Information providing device, information providing method, and information providing program

Abstract

To provide personalized recommended information to a customer.SOLUTION: An information providing device includes an acquisition unit that acquires product information on a first product used by a user, a determination unit that determines a recommendation time to make a recommendation on maintenance and inspection of the product information based on a first attribute to which the user belongs, and a notification unit that notifies a recommendation on the product information at the determined recommendation time.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information providing device, an information providing method, and an information providing program. [Background technology]

[0002] For customers who operate plants and various systems constantly, it is extremely important that products can continue to be used appropriately and that replacement, etc., can be considered at the appropriate time. For example, product vendors and manufacturers send information on maintenance and inspection as recommendations based on the customer's usage plan and vendor-derived data, and customers can refer to the recommended information to check information on maintenance and inspection, such as when to replace the product. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-106653 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in conventional technologies, recommendation information regarding product maintenance and inspections has been provided uniformly depending on the product, which has made it difficult to provide personalized recommendation information, which is what customers want.

[0005] The present invention has been made in view of the above, and has an object to provide personalized recommendation information to customers. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the information providing device of the present invention is characterized by having an acquisition unit that acquires product information regarding a first product used by a user, a determination unit that determines a recommendation time for making recommendations regarding maintenance and inspection of the product information based on a first attribute to which the user belongs, and a notification unit that notifies the recommendation regarding the product information at the determined recommendation time.

[0007] In order to solve the above-mentioned problems and achieve the objective, the information providing method of the present invention is characterized in that a computer executes a process of acquiring product information regarding a first product used by a user, determining a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs, and notifying the recommendation regarding the product information at the determined recommendation time.

[0008] In order to solve the above-mentioned problems and achieve the objective, the information provision program of the present invention is characterized in that it causes a computer to execute the following process: acquire product information regarding a first product used by a user; determine a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs; and notify the recommendation regarding the product information at the determined recommendation time.

[0009] According to the present invention, there is an effect that personalized recommendation information can be provided to customers. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an information providing system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of processing performed by the information providing system according to the embodiment. [Figure 3] FIG. 3 is a block diagram illustrating an example of the configuration of an information providing system according to the embodiment. [Figure 4]FIG. 4 is a diagram illustrating a change in the recommendation timing based on industry information of the information providing device according to the first embodiment. [Figure 5] FIG. 5 is a diagram illustrating the number of times that a user of the information providing device according to the first embodiment exchanges a product. [Figure 6] FIG. 6 is a diagram illustrating the actual usage period of a product by a user of the information providing device according to the first embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of a flow of a recommendation content determination process performed by the information providing device according to the first embodiment. [Figure 8] FIG. 8 is a diagram illustrating a specific flow of recommendation by the information providing device according to the first embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a processing result of the information providing apparatus according to the first embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of an application of the information providing device according to the first embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of a flowchart illustrating a process flow of the information providing device according to the first embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of a flowchart illustrating a process flow of determining a recommendation timing in the information providing device according to the first embodiment. [Figure 13] FIG. 2 is a diagram illustrating an example of a hardware configuration according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] (Explanation of recommendation status and areas for improvement) For customers (users) who operate plants constantly, it is extremely important to continue using products properly. Therefore, users consider product maintenance and inspection based on reports based on maintenance and inspection reports and system recommendations.

[0012] Traditionally, information on product replacement times has been provided to users based on business negotiations with sales representatives and proposals from maintenance and inspection reports. However, users are increasingly demanding more advanced personalized recommendations. To meet user needs, manufacturers provide not only simple information on product specifications and performance, but also information related to the maintenance and inspections desired by the user. Furthermore, manufacturers can learn about the user's situation and provide information at the appropriate time. There is a need for a recommendation system that can provide this kind of information.

[0013] An information providing system 100 that enables such information provision will be described with reference to the drawings.

[0014] An information providing device, an information providing method, and an information providing program according to an embodiment of the present invention will be described in detail below with reference to the accompanying drawings. Note that the present invention is not limited to the embodiment described below.

[0015] The following describes the configuration and processing of the information providing system 100 according to the embodiment, the configuration and processing of each device of the information providing system 100, the processing flow of the information providing device, and the effects of the embodiment.

[0016] (Configuration and processing of information provision system) First, the overall configuration of an information provision system according to the present invention will be described. Fig. 1 is a diagram showing an example of the overall configuration of an information provision system according to an embodiment. As shown in Fig. 1, an information provision system 100 according to the present invention is communicably connected to an information provision device 1 that generates recommendations, an external database 200, and a user terminal 300 operated by a customer, and executes a recommendation service that provides product recommendations to users.

[0017] The user terminal 300 is a computer used by a user who is a customer, and uses the recommendation service provided by the information providing system 100. For example, the user terminal 300 transmits product information, a usage plan, etc. set by the user to the information providing device 1. The user terminal 300 also receives and displays recommendations generated by the information providing device 1. The user receives the recommendations and requests product maintenance, etc. For example, the user terminal 300 may be able to access a member-only website (customer portal) of the recommendation service, allowing the user to set information on the member-only website, check recommendations, and request product maintenance, etc.

[0018] The information providing device 1 is an example of a computer that executes a recommendation service, and makes recommendations regarding product maintenance, etc. to users. For example, the information providing device 1 receives information such as product information and usage plans set by the user and registers it in the external database 200. The information providing device 1 also acquires data necessary for generating recommendations from the external database 200, analyzes the acquired data, and generates recommendations. The information providing device 1 also acquires data necessary for determining the timing of recommendations from the external database 200 and determines the timing of recommendations. The information providing device 1 transmits the generated recommendations at an appropriate time. Furthermore, the information providing device 1 registers the user's reactions to the recommendations (maintenance requests, etc.) in the external database 200.

[0019] The external database 200 accumulates data transmitted from the information providing device 1. Although not shown, the external database 200 further accumulates data by daily updating industry-specific product information data from a statistical system, inspector (serviceman) report data from a maintenance and inspection system, and the like.

[0020] Next, the prerequisite processing of the recommendation service will be described with reference to FIG. 1. As shown in FIG. 1(1), a user accesses a customer portal through a user terminal 300 and sets product information (such as product number), a usage plan, a desired time for providing recommendations, or desired recommendation items. Next, as shown in FIG. 1(2), the information providing device 1 acquires information from an external database 200 based on the information set by the user, generates recommendations, and sends them to the user. Next, as shown in FIG. 1(3), the information providing device 1 acquires the user's reaction to the recommendations and registers them in the external database 200.

[0021] The information providing device 1 registers the product information (product number, etc.) set by the user, the usage plan, the desired recommendation provision time, or the desired recommendation items in the corresponding external database 200. Note that the registration in the external database 200 is not limited to the information providing device 1, and may be performed by another device such as a user terminal 300.

[0022] Next, the processing of the initial recommendation after the prerequisite information has been registered will be described with reference to Figs. 1 and 2. First, the generation of recommendation information will be described. The information providing device 1 acquires product maintenance information, recommended items desired by the user, etc. from the external database 200. If industry information is included in the recommended items desired by the user, the information providing device 1 acquires the industry information from the external database 200. The information providing device 1 analyzes the acquired information and generates recommendation information.

[0023] Next, the recommendation timing will be explained. The information providing device 1 acquires the standard recommendation timing for a product from the external database 200, and acquires the recommendation timing for each industry. In this case, the information providing device 1 determines the recommendation timing for the industry as the recommendation timing. Furthermore, if there is a recommendation timing set by the user, the desired timing is acquired from the external database 200. In this case, the information providing device 1 determines the recommendation timing set by the user as the recommendation timing.

[0024] The information providing device 1 takes into consideration the user's budget and the like, and updates the recommendations to the customer portal a certain period before the determined recommendation time.

[0025] Thereafter, the information providing device 1 acquires the user's reaction to the recommendation and registers it in the external database 200.

[0026] Next, the process of second and subsequent recommendations will be described with reference to Figures 1 and 2. First, the generation of recommendation information will be described. The difference from the initial recommendation is that the information providing device 1 acquires feedback information, etc. from the external database 200. This enables the information providing device 1 to generate personalized recommendations.

[0027] Next, the timing of recommendation will be explained. The difference from the initial recommendation is that the information providing device 1 acquires feedback information in addition to the updated industry recommendation timing from the external database 200 and determines the recommendation timing. At this time, even if the user has set a recommendation timing, the information providing device 1 determines the recommendation timing from the feedback information. This allows the information providing device 1 to set a more personalized recommendation timing.

[0028] In the second and subsequent recommendations, the information providing device 1 updates the recommendation information to the customer portal and registers reactions to the recommendation in the external database 200, similar to the initial recommendation process.

[0029] (Configuration Examples and Processing Examples of Information Providing Device 1 and External Database 200) FIG. 3 is a block diagram illustrating an example of a configuration of the information providing device 1 and the external database 200 according to the embodiment.

[0030] (Example of external database 200 configuration) The external database 200 is communicably connected to the information providing device 1 and other devices, and updates the stored information. As shown in Fig. 3, the external database 200 stores a customer database 201, a product database 202 (corresponding to the product information and product data of the present invention), a recommendation database 203, a sales information database 204 (corresponding to the customer data and customer requests of the present invention), a service information database 205, etc.

[0031] The customer database 201 stores information about users. For example, the customer database 201 stores, for each user, basic information about the user (company name, industry, address, etc.), quotation data, order data, delivery record data, industry information (corresponding to the industry data according to the present invention), product registration information (products used, applications, required quality, etc.), accounting period, etc. The applications and required quality included in the product registration information will be described later.

[0032] The industry information stored here will be explained. The industry information is statistical data such as the usage status of each product for each industry, such as the food industry or the electric power industry, and the timing of recommendations. The industry information is updated at a fixed frequency. The usage status is the product status of each user, the maintenance status, the maintenance status such as replacement status, and the timing of maintenance. By analyzing the usage status, it is possible to identify, for example, the tendency for the usage period for each industry to be longer than the standard usage period, the tendency for the standard usage period to be observed, the tendency for the usage period to be shorter than the standard usage period, the product replacement period for each industry, the frequency of part replacement, etc.

[0033] The recommended period is statistical data on the replacement period for products, parts, etc. by industry. For example, in the road equipment industry, there is a tendency for products and parts to be replaced frequently in January in preparation for the busy season, so the recommended period is registered as January.

[0034] The product database 202 stores information about products, such as product shipping data, product lifespan data, part lifespan data, replacement part data, and product update information.

[0035] The recommendation database 203 stores information related to recommendations. For example, the recommendation database 203 stores the contents of recommendations sent (updated) in the past, the date of sending the recommendations, feedback information (corresponding to feedback data according to the present invention), and the like.

[0036] The feedback information registers the reactions of users who received recommendations. For example, user reactions include when to replace a product, when to replace parts, when to perform maintenance and inspections, when to perform repairs, product replacement cycles, and responses to recommendations. Responses to recommendations include information such as a request for part replacement six months after receiving a recommendation. This data serves as the basis for predicting future user behavior, determining when to send recommendations, and improving the accuracy of recommendations.

[0037] The sales information database 204 stores information related to user requests. The customer request information stored here includes, for example, information such as requesting industry trend information in the recommendation content, or requesting that the person in charge be notified by email separately from updates to the customer portal.

[0038] The service information database 205 stores information about services provided to users. For example, the service information database 205 stores inspection data about the inspection content and results of product inspections, repair and replacement data about product repairs and replacements, and the details and timing of such repairs and replacements, and calibration record data about product adjustments to correct errors.

[0039] (Information provision device 1) 3, the information providing device 1 has a communication unit 2, a storage unit 3, and a control unit 20. The information providing device 1 may also have an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information providing system 100, and a display unit (e.g., a liquid crystal display, etc.) that displays various information. The information providing device 1 and the external database 200 are communicably connected via the communication unit 2.

[0040] The communication unit 2 executes data communication with other devices, websites, etc. For example, the communication unit 2 performs data communication with each communication device via a router, etc. The communication unit 2 can also perform data communication with a user terminal, a customer portal, etc. (not shown).

[0041] The storage unit 3 can be, for example, a storage device such as a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), or an SSD (Solid State Drive). The storage unit 3 is provided with generated recommendation data 31 that stores recommendations generated by the recommendation generation unit.

[0042] The control unit 20 is a processing unit that controls the entire information providing device 1, and is realized by, for example, a processor. The control unit 20 functions as an input accepting unit 21, a data acquiring unit 22 (including an acquiring unit according to the present invention), a data analyzing unit 23 (including an analyzing unit according to the present invention), a recommendation generating unit 24 (including a generating unit according to the present invention), an output control unit 25 (including a determining unit and a notifying unit according to the present invention), and an external data registering unit 26. The input accepting unit 21, the data acquiring unit 22, the data analyzing unit 23, the recommendation generating unit 24, the output control unit 25, and the external data registering unit 26 are realized by electronic circuits included in the processor or processes executed by the processor.

[0043] The input accepting unit 21 registers information set by the user in a database. For example, the input accepting unit 21 registers information set in the customer portal by the user when the user starts using a product in an external database. Specifically, the input accepting unit 21 acquires product registration information set by the user and registers it in a customer database 201 included in the external database 200. The input accepting unit 21 also acquires information set by the user that the user wishes to provide and registers it in a sales information database 204 included in the external database 200.

[0044] Product registration information includes not only the product number of the product that has started to be used, but also its purpose, required quality, etc. The purpose is information including "the purpose of the product" and "the environment in which it is being used." The "purpose of the product" is information such as whether it is being used for plant control or temperature management. The "environment in which it is being used" is information such as whether it is being used in a hot and humid environment.

[0045] The required quality is set in terms of importance, for example, in three levels: "high," "medium," and "low." For "high," a single error will result in immediate replacement. For "medium," a replacement will occur after two or three errors. For "low," replacement will occur if multiple errors occur. For example, a user might set a "high" rating for safety-related devices such as fire alarms. Furthermore, even for the same thermometer, a device used for plant control would be set to "medium," while a device used for monitoring would be set to "low."

[0046] The information desired to be provided includes recommended items and timing. Recommended items are information related to maintenance and inspection, such as whether or not industry information is desired in the recommendation content, and whether parts storage information is desired following EOS (End Of Sale). Timing is information such as the desired recommendation time, for example, "every year, base time is October," "every three years, base time is May," or "I would like to use the product until its standard use period, so I would like recommendations to coincide with that."

[0047] Returning to FIG. 3, the data acquisition unit 22 acquires information necessary for generating recommendations from the external database 200. For example, the data acquisition unit 22 acquires product registration information and industry information from the customer database 201 included in the external database 200, and acquires product or part information from the product database 202. Furthermore, the data acquisition unit 22 acquires customer request information from the sales information database 204, and acquires feedback information from the recommendation database. Note that no feedback information is registered for the initial recommendation.

[0048] The data analysis unit 23 analyzes the information acquired by the data acquisition unit 22. For example, the data analysis unit 23 analyzes the user's response status and the response status by industry from the feedback information and converts the results into data. As an analysis of the user's response status, the data analysis unit 23 tallys up the time from the recommendation included in the feedback information to the estimate, order, etc. and calculates the average value, etc. Furthermore, as an analysis of the response status by industry, the data analysis unit 23 extracts information on the industry to which the user belongs and the product from the industry-specific information and tallys up the information.

[0049] Next, the data analysis unit 23 checks whether there are any factors that require a change in the recommendation time based on the acquired data or the aggregation results. To explain this by way of example, the data analysis unit 23 determines the recommendation time set by 60% or more of other users in the same industry as the industry recommendation standard time based on statistical data on recommendation times by industry, which is updated as needed. The data analysis unit 23 then compares the user's recommendation standard time with the industry recommendation standard time. If the comparison results in a discrepancy, the data analysis unit 23 analyzes the situation and concludes that "the user's recommendation standard time should be changed to the industry recommendation standard time." Note that the data analysis unit 23 suppresses the setting of the industry recommendation standard time if the ratio is less than 60%.

[0050] Here, a specific example of changing the standard recommendation period will be described. FIG. 4 is a diagram illustrating changing the recommendation period based on industry information. The vertical axis of FIG. 4 indicates the user company and industry, and the horizontal axis indicates the year and month. When setting the recommendation period for the third time, the data analysis unit 23 compares the industry recommendation period for the food industry, which is July, with the recommendation period for Company A in the food industry, which is May. In this case, since the recommendation periods are different, the data analysis unit 23 analyzes and concludes that "Company A's recommendation period will be postponed to July, which is the industry recommendation period." As a result, the recommendation period for Company A in the food industry is changed from May to July.

[0051] Furthermore, the data analysis unit 23 compares the industry recommendation period for the electric power industry, which is March, with the recommendation period for Company B, which is also in the electric power industry, which is June. In this case, since the recommendation periods are different, the data analysis unit 23 analyzes that "the recommendation period should be brought forward to March, which is the industry recommendation period." As a result, the recommendation period for Company B in the electric power industry is changed from June to March.

[0052] Next, we will explain how to change the recommendation period based on an analysis of feedback information. Figure 5 is a diagram illustrating the number of times a user has had product replacements. The vertical axis of Figure 5 represents the number of times product replacements, etc. have occurred (number of orders), and the horizontal axis represents the month. For example, the data analysis unit 23 analyzes that users place many orders in February based on the data shown in Figure 5, which is an aggregate of the implementation periods of product replacements, part replacements, and repairs from the feedback information. Therefore, the data analysis unit 23 analyzes that "the recommendation standard period initially set by the user should be changed from October to February." As a result, the recommendation period for the user is changed from October to February.

[0053] The data analysis unit 23 also checks whether there are any factors that require a change to the recommendation content. For example, the data analysis unit 23 creates additional information such as the average usage period and the replacement rate of relevant parts in the industry from the aggregated data by industry, and creates analysis result data to be added to the recommendation content.

[0054] Next, we will explain how to change recommended items based on an analysis of feedback information. Figure 6 is a diagram illustrating the actual usage period of a product by a user. The vertical axis of Figure 6 represents the number of years, and the horizontal axis represents the product. For example, the data analysis unit 23 compares the actual usage period of the user with the standard period based on the feedback information shown in Figure 6, and analyzes that "users tend to use products for longer than the standard usage period." As a result, the analysis results in "adding information on parts related to life extension, inspection information, etc. to the recommended items for the user."

[0055] 3, the recommendation generation unit 24 generates recommendations based on the data acquired by the data acquisition unit 22 and the analysis results of the data analysis unit 23. The output control unit 25 determines the recommendation time and issues the recommendation at the recommendation issue time calculated from the determined recommendation time.

[0056] For example, the following describes a flow in which the recommendation generation unit 24 determines the recommendation content and the output control unit 25 outputs the recommendation. Fig. 7 is a flowchart showing the generation of recommendations and the determination of the recommendation timing.

[0057] First, as shown in step S1 of Figure 7, the recommendation generation unit 24 acquires information about the products delivered to the user from the customer database 201 acquired by the data acquisition unit 22, and acquires the standard usage period of the product, information about the EOS (End Of Sale) date of the parts, maintenance information, etc. from the product database 202.

[0058] Next, as shown in step S2 of FIG. 7, the recommendation generating unit 24 creates basic recommendation items, such as product, standard usage period, and standard maintenance information, from the acquired information.

[0059] 7, the recommendation generation unit 24 acquires information desired by the user from the sales information database 204 acquired by the data acquisition unit 22. For example, the recommendation generation unit 24 acquires a request such as a desire for industry information in recommendations from the sales information database 204. In this case, the recommendation generation unit 24 adds this to the recommendation basic items.

[0060] Next, the recommendation generation unit 24 adds or changes recommended items based on the feedback information acquired in S1, as shown in step S4 of Fig. 7. For example, the recommendation generation unit 24 checks whether the data received from the data analysis unit 23 contains analysis result data indicating factors that should change the recommendation content, and adds or changes recommended items if analysis result data exists. Note that in the case of an initial recommendation, this process is not executed because feedback information has not been registered in the recommendation database 203.

[0061] In this way, the recommendation generator 24 executes S2 to S4 shown in FIG. 7 to determine recommended items.

[0062] Next, the recommendation generation unit 24 acquires information from the acquired product database 202, etc., in accordance with the determined recommendation items, and determines the contents, as shown in step S9 of Fig. 7. Furthermore, for recommendation items corresponding to industry information or feedback information, the recommendation generation unit 24 acquires information from the product database 202, etc., based on the analysis result data of the data analysis unit 23, and determines the contents.

[0063] 7, the output control unit 25 creates a reference recommendation time from the maintenance information etc. of the product in the product database 202 acquired in S1. For example, if after a user purchases a product, the product is recommended to be maintained every three years, the output control unit 25 sets the recommendation reference time to the month of purchase three years from now.

[0064] Furthermore, the output control unit 25 changes the recommendation time based on the industry information, as shown in S6 of Fig. 7. For example, the output control unit 25 checks whether there is analysis result data that requires a change in the recommendation time in the data received from the data analysis unit 23. For example, if there is an analysis result that indicates that the industry recommendation time is January for a plant in the road equipment industry to which the user belongs, the output control unit 25 changes the recommendation reference time from the introduction month to January.

[0065] Furthermore, the output control unit 25 changes the recommendation time based on the user's request, as shown in S7 of Fig. 7. For example, the output control unit 25 checks whether the user has set a desired recommendation time from the business information database 204 acquired in S1. If a desired recommendation time has been set, the output control unit 25 changes the recommendation time to the desired time.

[0066] Furthermore, as shown in S8 of Fig. 7, the output control unit 25 changes the recommendation time based on the feedback information acquired in S1. For example, the output control unit 25 checks whether the data received from the data analysis unit 23 contains analysis result data indicating that factors for changing the recommendation time exist, and changes the recommendation time if analysis result data exists. As a specific example, the output control unit 25 refers to the analysis result data of "order month and number of occurrences" shown in Fig. 5 as the analysis result data, and further changes and determines the recommendation time. Note that in the case of an initial recommendation, this process is not executed because feedback information is not registered in the recommendation database 203.

[0067] 7 to determine the recommendation time. Thereafter, the recommendation generation unit 24 and the output control unit 25 determine the contents of the recommendation items and the recommendation time, generate recommendations, and register them in the generated recommendation data 31 in the storage unit 3, as shown in S9.

[0068] Next, the output control unit 25 transmits the recommendation information when it is a period of time equivalent to several months before the recommended time. For example, the output control unit 25 is set to transmit the information three months before the recommended time, from the viewpoint of securing a budget, etc. In this case, the output control unit 25 acquires the recommendation data generated from the generated recommendation data 31 at a time equivalent to three months before the recommended time and updates it to the customer portal.

[0069] At this time, the output control unit 25 refers to the sales information database 204 and checks whether the customer requests in the sales information database 204 include a desired timing for sending recommendations, or a request to send an email to the person in charge informing them that the recommendations have been updated on the customer portal. If there is a customer request, the output control unit 25 changes the output timing to the desired timing, and after updating the recommendations on the customer portal, sends an email to the person in charge.

[0070] Furthermore, the output control unit 25 refers to the feedback information and changes the recommendation transmission time. For example, if the recommendation information is not the first time, the output control unit 25 refers to the recommendation database 203 and confirms from the recommendation reaction information that "the user has been making inquiries, etc. for about six months since receiving the recommendation information." In this case, the time set as three months before the recommendation reference time is changed to six months before, and the recommendation information is updated in the customer portal.

[0071] 3, the external data registration unit 26 acquires user reactions after the recommendation information is sent and registers them in the data. For example, the external data registration unit 26 registers the product replacement timing, part replacement timing, maintenance inspection timing, repair timing, product replacement cycle, and response to the recommendation in the feedback information contained in the recommendation database 203.

[0072] (Example of processing) Next, the operation of the recommendation process in the information providing device 1 of the embodiment having such a configuration will be described with reference to FIG. 8. FIG. 8 is a diagram for explaining a specific flow of recommendation. FIG. 8 shows the flow of processing in the information providing device 1 when the user sets product information and information to be provided and the information providing device 1 receives the set information. In this example, the input receiving unit 21 to the external data registration unit 26 are realized by software, but some or all of the input receiving unit 21 to the external data registration unit 26 may be realized by hardware. In either case, the same effects as those described below can be obtained.

[0073] (Prerequisite processing) The user installs product A, product B, and product D. Then, as shown in (1) of Figure 8, the user accesses the customer portal through the user terminal and sets product registration information, desired provision information, etc. For example, the user sets the use of product A to "high temperature and humidity, plant control" and the required quality to "medium." The user sets the use of product B to "high temperature and humidity, plant monitor" and the required quality to "medium." The user sets the use of product D to "high temperature and humidity, plant safety equipment" and the required quality to "high."

[0074] Furthermore, the user sets "industry information" for product A and "parts storage information" for product B as the information they wish to receive. The user does not set any information they wish to receive for product D. In addition, the user sets the recommendation reference period for products A, B, and D as "October, every three years."

[0075] Then, the information providing device 1 acquires the information set in the customer portal and registers the acquired information in the external database 200. Similarly, the input receiving unit 21 registers the product registration information set by the user in the customer database 201, and registers the provision request information set by the user in the sales information database 204.

[0076] (Processing for initial recommendation) Next, as shown in FIG. 8(2), the information providing device 1 performs an analysis based on the information acquired in FIG. 8(1) and makes an initial recommendation.

[0077] For example, the data acquisition unit 22 acquires general product information, standard usage period, and parts information for each of product A, product B, and product D set by the user from the product database 202. The data acquisition unit 22 also refers to the sales information database 204 to acquire information that the user desires to be provided for each of product A, product B, and product D.

[0078] Next, since it is set that industry information is desired for product A, the data acquisition unit 22 refers to the customer database 201 and acquires from the user basic information that the industry to which the user belongs is the food industry. Furthermore, the data acquisition unit 22 refers to the customer database 201 and acquires industry information about the food industry.

[0079] Next, the data analysis unit 23 analyzes data such as the usage period, part replacement record, and maintenance inspection record of product A in the food industry based on the industry information of the food industry acquired by the data acquisition unit 22. As a result, the data analysis unit 23 analyzes that "in the food industry, product A tends to have part X replaced once every three years, and the average usage period tends to be about five years longer than the standard usage period." Furthermore, the data analysis unit 23 analyzes that "50% of customers in the food industry replace part X every three years." The data analysis unit 23 transmits the analysis results to the recommendation generation unit 24.

[0080] (Recommendation generation and timing determination) Next, as shown in (3) of Fig. 8, the information providing device 1 determines the generation and timing of recommendations using the analysis results of (2) of Fig. 8. For example, the information providing device 1 determines the generation and timing of recommendations by sequentially determining the item, content, and timing.

[0081] First, we will explain product A. For example, in addition to the standard usage period, maintenance and inspection information, etc., which are basic recommendation items, the recommendation generation unit 24 sets industry information as an additional item for product A, since "industry information" is set in the desired provision information.

[0082] Next, the recommendation generation unit 24 acquires the contents of the standard usage period, maintenance and inspection information, etc., which are basic items of recommendations, for product A. The recommendation generation unit 24 acquires the standard usage period and general maintenance and inspection information of product A from the product database 202. As a result, the recommendation generation unit 24 confirms that an "inspection" is necessary for the third year.

[0083] Next, the recommendation generation unit 24 acquires the details of "industry information," an additional item of the recommendation, for product A, and if the industry information differs from general maintenance and inspection information, etc., prioritizes the industry information to determine the details.

[0084] Specifically, the recommendation generation unit 24 obtains the above-described analysis result for product A that "In the food industry, product A tends to have part X replaced once every three years, and the average usage period tends to be about five years longer than the standard usage period." In this case, since general maintenance and inspection information and industry information differ, the recommendation generation unit 24 sets the suggestion content as "Replacement of part X" and further registers the reason for the suggestion as "Replacement of part X is recommended because the food industry tends to use products longer than the standard usage period." Furthermore, in response to the analysis result regarding the replacement of part X that "50% of customers in the food industry replace part X every three years," the recommendation generation unit 24 registers the remarks as "50% of customers in the food industry replace part X every three years."

[0085] As a result, the recommendation generation unit 24 registers the above-described information as shown in the initial recommendation information for product A in Fig. 9. Furthermore, in response to the analysis result of the data analysis unit 23, that "the food industry uses products for five years longer than the standard use period," the recommendation generation unit 24 registers the industry average use period, which is five years longer than the standard use period, together with the standard use period, in the reference information.

[0086] Next, we will explain product B. For example, for product B, in addition to the standard usage period, maintenance and inspection information, etc., which are basic recommendation items, the recommendation generation unit 24 sets the parts storage information as an additional item because "parts storage information" is set in the provision request information.

[0087] The recommendation generation unit 24 acquires the contents of the standard usage period, maintenance and inspection information, etc., which are basic items of the recommendation, for product B, and acquires the standard usage period and maintenance information "replace part c in the third year." Next, the recommendation generation unit 24 acquires "part replacement cycle: 3 years" for "part storage information," which is an additional item of the recommendation, for product B.

[0088] As a result, the recommendation generation unit 24 registers the recommendation content as "replacement of part c" and the reason for the recommendation as "replacement of part c is recommended," as shown in the initial recommendation information for product B in Fig. 9. Furthermore, the recommendation generation unit 24 registers the replacement cycle and standard usage period of part c in the reference information.

[0089] The recommendation generating unit 24 then sets the basic recommendation items such as the standard usage period and maintenance and inspection information for product B, but does not set any additional items because the desired provision information has not been set.

[0090] Next, a description will be given of product D. For example, the recommendation generation unit 24 acquires, for product D, "inspection to be carried out in the third year" as the contents of the standard use period, maintenance and inspection information, etc., which are basic items of recommendation.

[0091] As a result, the recommendation generation unit 24 sets the recommendation content to "perform inspection" and further registers the reason for the recommendation as "perform inspection," as shown for product D in the initial recommendation information in Fig. 9. Furthermore, the recommendation generation unit 24 sets the standard usage period in the reference information.

[0092] (Regarding recommendation timing) Next, the timing of recommendation will be explained. Specifically, as shown in (3) of Fig. 8, the information providing device 1 determines the recommendation timing by successively determining the reference timing for recommendation, the recommendation timing based on industry information, and the recommendation timing based on customer requests. Note that since this is the first recommendation, feedback information is not used.

[0093] For example, the output control unit 25 creates a standard recommendation period of "every three years, March" from the acquired maintenance information of product A, product B, and product D in the product database 202.

[0094] Next, the output control unit 25 compares the analysis result by the data analysis unit 23, "Industry recommendation period for the food industry: July" with the "Standard recommendation period: March", and changes the standard recommendation period to "July every three years" based on the maintenance information of product A, product B, and product D, etc.

[0095] Furthermore, because the user has set a desired recommendation period, the output control unit 25 acquires the user-set recommendation period "October, every three years" registered in the sales information database 204. The output control unit 25 further changes the standard recommendation period for product A, product B, and product D to "October, every three years."

[0096] As a result, the recommendation generating unit 24 and the output control unit 25 register the generated recommendation information and the recommendation reference time in the generated recommendation data 31.

[0097] Thereafter, since the user has not registered a preference for the timing of sending recommendations, the output control unit 25 updates the recommendation information in the customer portal to three months before the standard recommendation reference period. In this case, the output control unit 25 updates the recommendation information to July, three months before the standard recommendation period of October.

[0098] When such product recommendations are made, the user checks the updated recommendation information on the customer portal and performs maintenance on product A, product B, and product D.

[0099] In addition, the external data registration unit 26 receives feedback information regarding the timing of part replacements, maintenance inspections, etc. for the user's products A, B, and D after receiving the recommendation information, as well as responses to inquiries, etc., and registers this as feedback information in the recommendation database 203.

[0100] (Processing for recommendations from the second time onwards) Next, we will describe the differences between the second and subsequent recommendation processes and the first recommendation process. The data acquisition unit 22 acquires user feedback information from the recommendation database 203 that was not registered in the first recommendation. Here, we will describe the creation of the third recommendation information, shown in the lower part of Figure 9.

[0101] The data analysis unit 23 compiles the feedback information on the periods for which product replacement, part replacement, and repairs were performed, and compiles the user's usage status as data as shown in Figures 5 and 6. From the statistical data shown in Figure 5, the data analysis unit 23 analyzes that, in the case of this user, "part replacement, etc., is often performed in February." Furthermore, from the statistical data on product usage status shown in Figure 6, the data analysis unit 23 analyzes that "the product is used for five years longer than the standard usage period."

[0102] (About recommended items and content from the second time onwards) The recommendation generation unit 24 compares the industry average usage period for product A by industry analyzed by the data analysis unit 23 with the user's usage period analyzed from the usage status and feedback information. As a result, the recommendation generation unit 24 registers the "standard usage period and industry average usage period" in the reference information, since both have been used for five years longer than the standard usage period. Note that, at the time of the third recommendation, the recommendation generation unit 24 determines that product A has exceeded the standard usage period and is approaching the industry average usage period, and adds "product A replacement information" to the remarks column instead of product life extension information.

[0103] Meanwhile, the recommendation generation unit 24 registers the following information as shown for product A in the third recommendation information in Figure 9. For example, the recommendation generation unit 24 determines that product A has exceeded its standard usage period and is approaching the industry average usage period at the time of the third recommendation. As a result, the recommendation generation unit 24 registers "product replacement" as the recommendation content and "the product has exceeded its standard usage period and is approaching the industry average usage period" as the reason for the recommendation.

[0104] Furthermore, the recommendation generation unit 24 acquires the analysis result of the analysis of the replacement status of product A in the food industry by the data analysis unit 23, that is, "60% of customers in the food industry replace product A within the average usage period." Based on the acquired analysis result, the recommendation generation unit 24 registers "60% of customers in the food industry replace product A within the average usage period" in the notes.

[0105] Next, the recommendation generation unit 24 registers the following information as shown in the third recommendation information for product B in Fig. 9. First, the recommendation generation unit 24 adds an item for product life extension information for product B in response to the analysis result from the data analysis unit 23 that "the product will be used for five years longer than the standard usage period."

[0106] The recommendation generation unit 24 then adds "estimated usage period equal to the standard usage period plus five years" to the reference information and registers it as the content of the product life extension information item. Furthermore, the recommendation generation unit 24 registers "replacement of part c" as the content of the proposal from the maintenance information for product B in the product database 202. Furthermore, the recommendation generation unit 24 acquires information on part c from the part information in the product database 202 as content corresponding to the part storage information item. Then, since the recommendation generation unit 24 can newly confirm that the EOS date is approaching, it registers "replacement of part c is recommended. The EOS date for part c is approaching" as the reason for the proposal.

[0107] As a result, the recommendation generation unit 24 registers in the notes "We recommend periodic replacement of part c, as it tends to be used for longer than the standard usage period," based on the analysis results of the data analysis unit 23 and the product life extension information.

[0108] Next, the recommendation generation unit 24 registers the following information as shown in product D of the third recommendation information in Fig. 9. For example, when the data analysis unit 23 analyzes the product usage status of the user included in the feedback information, it analyzes that "the user replaced the product for which the required quality was set to 'high' one year before the standard usage period."

[0109] In this case, the recommendation generation unit 24 receives the analysis result and registers "Product replacement" in the proposal content and "Replacement of product D is recommended" in the proposal reason. Furthermore, the recommendation generation unit 24 registers "Since the required quality is set to high, replacement of product D is recommended one year before the standard usage period" in the remarks field.

[0110] (Regarding the timing of recommendations from the second time onwards) Next, the determination of the timing of the second and subsequent recommendations will be described. For example, the output control unit 25 obtains analysis results from the data analysis unit 23, such as "part replacements, etc., are often carried out in February" and "reactions are made on average six months after receiving the recommendation information."

[0111] Based on the analysis results, the output control unit 25 changes the recommendation period from October to February. Furthermore, based on the analysis results, the output control unit 25 sets the recommendation transmission period to August of the previous year, six months before February, which is the reference period for recommendations. Then, the output control unit 25 updates the recommendation information to the customer portal at the set period.

[0112] (Processing flow) Next, the processing flow of the information providing device 1 will be described with reference to Figures 10 and 11. The steps in the flowcharts shown in the figures may be executed in a different order, and some processing may be added or omitted.

[0113] (Recommendation generation process flow) An example of the procedure for the recommendation generation process of the information providing device 1 will be described using the flowchart showing the flow of the recommendation generation process in Fig. 11. The information providing device 1 refers to the product database and acquires information such as the standard maintenance and standard usage period of the product (S10).

[0114] Next, the information providing device 1 refers to the business information database and acquires the recommended items requested by the user (S11).

[0115] Next, if the recommended items requested by the user include industry information (industry inspection information) or the like (S12: YES), the information providing device 1 refers to the customer database and acquires the industry information (S13).

[0116] If the recommended items requested by the user do not include industry information (industry inspection information) etc. (S12: NO), and if the recommendation being generated is the first one after obtaining the industry information (S13) (S14: YES), the information providing device 1 generates recommended information (S16).

[0117] If the recommendation being generated is not the first one (S14: NO), the information providing device 1 refers to the recommendation database, acquires information such as recommendation reactions (S15), and generates recommendation information (S16).

[0118] The determination of the recommendation time (S17) will be described later. The information providing device 1 transmits the recommendation at the time corresponding to the recommendation time (S18). The information providing device 1 registers the response to the recommendation in the recommendation database (S19).

[0119] (Recommendation timing decision process) An example of the procedure for determining the recommendation timing by the information providing device 1 will be described using the flowchart showing the flow of determining the recommendation timing in Fig. 12. The information providing device 1 refers to the product database and determines the recommendation timing based on standard maintenance etc. of the product (S31).

[0120] Next, the information providing device 1 refers to the customer database and changes the recommendation period for the user's industry (S32).

[0121] Next, if there is a recommendation period set by the user (S33: YES), the information providing device 1 refers to the business information database and changes the recommendation period to the period set by the user (S34).

[0122] Next, if the recommendation time set by the user is not present (S33: NO), and after the recommendation time is changed to the time set by the user (S34), the information providing device 1 checks whether it is the first recommendation (S35).

[0123] If it is the first recommendation (S35: YES), the information providing device 1 determines the recommendation timing (S37).

[0124] If it is not the first recommendation (S35: NO), the information providing device 1 refers to the recommendation database, changes the recommendation time (S36), and determines the recommendation time (S37).

[0125] (Effects of the embodiment) As is clear from the above description, the information providing device 1 according to the embodiment can achieve the following effects.

[0126] For example, the information providing device 1 can store industry information as data and change the recommendation time based on the results of analyzing the industry information. This makes it possible to set a recommendation time that is more suitable for the user, even if the user has not set the desired recommendation time.

[0127] For example, the information providing device 1 can store feedback information as data, analyze the feedback information, and generate recommendation information, thereby enabling the provision of more detailed and personalized recommendation information to users.

[0128] For example, the information providing device 1 can provide the results of analyzing industry information to users who request it, with the results reflected in the recommendations. This allows users to request part replacements, etc., with reference to industry trends.

[0129] Furthermore, the information providing device 1 can make recommendations at an appropriate time taking into consideration the industry information of the user. As a result, the information providing device 1 can suppress unnecessary recommendations even when there are a huge number of users to whom recommendations are to be made, reducing the processing load on the information providing device 1 that makes recommendations and speeding up the provision of recommendations to each user.

[0130] Furthermore, the information providing device 1 can change the items to be recommended for each user according to the fed-back information, and recommend appropriate items and content desired by the user. As a result, the information providing device 1 can appropriately select and recommend necessary information even when there are a huge number of users to whom recommendations are to be made, thereby suppressing unnecessary recommendations and reducing the processing load of the information providing device 1 that executes recommendations.

[0131] [Application examples] In addition to the information described above, the information providing device 1 can also make recommendations from service personnel in charge of maintenance and inspection using inspection information data.

[0132] For example, inspection information data from a service person in charge of maintenance and inspection, as shown in FIG. 10, is registered in the service information database 205 of the external database 200. The data acquisition unit 22 acquires inspection information data related to products. The data analysis unit 23 analyzes the product inspection information data in the same way as it analyzes feedback information, thereby generating more accurate recommendations. In addition, the inspection information data for each user enables the recommendation generation unit 24 to reflect comments from the service person recommending replacement, etc., in the recommendation information.

[0133] By sharing the recommendation information including the feedback information in the recommendation database 203 with the sales representative, the sales representative can also send reminders, etc. Furthermore, by registering the user information acquired by the sales representative as additional information in the recommendation database 203 as sales input data, the information can be unified, and more accurate recommendation information can be created.

[0134] [Numerical values, etc.] The items, recommendation contents, industry, various statuses registered in the database, number of devices, etc. used in the above embodiment are merely examples and can be changed as desired. Furthermore, the process flow explained in each flowchart can also be changed as appropriate within a consistent range.

[0135] In the above embodiment, industry is described as an example of the first attribute, but the present invention is not limited to this. For example, the first attribute may include business type, business model, region, etc. in addition to the industry in the above embodiment. For example, region may include information categorized by country, climate, etc. Examples of regional information include "repairs tend to occur during long holidays such as Golden Week or Obon in Japan and Chinese New Year," or "product replacement cycles tend to be shorter in hot and humid regions."

[0136] For example, in the above-described embodiment, when a user selects industry information, the information providing device 1 analyzes based on the industry information that "in the food industry, product A tends to be used for about five years longer than the standard usage period," and based on this analysis result, generates recommendations that suggest information on extending the life of product A, replacement information, etc.

[0137] On the other hand, when the user selects regional information, the information providing device 1 analyzes based on the regional information that "in Southeast Asia, product A tends to be replaced two years earlier than the standard usage period," and based on this analysis information, generates recommendations that suggest information on extending the life of product A, replacement information, etc.

[0138] Furthermore, the information providing device 1 can generate recommendations by combining information about the industry to which the user belongs and information about the region where the product is used. For example, if the user belongs to the chemical industry and uses product A in a hot and humid region, the information providing device 1 analyzes, based on the industry information and region information, that "in the hot and humid region of the chemical industry, product A tends to be used about three years shorter than its standard use period," and generates a recommendation that suggests replacement information, life extension information, etc. for product A based on this analysis result. On the other hand, if the user belongs to the chemical industry and uses product A in a cold and dry region, the information providing device 1 analyzes, based on the industry information and region information, that "in the cold and dry region of the chemical industry, product A tends to be used exactly as planned for its standard use period," and generates a recommendation that suggests life extension information, replacement information, etc. for product A.

[0139] In this way, the information providing device 1 analyzes that products used in hot and humid regions deteriorate faster based on product specifications, statistical information on product usage, etc., and generates replacement and maintenance recommendations earlier than when the product is used in a low-temperature, dry region. In other words, the information providing device 1 can dynamically generate and provide appropriate recommendations to users, even for the same product, taking into account the conditions of the region in which it is used.

[0140] As described above, the information providing device 1 can generate appropriate recommendations using information obtained by further dividing industry information by region, in other words, industry information segmented by region. Examples of regional information and recommendations include "early maintenance" and "replacement with waterproof products" in areas with heavy rainfall, and "replacement with dustproof products" in desert areas, and the information providing device 1 can make recommendations appropriate for the region.

[0141] 〔system〕 The information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified.

[0142] Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown. In other words, all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0143] Furthermore, all or any part of the processing functions performed by each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware using wired logic.

[0144] [Hardware] Next, an example of the hardware configuration of the information providing device 1 will be described. Note that other devices may also have a similar hardware configuration. FIG. 13 is a diagram showing an example of the hardware configuration according to an embodiment. As shown in FIG. 13, the information providing device 1 has a communication device 1a, an HDD (Hard Disk Drive) 1b, a memory 1c, and a processor 1d. Furthermore, the components shown in FIG. 13 are connected to each other via a bus or the like.

[0145] The communication device 1a is a network interface card or the like, and communicates with other servers. The HDD 1b stores programs and databases that operate the functions shown in FIG.

[0146] The processor 1d reads out from the HDD 1b or the like a program that executes the same processes as the respective processing units shown in FIG. 3 and loads it into the memory 1c, thereby operating a process that executes each function described in FIG. 3 or the like. For example, this process executes the same functions as the respective processing units of the information providing device 1. Specifically, the processor 1d reads out from the HDD 1b or the like a program that has the same functions as the communication unit 2, the input reception unit 21, the data acquisition unit 22, the data analysis unit 23, the recommendation generation unit 24, the output control unit 25, the external data registration unit 26, and the like. Then, the processor 1d executes a process that executes the same processes as the communication unit 2, the input reception unit 21, the data acquisition unit 22, the data analysis unit 23, the recommendation generation unit 24, the output control unit 25, the external data registration unit 26, and the like.

[0147] In this way, the information providing device 1 operates as a device that executes various processing methods by reading and executing a program. The information providing device 1 can also realize functions similar to those of the above-described embodiment by reading the program from a recording medium using a medium reading device and executing the read program. Note that the program in these other embodiments is not limited to being executed by the information providing device 1. For example, the present invention can also be applied in the same way to cases where another computer or server executes the program, or where these execute the program in cooperation with each other.

[0148] This program can be distributed via a network such as the Internet. In addition, this program can be recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, a magneto-optical disk (MO), or a digital versatile disk (DVD), and can be executed by being read from the recording medium by a computer.

[0149] (others) Some examples of combinations of the disclosed technical features are set out below.

[0150] (1) An information providing device comprising: an acquisition unit that acquires product information regarding a first product used by a user; a determination unit that determines a recommendation time for making recommendations regarding maintenance and inspection of the product information based on a first attribute to which the user belongs; and a notification unit that notifies the recommendation regarding the product information at the determined recommendation time.

[0151] (2) The information providing device described in (1), wherein the first attribute is a first industry, the acquisition unit acquires industry data in which the usage status of each product is registered for each industry including the first industry, and the determination unit acquires the usage status of the first product corresponding to the first industry from the industry data, identifies the usage trend of the first product in the first industry from the usage status of the first product, and determines the recommendation timing based on the usage trend of the first product.

[0152] (3) The information providing device described in (2), wherein the acquisition unit acquires product data in which the standard usage period of each product is registered, the determination unit acquires the standard usage period of the first product from the product data, determines a reference period for the recommendation based on the acquired standard usage period, changes the reference period for the recommendation based on the first industry, and the notification unit notifies the recommendation at the changed reference period for the recommendation.

[0153] (4) An information providing device described in any one of (1) to (3), wherein the acquisition unit acquires customer data in which requests regarding the timing of notification of recommendations regarding the product information are registered, and the determination unit changes the reference timing of the recommendations according to the notification timing of the customer data.

[0154] (5) An information providing device described in any one of (1) to (3), wherein the acquisition unit acquires feedback data in which the reaction of the user to the recommendation, to which the recommendation has been notified, is registered, and the determination unit changes the reference time for the recommendation based on the feedback data for the first product.

[0155] (6) An information providing device comprising: an acquisition unit that acquires product information regarding a first product used by a user; a generation unit that generates basic items that are items to be recommended for the first product based on the product information; and a notification unit that recommends the generated basic items to the user, wherein the generation unit updates the basic items based on feedback information that indicates the reaction of the user to the recommendation when notified of the recommendation.

[0156] (7) The information providing device described in (6), wherein the acquisition unit acquires customer requests including items for which the user requests recommendations regarding the first product, and the generation unit updates the basic items based on the customer requests.

[0157] (8) The information providing device according to (6) or (7), wherein the generating unit generates recommendation content that is content that recommends the first product from the product information based on the basic items.

[0158] (9) An information providing device as described in (7) or (8), wherein the acquisition unit acquires industry data in which the usage status of the first industry is registered when the customer request includes information on the usage status of the first industry to which the user belongs, and the generation unit updates the recommendation content based on the usage status of the first industry included in the industry data.

[0159] (10) The information providing device described in (9) further includes an analysis unit that creates statistical data that analyzes the implementation rate of product replacement and part replacement based on the usage status of the first industry included in the industry data, and the generation unit updates the recommendation content based on the statistical data.

[0160] (11) An information provision method in which a computer acquires product information regarding a first product used by a user, determines a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs, and notifies the recommendation regarding the product information at the determined recommendation time.

[0161] (12) An information providing program that causes a computer to execute a process of acquiring product information regarding a first product used by a user, determining a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs, and notifying the recommendation regarding the product information at the determined recommendation time.

[0162] (13) An information provision method in which a computer acquires product information about a first product used by a user, generates basic items that are items to recommend about the first product based on the product information, and recommends the generated basic items to the user, and the generating process updates the basic items based on feedback information that indicates the reaction of the user to the recommendation when notified of the recommendation.

[0163] (14) An information provision program that causes a computer to execute a process of acquiring product information regarding a first product used by a user, generating basic items that are items to recommend the first product based on the product information, and recommending the generated basic items to the user, wherein the generating process updates the basic items based on feedback information that indicates the reaction of the user to the recommendation when notified of the recommendation. [Explanation of symbols]

[0164] 1 Information provision device 1a Communication equipment 1b HDD 1c memory 1d processor 2. Communications Department 20 Control Unit 21 Input reception section 22 Data Acquisition Section 23 Data Analysis Department 24 Recommendation Generation Unit 25 Output control section 26 External Data Registration Section 3 Storage section 31 Generated recommendation data 200 External Databases 201 Customer Database 202 Product Database 203 Recommendation Database 204 Sales Information Database 205 Service Information Database 100 Information Provision System 300 User Terminals

Claims

1. an acquisition unit that acquires product information related to a first product used by a user; a determination unit that determines a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs; a notification unit that notifies the recommendation regarding the product information at the determined recommendation time; An information providing device comprising:

2. the first attribute is a first industry; the acquiring unit acquires industry data in which a usage status of each product is registered for each industry including the first industry, The determination unit acquiring a usage status of the first product corresponding to the first industry from the industry data; Identifying a usage trend of the first product in the first industry based on the usage status of the first product; determining the recommendation timing based on the usage trend of the first product; The information providing device according to claim 1 .

3. The acquisition unit Obtain product data that registers the standard usage period for each product, The determination unit obtaining a standard usage period of the first product from the product data; determining a reference time for the recommendation based on the acquired standard usage period; changing a reference time for the recommendation based on the first industry; The notification unit notifying the recommendation at the changed reference time for the recommendation; The information providing device according to claim 2 .

4. The acquisition unit Acquire customer data in which requests regarding the timing of notification of recommendations regarding the product information are registered; The determination unit changing the reference time for the recommendation in accordance with the notification time of the customer data; The information providing device according to claim 3 .

5. The acquisition unit obtaining feedback data in which the user who has been notified of the recommendation has registered a reaction to the recommendation; The determination unit changing the reference time for the recommendation based on feedback data for the first product; The information providing device according to claim 3 .

6. an acquisition unit that acquires product information related to a first product used by a user; a generation unit that generates basic items that are items to be recommended for the first product based on the product information; a notification unit that recommends the generated basic items to the user; The generation unit updating the basic items based on feedback information indicating a reaction of the user to the recommendation; Information providing device.

7. The acquisition unit acquiring customer requests including items for which the user requests recommendations regarding the first product; The generation unit Update the basic items based on the customer requests. The information providing device according to claim 6.

8. The generation unit generating recommendation content that is content that recommends the first product from the product information based on the basic items; The information providing device according to claim 7.

9. The acquisition unit If the customer request includes information on the usage status of a first industry to which the user belongs, obtain industry data in which the usage status of the first industry is registered; The generation unit updating the recommendation content based on a usage state of the first industry included in the industry data; The information providing device according to claim 8.

10. further comprising an analysis unit that generates statistical data by analyzing the implementation rate of product replacement and part replacement based on the usage status of the first industry included in the industry data; The generation unit updating the recommendation content based on the statistical data; The information providing device according to claim 9.

11. The computer Obtaining product information regarding a first product used by the user; determining a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs; notifying the recommendation regarding the product information at the determined recommendation time; How information is provided to perform the process.

12. On the computer, Obtaining product information regarding a first product used by the user; determining a recommendation time for making a recommendation regarding maintenance and inspection of the product information based on a first attribute to which the user belongs; notifying the recommendation regarding the product information at the determined recommendation time; An information providing program that executes processing.

13. The computer Obtaining product information regarding a first product used by the user; generating basic items that are items to be recommended for the first product based on the product information; Execute a process of recommending the generated basic items to the user; The generating process includes: updating the basic items based on feedback information indicating a reaction of the user to the recommendation; How information is provided to perform the process.

14. On the computer, Obtaining product information regarding a first product used by the user; generating basic items that are items to be recommended for the first product based on the product information; Execute a process of recommending the generated basic items to the user; The generating process includes: updating the basic items based on feedback information indicating a reaction of the user to the recommendation; An information providing program that executes processing.

Images