing user.

Further, the information providing device 100 may change the price range of the product depending on the attributes and timing of the accessing user. Further, the information providing device 100 may change the appeal points of the product depending on the attributes and timing of the accessing user.

In addition, the information providing device 100 estimates the season and time period when products sell well for users with specific attributes, and uses keywords to appeal to the users according to the number of products they want to sell (target number). You may also select an item or image and change exhibition-related data (text data and image data related to the item) including the item's listing title.

Additionally, the information providing device 100 estimates products that compete with the product currently on sale (competitive products), and changes the product information so that the product information is changed at the same time as the competing product or while avoiding the competing product. You may also select a time period.

Note that the information providing device 100 can continuously improve the accuracy of inference by repeating learning if changes in product information result in improved sales.

For example, the information providing device 100 stores information such as "target (user attributes)" x "product type" x "price" x "season (season, day of the week, time zone)" x "target quantity" x "product information (keyword, image)". ”, etc., and automatically change product information according to the attributes and time of day of the accessing user.

[1-3. Listing prediction system]
In the third embodiment of the present application, in electronic commerce, the information providing device 100 analyzes product information to predict the timing at which a specific product will be put up for sale on an EC site/app, and provides information regarding the predicted timing to the buyer. Provide to. FIG. 3 is an explanatory diagram showing an overview of the listing prediction system.

Usually, buyers do not know when a particular product will be listed on an EC site/app. Additionally, purchasers who are heavy users predict by themselves the timing when a particular product will be listed on an EC site/app based on rules of thumb or the like. Therefore, the information providing device 100 analyzes product information, predicts the timing at which a specific product will be listed on an EC site/app, and displays the product to potential buyers who wish to purchase the product or who are likely to purchase the product. Provide information about when

As shown in FIG. 3, the information providing device 100 receives a request for listing a product owned by the user U on an EC site/app from the terminal device 10 of the user U via the network N (see FIG. 5). It is accepted (step S21).

Subsequently, the information providing device 100 acquires and totals information regarding the attributes of the user U who has put the item up for sale (step S22). For example, the information providing device 100 displays the demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral) Acquire and aggregate information regarding attributes such as attributes).

Subsequently, the information providing device 100 acquires and totals information regarding the attributes of the products exhibited by the user U (step S23). For example, the information providing device 100 acquires and aggregates information regarding the brand, category, size, target user, etc. of the product as information regarding the attributes of the product exhibited by the user U.

Subsequently, the information providing device 100 acquires and totals information regarding the time when the user U put the product up for sale (step S24). For example, the information providing device 100 acquires and aggregates information regarding the time of year, day of the week, time zone, etc., in which the user U put the product up for sale.

Subsequently, the information providing device 100 totals the period (cycle) from when the user U purchases the product to when the product is sold on the EC site/app (step S25). That is, the information providing device 100 totals the period from when the user U obtains the product to when the product is put up for sale on the EC site/app. For example, the information providing device 100 obtains the time when the user U purchased (obtains) the product from the purchase history of the user U, and requests the listing of the product from the time the user U purchases (obtains) the product. Calculate the period up to the time of receipt.

At this time, the information providing device 100 may aggregate the period for each attribute of the user U who is the seller and the attribute of the product. Further, the information providing device 100 may also aggregate the EC sites/apps on which the user U has exhibited products.

Subsequently, the information providing device 100 estimates the listing timing according to 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 exhibition time (sale time) of a product based on product attributes and seasonality of the product. Furthermore, the information providing device 100 predicts the timing of listing the product at a flea market based on the period during which the product sells well on the EC site/app and the cycle of selling/repurchasing the product (cycle of letting go of the purchased product). .

Further, the information providing device 100 may predict the timing of listing the product based on the life cycle of the product. Furthermore, the information providing device 100 may predict the timing of putting the old model product on sale based on the scheduled time when the new model product will be put on the market.

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

For example, if a predetermined period of time has passed since user U purchased product 〇〇 on the EC site/app and the product sale/repurchase cycle (cycle of letting go of the purchased product) has been reached, the information providing device 100 may A message such as ``Would you like to exhibit product 〇〇?'' is provided to the terminal device 10 of user U who can become a seller.

At this time, the information providing apparatus 100 may set a threshold value/lower limit value of the exhibition timing to be provided depending on the type of product. For example, if the product is a durable consumer good such as an electrical appliance or furniture, the information providing device 100 determines the timing for listing the product only if a predetermined period (for example, one month) has passed since the user U purchased the product. may be limited to providing information about It seems that there are few opportunities or users to let go of the durable consumer goods that they have just purchased in a short period of time, and it is the users who are proposing to sell the durable consumer goods that they have just purchased in a short period of time (immediate sale, etc.). This is because the impression of U is not good. It also has the purpose of deterring resale. Furthermore, if the product is one that many users will part with in a short period of time, there is no need to encourage listing, and it is thought that the product will be listed in large quantities and there will be a surplus of the product. Note that if a predetermined period of time has not passed since the user U purchased the product, the information providing device 100 may provide information regarding the exhibition timing of the product after the predetermined period has elapsed.

In addition, the information providing device 100 sends a message to the terminal device 10 of the person who wants to purchase the product or the potential user who is likely to purchase the product at a predetermined period before the predicted timing of the product to be put up for sale. ” and other messages.

[1-4. Automatically gather sellers on EC and hold a fair]
In the fourth embodiment of the present application, the information providing device 100 analyzes fluctuations in demand and supply of products listed on the EC site/app and recommends an appropriate listing timing to the seller. A fair (event: fair) is held by automatically gathering exhibitors. Note that the fair may be a sale (seasonal bargain sale, time sale for a limited time/limited quantity, etc.), as well as a campaign, an event, or the like. FIG. 4 is an explanatory diagram showing an overview of processing when automatically gathering exhibitors and holding a fair.

Usually, sellers don't know when their items will sell. Therefore, the information providing device 100 analyzes past fluctuations in demand and supply of products similar to the product scheduled to be put up for sale, estimates the time when the demand for the product will increase, and proposes an appropriate listing timing to the seller. Furthermore, if the seller is already listing a product, the information providing device 100 notifies the seller of the time when demand for the product is expected to increase. This will automatically gather exhibitors and hold a fair.

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

Subsequently, the information providing device 100 acquires and totals information regarding the attributes of the user U who purchased the product (step S32). For example, the information providing device 100 may provide information on the demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. Acquire and aggregate information regarding attributes such as attributes).

Subsequently, the information providing device 100 acquires and totals information regarding the attributes of the products purchased by the user U (step S33). For example, the information providing device 100 acquires and totals information regarding codes, product names, prices, sizes/dimensions, weights, standards, etc. as information regarding the attributes of the products purchased by the user U. In addition, the information providing device 100 may acquire and aggregate information regarding the brand and category of the product, the target of the product (attributes of users expected to be the target/purchasing group), and the like. Note that in the case of an auction, the information providing apparatus 100 may acquire and total information regarding the starting price and the final winning bid price.

Subsequently, the information providing device 100 acquires and totals information regarding the quantity of products purchased by the user U (step S34). For example, the information providing device 100 acquires and totals information regarding the number of products purchased by the user U. Further, the information providing device 100 may acquire and total information regarding the number of products (number of items) that the user U has purchased at the same time.

Subsequently, the information providing device 100 acquires and totals information regarding the time when the user U purchased the product (step S35). For example, the information providing device 100 acquires and aggregates information regarding the season, day of the week, time zone, etc. when the user U purchased the product.

Subsequently, the information providing device 100 totals the product sales for each attribute and time of each user U who purchased the product, and accumulates the product sales (step S36). For example, the information providing device 100 aggregates and accumulates data related to each piece of acquired information and product sales as a set.

Next, the information providing device 100 estimates the user U who is the target 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 the sales according to the time (step S37). .

Subsequently, 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 FIG. 5) (step S38).

For example, the information providing device 100 sends a message via the network N (see FIG. 5) to the terminal device 10 of the user U who is expected to participate in the fair, saying, ``We are planning to hold a fair around XX.Would you like to participate?'' ” and other messages.

At this time, the information providing device 100 sends a message via the network N (see FIG. 5) to the terminal device 10 of the user U, who can become an exhibitor, saying, ``We are planning to hold a fair around XX. You may also provide a message such as "I don't know what to do."

In addition, the information providing device 100 sends a message via the network N (see FIG. 5) to the terminal device 10 of the user U who is interested in the target product of the fair and who is expected to purchase it, saying, “The fair is scheduled to be held around XX.” You may also provide a message such as "The item you are looking for is likely to be listed."

In this way, the information providing device 100 estimates how much demand there is for each product in electronic commerce, determines which products are likely to sell, and sends out special features about the products. The information providing device 100 looks at the balance of receipts for each product, and in order to collect sellers of products that can be expected to increase sales from among changing categories, the information providing device 100 sends messages to the owners of the products, etc., saying, ``Let's sell this.'' !”, and with the consent of the owner of the product, etc., the fair is automatically held.

Since consumers are more sensitive to other EC sites/apps than to flea markets, the information providing device 100 collects and analyzes changes in demand and supply of each product on other EC sites/apps, and proactively analyzes the changes in supply and demand for each product. A fair will be held at the flea market.

For example, in personal sales such as flea markets and auctions, the quantity of purchases and sales is small and products change frequently, making it difficult to accumulate sufficient information. If the information providing device 100 provides information from multiple angles, it is possible to accumulate sufficient information in a complex manner by tracking continuous transactions of the same product at online malls, shopping sites, etc.

[2. Configuration example of information processing system]
Next, the configuration of the information processing system 1 including the information providing apparatus 100 according to the embodiment will be described using FIG. 5. FIG. 5 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 5, the information processing system 1 according to the embodiment includes a terminal device 10 and an information providing device 100. These various devices are connected via a network N so that they can communicate 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 what is illustrated. For example, in FIG. 5, only one terminal device 10 is shown for simplification of illustration, but this is just an example and is not limited, and there may be two or more terminal devices.

The terminal device 10 is an information processing device used by the user U. For example, the terminal device 10 may be 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 device with a communication function, a car navigation system, a smart watch, or the like. These include wearable devices such as head-mounted displays, smart glasses, etc.

The terminal device 10 also supports wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), Bluetooth (registered trademark), and wireless LAN (Local It is possible to connect to a network N via short-distance wireless communication such as a 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, or the like. Note that the information providing device 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be explained using FIG. 6. FIG. 6 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. As shown in FIG. 6, the terminal device 10 includes a communication section 11, a display section 12, an input section 13, a positioning section 14, a sensor section 20, a control section 30 (controller), and a storage section 40. Be prepared.

(Communication Department 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 NIC (Network Interface Card), an antenna, or the like.

(Display section 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 (EL display). Further, the display unit 12 is a touch panel type display, but is not limited to this.

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

(Positioning unit 14)
The positioning unit 14 receives a signal (radio wave) sent from a GPS (Global Positioning System) satellite, and based on the received signal, determines position information (for example, latitude and longitude). That is, the positioning unit 14 positions the terminal device 10 . Note that GPS is just one example of GNSS (Global Navigation Satellite System).

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

(Wi-Fi positioning)
For example, the positioning unit 14 positions the terminal device 10 using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 performs Wi-Fi communication, etc., and determines the position of the terminal device 10 by measuring the distance to nearby base stations and access points.

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

(geomagnetic positioning)
Furthermore, the positioning unit 14 positions the terminal device 10 based on the geomagnetic pattern of the structure measured in advance and the geomagnetic sensor included in the terminal device 10 .

(RFID positioning)
Further, for example, if the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used at station ticket gates, stores, etc., or has a function to read an RFID tag. In this case, the location where the terminal device 10 used the terminal device 10 is recorded together with the information that the payment was made. The positioning unit 14 may measure the position of the terminal device 10 by acquiring such information. Further, the position may be determined by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

The positioning unit 14 may position the terminal device 10 using one or a combination of the above-mentioned positioning means, if necessary.

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

Note that each of the sensors 21 to 28 described above is merely an example and is not limited to the above. That is, the sensor section 20 may be configured to include a portion of each of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of each 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 moving direction, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects physical movements of the terminal device 10 such as tilt in three axes directions based on the angular velocity of the terminal device 10 and the like. The atmospheric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

Since the terminal device 10 is equipped with the above-mentioned acceleration sensor 21, gyro sensor 22, atmospheric pressure sensor 23, etc., it is possible to implement technologies such as pedestrian autonomous navigation (PDR) using these sensors 21 to 23, etc. It becomes possible to measure the position of the terminal device 10 using the . This makes it possible to obtain indoor position information that is difficult to obtain using positioning systems such as GPS.

For example, a pedometer using the acceleration sensor 21 can calculate the number of steps, walking speed, and distance walked. Furthermore, by using the gyro sensor 22, it is possible to know the direction of travel of the user U, the direction of the line of sight, and the inclination of the user's body. Further, from the atmospheric pressure detected by the atmospheric pressure sensor 23, it is also possible to know the altitude and the number of floors where the terminal device 10 of the user U is located.

The temperature sensor 24 detects, for example, the temperature around the terminal device 10. The sound sensor 25 detects, for example, sounds around the terminal device 10. The optical sensor 26 detects the illuminance around the terminal device 10 . The magnetic sensor 27 detects, for example, the earth's magnetism around the terminal device 10. The image sensor 28 captures an image of the surroundings of the terminal device 10.

The above-mentioned atmospheric pressure sensor 23, temperature sensor 24, sound sensor 25, optical sensor 26, and image sensor 28 each detect atmospheric pressure, temperature, sound, and illuminance, and capture images of the surroundings, so that the terminal device 10 It is possible to detect the surrounding environment and situation. Furthermore, it is 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 CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input/output port, etc., and various circuits. Further, the control unit 30 may be configured with hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control section 30 includes a transmitting section 31, a receiving section 32, and a processing section 33.

(Transmission unit 31)
The transmitting unit 31 receives, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and information measured by the positioning unit 14. The location information of the terminal device 10 and the like can be transmitted to the information providing device 100 via the communication unit 11.

(Receiving unit 32)
The receiving unit 32 can receive various information provided from 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 and the like. For example, the processing unit 33 can output various types of information transmitted by the transmitting unit 31 and various types of information received by the receiving unit 32 from the information providing device 100 to the display unit 12 for display.

(Storage unit 40)
The storage unit 40 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an optical disk. Ru. The storage unit 40 stores various programs, various data, and the like.

[4. Configuration example of information providing device]
Next, the configuration of the information providing apparatus 100 according to the embodiment will be described using FIG. 7. FIG. 7 is a diagram illustrating a configuration example of the information providing apparatus 100 according to the embodiment. As shown in FIG. 7, the information providing device 100 includes a communication section 110, a storage section 120, and a control section 130.

(Communication Department 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). Further, the communication unit 110 is connected to the network N (see FIG. 5) by wire or wirelessly.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as an HDD, an SSD, or an optical disk. As shown in FIG. 7, the storage unit 120 includes a user information database 121, a history information database 122, and so on.

(User information database 121)
The user information database 121 stores user information regarding the user U. For example, the user information database 121 stores various information such as user U's attributes. 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 includes items such as "user ID (identifier),""age,""gender,""home,""worklocation," and "interest."

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

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

Moreover, "home" indicates the location information of the home of the user U 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. Furthermore, for example, "home" may be a region name or address.

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

Moreover, "interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object in which the user U identified by the user ID has a high interest. For example, "interest" may be a search query (keyword) that the user U inputs into a search engine. In the example shown in FIG. 8, one "interest" is shown for each user U, but there may be a plurality of "interests".

For example, in the example shown in FIG. 8, the age of the user U identified by the user ID "U1" is "20s", and the gender is "male". Further, for example, the user U identified by the user ID "U1" indicates that his home is "LC11". Further, for example, the user U identified by the user ID "U1" indicates that the work location is "LC12". Further, for example, the user U identified by the user ID "U1" indicates that he is interested in "sports."

Here, in the example shown in FIG. 8, abstract values such as "U1", "LC11", and "LC12" are used for illustration, but "U1", "LC11", and "LC12" have specific values. It is assumed that information such as character strings and numerical values is stored. Below, abstract values may be illustrated in diagrams related to other information as well.

Note that the user information database 121 is not limited to the above, and may store various information depending on the purpose. For example, the user information database 121 may store various information regarding the terminal device 10 of the user U. In addition, the user information database 121 includes information such as demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. of user U. Information regarding attributes may also be stored. For example, the user information database 121 includes name, family composition, place of birth (locality), occupation, position, income, qualifications, type of residence (single-family house, condominium, etc.), presence or absence of a car, commuting/commuting time, commuting/commuting, etc. Memorizes information such as routes, commuter pass sections (stations, lines, etc.), frequently used stations (other than the stations closest to your home or work), lessons (location, time zone, etc.), hobbies, interests, lifestyle, etc. You can.

(History information database 122)
The history information database 122 stores various information related to history information (log data) indicating the actions 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” indicates identification information for identifying user U. Further, “position history” indicates a position history that is a history of the user U's position and movement. Further, “search history” indicates a search history that is a history of search queries input by the user U. In addition, “browsing history” indicates a browsing history that is a history of contents that the user U has viewed. Further, “purchase history” indicates a purchase history that is a history of purchases by user U. Moreover, "posting history" indicates a posting history that is a history of postings by user U. Note that the "posting history" may include questions regarding user U's belongings.

For example, in the example shown in FIG. 9, user U identified by user ID "U1" moves as per "location history #1", searches as per "search history #1", and searches as per "view history #1". This indicates that the content was viewed according to "history #1", a predetermined product, etc. was purchased at a predetermined store etc. according to "purchase history #1", and the content was posted according to "posting history".

Here, in the example shown in FIG. 9, abstracts such as "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" are used. Although the figures are shown using typical values, "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" are It is assumed that information such as specific character strings and numerical values is stored.

Note that 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 user U's usage history of a predetermined service. Further, the history information database 122 may store the user U's visit history to a physical store, visit history to a facility, or the like. Further, the history information database 122 may store the payment history of user U's payment using the terminal device 10 (electronic payment).

(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 attribute", "seller attribute", "purchasing group", and "listing timing".

"Product ID" indicates identification information for identifying a product. For example, the product ID indicates a product code, product name, etc. Moreover, the "exhibition title" indicates the exhibition title of the product exhibited on the EC site/app. Moreover, "product attribute" indicates the attribute of the product exhibited on the EC site/app. Further, "seller attribute" indicates the attribute of the seller who has put the product on the EC site/app. Furthermore, the "purchasing group" indicates the purchasing group of the products listed on the EC site/app. Moreover, "listing timing" indicates a listing timing suitable for listing a product on an EC site/app.

For example, in the example shown in Figure 10, the product identified by the product ID "Product #A" has "Exhibition Title #A" and "Product Attribute #A" posted on the EC site/app, and the main product ID is "Product #A". The attribute of the seller is "seller attribute #A," and the attribute of the main purchaser of the product is "purchasing group #A," indicating that it is preferable to list the product at the "seller timing."

Here, in the example shown in FIG. 10, "Product #A", "Exhibition title #A", "Product attribute #A", "Seller attribute #A", "Purchasing group #A", and "Exhibition timing #A" ", "Product #A", "Exhibition Title #A", "Product Attribute #A", "Seller Attribute #A", "Purchasing Group #A", and "Exhibition Title #A" It is assumed that information such as specific character strings and numerical values is stored in "Timing #A."

Note that the product information database 123 is not limited to the above, and may store various information depending on the purpose. For example, the product information database 123 may store identification information indicating the EC site/app where the product is displayed. The product information database 123 may also store information such as seasons, days of the week, and time periods when product sales change. The product information database 123 may also store the period (cycle) from when the user U purchases a product to when the product is sold on the EC site/app.

(Control unit 130)
Returning to FIG. 7, the explanation will be continued. The control unit 130 is a controller, and uses, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array) to control the information providing apparatus 100. This is achieved by executing various programs (corresponding to an example of an information processing program) stored in an internal storage device using a storage area such as a RAM as a work area. In the example shown in FIG. 7, the control unit 130 includes an acquisition unit 131, a totaling unit 132, an estimating unit 133, a changing unit 134, and a providing 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 and performs a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110.

The acquisition unit 131 also acquires user information regarding the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information indicating the user U (user ID, etc.), location information of the user U, attribute information of the user U, etc. from the terminal device 10 of the user U. Further, the acquisition unit 131 may acquire identification information indicating the user U, attribute information of the user U, etc. at the time of user U's user registration. The acquisition unit 131 then 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 based on the user ID or the like. The acquisition unit 131 then registers 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 regarding the attributes of the user U who has listed/purchased a product on the EC site/app. For example, the acquisition unit 131 acquires the demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral Acquire information regarding attributes, such as physical attributes).

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 code, product name, price, size/dimensions, weight, standards, etc. as information regarding the attributes of the product purchased by the user U. In addition, the acquisition unit 131 may acquire information regarding the brand and category of the product, the target of the product (attributes of users expected to be the target/purchasing group), and the like. Note that 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. Further, the acquisition unit 131 may acquire information regarding the number of products (number of items) that the user U purchased at the same time.

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 season, day of the week, time zone, etc. when the user U purchased the product.

(Tally section 132)
The aggregation unit 132 aggregates the attributes of products being exhibited in electronic commerce, the attributes of buyers, and the timing of purchases. At this time, the aggregation unit 132 aggregates information regarding the attributes of the user U who purchased the product. Further, the totaling unit 132 totals information regarding the attributes of the products purchased by the user U. Further, the totaling unit 132 totals information regarding the quantity of products purchased by the user U. Furthermore, the aggregation unit 132 aggregates information regarding the time when the user U purchased the product. Then, the totaling unit 132 totals the sales of the product for each attribute and period of each user U who purchased the product.

Furthermore, the tally unit 132 tallies the period (cycle) from when the user U purchases a product to when the product is sold on the EC site/app. That is, the totaling unit 132 totals the period from when the user U obtains the product to when it is put up for sale on the EC site/app. For example, the aggregation unit 132 obtains the time point at which the user U purchased (obtained) the product from the purchase history of the user U, and receives requests for listing the product from the time the user U purchases (obtains) the product. Collect the period up to the point in time.

At this time, the aggregation unit 132 may aggregate the period for each attribute of the user U who is the seller and the attribute of the product. Furthermore, the aggregation unit 132 may also aggregate the EC sites/apps on which the user U has exhibited products.

Further, the totaling unit 132 totals the sales of each product exhibited by each user U. For example, the aggregation unit 132 aggregates changes in sales before and after changing the listing title of a product. At this time, the aggregation unit 132 may aggregate data regarding the number of products (competitiveness) that include the same word after the change, the attributes of the purchaser, etc. in sets (groups). For example, for each product listed on an EC site/app, the aggregation unit 132 calculates the change in sales before and after changing the listing title including the product name, the number of products that include the same word after the change (competitiveness), and the purchaser's Data related to attributes, etc. is aggregated in sets (groups).

Note that the aggregation unit 132 may aggregate changes in sales before and after the change in the search tag, similarly to the exhibition title. Furthermore, the aggregation unit 132 may also aggregate changes in sales before and after changes in product descriptions. That is, the aggregation unit 132 may aggregate changes in sales before and after changes in text data such as exhibition titles, search tags, and/or product descriptions. Furthermore, if sales suddenly increase when the product image is changed, the totaling unit 132 also totals the change in sales before and after the product image is changed.

(Estimation unit 133)
The estimating unit 133 estimates the sales before and after the change in the listing title of the product currently being put up for sale, based on the relationship between the listing title and the sales for products that were put up for sale in the past in electronic commerce. For example, the estimating unit 133 estimates the sales before and after the product description of the product currently on sale is changed, based on the relationship between the product description and sales of products that have been put on sale in the past in electronic commerce. Furthermore, the estimating unit 133 estimates the sales before and after the change of the search tag of the product currently on sale based on the relationship between the search tag and sales of products that were put on sale in the past in electronic commerce. Furthermore, the estimating unit 133 estimates the sales before and after the image data of the product being put up for sale is changed, based on the relationship between the image data and the sales regarding the products put up for sale in the past in electronic commerce.

Furthermore, the estimating unit 133 estimates competing products based on the attributes of the products being exhibited in electronic commerce, the attributes of the buyers, and the time of purchase.

Furthermore, the estimating unit 133 analyzes product information of products currently being put up for sale in electronic commerce and estimates the listing timing at which the product will be put up for sale. For example, the estimating unit 133 analyzes the period from purchase to sale of a product listed in electronic commerce to estimate the timing at which the product is likely to be put up for sale. Furthermore, the estimating unit 133 analyzes the timing at which the sales of products listed in electronic commerce change and estimates the appropriate listing timing for listing the products.

Furthermore, the estimating unit 133 analyzes product information of products currently on sale in the online shopping mall, and estimates the timing at which the product will be put up for sale in interpersonal transactions.

Furthermore, the estimating unit 133 analyzes fluctuations in demand and supply of products exhibited in electronic commerce, and estimates the timing of a product fair and the number of participants in the fair. For example, the estimating unit 133 analyzes fluctuations in demand and supply of products exhibited in electronic commerce, and estimates the timing of a product fair and the product exhibitor. Furthermore, the estimating unit 133 analyzes fluctuations in demand and supply of products exhibited in electronic commerce, and estimates the timing of a product fair and the purchasers of the products.

Furthermore, the estimating unit 133 analyzes fluctuations in demand and supply of products listed in electronic commerce, and estimates potential product sellers and product listing timing.

Furthermore, the estimating unit 133 analyzes the fluctuations in demand and supply of products listed in e-commerce, estimates products whose sales are expected to increase, and estimates the timing of fairs for the estimated products and the sellers of the products. .

Furthermore, the estimating unit 133 analyzes fluctuations in demand and supply of products exhibited on the electronic shopping mall, and estimates the timing of a product fair and the product exhibitor in interpersonal transactions.

(Change section 134)
The changing unit 134 changes product information based on the attributes of the products being exhibited in the electronic commerce, the attributes of the buyers, and the aggregated results regarding the timing of the purchase, according to the characteristics of each period regarding the sales of the products being exhibited in the electronic commerce. change automatically.

For example, the changing unit 134 may adjust the change according to seasonal characteristics regarding the sales of products being exhibited in e-commerce based on the aggregated results regarding the attributes of the products being exhibited in e-commerce, the attributes of the purchasers, and the timing of purchases. Automatically change product information. Furthermore, the changing unit 134 changes the characteristics of each day of the week regarding the sales of the products being exhibited in e-commerce based on the aggregated results regarding the attributes of the products being exhibited in e-commerce, the attributes of the purchasers, and the timing of purchases. Automatically change product information. In addition, the changing unit 134 adjusts the characteristics of sales of products being exhibited in e-commerce by time period based on the aggregated results regarding the attributes of products being exhibited in e-commerce, the attributes of buyers, and the timing of purchases. automatically change product information.

Furthermore, the changing unit 134 changes the attributes of the product being exhibited in e-commerce, the attributes of the buyer, and the purchase timing based on the aggregated results regarding the attributes of the product being exhibited in e-commerce, the attributes of the purchaser, and the timing of purchase. Automatically change product information according to seasonal characteristics.

For example, the changing unit 134 changes the characteristics of each period regarding the sales of the products being exhibited in e-commerce based on the aggregated results regarding the attributes of the products being exhibited in e-commerce, the attributes of the purchasers, and the timing of purchases. Automatically change product prices.

In addition, the changing unit 134 changes the characteristics of sales of the products being exhibited in e-commerce based on the attributes of the products being exhibited in e-commerce, the attributes of buyers, and the timing of purchases based on the characteristics of each period regarding the sales of the products being exhibited in e-commerce. Automatically change product appeal points.

Further, the changing unit 134 automatically changes the product information according to the estimated product information of the competing product.

(Providing unit 135)
The providing unit 135 proposes a recommended listing title based on the estimated sales before and after changing the listing title of the product being put up for sale. For example, the providing unit 135 proposes changing the product name included in the listing title of the product being put up for sale, based on the estimated sales before and after changing the listing title of the product being put up for sale. Further, the providing unit 135 proposes a change to the catchphrase included in the listing title of the product being put up for sale, based on the estimated sales before and after changing the listing title of the product being put up for sale.

Further, the providing unit 135 proposes a recommended product description based on the estimated sales before and after the product description of the product being exhibited is changed. Further, the providing unit 135 proposes a recommended search tag based on the estimated sales before and after changing the search tag of the product being exhibited.

Further, the providing unit 135 proposes a recommended way to take image data based on the estimated sales before and after the image data of the product being exhibited is changed. For example, the providing unit 135 proposes a recommended change in the color tone of the image data based on the estimated sales before and after the change in the image data of the product being put up for sale. Further, the providing unit 135 proposes a recommended change in the layout of the image data based on the estimated sales before and after the change in the image data of the product being exhibited.

Further, the providing unit 135 analyzes the product information of the product being put up for sale in electronic commerce and provides the estimated put-on timing to the person who wishes to purchase the product.

For example, the providing unit 135 analyzes the period from purchase to sale of a product listed in electronic commerce and determines the possibility of listing the product at the estimated listing timing a certain period before the estimated listing timing. To provide a message conveying a certain fact to a person who wishes to purchase a product.

In addition, the providing unit 135 analyzes the period from purchase to sale of products listed in e-commerce and sends a message prompting the listing of the product at the estimated listing timing a predetermined period before the estimated listing timing. Provided to potential prospective sellers of the product.

Further, the providing unit 135 analyzes the product information of the product being put up for sale in electronic commerce and provides the estimated put-up timing to the potential person who plans to put up the product. For example, the providing unit 135 provides a potential product exhibitor with a message prompting the potential product exhibitor to exhibit the product at the estimated exhibit timing a predetermined period of time before the estimated exhibit timing.

In addition, the estimating unit 133 analyzes the attributes of the product listed in e-commerce, the attributes of the product seller, the purchasing demographic of the product, the period from purchase to sale of the product, and the timing at which the sales of the product change. Estimate the appropriate listing timing to list.

For example, the providing unit 135 analyzes the product purchasing demographic, the period from purchase to sale of the product, and the timing of changes in product sales to determine the estimated listing timing (suitable listing timing for listing the product). A message urging potential product exhibitors to exhibit the product at the estimated product timing is provided before the specified period.

In addition, the providing unit 135 analyzes the period from purchase to sale of the product and the timing at which the sales of the product change and calculates the timing before the specified period from the estimated listing timing (suitable listing timing for listing the item). , a message is provided to those who wish to purchase the product, informing them that the product may be listed at the estimated listing timing.

Further, the providing unit 135 analyzes the product information of the products being exhibited on the online shopping mall and provides the estimated timing of exhibiting the products in interpersonal transactions to those who wish to purchase the products.

Further, the providing unit 135 provides the participants with the timing of the product fair, and automatically gathers the participants at the time of the product fair to hold the fair. For example, the providing unit 135 provides the exhibitors with the timing of the product fair, and automatically gathers the exhibitors at the time of the product fair to hold the fair. Further, the providing unit 135 provides the purchaser with the timing of the product fair, and automatically gathers the buyers at the time of the product fair to hold the fair.

Further, the providing unit 135 analyzes the supply and demand fluctuations of products listed in electronic commerce and provides the estimated product listing timing to potential product exhibitors.

Further, the providing unit 135 provides potential product exhibitors with a message urging them to exhibit their products at the product fair a predetermined period of time before the product fair is held. Further, the providing unit 135 provides a message urging the person who wishes to purchase the product to participate in the product fair a predetermined period of time before the product fair is held.

In addition, the providing unit 135 provides the participants with the timing of the product fair in person-to-person transactions, which is estimated by analyzing the supply and demand fluctuations of products listed on the online shopping mall, and allows participants to participate in the product fair at the timing. automatically gather people and hold a fair.

[5. Processing procedure]
Next, a processing procedure by the information providing apparatus 100 according to the embodiment will be described using 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 the information regarding the attributes of the user U who exhibited/purchased on the EC site/app, which was acquired by the acquisition unit 131 (step S101).

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

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

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

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

Subsequently, the estimating unit 133 of the information providing device 100 estimates recommended exhibition titles and the like based on the aggregation results (step S106). That is, the estimating unit 133 estimates exhibited titles, etc. whose sales are expected to improve more than the current level, based on the aggregation results.

Subsequently, the change unit 134 of the information providing device 100 adjusts the sales of the product being exhibited in e-commerce based on the aggregated results regarding the attributes of the product being exhibited in the EC site/app, the attributes of the purchaser, and the timing of purchase. The product information is automatically changed according to the characteristics of each period (step S107).

Next, the estimating unit 133 of the information providing device 100 calculates the information based on the attributes of the user U who listed/purchased on the EC site/app, the attributes of the product, the period (cycle) from purchase to sale of the product, and fluctuations in supply and demand of the product. Then, the exhibition timing, the user U who will be the target of the fair, and the timing of the fair are estimated (step S108).

Subsequently, the providing unit 135 of the information providing device 100 sends, via the communication unit 110, information such as recommended exhibition titles, exhibition timing, and fair holding to the terminal device 10 of the user U who is an exhibitor or a prospective exhibitor. Information regarding the timing is provided (step S109). Further, the providing unit 135 may propose a setting for automatically changing product information (a setting for allowing automatic change of product information). Further, the providing unit 135 provides the terminal device 10 of the user U who may purchase the product, via the communication unit 110, with information regarding the exhibitor's exhibition timing and the fair holding time.

[6. Modified example]
The terminal device 10 and information providing device 100 described above may be implemented in various different forms other than the above embodiments. Therefore, a modification of the embodiment will be described below.

In the above embodiment, part or all of the processing executed by the information providing device 100 may actually be executed by the terminal device 10. For example, the process may be completed stand-alone (by the terminal device 10 alone). In this case, it is assumed that the terminal device 10 has the functions of the information providing device 100 in the above embodiment. Furthermore, in the embodiment described above, since the terminal device 10 cooperates with the information providing device 100, it appears to the user U that the terminal device 10 also executes the processing of the information providing device 100. That is, from another perspective, it can be said that the terminal device 10 includes the information providing device 100.

In the embodiment described above, the information providing device 100 provides a product name change recommendation on EC, an automatic change of product information according to user attributes and time, a listing prediction system, and an EC product name change recommendation in accordance with the settings etc. by the user U. A fair may be held in which exhibitors are automatically gathered together as appropriate. For example, the information providing apparatus 100 may perform all processes simultaneously or selectively.

[7. effect〕
As described above, the information processing device (information providing device 100) according to the present application determines whether a product is currently being listed for sale based on the relationship between the listing title and the sales of a product that has been listed in the past in electronic commerce. It includes an estimating unit 133 that estimates sales before and after title change, and a providing unit 135 that proposes recommended exhibition titles based on the estimation results.

For example, the providing unit 135 proposes changing the product name included in the exhibition title of the product currently on sale based on the estimation result.

Further, the providing unit 135 proposes a change to the catchphrase included in the exhibition title of the product being put up for sale based on the estimation result.

Furthermore, the estimating unit 133 estimates the sales before and after the product description of the product currently on sale is changed, based on the relationship between the product description and sales of products that have been put on sale in the past in electronic commerce. The providing unit 135 proposes recommended product descriptions based on the estimation results.

Furthermore, the estimating unit 133 estimates the sales before and after the change of the search tag of the product currently on sale based on the relationship between the search tag and sales of products that have been put on sale in the past in electronic commerce. The providing unit 135 proposes recommended search tags based on the estimation results.

Furthermore, the estimating unit 133 estimates the sales before and after the image data of the product being put up for sale is changed, based on the relationship between the image data and the sales related to the products put up for sale in the past in electronic commerce. The providing unit 135 proposes a recommended way to capture image data based on the estimation results.

At this time, the providing unit 135 proposes a recommended change in the color tone of the image data based on the estimation result.

Alternatively, the providing unit 135 proposes a change in the layout of the recommended image data based on the estimation result.

Through any one or a combination of the above-described processes, the information processing device according to the present application can propose a change to a more appropriate listing title in electronic commerce.

[8. Hardware configuration]
Further, the terminal device 10 and the information providing device 100 according to the embodiments described above are realized by, for example, a computer 1000 having a configuration as shown in FIG. 12. The information providing apparatus 100 will be described below as an example. FIG. 12 is a diagram showing an example of the hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and 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 to a bus. 1090.

The arithmetic unit 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 performs various processes. The arithmetic device 1030 is realized by, for example, 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 temporarily stores data used by the calculation device 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and includes a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid Disk Drive). This is realized using flash memory, etc. The secondary storage device 1050 may be a built-in storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), 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 the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface) and HDMI (registered trademark) (High Definition Multimedia Interface). Further, 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, for example, a USB or the like.

Further, 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, output device 1010 and input device 1020 may be wireless devices.

Moreover, the output device 1010 and the input device 1020 may be integrated like 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.

Note that the input device 1020 is, 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), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

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

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070. For example, the arithmetic device 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 realizes the functions of the control unit 130 by executing a program loaded onto the primary storage device 1040. Further, the arithmetic device 1030 of the computer 1000 may load a program obtained from another device via the network I/F 1080 onto the primary storage device 1040, and execute the loaded program. Furthermore, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I/F 1080, and may call and use program functions, data, etc. from other programs of other devices.

[9. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those that are in a so-called equivalent range. Furthermore, the aforementioned components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the constituent elements can be made without departing from the gist of the embodiments described above.

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

Furthermore, each component of each device shown in the drawings is functionally conceptual, and does not necessarily need to be physically configured as shown in the drawings. In other words, the specific form of distributing and integrating each device is not limited to what is shown in the diagram, and all or part of the devices can be functionally or physically distributed or integrated in arbitrary units depending on various loads and usage conditions. Can be integrated and configured.

For example, the information providing device 100 described above may be realized by a plurality of server computers, and depending on the function, it may be realized by calling an external platform etc. using an API (Application Programming Interface), network computing, etc. can be changed flexibly.

Furthermore, the above-described embodiments and modifications can be combined as appropriate within a range that does not conflict with the processing contents.

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

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 Totalization unit 133 Estimation unit 134 Change unit 135 Provision unit

Claims (10)

an aggregation unit that aggregates and accumulates changes in sales before and after changes in listing titles for products that have been listed in the past in e-commerce;
an estimation section that estimates sales before and after changing the listing title of the product being listed from the accumulated tabulation results ;
A provision department that proposes recommended listing titles based on the estimation results;
Equipped with
The estimation unit constructs a model using the accumulated aggregation results as learning data, and uses the model to infer a more preferable listing title and a change in sales when changing the listing title.
An information processing device characterized by: The information processing device according to claim 1, wherein the providing unit proposes changing a product name included in an exhibition title of a product currently on sale based on the estimation result. The information processing device according to claim 1 or 2, wherein the providing unit proposes a change to a catchphrase included in an exhibition title of a product currently on sale, based on the estimation result. The aggregation unit aggregates and accumulates changes in sales before and after changes in product descriptions regarding products exhibited in the past in the electronic commerce,
The estimating unit estimates the sales before and after the product description of the product being exhibited is changed from the accumulated aggregation results ,
The information processing device according to any one of claims 1 to 3, wherein the providing unit proposes a recommended product description based on the estimation result. The aggregation unit aggregates and accumulates changes in sales before and after changes in search tags regarding products exhibited in the past in the electronic commerce,
The estimating unit estimates the sales before and after changing the search tag of the product being exhibited from the accumulated aggregation results ,
The information processing device according to any one of claims 1 to 4, wherein the providing unit proposes a recommended search tag based on the estimation result. The aggregation unit aggregates and accumulates changes in sales before and after changes in image data regarding products exhibited in the past in the electronic commerce,
The estimation unit estimates the sales before and after the image data of the product being exhibited is changed from the accumulated aggregation results ,
The information processing apparatus according to any one of claims 1 to 5, wherein the providing unit proposes a recommended way of capturing image data based on the estimation result. The information processing apparatus according to claim 6, wherein the providing unit proposes a recommended change in color tone of the image data based on the estimation result. The information processing apparatus according to claim 6 or 7, wherein the providing unit proposes a recommended change in the layout of image data based on the estimation result. An information processing method executed by an information processing device, the method comprising:
an aggregation step of aggregating and accumulating changes in sales before and after changing the listing title for products previously listed in e-commerce;
an estimation step of estimating the sales before and after changing the listing title of the product being listed from the accumulated tabulation results ;
A provision process that proposes recommended listing titles based on the estimation results;
including;
In the estimation step, a model is constructed using the accumulated aggregation results as learning data, and the model is used to infer a more preferable listing title and changes in sales when changing the listing title.
An information processing method characterized by: an aggregation procedure for aggregating and accumulating changes in sales before and after a change in the listing title for products previously listed in e-commerce;
an estimation procedure for estimating the sales before and after changing the listing title of the product being listed from the accumulated aggregation results ;
A provision procedure for proposing recommended listing titles based on the estimation results;
An information processing program for causing a computer to execute
In the estimation procedure, a model is constructed using the accumulated aggregation results as learning data, and the model is used to infer a more preferable listing title and changes in sales when changing the listing title.
An information processing program characterized by :

Images