Auction support apparatus
The auction support device addresses consumer and business challenges in car auctions by identifying and notifying users about relevant vehicles, enhancing service utilization through personalized automobile auction participation.
Patent Information
- Application Number
- JP2024020732
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-02-15
- Publication Date
- 2025-08-27
AI Technical Summary
Ordinary consumers face high barriers to participating in car auctions, and existing support services for businesses providing automobile auction services are not cost-effective.
An auction support device that includes a first automobile selection information storage means, listing information acquisition means, characteristic information acquisition means, and detection information provision means to identify and notify users about relevant automobiles up for auction, based on user characteristics and preferences.
The device supports businesses and encourages consumers to use automobile auction services by automatically selecting and promoting vehicles that meet user needs, thereby enhancing service utilization.
Smart Images
Figure 2025124968000001_ABST
Abstract
Description
[Technical Field]
[0001] This relates to technology for services involving participation in automobile auctions. [Background technology]
[0002] When purchasing a car, there are two options: buying a new car or a used car, and the choice depends on the prospective buyer's financial and time availability, whether they prefer older cars, etc. When purchasing a used car, on the other hand, people generally check websites and magazines that offer used car information to see if the car they want is for sale, and then purchase it from a retailer that sells the car they want.
[0003] On the other hand, used car retailers buy cars directly from consumers and resell them after servicing, or sell cars purchased at car auctions. Note that car auctions are a professional market, and it is not common for consumers to participate. Summary of the Invention [Problem to be solved by the invention]
[0004] Against this background, although it is possible for ordinary consumers to participate in car auctions and purchase the car of their choice under the system, the hurdles to participation are high, and for businesses, the support services are not cost-effective.
[0005] In view of the above problems, the present invention aims to provide an auction support device that supports businesses that provide automobile auction services and encourages automobile buyers to use the service. [Means for solving the problem]
[0006] One form of the disclosed auction support device is characterized by having a first automobile selection information storage means that associates and stores user characteristic information that represents a user's characteristics with automobile identification information that identifies automobiles that the user is likely to be interested in; a listing information acquisition means that acquires listing information related to automobile auctions; a characteristic information acquisition means that acquires one of the user characteristic information related to one of the users; a first automobile selection means that extracts one of the automobile identification information corresponding to the one of the user characteristic information from the first automobile selection information storage means; and a first detection information provision means that detects, based on the listing information, that a automobile identified by the one of the automobile identification information has been put up for auction, and provides information related to the detected automobile to the one user. [Effects of the Invention]
[0007] The disclosed auction support device supports businesses that provide automobile auction services and promotes the use of the service by those who wish to purchase automobiles. [Brief explanation of the drawings]
[0008] [Figure 1] 1 is a diagram illustrating an overview of an auction support device according to an embodiment of the present invention. [Figure 2] 1 is a functional block diagram of an auction support device according to an embodiment of the present invention. [Figure 3] FIG. 3 is a diagram showing an example of a first automobile selection information storage means according to the present embodiment. [Figure 4] FIG. 3 is a diagram showing an example of a sales point storage means according to the present embodiment. [Figure 5] FIG. 2 is a diagram showing an example of a sales amount storage means according to the present embodiment. [Figure 6] FIG. 3 is a diagram illustrating an example of a store attribute storage means according to the present embodiment. [Figure 7] FIG. 3 is a diagram showing an example of an automobile selection information storage means according to the present embodiment. [Figure 8]1 is a diagram illustrating an example of a hardware configuration of an auction support device according to an embodiment of the present invention. [Figure 9] 10 is a flowchart showing a flow of an example of processing by the auction support device according to the present embodiment. [Figure 10] 10 is a flowchart showing a flow of an example of processing by the auction support device according to the present embodiment. [Figure 11] 10 is a flowchart showing a flow of an example of processing by the auction support device according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION
[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described with reference to the drawings. (Operation principle of the auction support device according to this embodiment)
[0010] An overview of an auction support device 100 according to this embodiment (hereinafter simply referred to as "the device") will be described using Figure 1. Figure 1 is a diagram showing the connection relationship between the device 100 and other devices. The device 100 is connected to a user terminal 490 and a store terminal 410 via a communication network 480.
[0011] The communication network 480 may be a public communication network such as the Internet, and may be wired or wireless. The user terminal 490 is a terminal operated by the user 420 of the device 100, and may be a mobile information terminal such as a smartphone or a personal computer.
[0012] The store terminal 410 is installed in a store 390 for using the car auction participation service provided by the device 100, and is operated by a user 420 who visits the store 390 in order to use the car auction participation service provided by the device 100. As will be described later, the store 390 can take various forms, such as an urban or suburban type, an independent store, or a store installed in a shopping mall.
[0013] Fig. 2 is a functional block diagram of the device 100. As shown in Fig. 2, the device 100 includes a first vehicle selection information storage means 110, a sales point storage means 120, a sales amount storage means 130, a store attribute storage means 140, a second vehicle selection information storage means 150, an exhibition information acquisition means 160, a characteristic information acquisition means 170, a first vehicle selection means 180, a first detection information provision means 190, a sales point extraction means 200, a proposal creation means 210, a sales amount extraction means 220, a net amount calculation means 230, a user behavior analysis means 240, a similar store identification means 250, a second vehicle selection means 260, and a second detection information provision means 270.
[0014] The first vehicle selection information storage means 110 stores, in association with each other, user characteristic information 430 that indicates the characteristics of the user 420 and vehicle identification information 330 that identifies vehicles that the user 420 may be interested in. The user characteristic information 430 is not particularly limited as long as it is information that indicates the characteristics of the user 420, and may include, for example, the lifestyle, family structure, occupation, age, sex, annual income, hobbies, type of housing (owner-occupied or rented, apartment or detached house), whether or not the user 420 owns a vehicle, and the like.
[0015] The automobile identification information 330 is information for identifying differences in the automobiles put up for auction 310, such as the model, grade, new car registration year, color, equipment, etc.
[0016] Fig. 3 is a diagram showing an example of the first vehicle selection information storage means 110. As shown in Fig. 3, the first vehicle selection information storage means 110 stores, for example, user characteristic information 430: having children, and vehicle identification information 330: minivan A, 3-5 years old, white or black, sliding door, etc. In addition, the first vehicle selection information storage means 110 stores, for example, user characteristic information 430: likes camping, and vehicle identification information 330: SUVC, four-wheel drive, etc., in association with each other.
[0017] 3, the first vehicle selection information storage means 110 may store one piece of user characteristic information 430 in association with a plurality of pieces of vehicle identification information 330. The first vehicle selection information storage means 110 may store one piece of user characteristic information 430 in association with a single piece of vehicle identification information 330.
[0018] The sales point storage means 120 stores a combination of user characteristic information 430 and vehicle identification information 330 in association with sales point information 340 when introducing a vehicle identified by the vehicle identification information 330 to the user 420. Here, the sales point information 340 is information indicating the merits of the user 420 purchasing the introduced vehicle, the reason for introducing a vehicle corresponding to the user 420, etc.
[0019] 4 is a diagram showing an example of the sales point storage means 120. As shown in FIG. 4, the sales point storage means 120 stores, for example, a combination of user characteristic information 430: having children, and automobile identification information 330: minivan A, 3-5 years old, white, sliding door, ..., in association with sales point information 340: easy to get in and out of when dropping off and picking up children from kindergarten or nursery school. Reasonable price.
[0020] In addition, the sales point storage means 120 stores, for example, the combination of user characteristic information 430: elderly person and automobile identification information 330: hybrid D, 3-5 years old, gray, brake assist function, ... in association with sales point information 340: realize safe driving with comprehensive driving assistance functions!
[0021] The sales amount storage means 130 stores the automobile identification information 330 in association with the estimated sales amount 370 of the automobile identified by the automobile identification information 330. In other words, the sales amount storage means 130 stores the estimated sales amount 370 for each automobile.
[0022] Fig. 5 is a diagram showing an example of the sales amount storage means 130. As shown in Fig. 5, the sales amount storage means 130 stores, for example, automobile identification information 330 such as model E, model year 2020, color white, equipment with collision safety device, etc., in association with an expected sales amount 370 of 1,500,000 yen. The sales amount storage means 130 also stores, for example, automobile identification information 330 such as model F, model year 2019, color black, equipment with car navigation system, etc., in association with an expected sales amount 370 of 900,000 yen.
[0023] The store attribute storage means 140 is connected to the device 100 and stores store attribute information 400, which is information representing the characteristics of the store 390, for each store 390 in which a store terminal 410 is installed for using the services provided by the device 100. The store attribute information 400 is information that distinguishes and identifies the characteristics of the store 390, such as whether the store is urban or suburban, the store format (standalone or installed in a shopping mall), and the main customer base.
[0024] Fig. 6 is a diagram showing an example of store attribute storage means 140. As shown in Fig. 6, store attribute storage means 140 stores, for example, store identification information 100 in association with store attribute information 400 indicating that the area is one of Tokyo's 23 wards and that the location is in a building in an office district. Also, store attribute storage means 140 stores, for example, store identification information 200 in association with store attribute information 400 indicating that the area is Saitama / Saitama City and that the location is installed in a suburban shopping mall.
[0025] The second vehicle selection information storage means 150 stores the preference tendency 460 of the store user 440 who uses the store 390 and the vehicle identification information 330 that identifies the vehicle that the store user 440 is likely to be interested in, in association with each other.
[0026] Fig. 7 is a diagram showing an example of the second vehicle selection information storage means 150. As shown in Fig. 7, the second vehicle selection information storage means 150 stores, for example, preference tendency 460: preference for imported cars, and vehicle identification information 330: imported vehicle AA, one year old, black, ... in association with each other. Furthermore, the second vehicle selection information storage means 150 stores, for example, preference tendency 460: being an early adopter, and vehicle identification information 330: EV vehicle CC, three years old, ... in association with each other.
[0027] The selling information acquisition means 160 acquires selling information 320 related to the automobile auction 310. The selling information 320 is information (automobile identification information 330) related to automobiles being offered at the auction 310 at the time of processing by the selling information acquisition means 160. By processing the selling information acquisition means 160, it is possible to know what kind of automobiles are being offered at the auction 310.
[0028] The characteristic information acquiring means 170 acquires one piece of user characteristic information 430 related to one user 420. One user 420 may be, for example, a user who uses a service provided by the device 100 using a user terminal 490, or may be a user who visits the store 390.
[0029] For example, the characteristic information acquiring means 170 acquires information such as "having children" and "liking camping" as one piece of user characteristic information 430 for one user 420.
[0030] The first vehicle selection means 180 extracts one piece of vehicle identification information 330 corresponding to one piece of user characteristic information 430 acquired by the characteristic information acquisition means 170 from the first vehicle selection information storage means 110. Through the processing by the first vehicle selection means 180, it is possible to automatically select a vehicle that meets the needs that the user 420 has implicitly or unconsciously, rather than a vehicle other than the vehicle that the user 420 directly desires.
[0031] 3, when the characteristic information acquisition means 170 acquires "having children" as user characteristic information 430, the first vehicle selection means 180 extracts, for example, "minivan A, 3-5 years old, white or black, sliding door, ..." as vehicle identification information 330. At the same time, the first vehicle selection means 180 may also extract, for example, "light vehicle B, 1 year old, white or black, large door opening, ..." as vehicle identification information 330.
[0032] As shown in Figure 3, when the characteristic information acquisition means 170 acquires "likes camping" as user characteristic information 430, the first vehicle selection means 180 extracts, for example, "SUVC, four-wheel drive, ..." as vehicle identification information 330.
[0033] The first detected information providing means 190 detects, based on the auction information 320, that a vehicle identified by the vehicle identification information 330 extracted by the first vehicle selection means 180 has been put up for auction 310. Then, the first detected information providing means 190 provides information about the detected vehicle to the user 420 who provided the user characteristic information 430. Possible methods of providing the information include, but are not limited to, email, short message, and application push notification.
[0034] The sales point extraction means 200 extracts, from the sales point storage means 120, sales point information 340 corresponding to the user characteristic information 430 acquired by the characteristic information acquisition means 170 and the vehicle identification information 330 extracted by the first vehicle selection means 180.
[0035] The processing by the sales point extraction means 200 clarifies the reason for introducing the vehicle to the user 420, and promotes the use of the service by those who wish to purchase the vehicle 420, 440.
[0036] Assume that the characteristic information acquisition means 170 acquires "having children" as user characteristic information 430, and the first vehicle selection means 180 extracts "minivan A, 3-5 years old, white or black, sliding doors, ..." as vehicle identification information 330. As shown in Fig. 4, the selling point extraction means 200 extracts, for example, "easy to get in and out of when dropping off and picking up children at kindergarten or nursery school, and reasonably priced" as corresponding selling point information 340.
[0037] Also, assume that the characteristic information acquisition means 170 acquires "elderly" as user characteristic information 430, and the first vehicle selection means 180 extracts "hybrid D, 3-5 years old, gray, brake assist function, ..." as vehicle identification information 330. As shown in Fig. 4, the selling point extraction means 200 extracts, for example, "Enhance safe driving with comprehensive driving assistance functions!" as the corresponding selling point information 340.
[0038] The proposal creation means 210 creates a proposal 350 for the vehicle identified by the vehicle identification information 330 extracted by the first vehicle selection means 180, based on the sales point information 340 extracted by the sales point extraction means 200. The proposal creation means 210 may, for example, insert the sales point information 340 extracted by the sales point extraction means 200 into a template for the proposal 350.
[0039] Furthermore, the proposal creation means 210 may provide the sales point information 340 extracted by the sales point extraction means 200 to a generating AI (Artificial Intelligence) 360 and request the generating AI 360 to create a proposal 350.
[0040] The processing by the proposal creation means 210 makes the reason for recommending the vehicle to the user 420 clear and easy to understand, thereby promoting the use of the service by those who wish to purchase the vehicle 420, 440. The first detected information providing means 190 may provide the proposal 350 to the user 420.
[0041] When one user 420 owns a car, the selling price extraction means 220 extracts the estimated selling price 370 of the car owned by the one user 420 from the selling price storage means 130.
[0042] Assume that one user 420 owns a car identified by the following automobile identification information 330: "model type E, model year 2020, color gray, equipped with collision safety device, ...." As shown in FIG. 5, the sales amount extraction means 220 extracts, for example, "1,500,000 yen" as the expected sales amount 370.
[0043] Also, assume that one user 420 owns a car identified by the car identification information 330: "model F, year 2019, color black, equipment includes car navigation, ...." As shown in FIG. 5, the sales amount extraction means 220 extracts, for example, "900,000 yen" as the expected sales amount 370.
[0044] The net amount calculation means 230 calculates a net expenditure amount 380 for purchasing the vehicle based on the acquisition cost of the vehicle identified by the vehicle identification information 330 extracted by the first vehicle selection means 180 and the estimated sales amount 370 extracted by the sales amount extraction means 220. At this time, the first detection information provision means 190 provides the net expenditure amount 380 to the user 420.
[0045] The net amount calculation means 230 calculates a net expenditure amount 380 for purchasing the vehicle based on the acquisition cost of the vehicle identified by the vehicle identification information 330 extracted by the second vehicle selection means 260 and the estimated sales amount 370 extracted by the sales amount extraction means 220. At this time, the second detection information provision means 270 provides the net expenditure amount 380 to the store user 440.
[0046] Processing by the net amount calculation means 230 makes it possible to provide the user 420 with a financial guideline for purchasing a car, thereby promoting the use of the service by those wishing to purchase a car 420, 440.
[0047] The user behavior analysis means 240 identifies a preference tendency 460 of a store user 440 at one store 390 based on an operation 450 of the store user 440 at a store terminal 410 installed at the one store 390 .
[0048] Furthermore, the user behavior analysis means 240 identifies preference trends 460 of store users 440 at one store 390 based on contract information 470 of the auction 310 at the one store 390 .
[0049] Here, preference trends 460 are information that identifies the preferences of store users 440, such as, for example, "I like imported cars," "I'm an early adopter," or "I like SUVs," but are not limited to these examples.
[0050] The similar store identification means 250 identifies another store 390 whose store attribute information 400 is similar to that of the one store 390 from the store attribute storage means 140. Here, the criteria for determining whether the one store 390 and the other store 390 are similar to each other can be determined as appropriate.
[0051] The second vehicle selection means 260 extracts, from the second vehicle selection information storage means 150, vehicle identification information 330 that corresponds to the preference tendency 460 identified by the user behavior analysis means 240.
[0052] Assume that the user behavior analysis means 240 has identified "likes imported cars" as preference tendency 460. As shown in FIG. 7, the second automobile selection means 260 extracts, for example, "model is imported car AA," "year is one year old," "color is black," and "..." as automobile identification information 330. At the same time, the second automobile selection means 260 also extracts, for example, "model is imported car BB," "year is one year old," "color is black," and "..." as automobile identification information 330.
[0053] Assume that the user behavior analysis means 240 has identified "early adopter" as the preference tendency 460. As shown in Fig. 7, the second vehicle selection means 260 extracts, for example, "vehicle type is EV CC," "model year is three years old," and "..." as the vehicle identification information 330.
[0054] The second detected information providing means 270 detects, based on the auction information 320, that a vehicle identified by the vehicle identification information 330 extracted by the second vehicle selection means 260 has been put up for auction 310. Then, the second detected information providing means 270 provides information about the detected vehicle to store users 440 at other stores 390 identified by the similar store identification means 250. Possible methods of providing the information include, but are not limited to, email, short messages, and application push notifications.
[0055] By the processing by the above means 240 to 270, it is possible to automatically select and introduce cars that meet the needs that the store user 440 has subconsciously, rather than cars other than those that the store user 440 directly desires, thereby promoting the use of the service by those who wish to purchase cars 420, 440.
[0056] Based on the above-described operating principle, the device 100 supports businesses that provide an automobile auction service 310 and promotes the use of the service by would-be automobile buyers 420, 440. (Hardware Configuration of the Auction Support Device According to the Present Embodiment)
[0057] An example of the hardware configuration of the present device 100 will be described using Fig. 8. Fig. 8 is a diagram showing an example of the hardware configuration of the present device 100. As shown in Fig. 8, the present device 100 has a CPU (Central Processing Unit) 510, a ROM (Read-Only Memory) 520, a RAM (Random Access Memory) 530, an auxiliary storage device 540, a communication I / F 550, an input device 560, a display device 570, and a recording medium I / F 580.
[0058] CPU 510 is a device that executes programs stored in ROM 520, performs arithmetic processing on data loaded into RAM 530 in accordance with program instructions, and controls the entire device 100. ROM 520 stores programs and data to be executed by CPU 510. When CPU 510 executes a program stored in ROM 520, the programs and data to be executed are loaded into RAM 530, and RAM 530 temporarily holds the arithmetic data during the calculation.
[0059] The auxiliary storage device 540 is a device that stores the OS (Operating System), which is basic software, the application program according to the present embodiment, and the like, together with related data. The auxiliary storage device 540 is, for example, a hard disk drive (HDD) or a flash memory.
[0060] The communication I / F 550 is an interface for connecting to a communication network 480 such as a wired or wireless LAN (Local Area Network) or the Internet, and for transmitting and receiving data to and from another device 410 that provides a communication function.
[0061] The input device 560 is a device such as a keyboard for inputting data into the device 100. The display device (output device) 570 is a device formed of an LCD (Liquid Crystal Display) or the like, and functions as a user interface when the user uses the functions of the device 100 or when making various settings. The recording medium I / F 580 is an interface for sending and receiving data to and from a recording medium 590 such as a CD-ROM, DVD-ROM, or USB memory.
[0062] Each of the means included in device 100 may be realized by CPU 510 executing a program corresponding to each of the means stored in ROM 520 or auxiliary storage device 540. Each of the means included in device 100 may also be realized by hardware that performs the processing associated with the means. Alternatively, device 100 may be caused to execute the program by reading the program according to the present invention from an external server device via communication I / F 550 or by reading the program according to the present invention from storage device 590 via recording medium I / F 580. (Example of processing by the auction support device according to this embodiment) An example of processing by the device 100 will be described below. (1) Proposal process to the user 420 by the device 100
[0063] The process of making a suggestion to the user 420 by the device 100 will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the flow of an example of the process of making a suggestion to the user 420 by the device 100.
[0064] In S10, the selling information acquisition means 160 acquires selling information 320 related to the automobile auction 310. The selling information 320 is information (automobile identification information 330) related to automobiles being offered at the auction 310 at the time of processing by the selling information acquisition means 160. By processing the selling information acquisition means 160, it is possible to know what kind of automobiles are being offered at the auction 310.
[0065] In S20, characteristic information acquisition means 170 acquires one user characteristic information 430 related to one user 420. One user 420 may be, for example, a user who uses a service provided by device 100 using user terminal 490, or may be a user who visits store 390.
[0066] For example, the characteristic information acquiring means 170 acquires information such as "having children" and "liking camping" as one piece of user characteristic information 430 for one user 420.
[0067] In S30, the first vehicle selection means 180 extracts from the first vehicle selection information storage means 110 one piece of vehicle identification information 330 that corresponds to one piece of user characteristic information 430 acquired in S20.
[0068] 3, when the characteristic information acquisition means 170 acquires "having children" as user characteristic information 430, the first vehicle selection means 180 extracts, for example, "minivan A, 3-5 years old, white or black, sliding door, ..." as vehicle identification information 330. At the same time, the first vehicle selection means 180 may also extract, for example, "light vehicle B, 1 year old, white or black, large door opening, ..." as vehicle identification information 330.
[0069] As shown in Figure 3, when the characteristic information acquisition means 170 acquires "likes camping" as user characteristic information 430, the first vehicle selection means 180 extracts, for example, "SUVC, four-wheel drive, ..." as vehicle identification information 330.
[0070] In S50, the sales point extraction means 200 extracts from the sales point storage means 120 the sales point information 340 corresponding to the user characteristic information 430 acquired in S20 and the automobile identification information 330 extracted in S30.
[0071] Assume that the characteristic information acquisition means 170 acquires "having children" as user characteristic information 430, and the first vehicle selection means 180 extracts "minivan A, 3-5 years old, white or black, sliding doors, ..." as vehicle identification information 330. As shown in Fig. 4, the selling point extraction means 200 extracts, for example, "easy to get in and out of when dropping off and picking up children at kindergarten or nursery school, and reasonably priced" as corresponding selling point information 340.
[0072] Also, assume that the characteristic information acquisition means 170 acquires "elderly" as user characteristic information 430, and the first vehicle selection means 180 extracts "hybrid D, 3-5 years old, gray, brake assist function, ..." as vehicle identification information 330. As shown in Fig. 4, the selling point extraction means 200 extracts, for example, "Enhance safe driving with comprehensive driving assistance functions!" as the corresponding selling point information 340.
[0073] Furthermore, in S50, the proposal creation means 210 creates a proposal 350 for the vehicle identified by the vehicle identification information 330 extracted in S30, based on the sales point information 340 extracted in S50. The proposal creation means 210 may, for example, insert the sales point information 340 extracted by the sales point extraction means 200 into a template for the proposal 350.
[0074] Furthermore, the proposal creation means 210 may provide the sales point information 340 extracted by the sales point extraction means 200 to a generating AI (Artificial Intelligence) 360 and request the generating AI 360 to create a proposal 350.
[0075] In S60, the first detection information providing means 190 detects, based on the auction information 320, that the automobile identified by the automobile identification information 330 extracted in S30 has been put up for auction 310. Furthermore, in S60, the first detection information providing means 190 provides the information about the automobile detected in S60 and the proposal 350 created in S50 to the user 420 who provided the user characteristic information 430 in S20. Possible methods of providing this information include, but are not limited to, email, short message, and application push notification.
[0076] By carrying out the above-described processing, the device 100 supports the business that provides the car auction service 310 and promotes the use of the service by those who wish to purchase cars 420, 440. (2) Proposal processing to the store user 440 by the device 100
[0077] The process of making a suggestion to the store user 440 by the device 100 will be described with reference to Fig. 10. Fig. 10 is a flowchart showing the flow of an example of the process of making a suggestion to the store user 440 by the device 100.
[0078] In S110, the selling information acquisition means 160 acquires selling information 320 related to the automobile auction 310. The selling information 320 is information (automobile identification information 330) related to automobiles being offered at the auction 310 at the time of processing by the selling information acquisition means 160. By processing the selling information acquisition means 160, it is possible to know what kind of automobiles are being offered at the auction 310.
[0079] In S120, the user behavior analysis means 240 identifies a preference tendency 460 of a store user 440 in one store 390 based on an operation 450 of the store user 440 at a store terminal 410 installed in the one store 390.
[0080] In addition, in S120, the user behavior analysis means 240 may be configured to identify the preference trends 460 of the store users 440 at one store 390 based on the contract information 470 of the auction 310 at one store 390.
[0081] Here, preference trends 460 are information that identifies the preferences of store users 440, such as, for example, "I like imported cars," "I'm an early adopter," or "I like SUVs," but are not limited to these examples.
[0082] In S130, the second vehicle selection means 260 extracts, from the second vehicle selection information storage means 150, the vehicle identification information 330 that corresponds to the preference tendency 460 identified in S120.
[0083] Assume that the user behavior analysis means 240 has identified "likes imported cars" as preference tendency 460. As shown in FIG. 7, the second automobile selection means 260 extracts, for example, "model is imported car AA," "year is one year old," "color is black," and "..." as automobile identification information 330. At the same time, the second automobile selection means 260 also extracts, for example, "model is imported car BB," "year is one year old," "color is black," and "..." as automobile identification information 330.
[0084] Assume that the user behavior analysis means 240 has identified "early adopter" as the preference tendency 460. As shown in Fig. 7, the second vehicle selection means 260 extracts, for example, "vehicle type is EV CC," "model year is three years old," and "..." as the vehicle identification information 330.
[0085] In S140, the similar store identification means 250 identifies other stores 390 whose store attribute information 400 is similar to that of the one store 390 from the store attribute storage means 140. Here, the criteria for determining whether the one store 390 and the other stores 390 are similar to each other can be determined as appropriate.
[0086] At S150, the second detected information providing means 270 detects, based on the auction information 320, that the automobile identified by the automobile identification information 330 extracted at S130 has been put up for auction at the auction 310. Furthermore, at S150, the second detected information providing means 270 provides information about the detected automobile to the store user 440 at the other store 390 identified at S140. Possible methods of providing the information include, but are not limited to, email, short message, and application push notification.
[0087] By carrying out the above-described processing, the device 100 supports the business that provides the car auction service 310 and promotes the use of the service by those who wish to purchase cars 420, 440. (3) Proposal processing by the device 100 to the user 420 or the store user 440
[0088] The process of making a proposal to the user 420 or the store user 440 by the device 100 will be described with reference to Fig. 11. Fig. 9 is a flowchart showing the flow of an example of the process of making a proposal to the user 420 or the store user 440 by the device 100.
[0089] In S210, if one user 420 owns a car, the sales amount extraction means 220 extracts the estimated sales amount 370 of the car owned by the one user 420 from the sales amount storage means 130.
[0090] Assume that one user 420 owns a car identified by the following automobile identification information 330: "model type E, model year 2020, color gray, equipped with collision safety device, ...." As shown in FIG. 5, the sales amount extraction means 220 extracts, for example, "1,500,000 yen" as the expected sales amount 370.
[0091] Also, assume that one user 420 owns a car identified by the car identification information 330: "model F, year 2019, color black, equipment includes car navigation, ...." As shown in FIG. 5, the sales amount extraction means 220 extracts, for example, "900,000 yen" as the expected sales amount 370.
[0092] In S220, the net amount calculation means 230 calculates the net expenditure amount 380 for purchasing the vehicle based on the acquisition cost of the vehicle identified by the vehicle identification information 330 extracted in S30 and the expected selling price 370 extracted in S210.
[0093] In addition, in S220, the net amount calculation means 230 may calculate the net expenditure amount 380 for purchasing the vehicle based on the acquisition cost of the vehicle identified by the vehicle identification information 330 extracted in S130 and the expected sales price 370 extracted in S220.
[0094] In S230, the first detected information providing means 190 provides the net expenditure amount 380 to the user 420. Alternatively, the second detected information providing means 270 may provide the net expenditure amount 380 to the store user 440 in S230.
[0095] By carrying out the above-described processing, the device 100 supports the business that provides the car auction service 310 and promotes the use of the service by those who wish to purchase cars 420, 440.
[0096] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the present invention as defined in the claims. [Explanation of symbols]
[0097] 100 Auction Support Device 110 First vehicle selection information storage means 120 Sales point storage means 130 Sales amount storage means 140 Store attribute storage means 150 Second vehicle selection information storage means 160 Listing information acquisition means 170 Feature information acquisition means 180 First vehicle selection method 190 First detection information providing means 200 Selling Point Extraction Method 210 Proposal Creation Methods 220 Sales amount extraction means 230 Net amount calculation method 240 User Behavior Analysis Tools 250 Means for identifying similar stores 260 Second vehicle selection method 270 Second detection information provision means 310 Car Auction 320 Listing Information 330 Motor Vehicle Identification Information 340 Selling Point Information 350 Proposal 360 Generation AI 370 Estimated sales price 380 Net expenditures 390 stores 400 Store attribute information 410 Store terminal 420 users 430 User Characteristics Information 440 store users 450 Store User Operations 460 Store User Preferences 470 Auction sales information 480 Communication Network 490 user terminals 510 CPU 520 ROM 530 RAM 540 Auxiliary storage 550 Communication Interface 560 Input Device 570 Output Device 580 Recording Media Interface 590 Recording Media
Claims
1. a first vehicle selection information storage means for storing user characteristic information representing a user's characteristics and vehicle identification information identifying a vehicle that the user is likely to be interested in, in association with each other; a means for acquiring listing information relating to automobile auctions; a feature information acquisition means for acquiring one of the user feature information related to one of the users; a first vehicle selection means for extracting one of the vehicle identification information corresponding to the one of the user characteristic information from the first vehicle selection information storage means; and a first detection information providing means for detecting, based on the auction listing information, that a vehicle identified by the one vehicle identification information has been put up for auction, and providing information about the detected vehicle to the one user.
2. a sales point storage means for storing a combination of the user characteristic information and the vehicle identification information in association with sales point information when introducing the vehicle identified by the vehicle identification information to the user; a sales point extraction means for extracting, from the sales point storage means, one piece of sales point information corresponding to the one piece of user characteristic information and the one piece of automobile identification information; 2. The auction support device according to claim 1, further comprising proposal creation means for creating a proposal for the vehicle identified by said one piece of vehicle identification information based on said one piece of selling point information.
3. 3. The auction support device according to claim 2, wherein the proposal creation means provides the one selling point information to a generation AI (Artificial Intelligence) and requests the generation AI to create a proposal regarding the vehicle identified by the one vehicle identification information.
4. a sales price storage means for storing an automobile and an estimated sales price of the automobile in association with each other; a sales price extraction means for extracting an estimated sales price of the vehicle owned by the one user from the sales price storage means when the one user owns the vehicle; and a net amount calculation means for calculating a net expenditure amount when purchasing the vehicle identified by the one vehicle identification information based on the acquisition cost of the vehicle identified by the one vehicle identification information and the estimated sales amount extracted by the sales amount extraction means, 3. The auction support device according to claim 2, wherein the first detection information providing means provides the net expenditure amount.
5. a store attribute storage means for storing store attribute information representing characteristics of each store that is connected to the auction support device and that has a store terminal installed for using services provided by the auction support device; a user behavior analysis means for identifying a preference trend of a store user at one of the stores based on an operation of the store user at the store terminal installed at the one of the stores; a similar store specifying means for specifying another store having similar store attribute information to the one store from the store attribute storage means; a second vehicle selection information storage means for storing the preference tendency and vehicle identification information that identifies a vehicle that the store user is likely to be interested in, in association with each other; a second vehicle selection means for extracting, from the second vehicle selection information storage means, the vehicle identification information corresponding to the preference tendency identified by the user behavior analysis means; and a second detection information providing means for detecting, based on the auction listing information, that a vehicle identified by the vehicle identification information extracted by the second vehicle selection means has been put up for auction, and providing information about the detected vehicle to the store user at the other store.
6. a store attribute storage means for storing store attribute information representing characteristics of each store that is connected to the auction support device and that has a store terminal installed for using services provided by the auction support device; a user behavior analysis means for identifying the preference trends of store users at one of the stores based on the contract information of the auction at the one of the stores; a similar store specifying means for specifying another store having similar store attribute information to the one store from the store attribute storage means; a second vehicle selection information storage means for storing the preference tendency and vehicle identification information that identifies a vehicle that the store user is likely to be interested in, in association with each other; a second vehicle selection means for extracting, from the second vehicle selection information storage means, the vehicle identification information corresponding to the preference tendency identified by the user behavior analysis means; and a second detection information providing means for detecting, based on the auction listing information, that a vehicle identified by the vehicle identification information extracted by the second vehicle selection means has been put up for auction, and providing information about the detected vehicle to the store user at the other store.
7. An auction support method executed on a computer having a first automobile selection information storage means that stores user characteristic information that represents a user's characteristics and automobile identification information that identifies automobiles that the user is likely to be interested in, in association with each other, the method comprising: A step in which a commodity information acquisition means acquires commodity information related to an automobile auction; A step in which a feature information acquisition means acquires one of the user feature information related to one of the users; A step in which a first vehicle selection means extracts one of the vehicle identification information corresponding to the one of the user characteristic information from the first vehicle selection information storage means; a step in which a first detection information providing means detects, based on the auction information, that a vehicle identified by the one vehicle identification information has been put up for auction, and provides information about the detected vehicle to the one user.
8. the computer has a sales point storage means for storing a combination of the user characteristic information and the vehicle identification information in association with sales point information for use in introducing the vehicle identified by the vehicle identification information to the user; a step in which a sales point extraction means extracts, from the sales point storage means, one piece of sales point information corresponding to the one piece of user characteristic information and the one piece of vehicle identification information; 8. The auction support method according to claim 7, further comprising a step in which proposal creation means creates a proposal for the vehicle identified by said one vehicle identification information based on said one selling point information.
9. The auction support method according to claim 8, characterized in that the proposal creation means provides the one selling point information to a generation AI (Artificial Intelligence) and requests the generation AI to create a proposal regarding the vehicle identified by the one vehicle identification information.
10. The computer has a sales price storage means for storing an automobile and an estimated sales price of the automobile in association with each other, a step in which a sales price extraction means extracts an estimated sales price of the automobile owned by the one user from the sales price storage means when the one user owns an automobile; a step in which a net amount calculation means calculates a net expenditure amount when purchasing the vehicle identified by the one vehicle identification information based on the acquisition cost of the vehicle identified by the one vehicle identification information and the expected sales amount extracted by the sales amount extraction means; 9. The auction support method according to claim 8, wherein the first detection information providing means provides the net expenditure amount.
11. the computer has a store attribute storage means for storing store attribute information representing characteristics of each store, the store attribute information being connected to the computer and having a store terminal for using a service provided by the computer installed therein; a step in which user behavior analysis means identifies a preference tendency of the store user at the one store based on an operation of the store user at the store terminal installed in the one store; a step in which a similar store specifying means specifies, from the store attribute storage means, another store whose store attribute information is similar to that of the one store, The computer further comprises a second vehicle selection information storage means for storing the preference tendency and vehicle identification information that identifies vehicles that the store user is likely to be interested in, in association with each other; A step in which a second vehicle selection means extracts the vehicle identification information corresponding to the preference tendency identified by the user behavior analysis means from the second vehicle selection information storage means; The auction support method according to claim 7, further comprising a step in which a second detection information providing means detects, based on the auction listing information, that a vehicle identified by the vehicle identification information extracted by the second vehicle selection means has been put up for auction, and provides information about the detected vehicle to the store user at the other store.
12. the computer has a store attribute storage means for storing store attribute information representing characteristics of each store, the store attribute information being connected to the computer and having a store terminal for using a service provided by the computer installed therein; a step in which user behavior analysis means identifies preference trends of store users at one of the stores based on contract information of the auction at the one of the stores; a step in which a similar store specifying means specifies, from the store attribute storage means, another store whose store attribute information is similar to that of the one store, The computer further comprises a second vehicle selection information storage means for storing the preference tendency and vehicle identification information that identifies vehicles that the store user is likely to be interested in, in association with each other; A step in which a second vehicle selection means extracts the vehicle identification information corresponding to the preference tendency identified by the user behavior analysis means from the second vehicle selection information storage means; The auction support method according to claim 7, further comprising a step in which a second detection information providing means detects, based on the auction listing information, that a vehicle identified by the vehicle identification information extracted by the second vehicle selection means has been put up for auction, and provides information about the detected vehicle to the store user at the other store.
13. An auction support program for causing a computer to execute the method according to any one of claims 7 to 12.