Computer, method executed by computer, and program

Abstract

To allow only a good buyer to register his / her desired condition in a condition database.SOLUTION: The computer according to the present invention is connected to a member database that stores a flag indicating whether each member is a good buyer for the purchase of real estate property, and a condition database that stores information indicating the desired conditions for the purchase of real estate property for each member who is indicated as a good buyer by the flag, and the computer determines whether the user connected to the computer is a good buyer registered in the member database, and when it determines that the user is a qualified buyer registered in the member database, displays a page for entering desired conditions, and registers the information entered on the page as information indicating the user's desired conditions in the condition database.SELECTED DRAWING: Figure 11

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program, and more particularly to an information processing apparatus, an information processing method, and a program used for selling real estate properties such as condominiums.

Background Art

[0002] In recent years, in the sale of real estate properties such as condominiums, the use of sales sites installed on the Web has been increasing. According to the sales site, it becomes easier to reach potential customers compared to waiting at the real estate agency's storefront, so it becomes possible to expect an improvement in the closing rate.

[0003] Patent Document 1 discloses an example of a sales support apparatus used at a real estate sales site. The sales support apparatus according to this example has a function of allowing a purchaser to input a desired monthly payment amount and extracting and displaying real estate properties for which the total monthly payment amount is less than or equal to the desired payment amount.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Incidentally, potential real estate buyers include those who are living in rental properties. That is, among those living in rental properties, there are people who are living while thinking that it might be better to purchase rather than continue renting, and such people can be said to be potential real estate buyers. Therefore, there is a need for a technology that can effectively appeal to people living in rental properties to purchase real estate for relocation. In this regard, it might seem that the technology described in Patent Document 1 can present real estate suitable for potential buyers, but since the potential buyers arbitrarily input the monthly desired payment amount that is the basis for extraction, the presented real estate is not necessarily suitable for the potential buyers.

[0006] Therefore, one object of the present invention is to provide an information processing apparatus, an information processing method, and a program that can effectively appeal to people living in rental properties to purchase real estate for relocation.

[0007] Also, as a provider of a sales site, attracting high-quality buyers with high purchasing intent and corresponding financial resources to one's own site is one of the points for improving the conversion rate. However, it has been difficult to attract high-quality buyers on conventional sales sites that treat all buyers equally.

[0008] Therefore, another object of the present invention is to provide an information processing apparatus, an information processing method, and a program that can provide a sales site capable of attracting high-quality buyers.

Means for Solving the Problems

[0009] An information processing apparatus according to a first aspect of the present invention extracts one or more properties from a database that stores information on a plurality of properties based on input rental property information, which is rental property information input by a first user, and outputs information indicating each of the one or more extracted properties to the first user.

[0010] The information processing apparatus according to the second aspect of the present invention registers the information of the property for sale input by the second user, who is the seller, in either a property database that stores information on a plurality of properties for sale or a non-public property database that stores information on a plurality of non-public properties for sale according to the selection of the second user, registers information indicating the desired conditions of the property to be purchased input by the third user, who is the buyer, in a condition database, and distributes the information of the property for sale to the third user when the property for sale registered in the property database or the non-public property database matches the desired conditions registered in the condition database.

[0011] The information processing method according to the first aspect of the present invention includes a step of extracting one or more properties from a database that stores information on a plurality of properties based on input rental property information, which is information on a rental property input by a first user, and a step of outputting information indicating each of the one or more extracted properties to the first user.

[0012] The information processing method according to the second aspect of the present invention includes a step of registering the information of the property for sale input by the second user, who is the seller, in either a property database that stores information on a plurality of properties for sale or a non-public property database that stores information on a plurality of non-public properties for sale according to the selection of the second user, a step of registering information indicating the desired conditions of the property to be purchased input by the third user, who is the buyer, in a condition database, and a step of distributing the information of the property for sale to the third user when the property for sale registered in the property database or the non-public property database matches the desired conditions registered in the condition database.

[0013] The program according to the first aspect of the present invention causes a computer to execute a step of extracting one or more properties from a database that stores information on a plurality of properties based on input rental property information, which is rental property information input by a first user, and a step of outputting information indicating each of the one or more extracted properties to the first user.

[0014] The program according to the first aspect of the present invention causes a computer to execute a step of registering, according to the selection of a second user who is a seller, the information on the property for sale input by the second user in either a property database that stores information on a plurality of properties for sale or a non-public property database that stores information on a plurality of non-public properties for sale, a step of registering in a condition database information indicating the desired conditions of a property for purchase input by a third user who is a buyer, and a step of delivering information on the property for sale to the third user when the property for sale registered in the property database or the non-public property database matches the desired conditions registered in the condition database.

Advantages of the Invention

[0015] According to the first aspect of the present invention, since the property for sale is extracted based on the information on the rental property input by the user, it becomes possible to effectively appeal to the person living in the rental property to purchase real estate for relocation.

[0016] According to the second aspect of the present invention, the information on the non-public property for sale is registered in a non-public property database provided separately from the property database, and the information on the property for sale that matches the desired conditions is delivered to the buyer who is allowed to register the desired conditions in the condition database in advance, so that it becomes possible to provide a sales site that can attract excellent buyers.

Brief Description of the Drawings

[0017]

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DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0019] FIG. 1 is a diagram showing the system configuration of an information processing system 1 according to an embodiment of the present invention. As shown in the figure, the information processing system 1 has a configuration in which an information processing apparatus 10 and user terminals 30 and 31 are interconnected via a network 3. The network 3 is, for example, the Internet, and is connected to various WEB sites including a sales site 2 that sells real estate properties such as condominiums, in addition to the information processing apparatus 10 and the user terminals 30 and 31.

[0020] The information processing apparatus 10 is a server computer, and functionally includes three types of servers, namely, a planner server 11, a members market server 12, and a recommender server 13, and seven types of databases, namely, a condominium database 20, a rental property database 21, a property database 22, a non-public property database 23, a member database 24, a condition database 25, and a delivery database 26.

[0021] Among these, the Planner Server 11 is a server that plays a role of having users living in rental properties input information on the rental properties they are living in, extracting sales properties based on the input information, and presenting them to the users. It is connected to the condominium database 20, the rental property database 21, and the property database 22. The Members Market Server 12 is a server that functions as a sales site for selling properties such as condominiums on the network 3, and is connected to the Recommender Server 13 and the property database 22. The Recommender Server 13 is a server for selling the properties uploaded to the Members Market Server 12 confidentially, and is connected to the Members Market Server 12, the property database 22, the confidential property database 23, the member database 24, the condition database 25, and the distribution database 26. Details of each will be described separately later. In this embodiment, although each server and each database will be described as being implemented in one information processing device 10, each server and each database may be implemented distributively in a plurality of information processing devices 10.

[0022] The user terminals 30 and 31 are each a computer personally used by the user. FIG. 1 shows an example in which the user terminal 30 is a smartphone and the user terminal 31 is a notebook personal computer, but the specific types of the user terminals 30 and 31 are not limited to these. For example, the user terminals 30 and 31 may be configured by a tablet computer or a desktop personal computer. Hereinafter, the description will continue on the premise that the user terminal 30 is a smartphone and the user terminal 31 is a personal computer.

[0023] FIG. 2 is a diagram showing the basic hardware configurations of the information processing device 10 and the user terminals 30 and 31 respectively. As shown in the figure, the information processing device 10 and the user terminals 30 and 31 each have a configuration in which a processor 101, a storage device 102, a communication device 103, an input device 104, and an output device 105 are interconnected via a bus 106.

[0024] The processor 101 is a central processing unit that reads and executes programs stored in the storage device 102. Each process described later as a process performed by the information processing device 10 and the user terminals 30 and 31 is realized by each processor 101 reading and executing a program stored in each storage device 102. The processor 101 is configured to be communicable with each part within the server via the bus 106, and performs control of each part, processing of data stored in the storage device 102, etc. according to the description of the program to be executed.

[0025] The storage device 102 is a device that temporarily or permanently stores various programs and various data. The storage device 102 is usually composed of a combination of a plurality of storage devices such as a main storage device composed of DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory), and an auxiliary storage device composed of a hard disk or an SSD (Solid State Drive).

[0026] The communication device 103 is a device that executes communication with an external communication device (including the network 3 shown in FIG. 1) according to the control of the processor 101. The communication method performed by the communication device 103 is not particularly limited, and examples include wired or wireless WAN (Wide Area Network) or LAN (Local Area Network).

[0027] The input device 104 is a device that receives input from a user, and includes various input means such as a mouse, a keyboard, and a touch panel. The content of the user input received by the input device 104 is transmitted to the processor 101 via the bus 106. The output device 105 is a device that outputs to the user according to the control of the processor 101, and includes various output means such as a display and a speaker.

[0028] Hereinafter, the processing executed by the information processing apparatus 10 will be described in detail. In the following description, first, the processing executed by the Planner Server 11 will be described with reference to FIGS. 3 to 8, and then, the processing executed by the Members Market Server 12 and the Recommender Server 13 will be described with reference to FIGS. 9 to 17.

[0029] First, the processing executed by the Planner Server 11 will be described. FIG. 3 is a diagram showing the structures of the condominium database 20, the rental property database 21, and the property database 22 connected to the Planner Server 11. Among these, the condominium database 20 is a database that stores information on condominiums as buildings, and is associated with a condominium ID for identifying the condominium, and stores the property name (name of the condominium), address, latitude / longitude, nearest station, walking time from the nearest station (required time when walking from the nearest station), building structure (S structure, RC structure, SRC structure, etc.), construction year (year in which the condominium was built), total number of households, return rate (a numerical value representing the apparent profitability of how much rental income can be obtained with respect to the property price), and the like.

[0030] The rental property database 21 is a database that stores information on properties such as a single room in a condominium that is a rental unit (hereinafter referred to as a "rental property"), and is associated with a rental property ID for identifying the rental property, and stores the condominium ID, rent, floor area, layout (3LDK, 1R, etc.), number of rooms (number of rooms included in the property), floor where it is located, balcony direction (south, southeast, etc.), corner room flag (information indicating whether it is a corner room), presence / absence of renovation (information indicating whether it has been renovated), type of right (information indicating whether it is a condominium with a leasehold right or a condominium with an ownership right), and the like.

[0031] The property database 22 is a database that stores information on properties such as a single room in an apartment that serves as a unit of sales (hereinafter referred to as a "judged property"), and is configured to store the apartment ID, price, price deviation score (value), exclusive area, layout (3LDK, 1R, etc.), number of rooms (number of rooms in the property), floor, balcony direction (south, southeast, etc.), and whether or not a deal has been concluded (information indicating whether or not a deal has been concluded), in association with a property for sale ID for identifying the property for sale.

[0032] The data stored in the condominium database 20, rental property database 21, and property database 22 is registered in each database by the planner server 11 or the members' market server 12. More specifically, the planner server 11 is configured to collect information on rental properties and properties for sale by visiting one or more sales sites 2 on the network 3, and register the information in each database. The members' market server 12 is configured to collect information on rental properties and properties for sale by accepting input from sellers or managers of rental properties, and register the information in each database.

[0033] 4 is a flow diagram showing the process flow of the property for sale extraction process executed by the planner server 11. The information processing device 10 plays a role of effectively appealing to people living in rental properties to purchase real estate for relocation by executing this property for sale extraction process by the planner server 11. The contents of the property for sale extraction process will be described in detail below with reference to FIG. 4.

[0034] The planner server 11 first generates an input page for information (hereinafter referred to as "input rental property information") about the currently occupied rental property (hereinafter referred to as "occupied rental property") and displays it on the display of the user terminal 30, 31 (step S1).

[0035] FIG. 7 is a diagram showing an example of a screen displayed on the display of the user terminal 30 which is a smartphone. Although an example of display on a smartphone is shown in the figure, the content is the same for the screen displayed on the user terminal 31 which is a personal computer. The information input page 40 shown in FIG. 7 is an example of the information input page displayed in step S1. As shown in the figure, in addition to the image and explanatory text, the information input page 40 has a property name input field 40a for inputting the property name of the condominium in which the user currently resides, a rent input field 40b for inputting the rent, a size input field 40c for inputting the size, a floor input field 40d for inputting the floor where it is located, a corner room button 40e for selecting whether it is a corner room or not, a south-facing button 40f for selecting whether it is south-facing or not, a renovated button 40g for selecting whether it has been renovated or not, and a transition button 40h for proceeding with the process. Among these, the property name input field 40a is preferably configured by a combo box in which the property names of each condominium stored in the condominium database 20 can be selected by the user.

[0036] Returning to FIG. 4, the planner server 11 that has displayed the information input page 40 determines whether the transition button 40h in the information input page 40 has been pressed (step S2). If the planner server 11 determines in step S2 that the transition button 40h has been pressed, after obtaining the basic information (nearest station, walking distance from the nearest station, year of construction, etc.) of the rental property in which the user resides, indicated by the input rental property information input on the information input page 40, from the condominium database 20 (step S3), it sequentially executes an appropriate rent estimation process (step S4) for estimating the appropriate rent of the rental property in which the user resides and an appropriate purchase price estimation process (step S5) for estimating the appropriate purchase price of the rental property in which the user resides.

[0037] FIG. 5 is a flowchart showing details of the appropriate rent estimation process executed in step S4. As shown in the figure, the planner server 11 that has started the appropriate rent estimation process first extracts condominiums located in the vicinity of the rented property currently in residence from the condominium database 20 (step S20). Specifically, based on the addresses in the condominium database 20, it may be possible to extract condominiums within the same ward as the rented property currently in residence, or based on the nearest station in the condominium database 20, it may be possible to extract condominiums that have the same nearest station as the rented property currently in residence, or based on the latitude and longitude in the condominium database 20, it may be possible to extract condominiums whose distance from the rented property currently in residence is within a predetermined value.

[0038] Next, the planner server 11 extracts properties similar to the rented property currently in residence (hereinafter referred to as "nearby similar rented properties") from the rented properties of the condominiums extracted in step S20 (properties stored in the rented property database 21) (step S21). Specifically, the planner server 11 first obtains the floor area, walking distance to the nearest station, and the year of construction of the rented property currently in residence. The floor area is the numerical value entered in the area input field 40c of the information input page 40 (see FIG. 7), and the walking distance to the nearest station and the year of construction are information included in the basic information obtained in step S3. The planner server 11 also obtains the condominium ID, walking distance to the nearest station, and the year of construction of each condominium extracted in step S20 from the condominium database 20, and extracts the rented property having the obtained condominium ID from the rented property database 21. Then, the planner server 11 obtains the floor area of the extracted rented property from the rented property database 21. The planner server 11 extracts nearby similar rented properties based on the floor area, walking distance to the nearest station, and the year of construction of the rented property currently in residence and other rented properties obtained as described above. Specifically, properties whose differences in floor area, walking distance to the nearest station, and the year of construction from the rented property currently in residence are each within a predetermined value may be extracted as nearby similar rented properties. Here, an example using the floor area, walking distance to the nearest station, and the year of construction as criteria for similarity judgment has been described, but of course, other criteria may be used.

[0039] Subsequently, the Planner Server 11 corrects the rent of the extracted neighboring similar rental properties so that conditions other than the criteria used for the similarity determination in step S21 match the conditions of the occupied rental property (step S22). This correction is performed based on the information input on the information input page 40 and the information of the corresponding neighboring similar rental properties. To give a specific example, when the floor where the occupied rental property is located is a low floor and the floor where the neighboring similar rental property is located is a high floor, the rent of the neighboring similar rental property is corrected in the downward direction. Also, when the occupied rental property is a corner room and the neighboring similar rental property is not a corner room, the rent of the neighboring similar rental property is corrected in the upward direction. Further, when the occupied rental property faces south and the neighboring similar rental property faces north, the rent of the neighboring similar rental property is corrected in the upward direction. Also, when the occupied rental property has been renovated and the neighboring similar rental property has not been renovated, the rent of the neighboring similar rental property is corrected in the upward direction. The degree of increase and decrease may be determined according to the stored content of a table prepared in advance that includes various cases, or various cases may be pre-learned by an artificial intelligence, and determined based on the output result of this artificial intelligence.

[0040] Finally, the Planner Server 11 obtains the average value of the corrected rent and acquires it as the appropriate rent of the occupied rental property (step S23), thereby ending the appropriate rent estimation process.

[0041] FIG. 6 is a flowchart showing details of the appropriate purchase price estimation process executed in step S5. As shown in the figure, the planner server 11 that has started the appropriate purchase price estimation process first extracts condominiums located in the vicinity of the currently occupied rental property from the condominium database 20 (step S30). Specifically, similar to step S20 described above, based on the address in the condominium database 20, it may be possible to extract condominiums within the same ward as the currently occupied rental property, or based on the nearest station in the condominium database 20, it may be possible to extract condominiums with the same nearest station as the currently occupied rental property, or based on the latitude and longitude in the condominium database 20, it may be possible to extract condominiums within a predetermined distance from the currently occupied rental property. However, in step S30, it is preferable to extract condominiums over a geographically wider range compared to the extraction in step S20 described above and step S34 described later. By doing so, in the subsequent step S31, it becomes possible to extract a larger number of properties for calculating the return.

[0042] Next, the planner server 11 extracts the properties (for-sale properties and rental properties) of the condominiums extracted in step S30 from at least one of the property database 22 and the rental property database 21, and extracts properties (hereinafter referred to as "nearby similar properties") similar to the currently occupied rental property from the extracted properties (step S31). The criteria for similarity here may be the same as in step S21 described above.

[0043] Subsequently, the planner server 11 acquires the prices and rents of each of the nearby similar properties extracted in step S31 (step S32). Specifically, the prices of for-sale properties and rents, as well as the prices and rents of rental properties, are acquired or estimated from the prices stored in the property database 22 and the rents stored in the rental property database 21.

[0044] Next, the Planner Server 11 calculates the rate of return of each neighboring similar property using the price and rent of each neighboring similar property acquired in step S32 according to the following formula (1), and obtains the average value thereof (step S33). Here, in formula (1), A is the price of each neighboring similar property, B is the rent of each neighboring similar property, and C is the rate of return of each neighboring similar property. C = (B × 12) / A × 100 ···(1)

[0045] Next, the Planner Server 11 extracts condominiums located near the rental property currently in residence from the condominium database 20 (step S34), and extracts properties similar to the rental property currently in residence (neighboring similar rental properties) from the extracted condominium rental properties (step S35). The details of the processing in steps S34 and S35 are the same as the processing in steps S20 and S21.

[0046] Next, the Planner Server 11 estimates the price of each neighboring similar rental property according to the following formula (2) based on the average value of the rate of return calculated in step S33 and the rent of each neighboring similar rental property extracted in step S35 (set in the rental property database 21) (step S36). Here, in formula (2), D is the rent of each neighboring similar rental property, E is the average value of the rate of return calculated in step S33, and F is the estimated value of the price of each neighboring similar rental property. F = (D × 12) × 100 / E ···(2)

[0047] Finally, the Planner Server 11 obtains the average value of the prices estimated in step S36 and acquires it as the appropriate purchase price of the rental property currently in residence (step S37), thereby ending the appropriate purchase price estimation process.

[0048] Return to FIG. 4. The planner server 11 that has completed steps S4 and S5 calculates the loan repayment amount when purchasing a rental property during residence based on the appropriate purchase price estimated in step S5 (step S6). In this calculation, it is preferable for the planner server 11 to calculate the loan repayment amount using a predetermined repayment period and repayment method (such as a fixed amount type or a fixed rate type) and the latest interest rate. It is also possible to allow the user to input the repayment period and repayment method on the information input page 40 shown in FIG. 7 and calculate the loan repayment amount using the input repayment period and repayment method. Thereafter, the planner server 11 generates an information output page including the appropriate rent estimated in step S4 and the loan repayment amount calculated in step S6, and displays it on the displays of the user terminals 30 and 31 (step S7).

[0049] The information output page 41 shown in FIG. 7 is an example of the information output page displayed in step S7. The "current rent" included in the information output page 41 shown in the figure is the rent of the rental property during residence input in the rent input field 40b of the information input page 40, the "appropriate rent" is the appropriate rent estimated in step S4, and the "loan repayment amount" is the loan repayment amount calculated in step S6. The information output page 41 also displays the difference between the "current rent" and the "appropriate rent", and the difference between the "current rent" and the "loan repayment amount". By looking at this information output page 41, the user can know whether the current rent is appropriate and how much the loan repayment amount would be if it is assumed that the current rental property is purchased compared to the current rent.

[0050] Return to FIG. 4. Subsequently, the planner server 11 extracts from the property database 22 a property that can be purchased at a price equivalent to the appropriate purchase price estimated in step S5 and is a more preferable property for sale (step S8). Here, "equivalent" means that the difference between the price stored in the property database 22 and the appropriate purchase price estimated in step S5 is within a predetermined value. Also, "more preferable" means, for example, that the floor area is larger than that of the currently rented property, the construction year is newer, or it is located within a popular area (for example, in the case of Tokyo, Chuo Ward, Chiyoda Ward, Minato Ward, Bunkyo Ward, Shinjuku Ward, Shibuya Ward, etc.).

[0051] The planner server 11 determines whether the transition button (for example, the "Next" button included in the information output page 41 of FIG. 7) on the information output page 41 has been pressed (step S9). The planner server 11 that determines in step S9 that the transition button has been pressed generates an information output page including a list of the properties for sale extracted in step S8 and displays it on the displays of the user terminals 30, 31 (step S10).

[0052] The information output page 42 shown in FIG. 7 is an example of the information output page displayed in step S10. As shown in the figure, on the information output page 42, information on a plurality of properties for sale is listed together with the "View Property" button and the "Consult" button. The information input page 43 shown in FIG. 7 is an example of the page displayed when the user presses the "Consult" button among them. The information input page 43 is a page for inputting the user's information and requests. When the user presses the "Inquire" button included therein, the planner server 11 generates an e-mail including the input user's information and requests and the information on the corresponding currently rented property and property for sale, and sends it to the e-mail address of a predetermined salesperson. Thereby, the salesperson can directly introduce the property for sale to the user who accessed the information input page 40.

[0053] FIG. 8 is a sequence diagram of the sales property extraction process executed by the planner server 11. Hereinafter, by referring to this FIG. 8, the process performed by the planner server 11 will be described from another perspective.

[0054] First, the planner server 11 circulates through one or more sales sites 2 and collects information on rental properties and sales properties from each (step S100). Then, based on the collected information, records of the condominium database 20, the rental property database 21, and the property database 22 are generated and registered in each (step S101).

[0055] Next, the planner server 11 receives input of information on the rental property in which the user is living from the user terminals 30, 31 (step S102), and acquires the basic information thereof from the condominium database 20 (step S103). Subsequently, the planner server 11 extracts neighboring similar rental properties that are located in the neighborhood of the rental property in which the user is living and are similar to the rental property in which the user is living from the condominium database 20 and the rental property database 21 (step S104). Then, after correcting the rent of the extracted neighboring similar rental properties so as to meet the conditions of the rental property in which the user is living (step S105), the average value of the corrected rent is presented to the user as the appropriate rent of the rental property in which the user is living (step S106).

[0056] Also, the planner server 11 extracts neighboring similar properties similar to the rental property in which the user is living from the condominium database 20 and the property database 22 (step S107), and acquires the price and rent thereof from the data stored in the property database 22 and the rental property database 21 (step S108). Then, using the above-described formula (1), the average value of the return on investment of each of the extracted neighboring similar properties is calculated (step S109).

[0057] The planner server 11 further locates near the rental property in which the user is currently living, and extracts neighboring similar rental properties similar to the rental property in which the user is currently living from the condominium database 20 and the rental property database 21 (step S110). Then, by substituting the average value of the return calculated in step S109 and the rent of each neighboring similar rental property extracted in step S110 into the above formula (2), the price of each neighboring similar rental property is estimated, and the appropriate purchase price of the rental property in which the user is currently living is estimated from the results (step S111). The planner server 11 calculates the loan repayment amount when the user purchases the rental property in which the user is currently living based on the appropriate purchase price estimated in this way, and presents it to the user (step S112).

[0058] Finally, the planner server 11 extracts from the property database 22 a property for sale that can be purchased at a price equivalent to the appropriate purchase price estimated in step S111 and is more preferable (step S113), and presents the information of the extracted property for sale to the user (step S114).

[0059] As described above, according to the planner server 11 according to the present embodiment, since the property for sale is extracted based on the information of the rental property in which the user is currently living input by the user, it is possible to effectively appeal to the person living in the rental property for the purchase of real estate for relocation.

[0060] Further, according to the planner server 11 according to the present embodiment, since the appropriate rent and the appropriate purchase price of the rental property in which the user is currently living are presented, the user can know these facts when the current rent is too high or when the loan repayment amount when purchased is lower than the current rent. This can be a motivation to encourage relocation. Therefore, according to the planner server 11 according to the present embodiment, it is possible to more effectively appeal to the person living in the rental property for the purchase of real estate for relocation.

[0061] In addition, although the planner server 11 according to the present embodiment displays an information output page including a list of properties for sale in step S10, it may also display an information output page including a list of rental properties, or an information output page including a list of both properties for sale and rental properties. In this case, the planner server 11 may extract from the rental property database 21 rental properties that can be rented at a price equivalent to the rent input by the user on the information input page displayed in step S1 and that are more preferable. Here, "equivalent" means that the difference between the rent stored in the rental property database 21 and the rent input by the user is within a predetermined value. Also, "more preferable" means, for example, that the floor area is larger than that of the currently rented property, the year of construction is newer, or it is within a popular area (for example, in the case of Tokyo, Chuo Ward, Chiyoda Ward, Minato Ward, Bunkyo Ward, Shinjuku Ward, Shibuya Ward, etc.).

[0062] Next, the processing executed by the members market server 12 and the recommender server 13 will be described. FIG. 9 is a diagram showing the structures of the non-public property database 23, the member database 24, the condition database 25, and the distribution database 26 connected to at least one of the members market server 12 and the recommender server 13. Among these, the structure of the non-public property database 23 is the same as that of the property database 22 shown in FIG. 3. However, only the information of the properties for sale selected by the user who is the seller to be made non-public is stored in the non-public property database 23. This point will be described in detail later.

[0063] The member database 24 is a database that stores information of members of the service provided by the recommender server 13, and is configured to store the name and address information, etc. in association with each other in association with the member ID. The address information is, for example, an email address or an SNS address. In the member database 24, information of users who can be the buyers of the properties for sale registered in the non-public property database 23 is registered in advance.

[0064] The condition database 25 is a database that stores information indicating the desired conditions of the property to be purchased. It is configured to store, in association with a condition ID, the member ID, the station, the walking distance from the station (the required time when walking from the station), the price range, the floor area, the floor plan, the number of rooms, the balcony direction, and the like. As can be understood from the inclusion of the member ID, the information registered in the condition database 25 is information indicating the desired conditions of the users registered in the member database 24.

[0065] The distribution database 26 is a database that stores information on the properties for sale that match the desired conditions. It is configured to store, in association with a combination of a condition ID and a property for sale ID, the date when the distribution was executed, and the like.

[0066] Figure 10 is a flowchart showing the processing flow of the property for sale registration process executed by the members market server 12. Further, Figure 11 is a flowchart showing the processing flow of the desired condition registration process executed by the recommender server 13, and Figure 12 is a flowchart showing the processing flow of the distribution process executed by the recommender server 13. The information processing apparatus 10 plays a role of providing a sales site that can attract excellent buyers by executing these processes by the members market server 12 and the recommender server 13. Hereinafter, the content of each process will be described in detail with reference to Figures 10, 11, and 12 in order.

[0067] First, referring to Figure 10, the members market server 12 that has started the property for sale registration process first generates a public type selection page and displays it on the displays of the user terminals 30, 31 (step S40).

[0068] FIG. 13(a) is a diagram showing a publication type selection page 50 which is an example of the publication type selection page displayed in step S40. Although FIGS. 13(a), 13(b), 14, and 15 described later show examples of display on a personal computer, the content of the screen displayed on the user terminal 30 which is a smartphone is the same. As shown in FIG. 13(a), the publication type selection page 50 includes a selection button 50a for selecting sale by publication and a selection button 50b for selecting sale by non-publication.

[0069] Return to FIG. 10. The members market server 12 determines whether the user has selected sale by publication by obtaining the type of button pressed by the user on the displayed publication type selection page 50 (step S41). If it is determined that the user has selected sale by publication, the process proceeds to step S42, and if it is determined that the user has not selected sale by publication (has selected sale by non-publication), the process proceeds to step S46.

[0070] The Members Market Server 12 that has advanced the process to step S42 generates an information input page for publicly offered properties and displays it on the displays of the user terminals 30 and 31 (step S42). Although not shown, the information input page displayed at this time may be the same as the information input page 51 shown in FIG. 13(b) described later. The Members Market Server 12 determines whether the user has pressed the transition button on the information input page displayed in step S42 (step S43). If it is determined that the button has been pressed, it waits for confirmation by the salesperson as necessary (step S42). This waiting may end, for example, when a page including a confirmation button is displayed on the salesperson's terminal and the salesperson presses the confirmation button. By providing step S42, it becomes possible to appraise the property for sale (including correction of the input information) by the salesperson before registering the property for sale input by the user in the property database 22. When the waiting ends by the salesperson pressing the confirmation button, the Members Market Server 12 registers the property for sale input by the user in the property database 22 and ends the property for sale registration process for publicly offered properties.

[0071] On the other hand, the Members Market Server 12 that has advanced the process to step S46 generates an information input page for non-publicly offered properties and displays it on the displays of the user terminals 30 and 31 (step S46).

[0072] FIG. 13(b) is a diagram showing an example of the information input page 51 that is the information input page displayed in step S46. As shown in the figure, the information input page 51 includes columns for inputting or selecting name, telephone number, email address, desired contact method, postal code and address of the location of the property for sale, condominium name, room number, floor area, desired time of sale, range of desired selling price, and other matters, and a transition button 51a.

[0073] Return to FIG. 10. The Members Market Server 12 determines whether the user has pressed the transition button 51a on the information input page 51 displayed in step S46 (step S47). If it is determined that the button has been pressed, it waits for confirmation by the salesperson as necessary (step S48). The content and meaning of this waiting are the same as in step S44. When the waiting ends by the salesperson pressing the confirmation button, the Members Market Server 12 sends the property for sale input by the user to the Recommender Server 13 and registers it in the non-public property database 23 via the Recommender Server 13. Through the processing up to this point, the Members Market Server 12 finishes the property registration process for non-public properties for sale.

[0074] Next, referring to FIG. 11, the Recommender Server 13 that has started the desired condition registration process first performs member authentication to confirm whether the connected user is a member registered in the member database 24 (step S50). Then, based on the result of the member authentication, it determines whether the user is a member (step S51). If the user is a member, the process proceeds to step S52, while if the user is not a member, the desired condition registration process ends. This prevents non-members from registering desired conditions.

[0075] The Recommender Server 13 that has proceeded to step S52 generates an information input page for the desired conditions and displays it on the displays of the user terminals 30, 31 (step S52).

[0076] FIG. 14 is a diagram showing an information input page 52 which is an example of the information input page displayed in step S52. As shown in this figure, the information input page 52 is configured to have columns for inputting or selecting the area of the desired property, the property image, etc., and a transition button 52a. The column for inputting or selecting the area is configured such that the user can select the input method from several input methods such as the area of interest, the line / station, the ward, etc. The column for inputting or selecting the property image is configured such that the user can select from a plurality of predetermined images. Of course, columns for inputting or selecting other information such as the price range, the floor area, the floor plan, the number of rooms, the balcony direction, etc. of the desired property may be provided in the information input page 52.

[0077] Return to FIG. 11. The recommender server 13 determines whether the user has pressed the transition button 52a on the information input page 52 displayed in step S52 (step S53). Then, if it is determined that the button has been pressed, the input information is registered in the condition database 25 (step S54), and the desired condition registration process is terminated.

[0078] Finally, referring to FIG. 12, the distribution process performed by the recommender server 13 will be described. The recommender server 13 is configured to execute this distribution process in response to registering the non-publicly sold property in the non-public property database 23 in step S49 shown in FIG. 10.

[0079] The recommender server 13 that has registered a new non-publicly sold property in the non-public property database 23 first performs the processes of steps S61 and S62 for each record in the condition database 25 (step S60). Specifically, it is determined whether the newly registered non-publicly sold property matches the desired conditions indicated by the target record (step S61), and if it is determined that they match, the combination of the corresponding condition ID and the sales property ID is registered in the distribution database 26 (step S62). At this point, the date in the newly registered record is not filled in.

[0080] After the recommender server 13 finishes the repetitive process of step S60, it then performs the processes of steps S64 to S68 for each record without a date entry registered in the distribution database 26 (step S63). Specifically, the recommender server 13 first reads out the member ID corresponding to the condition ID from the condition database 25 (step S64), and reads out the address information corresponding to the read member ID from the member database 24 (step S65). Subsequently, the recommender server 13 generates a distribution page including the information of the property stored in the non-public property database 23 in association with the sales property ID (step S66). Then, it sends the distribution page generated in step S66 to the address information read in step S65 (step S67), sets the current date in the date in the distribution database 26 (step S68), and finishes the process for that record. After the recommender server 13 finishes the repetitive process of step S63, it finishes the distribution process.

[0081] FIG. 15 is a diagram showing a distribution page 53 which is an example of the distribution page generated in step S66. As shown in the figure, the distribution page 53 is a page including various information of the sales property to be distributed. The recommender server 13 generates this distribution page 53 by reading information from the non-public property database 23.

[0082] As shown in FIG. 15, a graph area 53a showing the benefits of the sales property is arranged on the distribution page 53. The recommender server 13 is configured to generate the information to be displayed in this graph area 53a based on the price and deviation value stored in the property database 22 and the non-public property database 23. This will be described in detail below.

[0083] First, regarding the deviation value, when generating the distribution page 53, the recommender server 13 extracts similar properties (including at least one of the properties for sale stored in the property database 22, the properties for sale stored in the non-public property database 23, and the rental properties stored in the rental property database 22) from the property database 22 and the non-public property database 23 for the property for sale to be distributed. As criteria for determining similar properties, for example, address (whether in the same ward), nearest station (whether the nearest station is the same), floor area (whether the difference in floor area is within a predetermined value), floor where located (whether on the same floor), balcony direction (whether in the same direction), etc. may be used.

[0084] The recommender server 13 that has extracted similar properties calculates the average value and variance of the prices of the extracted properties. The price used here may be obtained or estimated in the same manner as in step S32 of FIG. 6. The recommender server 13 calculates the price deviation value for each of the property for sale to be distributed and the extracted similar properties using the calculated average value and variance, and stores them in the property database 22 and the non-public property database 23. The deviation value calculated in this way becomes information indicating the profitability of each property for sale within the similar property group.

[0085] The recommender server 13 generates a curve graph (for example, a normal distribution curve) based on the calculated average value and variance, and draws it within the graph area 53a (the "price distribution" shown in the figure). Also, based on the deviation values of each of the property for sale to be distributed and the extracted similar properties, these properties for sale are plotted on the normal distribution curve. At this time, as illustrated in FIG. 15, the recommender server 13 uses markers of different shapes for the property to be distributed, the un-contracted similar properties, and the contracted similar properties. This enables the user to intuitively understand the profitability of the property to be distributed within the similar property group.

[0086] Figure 16 is a sequence diagram of a part of the sales property registration process and distribution process (up to registration in the distribution database 26) executed by the Members Market Server 12 and the Recommender Server 13. Further, Figure 17 is a sequence diagram of the member registration process, desired condition registration process, and the remaining part of the distribution process executed by the Recommender Server 13. Hereinafter, by referring to these Figures 16 and 17, the processes performed by the Members Market Server 12 and the Recommender Server 13 will be described from another perspective.

[0087] First, referring to Figure 16, the Members Market Server 12 first receives information on a sales property from the user terminals 30, 31 of the user who is the seller (step S120). Then, it determines whether the user wishes for non-disclosure (step S121). If the user does not wish for non-disclosure, it registers the property in the property database 22 (step S122). On the other hand, if the user wishes for non-disclosure, it transfers the information on the sales property to the Recommender Server 13 (step S123).

[0088] The Recommender Server 13 that has received the transfer of the sales property information registers the information in the non-disclosed property database 23 (step S124), extracts desired conditions that match the registered sales property information from the condition database 25 (step S125), and registers the combination of the condition ID of the extracted desired condition and the sales property ID of the registered sales property information in the distribution database 26 (step S126).

[0089] Next, referring to Figure 17, first, at the stage of registering a member, the Recommender Server 13 receives personal information from the user terminals 30, 31 of the user who is the buyer of the non-disclosed sales property (step S130). After having the reviewer conduct a review (step S131), it registers the information in the member database 24 (step S132). The review in step S131 is a review of whether the user is a user sufficient to be registered as an excellent buyer. If the review result shows that the user is not a user sufficient to be registered as an excellent buyer, step S132 is not executed.

[0090] Next, at the stage of registering desired conditions, the recommender server 13 first authenticates whether the user of the user terminal 30, 31 is a member registered in the member database 24 (step S133). If authenticated as a member, the recommender server 13 receives information indicating the desired conditions from the user terminal 30, 31 of the user (step S134) and registers the information in the condition database 25 (step S135). The member authentication in step S133 may be, for example, authentication using a member ID and password.

[0091] Finally, at the stage of executing distribution of sales property information, the recommender server 13 first acquires a combination of a condition ID and a sales property ID from the distribution database 26 (step S140). Then, the recommender server 13 acquires a member ID corresponding to the condition ID from the condition database 25 (step S141), and further acquires address information corresponding to the acquired member ID from the member database 24 (step S142).

[0092] Next, the recommender server 13 reads out the information of the property for sale ID acquired in step S140 from the private property database 23 (step S143), and generates a distribution page based on the read out information (step S144). The specific contents of the distribution page are as described above. After that, the recommender server 13 transmits the distribution page generated in step S144 to the address information acquired in step S142 (step S145), and ends the process.

[0093] As described above, according to the member's market server 12 and recommender server 13 of this embodiment, information on non-public properties for sale is registered in a non-public property database 23 separate from the property database 22, and information on properties for sale that match the desired conditions is distributed to buyers who are permitted to register their desired conditions in advance in the condition database 25, making it possible to provide a sales site that gives preferential treatment to and attracts quality buyers.

[0094] Note that, in response to registering the non-publicly sold properties in the non-public property database 23 in step S49 shown in FIG. 10, the recommender server 13 according to the present embodiment starts the distribution process shown in FIG. 12 and distributes a distribution page including information on the non-publicly sold properties stored in the non-public property database 23. However, in response to registering the publicly sold properties in the property database 23 in step S45 shown in FIG. 10, the distribution process shown in FIG. 12 may be started, and a distribution page including information on the publicly sold properties stored in the property database 23 may be distributed, or both of these may be executed. When distributing a distribution page including information on the publicly sold properties, in step S61, the recommender server 13 determines whether the newly registered publicly sold property matches the desired conditions indicated by the highlighted record. If it is determined that they match, in step S62, the combination of the corresponding condition ID and the sales property ID may be registered in the distribution database 26. Further, in step S66, the recommender server 13 may generate a distribution page including information on the property stored in the property database 22 in association with the sales property ID.

[0095] As described above, the preferred embodiments of the present invention have been described. However, the present invention is not limited to such embodiments, and it goes without saying that the present invention can be implemented in various modes without departing from the gist thereof.

[0096] For example, in FIG. 1, the property database 22 and the non-public property database 23 are depicted separately, but they may be integrated into one database. In this case, in order to distinguish between publicly sold properties and non-publicly sold properties, it is preferable to provide a public availability flag for each record, for example.

[0097] In the above-described embodiment, an example in which only excellent buyers are registered in the member database 24 has been described. However, users other than excellent buyers may also be registered as members. In this case, by providing a flag in the member database 24 to identify whether a user is an excellent buyer or not, only excellent buyers may be allowed to register their desired conditions, and non-publicly sold property information may be distributed to them.

Explanation of Signs

[0098] 1 Information processing system 2 Sales site 3 Network 10 Information processing device 11 Planner server 12 Members market server 13 Recommender server 20 Condominium database 21 Rental property database 22 Property database 23 Non-public property database 24 Member database 25 Condition database 26 Distribution database 30,31 User terminal 40,43,51,52 Information input page 40a Property name input field 40b Rent input field 40c Input field 40d Floor input field 40e Corner room button 40f South-facing button 40g Renovated button 40h,51a,52a Transition button 41,42 Information output page 50 Public type selection page 50a,50b Selection button 53 Distribution page 53a Graph area 101 Processor 102 Storage device 103 Communication device 104 Input device 105 Output device 106 Bus

Claims

1. A computer connected to a member database that stores for each member a flag for identifying whether the member is a good buyer in the purchase of real estate properties, and a condition database that stores information suggesting desired conditions for the purchased properties for each member indicated as a good buyer by the flag, determining whether the connected user is the good buyer registered in the member database, when it is determined that the user is the good buyer registered in the member database, displaying an input page for the information suggesting the desired conditions, registering the information input on the input page in the condition database as information suggesting the desired conditions of the user, a computer.

2. The member database further stores address information for each member, when a new property for sale, which is a real estate property to be sold, occurs, delivering the information of the new property for sale to the address information stored in the member database in association with the good buyers who match the information suggesting the desired properties registered in the condition database, The computer according to claim 1.

3. A method executed by a computer connected to a member database that stores for each member a flag for identifying whether the member is a good buyer in the purchase of real estate properties, and a condition database that stores information suggesting desired conditions for the purchased properties for each member indicated as a good buyer by the flag, a step of determining whether the connected user is the good buyer registered in the member database, a step of displaying an input page for the information suggesting the desired conditions when it is determined that the user is the good buyer registered in the member database, a step of registering the information input on the input page in the condition database as information suggesting the desired conditions of the user, a method including the above.

4. In a computer connected to a member database that stores for each member a flag for identifying whether the member is a good buyer in the purchase of real estate properties, and a condition database that stores information suggesting desired conditions for the purchased properties for each member indicated as a good buyer by the flag, a step of determining whether the connected user is the good buyer registered in the member database, When it is determined that the buyer is an excellent buyer registered in the member database, a step of displaying an input page for information suggesting the desired conditions; A step of registering the information input on the input page in the condition database as information suggesting the desired conditions of the user; A program for causing the above to be executed.

Images