JP7410069B2 - Provision device, method and program - Google Patents

Description

The present invention relates to a providing device, a providing method, and a providing program.

Conventionally, techniques related to information distribution via the Internet have been provided. As an example of such a technique, a technique for transmitting a thank you message to a specified party is provided.

JP2019-101646A

However, with the above-mentioned technology, it is not always possible to provide an appropriate message depending on the purchasing behavior of the user.

For example, with the above-mentioned technology, messages of gratitude such as "Thank you" are only sent and received within an organization such as a company, and appropriate messages are not necessarily provided depending on the purchasing behavior of users.

The present application has been made in view of the above, and aims to provide appropriate messages according to the purchasing behavior of users.

The providing device according to the present application includes a detection unit that detects a purchase behavior related to a purchase of a transaction object of a user, and a message based on the context of the purchase behavior, in accordance with the purchase behavior detected by the detection unit. The invention is characterized by having a provision section that provides the information to users.

According to one aspect of the embodiment, it is possible to provide an appropriate message according to the purchasing behavior of the user.

FIG. 1 is a diagram illustrating an example of information provision processing according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information providing apparatus according to an embodiment. FIG. 3 is a diagram illustrating an example of a user information database according to the embodiment. FIG. 4 is a diagram illustrating an example of a transaction target information database according to the embodiment. FIG. 5 is a flowchart illustrating an example of the procedure of information provision processing according to the embodiment. FIG. 6 is a hardware configuration diagram showing an example of a computer that implements the functions of the information providing device.

DESCRIPTION OF THE PREFERRED EMBODIMENTS Below, a mode for implementing a providing apparatus, a providing method, and a providing program (hereinafter referred to as "embodiments") according to the present application will be described in detail with reference to the drawings. Note that the providing device, providing method, and providing program according to the present application are not limited by this embodiment. Further, in each of the embodiments below, the same parts are given the same reference numerals, and redundant explanations will be omitted.

[1. Embodiment]
The information providing process realized by the providing device and the like of this embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information provision processing according to an embodiment. Note that in FIG. 1, it is assumed that the information providing process according to the embodiment is realized by the information providing apparatus 10, which is an example of the providing apparatus according to the present application.

As shown in FIG. 1, the information providing system 1 according to the embodiment includes an information providing device 10 and a terminal device 100. The information providing device 10 and the terminal device 100 are connected to be able to communicate with each other by wire or wirelessly via a network N (for example, see FIG. 2). The network N is, for example, a WAN (Wide Area Network) such as the Internet. Note that the information providing system 1 shown in FIG. 1 may include a plurality of information providing apparatuses 10 and a plurality of terminal devices 100.

The information providing device 10 shown in FIG. 1 is an information processing device that performs information providing processing, and is realized by, for example, a server device, a cloud system, or the like. In the example of FIG. 1, the information providing device 10 manages information such as product information regarding transaction objects (products) and user information regarding users, and uses various services related to electronic commerce based on this information. provided to the person. In the example shown in FIG. 1, an example is shown in which the information providing device 10 provides a shopping service, which is an example of an electronic commerce service.

Note that the information providing device 10 may have a function as a web server that provides a website related to the service. Further, the information providing device 10 may be a device that delivers information to be displayed on an application related to various services installed on the terminal device 100 to the information providing device 10. Furthermore, the information providing device 10 may be a server that distributes application data itself.

Further, the information providing device 10 may function as a distribution device that distributes control information to the terminal device 100. Here, the control information is written in, for example, a script language such as JavaScript (registered trademark) or a style sheet language such as CSS (Cascading Style Sheets). Note that the application itself distributed from the information providing device 10 may be regarded as control information.

The terminal device 100 shown in FIG. 1 is an information processing device used by a user. The terminal device 100 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. Further, the terminal device 100 displays information distributed by the information providing device 10 using a web browser or an application. Note that the example shown in FIG. 1 shows a case where the terminal device 100 is a smartphone.

An example of the information providing process performed by the information providing device 10 will be described below with reference to FIG. Note that in the following description, it is assumed that the terminal device 100 is used by the user U1. Furthermore, in the following description, the terminal device 100 may be equated with the user U1. That is, below, the user U1 can also be read as the terminal device 100.

First, the information providing device 10 detects purchasing behavior related to the purchase of a product by a user in the shopping service provided by the information providing device 10 (step S1). For example, the information providing device 10 detects purchasing behavior such as operations related to registering products as favorites, posting product evaluations (reviews), adding products to a virtual cart in a shopping service, and purchasing products. . In the example of FIG. 1, it is assumed that the information providing apparatus 10 detects a purchase operation for product #1 by the user U1.

Next, the information providing device 10 extracts a message to be provided to the user U1 using the model M that has learned the relationship between the context of the purchasing behavior and the message to be provided to the user according to the purchasing behavior ( Step S2). For example, the information providing device 10 can provide information such as the content of the user's purchasing behavior, user information (e.g., demographic attributes, psychographic attributes, etc.), product information (e.g., category (concept)) of the product that is the target of the purchasing behavior. When the context of the purchase behavior is input, including information such as information such as information such as information, price, inventory, etc.), and the user's behavior history leading up to the purchase behavior (e.g., product information viewing history, product purchase history, etc.) , generates a model M trained to output a message that satisfies the user's desire for approval regarding purchasing behavior. Then, the information providing device 10 extracts a message to be provided to the user U1 by inputting the context of the purchasing behavior of the user U1 into the model M and causing the model M to output a message.

To give a specific example, the information providing device 10 provides the context of the purchasing behavior and a message group that satisfies the user's desire for approval regarding the purchasing behavior (for example, ``You bought a nice product'', ``As expected of you'', We conducted an AB test to identify the relationship between the customer and customers (e.g., "You finally bought it!"), and found that when the context of purchasing behavior was input, more positive reactions were obtained from users in the AB test. Model M is trained to output the determined message. Here, the information providing device 10 is configured to provide information such as when the review of the product or shopping service posted by the user to whom the message was provided is greater than or equal to a predetermined threshold, or when the user to whom the message was provided purchases the product again. It is determined that a positive response has been obtained from the user.

Subsequently, the information providing device 10 provides the message to the terminal device 100 and causes the message to be output (step S3). For example, the information providing device 10 provides the terminal device 100 with a message output from the model M, and causes the message to be displayed on a screen indicating that the purchase operation for product #1 has been completed.

Note that the information providing device 10 may display a message at the timing when the screen indicating that the purchase operation has been completed transitions to the top screen of the shopping service.

Subsequently, the information providing device 10 acquires behavior information of the user U1 after the message was provided (step S4). For example, the information providing device 10 acquires behavior information of the user U1 in a shopping service. To give a specific example, the information providing device 10 provides reviews posted by users regarding product #1, information indicating whether user U1 has purchased product #1 again, and information regarding product #1. Information indicating whether an operation for sharing with other users (for example, pressing a share button) has been performed in an SNS service or the like is acquired.

Subsequently, the information providing device 10 evaluates the message provided to the user U1 based on the acquired behavior information (step S5). For example, the information providing device 10 evaluates whether the user U1 is positive about the provided message. To give a specific example, if the review posted by the user regarding product #1 is greater than or equal to a predetermined threshold, or if user U1 purchases product #1 again, the information providing device 10 When the user U1 presses the share button for information regarding the message, the user U1 evaluates the provided message as positive.

Subsequently, the information providing device 10 causes the model M to learn the evaluation result of the message provided to the user U1 (step S6). For example, the information providing device 10 uses learning data such as an evaluation result indicating whether the user U was positive about the message provided to the user U1, product information of product #1, user information of the user U1, etc. Machine learning of model M is performed as follows.

Note that learning of the model M may be performed using various conventional techniques related to machine learning as appropriate. For example, the learning of the model M may be performed using a technique related to machine learning of supervised learning such as SVM (Support Vector Machine). Further, the learning of the model M may be performed using a technique related to machine learning of unsupervised learning. Further, learning of the model M may be performed using deep learning technology. Further, learning of the model M may be performed using various deep learning techniques such as DNN (Deep Neural Network), RNN (Recurrent Neural Network), and CNN (Convolutional Neural Network) as appropriate. Note that the above description regarding the learning of the model M is an example, and the learning of the model M may be performed by a learning method appropriately selected depending on obtainable information and the like.

Further, for example, the information providing device 10 may be trained to register a message in a dictionary and output the ID of the corresponding message when the context of purchasing behavior is input to the model M.

As described above, the information providing apparatus 10 according to the embodiment provides a message that satisfies the user's desire for approval in accordance with the user's purchasing behavior based on the context of the purchasing behavior. As a result, the information providing device 10 according to the embodiment can improve the user's purchasing behavior even in cases such as shopping in an e-commerce service, where there is no call from a store staff and the purchase behavior does not occur due to interaction with other people. By providing a message that praises (satisfies the desire for approval), it is possible to encourage the next conversion (new purchasing behavior, etc.). That is, the information providing device 10 according to the embodiment can provide an appropriate message depending on the user's purchasing behavior.

Furthermore, the information providing device 10 according to the embodiment can evaluate a user's behavior (reaction) to a provided message using a model, and perform machine learning of the model using the evaluation results. That is, the information providing device 10 according to the embodiment can improve the accuracy of messages provided according to the user's purchasing behavior.

[2. Specific example of message]
Here, in the example of FIG. 1, a specific example of a message provided by the information providing device 10 based on the context of the purchasing behavior of the user U1 will be described. For example, the information providing device 10 provides a message that understands the user U1's feelings leading up to the purchase of product #1 based on the context of purchasing behavior. To give a specific example, if user U1's product browsing history indicates that he or she has viewed multiple products in the same category as product #1 (in other words, if the user has selected and purchased from multiple products), The information providing device 10 provides a message such as "You chose this after comparing!". In addition, user U1's behavior history may indicate multiple times that he or she has placed product #1 in the shopping cart but has not made a purchase, or the user U1 may have viewed content showing product information for product #1 multiple times. (In other words, if you are thinking about purchasing product #1), the information providing device 10 provides a message such as "You finally bought it!". Furthermore, if the product browsing history of user U1 indicates that the user has not viewed any other products in the same category as product #1 (in other words, if the user has purchased the product without worrying), the information providing device 10 may indicate, "As expected. It provides a message such as "That's right."

Further, for example, the information providing device 10 provides a message that gives a sense of security and a sense of value for purchasing product #1 based on the context of the purchasing behavior. To give a specific example, if product #1 is a fresh food and you purchase it when product #1 is in season, the information providing device 10 will say, "Product #1 is in season now, and this year is a bumper crop. It looks like it's unusually sweet. Please enjoy it!'' Further, if the sales status of product #1 is good, the information providing device 10 provides messages such as "You bought a good product" and "It's selling now." Further, when the number of products #1 in stock is less than a predetermined threshold, the information providing device 10 provides a message such as "There are only N items left (N is the number of products #1 in stock)".

Further, for example, when product #1 is purchased at a discount price that is discounted from a predetermined price (for example, suggested retail price), the information providing device 10 provides a message that gives a sense of value in accordance with the discount price. do. To give a specific example, when product #1 is purchased at a discounted price, the information providing device 10 provides messages such as "You got a good deal!", "You got a cheap price!", etc. Furthermore, if the user purchases product #1 at the time when product #1 is the cheapest within a predetermined period, the information providing device 10 provides a message such as "This is the cheapest price in the past few days!" Further, if there are multiple providers (stores) that sell product #1 and product #1 is purchased from the provider that sells product #1 at the lowest discount price, the information providing device 10 may It's the cheapest!" and so on.

Note that the information providing device 10 may provide a message not only on the screen indicating that the purchase operation for product #1 has been completed, but also at the timing when various purchasing behaviors of the user U1 are detected. For example, the information providing device 10 may provide a message that gives a sense of security and a sense of value for purchasing the product #1 at the timing when the user U1 registers the product #1 as a favorite or when the user U1 adds the product to the cart. . To give a specific example, the information providing device 10 may display items such as ``You have great taste!'' and ``Not many items have been added in the past few days'' when the user U1 registers item #1 as a favorite or adds it to the cart. It's the cheapest!" and so on. Further, the information providing device 10 provides a message at a timing when product #1 is registered as a favorite for a predetermined number of times or more, or at a timing when content indicating product information for product #1 is viewed for a predetermined number of times or more.

Further, the information providing device 10 may provide the message at a timing when the context of the user U1's purchasing behavior satisfies a predetermined condition after various purchasing behaviors of the user U1 are detected. For example, the information providing device 10 determines the timing when the number of sales of product #1 exceeds a predetermined threshold after user U1 purchases it, or when another user's evaluation of product #1 after user U1 purchases a predetermined timing. At the timing when the threshold value is exceeded, a message (for example, "You bought a good product") that gives a sense of security regarding the purchase of product #1 is provided to the user U1. In addition, the information providing device 10 determines that the purchasing behavior of the user U1 is correct for a product that has a predetermined relationship with the product #1 (for example, a product that was purchased together with the product #1 by users equal to or higher than a predetermined threshold). At the detected timing, a message praising the purchasing behavior of the user U1 (for example, "You have good taste!") is provided. Furthermore, after the user U1 views content showing product information for product #1 or registers product #1 as a favorite, the information providing device 10 displays product #1 at the timing when product #1 is in season. A message (for example, "Now is the season") that gives a sense of value for the purchase of item 1 is provided.

Further, the information providing device 10 may provide the message at a timing when a predetermined period has elapsed after various purchasing behaviors of the user U1 are detected. For example, after a predetermined period has elapsed since the user U1 purchased product #1, the information providing device 10 provides a message based on the number of sales of product #1 in a predetermined period. In addition, the information providing device 10 is configured to provide information after a predetermined period of time has elapsed since the user U1 viewed the content showing the product information of the product #1 or registered the product #1 as a favorite (in other words, the user U1 The message is provided at a time when it is assumed that the customer has forgotten about the existence of product #1.

The information providing device 10 also sends messages set by the provider of the product #1 (for example, the manager of the store that sells the product #1, the manufacturer of the product #1, etc.) A message or the like based on the posted review (for example, the reason for purchasing the product) may be provided. For example, the information providing device 10 provides a message input by the provider, a message selected by the provider from among the messages presented to the provider by the information providing device 10, and the like. In addition, the information providing device 10 provides a message indicating that a predetermined profit (coupon, etc.) has been given to the user U1 from the provider of the product #1 in accordance with the purchasing behavior.

[3. Configuration of information providing device]
Next, the configuration of the information providing device 10 will be explained using FIG. 2. FIG. 2 is a diagram illustrating a configuration example of an information providing apparatus according to an embodiment. As shown in FIG. 2, the information providing device 10 includes a communication section 20, a storage section 30, and a control section 40.

(About the communication department 20)
The communication unit 20 is realized by, for example, a NIC (Network Interface Card). The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the terminal device 100 and the like.

(About the storage unit 30)
The storage unit 30 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 a hard disk or an optical disk. As shown in FIG. 2, the storage unit 30 includes a user information database 31, a transaction object information database 32, and a model database 33.

(About the user information database 31)
The user information database 31 stores various information regarding users who use the electronic commerce service provided by the information providing device 10. Here, an example of information stored in the user information database 31 will be explained using FIG. 3. FIG. 3 is a diagram illustrating an example of a user information database according to the embodiment. In the example of FIG. 3, the user information database 31 has items such as "user ID", "attribute", and "behavior history".

"User ID" indicates identification information for identifying a user. "Attribute" indicates the user's attributes (for example, demographic attributes, psychographic attributes, etc.). "Action history" indicates the action history of the user in the electronic payment service provided by the information providing device 10, and stores information such as a viewing history of transaction object information and a purchase history of transaction object information.

That is, FIG. 3 shows an example in which the attribute of the user identified by the user ID "UID #1" is "Attribute #1" and the behavior history is "Action History #1."

(About transaction target information database 32)
The transaction object information database 32 stores various information regarding transaction objects in the electronic commerce service provided by the information providing device 10. Here, an example of information stored in the transaction target information database 32 will be explained using FIG. 4. FIG. 4 is a diagram illustrating an example of a transaction target information database according to the embodiment. In the example of FIG. 4, the transaction object information database 32 has items such as "transaction object ID,""providerID,""category,""price,""inventory,""salesstatus," and "evaluation information." .

“Transaction object ID” indicates identification information for identifying a transaction object. “Provider ID” indicates identification information for identifying the provider of the transaction target. “Category” indicates the category of the transaction object. "Price" indicates a predetermined price (suggested retail price, etc.) for the transaction object, a discounted price, or the like. “Stock” indicates the stock of the transaction object. “Sales status” indicates the sales status of the transaction object. “Evaluation information” indicates evaluation information posted by users etc. regarding the transaction object.

That is, in FIG. 4, the transaction object identified by the transaction object ID "PID #1" is provided by the provider identified by the provider ID "SID #1", belongs to the category "Category #1", and has a price An example is shown in which the item is "Price #1", the inventory is "Inventory #1", the sales status is "Sales status #1", and the evaluation information is "Evaluation information #1".

Note that the transaction object information database 32 may further store information such as the best season for the transaction object, the design of the transaction object (for example, an image of the transaction object), etc., as the transaction object information.

(About model database 33)
The model database 33 stores a model that outputs a message that satisfies the user's desire for approval regarding the purchasing behavior when the context of the purchasing behavior is input.

(About the control unit 40)
The control unit 40 is a controller, and various programs stored in the storage device inside the information providing device 10 use the RAM as a work area by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). This is achieved by executing as . Further, the control unit 40 is a controller, and is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in FIG. 2, the control unit 40 according to the embodiment includes a detection unit 41, a provision unit 42, an acquisition unit 43, an evaluation unit 44, and a learning unit 45, and performs information processing described below. To realize or carry out the functions and actions of

(About the detection unit 41)
The detection unit 41 detects purchase behavior related to the purchase of a transaction object by a user. For example, in the example of FIG. 1, the detection unit 41 detects the purchasing behavior of the user in the shopping service provided by the information providing device 10.

Furthermore, the detection unit 41 may detect purchasing behavior that indicates that a predetermined operation has been performed on a transaction object in an electronic commerce service. For example, in the example of FIG. 1, the detection unit 41 detects that an operation related to registering a product as a favorite or posting of a product review has been performed.

Furthermore, the detection unit 41 may detect purchasing behavior that indicates that an operation of inserting a transaction object into a virtual cart in an electronic commerce service has been performed. For example, in the example shown in FIG. 1, the detection unit 41 detects an operation of inserting a product into a virtual cart in a shopping service.

Furthermore, the detection unit 41 may detect purchase behavior indicating that a user has purchased a transaction object in an electronic commerce service. For example, in the example of FIG. 1, the detection unit 41 detects a purchase operation for product #1 by the user U1.

Furthermore, the detection unit 41 may detect purchasing behavior regarding a predetermined combination of transaction objects. For example, the detection unit 41 detects purchasing behavior regarding a combination of products purchased by users equal to or higher than a predetermined threshold. When such purchasing behavior is detected, the providing unit 42, which will be described later, provides a message (for example, "You have great taste!") that satisfies the user's desire for approval.

Note that when the user performs various operations, a button or the like is clicked and new content is provided. It may also be possible to identify (that is, detect) what kind of purchasing behavior was carried out in response to the incident.

(About the providing section 42)
In accordance with the purchasing behavior detected by the detection unit 41, the providing unit 42 provides the user with a message based on the context of the purchasing behavior. For example, in the example of FIG. 1, the providing unit 42 provides a message that satisfies the user U1's desire for approval regarding purchasing behavior.

Further, the providing unit 42 may provide messages based on purchasing behavior related to purchases of transaction objects by other users. For example, in the example of FIG. 1, the providing unit 42 provides a message that gives a sense of security and a sense of value for purchasing product #1, based on the purchasing behavior of other users regarding product #1.

Further, the providing unit 42 may provide a message based on a review posted for the transaction target. For example, in the example of FIG. 1, the providing unit 42 provides a message based on a review posted for product #1.

Further, the providing unit 42 may provide a message based on user information regarding the user. For example, in the example of FIG. 1, the providing unit 42 refers to the user information database 31 and provides a message based on the demographic attributes, psychographic attributes, etc. of the user U1. Further, in the example of FIG. 1, the providing unit 42 refers to the user information database 31 and provides a message based on the user U1's behavior history including the product information browsing history, product purchase history, and the like.

Note that the providing unit 42 may provide messages based on the user's emotions. For example, the providing unit 42 may determine the time from when a transaction object is placed in the cart until the purchase, the content of the user's operation on the terminal device 100 (for example, the scrolling speed of content, the strength of the tap, etc.), the wearable It provides messages based on the user's emotions estimated from the user's biometric information obtained from the device, content viewed by the user, etc.

Further, the providing unit 42 may provide a message based on transaction object information regarding the transaction object. For example, in the example of FIG. 1, the providing unit 42 refers to the transaction object information database 32 and provides a message based on the product information of the product that is the object of the user U1's purchasing behavior.

Further, the providing unit 42 may provide a message based on the discount price at which the user purchased the transaction object. For example, in the example of FIG. 1, the providing unit 42 provides a message that gives a sense of value in accordance with the discount price of product #1.

Further, the providing unit 42 may provide a message based on information regarding the inventory of the transaction object when the user purchases the transaction object. For example, in the example of FIG. 1, the providing unit 42 provides a message based on the sales status, inventory quantity, etc. of product #1.

Further, the providing unit 42 may provide a message set by the provider of the transaction object. For example, in the example of FIG. 1, the providing unit 42 provides a message set by the provider of product #1.

Further, the providing unit 42 may provide a message including information regarding a predetermined benefit given to the user by the provider. For example, in the example of FIG. 1, the providing unit 42 provides a message indicating that a predetermined profit has been given to the user U1 from the provider of the product #1 in accordance with the purchasing behavior.

Further, the providing unit 42 may provide a message based on the user's actions up to the purchase action. For example, in the example of FIG. 1, the providing unit 42 may indicate that the user U1's product browsing history indicates that he or she has viewed multiple products in the same category as product #1, or that the user U1's behavior history indicates that If you put product #1 in the shopping cart and then indicate multiple times that you did not purchase it, or if you viewed content showing product information for product #1 multiple times, you will end up purchasing product #1. Provides a message that understands the feelings of the user U1.

Further, the providing unit 42 may provide the message at a timing depending on the context. For example, in the example of FIG. 1, the providing unit 42 provides a message at a timing when the context of the user U1's purchasing behavior satisfies a predetermined condition after various purchasing behaviors of the user U1 are detected.

Further, the providing unit 42 may provide the message at a timing based on transaction object information regarding the transaction object. For example, in the example of FIG. 1, the providing unit 42 determines the timing when the number of sales of product #1 exceeds a predetermined threshold after purchase by user U1, At the timing when the evaluation of product #1 becomes equal to or higher than a predetermined threshold, a message giving a sense of security about purchasing product #1 is provided to user U1.

Further, the providing unit 42 may provide a message to be output on a screen displayed on a terminal device used by the user depending on the purchasing behavior. For example, in the example of FIG. 1, the providing unit 42 provides a message displayed on the screen indicating that the purchase operation for product #1 has been completed.

Note that the providing unit 42 displays information on the screen when various purchasing actions are performed, such as an operation related to registering a product as a favorite or an operation of adding a product to a virtual cart in a posting shopping service (product evaluation). Messages may also be provided. Further, the providing unit 42 may cause the terminal device 100 to output the message to be provided as a voice. For example, the providing unit 42 provides a message that is output as a voice, such as an avatar displayed on the terminal device 100.

The providing unit 42 also provides a message that is provided to the user in accordance with the purchase behavior related to the purchase of the transaction target by the user, and that the message is used after the message is provided based on the context of the purchase behavior. The message may be provided to the user using a model that has been trained to evaluate the message based on the user's behavior information. For example, to explain with reference to FIG. Provided to.

(About the acquisition unit 43)
The acquisition unit 43 acquires a message that is provided to the user in accordance with the purchase behavior related to the purchase of the transaction object of the user, and that is a message that is provided to the user after the message based on the context of the purchase behavior is provided. Obtain behavioral information. For example, in the example of FIG. 1, the acquisition unit 43 acquires behavior information of the user U1 in the shopping service after the message is provided.

(About the evaluation section 44)
The evaluation unit 44 evaluates the message based on the behavior information acquired by the acquisition unit 43. For example, the evaluation unit 44 evaluates the user's reaction to the provided message.

Furthermore, the evaluation unit 44 may evaluate whether the user is positive about the message. For example, in the example of FIG. 1, the evaluation unit 44 evaluates whether the user U1 is positive about the provided message.

Further, the evaluation unit 44 may evaluate that the user is positive about the message when the user visits a site corresponding to a provider that provides a transaction object. For example, to explain using FIG. 1 as an example, when the user U1 revisits the site of the provider that provides product #1 in the shopping service, the evaluation unit 44 determines that the user U1 confirms the message in response to the message. Evaluate it as being accurate.

Further, the evaluation unit 44 may evaluate that the user is positive about the message if the evaluation posted by the user for the provider that provides the transaction object is equal to or higher than a predetermined threshold. . For example, to explain using FIG. 1 as an example, if the user U1's evaluation of the provider of product #1 is equal to or higher than a predetermined threshold, the evaluation unit 44 determines that the user U1 is positive in response to the message. It is evaluated that

Furthermore, if the user purchases the transaction object again, the evaluation unit 44 may evaluate that the user is positive about the message. For example, in the example of FIG. 1, if the user U1 purchases product #1 again, the evaluation unit 44 evaluates that the user U1 is positive about the message.

Moreover, the evaluation unit 44 may evaluate that the user is positive about the message if the evaluation posted by the user for the transaction object is equal to or higher than a predetermined threshold. For example, in the example of FIG. 1, if the review posted by the user regarding product #1 is greater than or equal to a predetermined threshold, the evaluation unit 44 evaluates that the user U1 is positive about the message.

In addition, if the user performs an operation to share information regarding the transaction object with other users in an electronic commerce service that provides the transaction object, the evaluation unit 44 evaluates whether the user responds positively to the message. It may be evaluated that For example, in the example of FIG. 1, the evaluation unit 44 determines that if user U1 purchases product #1 again, if user U1 presses the share button for information regarding product #1, if user U1 Rate it as positive.

Furthermore, the evaluation unit 44 may evaluate whether the user is positive about the message based on information input by the user regarding the content for accepting evaluation of the message. For example, the evaluation unit 44 provides the user with content for inputting the user's feelings and state of mind when receiving the message, and evaluates the message based on the information input to the content.

(About learning section 45)
The learning unit 45 causes the model to learn the evaluation results by the evaluation unit 44. For example, in the example of FIG. 1, the learning unit 45 performs machine learning on the model M using, as learning data, an evaluation result indicating whether the user U was positive about the message provided to the user U1.

Further, the learning unit 45 may learn a model for each user information regarding the user. For example, the learning unit 45 uses the evaluation result of a message and user information about the user who provided the message as learning data, and determines what kind of message to provide to the user associated with what kind of user information. The model learns how to obtain more positive evaluations by doing so.

Further, the learning unit 45 may learn a model for each user attribute. For example, the learning unit 45 uses the evaluation result of a message and the attributes of the user who provided the message as learning data, and determines what kind of message should be provided to the user with what attributes to make it more positive. Train the model to see if it can be evaluated.

Further, the learning unit 45 may learn the model for each behavior of the user up to purchase behavior. For example, the learning unit 45 uses the evaluation results of the message and the actions of the user who provided the message up to the purchasing action (for example, browsing history, purchase history, etc.) as learning data, and determines what actions to take. The model learns what kind of messages to provide to selected users to get more positive evaluations.

Further, the learning unit 45 may learn a model for each user's emotion when a message is provided. For example, the learning unit 45 uses the evaluation result of a message and the user's emotion when providing the message as learning data, and determines what kind of message should be provided to the user with what kind of emotion to make it more positive. The model learns whether it can obtain a certain evaluation. To give a specific example, the learning unit 45 learns the time from when a transaction object is placed in the cart until the purchase, the user's operation details on the terminal device 100, the user's information obtained from the wearable device, etc. The model uses the user's emotions estimated from biometric information, content viewed by the user, etc. as learning data.

Further, the learning unit 45 may learn the model for each transaction object information regarding the transaction object. For example, the learning unit 45 uses the message evaluation results and the transaction object information regarding the transaction object that is the target of the purchasing behavior as learning data, and the learning unit 45 uses the message evaluation result and the transaction object information regarding the transaction object that is the target of the purchasing behavior as learning data, and determines which transaction object the user has performed the purchasing behavior for. The model learns whether providing such messages will result in more positive evaluations.

Further, the learning unit 45 may learn the model for each sales situation of the transaction target. For example, the learning unit 45 uses the message evaluation results and the sales status of the transaction target, which is the target of purchasing behavior, as learning data, and determines what kind of message should be provided in what kind of sales situation to make it more positive. The model learns whether it can obtain a good evaluation.

Further, the learning unit 45 may learn the model for each quantity of inventory to be traded. For example, the learning unit 45 uses the message evaluation result and the inventory quantity of the transaction object that is the target of purchasing behavior as learning data, and determines what kind of message should be provided for what inventory quantity to make it more positive. The model learns whether it can obtain a good evaluation.

Further, the learning unit 45 may learn a model for each category of transaction object. For example, the learning unit 45 uses the message evaluation results and the category of the transaction object that is the target of purchasing behavior as learning data, and determines what kind of message should be provided for what kind of category to obtain a more positive evaluation. Let the model learn whether it can obtain the desired results.

[4. Information provision processing flow]
The procedure of the information providing process of the information providing device 10 according to the embodiment will be explained using FIG. 5. FIG. 5 is a flowchart illustrating an example of the procedure of information provision processing according to the embodiment.

As shown in FIG. 5, the information providing device 10 determines whether purchasing behavior has been detected (step S101). When purchasing behavior is not detected (step S101; No), the information providing device 10 waits until purchasing behavior is detected.

On the other hand, when purchasing behavior is detected (step S101; Yes), the information providing device 10 uses the model to provide the user with a message based on the context of the purchasing behavior (step S102). Subsequently, the information providing device 10 acquires behavior information of the user after the message is provided (step S103). Subsequently, the information providing device 10 evaluates the message based on the behavior information (step S104). Subsequently, the information providing device 10 causes the model to learn the evaluation results (step S105), and ends the process.

[5. Modified example]
The embodiments described above are merely examples, and various modifications and applications are possible.

[5-1. About transaction information〕
In the above-described embodiment, an example was given in which the providing unit 42 provides a message based on the transaction object information indicating the transaction object category, price, inventory, sales status, etc. The information is not limited, and may be any information that can be obtained regarding the transaction object.

[5-2. Regarding processing mode]
Among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, and conversely, all of the processes described as being performed manually can be performed manually. Alternatively, some of the steps can be performed automatically using known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above text 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.

Further, 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.

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

[6. effect〕
As described above, the information providing apparatus 10 according to the embodiment includes the detection section 41, the provision section 42, the acquisition section 43, the evaluation section 44, and the learning section 45. The detection unit 41 detects purchase behavior related to the purchase of a transaction object by a user. In accordance with the purchasing behavior detected by the detection unit 41, the providing unit 42 provides the user with a message based on the context of the purchasing behavior. The providing unit 42 also provides a message that is provided to the user in accordance with the purchase behavior related to the purchase of the transaction target by the user, and that the message is used after the message is provided based on the context of the purchase behavior. The message is provided to the user using a model trained on the evaluation results of the message based on the user's behavior information. The acquisition unit 43 acquires a message that is provided to the user in accordance with the purchase behavior related to the purchase of the transaction object of the user, and that is a message that is provided to the user after the message based on the context of the purchase behavior is provided. Obtain behavioral information. The evaluation unit 44 evaluates the message based on the behavior information acquired by the acquisition unit 43. The learning unit 45 causes the model to learn the evaluation results by the evaluation unit 44.

As a result, the information providing device 10 according to the embodiment can improve the user's purchasing behavior even in cases such as shopping in an e-commerce service, where there is no call from a store staff and the purchase behavior does not occur due to interaction with other people. By providing a message that compliments the user, it is possible to encourage further conversion, so it is possible to provide an appropriate message according to the user's purchasing behavior. In addition, the information providing device 10 according to the embodiment can evaluate the user's behavior in response to the provided message using the model, and perform machine learning of the model using the evaluation results. It is possible to improve the accuracy of messages provided according to actions.

Furthermore, in the information providing device 10 according to the embodiment, for example, the detection unit 41 detects purchasing behavior that indicates that a predetermined operation has been performed on a transaction object in an electronic commerce service. Furthermore, the detection unit 41 detects purchasing behavior that indicates that an operation of inserting a transaction object into a virtual cart in an electronic commerce service has been performed. Furthermore, the detection unit 41 detects purchasing behavior indicating that a user has purchased a transaction object in an electronic commerce service. Furthermore, the detection unit 41 detects purchasing behavior regarding a predetermined combination of transaction objects.

As a result, the information providing device 10 according to the embodiment can provide appropriate messages according to various purchasing behaviors of users, and thus can improve user satisfaction with electronic commerce services.

Further, in the information providing device 10 according to the embodiment, for example, the providing unit 42 provides a message based on purchasing behavior related to the purchase of a transaction object by another user. Further, the providing unit 42 provides a message based on a review posted for the transaction target. Further, the providing unit 42 provides a message based on user information regarding the user. Further, the providing unit 42 provides a message based on transaction object information regarding the transaction object. Further, the providing unit 42 provides a message based on the discount price at which the user purchased the transaction object. Further, the providing unit 42 provides a message based on information regarding the stock of the transaction object when the user purchases the transaction object. Further, the providing unit 42 provides a message set by the provider of the transaction object. Further, the providing unit 42 provides a message including information regarding a predetermined benefit given to the user by the provider. Further, the providing unit 42 provides messages based on the user's actions up to the purchasing action. Further, the providing unit 42 provides messages at timings depending on the context. Further, the providing unit 42 provides messages at timings based on transaction object information regarding transaction objects. Further, the providing unit 42 provides a message to be output on a screen displayed on a terminal device used by the user according to the purchasing behavior.

Thereby, the information providing device 10 according to the embodiment can provide an appropriate message at an appropriate timing based on the context of the user's purchasing behavior, thereby improving user satisfaction with the e-commerce service. be able to.

Further, in the information providing device 10 according to the embodiment, for example, the evaluation unit 44 evaluates whether the user is positive about the message. Furthermore, when the user visits a site corresponding to a provider that provides a transaction object, the evaluation unit 44 evaluates that the user is positive about the message. Furthermore, if the evaluation posted by the user on the provider of the transaction object is equal to or higher than a predetermined threshold, the evaluation unit 44 evaluates the message as positive by the user. Furthermore, if the user purchases the transaction object again, the evaluation unit 44 evaluates that the user is positive about the message. Furthermore, if the evaluation posted by the user for the transaction object is equal to or higher than a predetermined threshold, the evaluation unit 44 evaluates that the user is positive about the message. In addition, if the user performs an operation to share information regarding the transaction object with other users in an electronic commerce service that provides the transaction object, the evaluation unit 44 evaluates whether the user responds positively to the message. It is evaluated that Furthermore, the evaluation unit 44 evaluates whether the user is positive about the message based on the information input by the user regarding the content for accepting the evaluation of the message.

Thereby, the information providing apparatus 10 according to the embodiment can appropriately evaluate the message provided to the user and perform model learning, thereby improving the accuracy of the model.

Furthermore, in the information providing device 10 according to the embodiment, for example, the learning unit 45 learns a model for each user information regarding a user. Further, the learning unit 45 trains a model for each user attribute. Further, the learning unit 45 causes the model to be trained for each behavior of the user up to the purchase behavior. Furthermore, the learning unit 45 trains a model for each user's emotion when a message is provided. Further, the learning unit 45 causes the model to learn for each transaction object information regarding the transaction object. Further, the learning unit 45 trains the model for each sales situation of the transaction object. Further, the learning unit 45 trains the model for each quantity of inventory to be traded. Further, the learning unit 45 causes the model to be trained for each category of transaction object.

As a result, the information providing device 10 according to the embodiment can learn the model for each context of purchasing behavior and output an appropriate message for each context, thereby improving user satisfaction with e-commerce services. can be done.

[7. Hardware configuration]
Further, the information providing apparatus 10 according to each of the embodiments described above is realized by, for example, a computer 1000 having a configuration as shown in FIG. The information providing device 10 will be described below as an example. FIG. 6 is a hardware configuration diagram showing an example of a computer that implements the functions of the information providing device. Computer 1000 has CPU 1100, ROM 1200, RAM 1300, HDD 1400, communication interface (I/F) 1500, input/output interface (I/F) 1600, and media interface (I/F) 1700.

CPU 1100 operates based on a program stored in ROM 1200 or HDD 1400, and controls each part. The ROM 1200 stores a boot program executed by the CPU 1100 when the computer 1000 is started, programs depending on the hardware of the computer 1000, and the like.

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. Communication interface 1500 receives data from other devices via communication network 500 (corresponding to network N in the embodiment) and sends it to CPU 1100, and also sends data generated by CPU 1100 to other devices via communication network 500. Send to device.

The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and mouse via an input/output interface 1600. CPU 1100 obtains data from an input device via input/output interface 1600. Further, CPU 1100 outputs the generated data to an output device via input/output interface 1600.

Media interface 1700 reads programs or data stored in recording medium 1800 and provides them to CPU 1100 via RAM 1300. CPU 1100 loads this program from recording medium 1800 onto RAM 1300 via media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. etc.

For example, when the computer 1000 functions as the information providing device 10, the CPU 1100 of the computer 1000 realizes the functions of the control unit 40 by executing a program loaded onto the RAM 1300. Further, each data in the storage device of the information providing device 10 is stored in the HDD 1400. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired from another device via a predetermined communication network.

[8. others〕
Some of the embodiments of the present application have been described above in detail based on the drawings, but these are merely examples, and various modifications and variations may be made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure section of the invention. It is possible to carry out the invention in other forms with modifications.

Further, the configuration of the information providing apparatus 10 described above can be changed flexibly, such as implementing some functions by calling an external platform or the like using an API (Application Programming Interface), network computing, or the like.

Further, the "unit" described in the claims can be read as "means", "circuit", etc. For example, the detection section can be read as a detection means or a detection circuit.

10 information providing device 20 communication unit 30 storage unit 31 user information database 32 transaction target information database 33 model database 40 control unit 41 detection unit 42 provision unit 43 acquisition unit 44 evaluation unit 45 learning unit 100 terminal device

Claims (16)

a detection unit that detects purchasing behavior indicating that a user has purchased a transaction object in the e-commerce service;
The context of the purchasing behavior detected by the detection unit is input to a model that has been trained to output a message according to the purchasing behavior when the context of the purchasing behavior is input, and the message output from the model is output. A providing device comprising: a providing unit that provides transaction object information regarding the transaction object to the user at a timing when a predetermined condition is satisfied. The detection unit is
The providing device according to claim 1, wherein the providing device detects the purchasing behavior indicating that a predetermined operation has been performed on the transaction object in an electronic commerce service. The detection unit is
The providing device according to claim 1 or 2, further comprising: detecting the purchasing behavior indicating that an operation of inserting the transaction object into a virtual cart in an electronic commerce service is performed. The provision department is
The providing device according to any one of claims 1 to 3, wherein the providing device provides the message based on a review posted for the transaction object. The provision department is
Provision according to any one of claims 1 to 4, characterized in that the context further indicating user information about the user is input into the model and the message output from the model is provided. Device. The provision department is
Any one of claims 1 to 5, characterized in that the context further indicating a discount price at which the user purchased the transaction object is input into the model, and the message output from the model is provided. The providing device according to any one of the above. The provision department is
2. The method further comprises inputting the context into the model, which further indicates information regarding the inventory of the transaction object at the time the user purchased the transaction object , and providing the message output from the model. 6. The providing device according to any one of 6 to 6. The provision department is
8. The method according to claim 1 , further comprising inputting the context into the model and providing the message set by the provider of the transaction object, which is output from the model. providing equipment. The provision department is
The providing device according to claim 8, wherein the providing device provides the message including information regarding a predetermined benefit given to the user by the provider. The detection unit is
The providing device according to any one of claims 1 to 9, wherein the purchasing behavior regarding a predetermined combination of the transaction objects is detected. The provision department is
Any one of claims 1 to 10, characterized in that the context further indicating the user's behavior leading up to the purchasing behavior is input into the model, and the message output from the model is provided. The provision device described in . The provision department is
A message provided to a user in response to purchase behavior related to the purchase of the transaction object of the user, based on behavioral information of the user after the message is provided based on the context of the purchase behavior. Any one of claims 1 to 11, characterized in that the context is input to the model that has learned an evaluation result of evaluating the message, and the message output from the model is provided to the user. The providing device according to item 1. The provision department is
The providing device according to any one of claims 1 to 12, wherein the message is provided at a timing according to the context. The provision department is
14. The providing device according to claim 1, wherein the message is provided to be output on a screen displayed on a terminal device used by the user in accordance with the purchasing behavior. A providing method executed by a computer, comprising:
a detection step of detecting purchasing behavior indicating that a user has purchased a transaction object in the e-commerce service;
The context of the purchasing behavior detected in the detection step is input to a model that has been trained to output a message according to the purchasing behavior when the context of the purchasing behavior is input, and the message output from the model is output. and a providing step of providing transaction object information regarding the transaction object to the user at a timing when a predetermined condition is satisfied. a detection procedure for detecting purchasing behavior indicating that a user has purchased a transaction object in an e-commerce service;
A model that has been trained to output a message according to the purchasing behavior when the context of the purchasing behavior is input is inputted with the context of the purchasing behavior detected by the above detection procedure, and the message output from the model is output. A providing program that causes a computer to execute the following steps: 1. A providing procedure for providing transaction object information to the user at a timing when transaction object information regarding the transaction object satisfies a predetermined condition.

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