JP2008171044A - Real estate item transaction support system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a real estate item transaction support system for enabling a person in charge to grasp a tendency of a potential user having a certain level of buying inclination. <P>SOLUTION: The system comprises a real estate item database 51 which is composed of a plurality of Web pages linked to one another and in which each Web page displays an image of a floor plan etc., of the concerned item and an item for specifying browsing of information differing from the image; an item attribute database 52 in which a plurality of item attributes each showing a feature of the user and weighting values of the item attributes are stored for each item; a Web page delivery unit 6 for extracting the concerned Web page from the database 51 in response to a browsing request and delivering the Web page to a client device 2; a storage unit 7 for storing the number of times of the requests for each Web page and for each user; and a totaling unit 8 for totaling products of the stored number of the times and the weighting value for each item attribute. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a system that supports transactions of real estate properties such as each room of an apartment house, a detached house, and a tenant.

In recent years, with the spread of broadband on the Internet, not only model rooms and scattered advertisements, but many real estate sales companies have set up homepages to post information on real estate properties on the homepage so that users can view them on their home computers. ing. Among such systems, particularly those that support real estate transactions, for example, those that deliver a 3D CG video in a walk-through format (Patent Document 1), and those that propose a floor plan that conforms to user input conditions (Patent Document 2) ), Which inquires for a property that matches the user's input conditions and simulates a loan or the like (Patent Document 3) is known.
JP 2001-236396 A JP2003-345860 JP 2002-189791

  However, all of the conventional support systems simply distribute the information on the property being handled to an unspecified number of users, and at best only prompt the request for materials, or input only when the user inputs a predetermined condition. The property that meets the conditions is extracted from the database and inquired. Accordingly, the sales staff cannot actively conduct business activities until they receive a document request from the user or have the desired conditions entered.

Further, in the former system, there are many cases where the person in charge receives a request for data and proposes a product to the user, and the proposal becomes inappropriate, or the user is not so willing to purchase. In the latter type of system, users cannot make inquiries unless the user decides the conditions. However, the majority of users who do not have real estate purchase tend to be reluctant to enter the conditions. Is very limited. Therefore, it is difficult for the person in charge to grasp the tendency of potential users who have some willingness to purchase.
On the other hand, there are users who feel that it is troublesome to come to the business even though they are not so willing to purchase, while there are users who are highly motivated to purchase but have no experience and are not confident in selecting conditions.
Therefore, an object of the present invention is to propose a system in which a person in charge can grasp the tendency of potential users who have a certain degree of purchase intention in order for the person in charge to conduct sales activities efficiently.

In order to solve the problem, the real estate property transaction support system of this invention
A system for delivering real estate property information from a server via a communication network in response to a request from a client device of a specific user, the server including a real estate property database, an item attribute database, a web A page distribution unit, a storage unit, and a totaling unit are provided. The specific user refers to a user to whom a user ID is assigned in advance when visiting a model room or visiting a consultation desk.

  The real estate property database is composed of a plurality of web pages linked to each other for each property, and each web page is one or more still images and / or videos of the appearance, interior view, view, floor plan and surrounding facilities of the property, and One or more types selected from symbols, icons, marks, and a specified coordinate range, and an item for designating browsing of information different from the still image and / or moving image is displayed. Here, the information different from the still image and / or the moving image includes, for example, a link destination web page displayed by clicking a link destination icon, a balloon displayed by an on-mouse, a rollover, the still image and / or Alternatively, it refers to a new image created by dragging or pasting the symbol, mark or the like on a moving image.

The item attribute database stores, for each item, a plurality of item attributes each indicating the characteristics of the user, such as “child support” and “car ownership”, and weight values of the item attributes.
The web page distribution unit extracts a corresponding web page from the real estate property database in response to a browsing request from the client device, and distributes the web page to the client device via a communication network.
The storage unit stores the number of browsing requests for each web page and for each user.
A totaling unit totals the product of the accumulated number of browsing requests and the weighting value for each item attribute to create total data.

  According to the system of this invention, every time the user starts browsing the web page, the weighting value of the attribute belonging to the item designating the web page is added by the counting unit. This is aggregated for each item attribute. Since the web page to be browsed and the number of browsing times are different for each user, the item attribute having a large (or small) total value is also different for each user. Therefore, the user's characteristics can be grasped from the aggregated data, and the sales representative can propose a product that has been won.

  When the same web page is browsed for a long time at least, the number of browsing times is estimated that the user is deeply interested in the information included in the web page. Therefore, in addition to each database and each part, a preferred system of the present invention further includes a measuring unit that measures browsing time and browsing time for each web page, and a corresponding item whenever the browsing time exceeds a certain value. And an arithmetic unit that adds a predetermined value to the weighting value to which it belongs.

  In some cases, the user's characteristics can be grasped according to the browsing time regardless of the web page to be browsed. Therefore, another preferable system of the present invention further includes the measurement unit and a calculation unit that adds a predetermined value to all weighting values of a predetermined item attribute according to the browsing time, in addition to the databases and the units. Prepare.

  Similarly, a person-in-charge database in which the ID of the specific user and the ID of the person in charge of sales of the property are stored in correspondence with each other, and an output unit that outputs the aggregated data for each salesperson ID by referring to the person-in-charge database. Are preferably provided. This is because each person in charge can grasp the characteristics of the user in charge and analyze the tendency.

  Similarly, a guess database storing various combinations of a plurality of prioritized item attributes and user tendencies, and a user who sorts the aggregated data and matches with reference to the guess database It is preferable to provide an analysis unit that acquires the tendency. This is because the user's tendency analyzed objectively can be acquired.

  Furthermore, an analysis result database that stores the combinations of item attributes sorted by the analysis unit in association with the ID of the specific user, and various combinations and sales methods of a plurality of item attributes with priorities. It is preferable that a proposal master table stored in correspondence with each other and a collation unit that collates a combination of item attributes in the proposal master table with a combination in the analysis result database and obtains a matching sales method for each user. This is because even inexperienced sales personnel can conduct sales activities with a high contract rate.

  Further, the sales method database for each user acquired by the collation unit and the sales result database storing the sales person's sales results for the specific user in correspondence with each other, the sales results are aggregated, and the statistics for each item of the sales method It is preferable to include a statistical result database stored and stored and a review unit that updates the proposal master table based on the statistical database. This is because the contract rate can be further increased.

  In the system of the present invention, the user need only browse a web page of interest without explicitly presenting special conditions. Therefore, the person in charge can propose the product which has won even the indecisive user. Moreover, since the user is specified, it is possible to actively and efficiently conduct business activities. On the other hand, even if it is a user, as long as it is a winning product, it is possible to make a contract with satisfaction. Therefore, real estate transactions become active.

Embodiment 1
The real estate transaction support system of an embodiment is explained with a drawing. FIG. 1 shows a schematic configuration of the system. This system 1 is a system for distributing real estate property information from a server 4 via a communication network 3 in response to a request from a client device 2 of a specific user. The server 4 includes a storage unit 5 that stores various databases, a web page distribution unit 6, a storage unit 7, a totaling unit 8, an output unit 9, and an analysis unit 10. The analysis unit 10 is optional.
The storage unit 5 is composed of a magnetic disk, a semiconductor memory, and the like in hardware, and a real estate property database 51, an item attribute database 52, a person-in-charge database 53, and a guess database 54 are stored in the storage area if necessary. Has been.

  The real estate property database 51 includes a plurality of web pages linked to each other for each room in the case of each property, that is, an apartment house. Each web page displays an item for designating one or more still images and / or videos, and a linked web page among the appearance, interior view, view, floor plan, and surrounding facilities of the property. The surrounding facilities may be displayed together with a map or the like. The item is an icon or a link heading provided with a radio button. On the web page, not only the item that specifies the linked web page, but also icons such as furniture that can be dragged and pasted on the floor plan, a mark for ballooning out details of facilities and places on the map with an on-mouse, etc. Items may also be displayed. Still images and moving images may be real images or 3D CG virtual images. Examples of web pages are shown in FIGS.

  The web page 51a in FIG. 2 is a top page, and a plurality of icons 51b, 51b,... For designating linked pages are displayed together with a pull-down menu. For example, when the “3D walkthrough” icon is clicked, the web page shown in FIG. 3 is displayed. The web page 51c in FIG. 3 displays an interior view of a room with a housing complex. The left column shows a floor plan 51d of the entire room, and the right column displays a three-dimensional CG virtual image 51e in a walk-through format of the interior view. ing. A “return” button 51f is provided at the bottom of the left column, and a viewpoint movement button 51g, a movement speed setting button 51h, and the like are provided as appropriate at the bottom of the right column. Further, in the floor plan 51d, a room designation icon (not shown) is displayed at the center of each room, and by clicking this, it is possible to jump to the video of the corresponding room. These web pages are linked to each other as shown in a tree form in FIG.

  As shown in FIG. 5, the item attribute database 52 includes a plurality of item attributes 52 a each indicating the characteristics of the user, such as “child support” and “car ownership”, and weight values of the item attributes 52 a, “park”, This is stored for each item 52b such as “child's room”. As shown in FIG. 6, the person-in-charge database 53 stores the ID of a specific user and the ID of a person in charge of selling a property in association with each other. As shown in FIG. 7, the guess database 54 stores various combinations of a plurality of item attributes with priorities in association with user tendencies. For example, as shown in FIG. In the case of the combination of 1, the item attributes are arranged in the order of “child support”, “train commuting”, “student”, etc., and are associated with the user tendency of “training / commuting to school with children”.

  The web page distribution unit 6 extracts a corresponding web page from the real estate property database 51 in response to a browsing request from the client device 2 and distributes it to the client device 2 via the communication network 3 such as the Internet. A web browser is installed in the client device 2. The storage unit 7 stores the number of browsing requests for each web page and for each user. The tabulation unit 8 tabulates the product of the accumulated number of browsing requests and the weighting value for each item attribute to create tabulated data.

  Next, the operation of the system 1 will be described with reference to the flowchart of FIG. The user is a person who, for example, visited a model room in advance and was handed a CD storing the user ID and the URL of the server 4 at that time. When the user inserts the CD into the CD drive of the client device 2, a web browser is activated on the client device 2 and accesses the URL of the server 4. Then, the web page distribution unit 6 identifies the user ID, reads the web page 51a (top page) from the real estate property database 51, and distributes it to the client device 2.

  The user clicks on an icon 51b of interest from the menu displayed on the web page 51a. The web page distribution unit 6 reads the requested web page (for example, the web page 51 c) from the real estate property database 51 and distributes it to the client device 2. The storage unit 7 records this as one browsing request for the web page 51c. Further, when the user clicks “kid room” from the floor plan 51 d displayed on the web page 51 c, the video 51 e in the right column jumps to the child room. The storage unit 7 records this as one browsing request for the web page of “child room”. Thus, the number of browsing requests for each web page is accumulated. Although not shown in the figure, even when an on-mouse balloon or a furniture icon is dragged, it is recorded and stored as a single browsing request for predetermined information.

  When the user clicks a “logout” button (not shown) or closes the browser, the web page distribution unit 6 stops the distribution. The totaling unit 8 multiplies the number of browsing requests accumulated for each item corresponding to each web page by the weighting value of the item in the item attribute database 52, totals for each item attribute 52a, and calculates the total data. create. An example of the generated total data is shown in FIG. In FIG. 9, the number of points 10 shown in the field of the attribute “child support” of the user ID “c” is an aggregate value when browsing of “children's room” and “primary and junior high school” is requested twice each. Similarly, the number of points 7 shown in the field of the attribute “old man support” of the user ID “a” is a total value when “park” is requested once and “barrier free” is viewed twice. is there.

  The total data is output from the output unit 9 and displayed on a monitor (not shown) connected to the server 4 or printed out. When the person-in-charge database 53 in which the user ID and the salesperson ID of the property are stored in correspondence with each other as shown in FIG. 10 is stored in the storage unit 5 of the server 4, the aggregated data in FIG. Sorted by the person in charge and output. The sales representative analyzes the user's tendency with reference to this, and proposes a barrier-free type room and garage with a child room for Mr. Lee, for example, the user identified by the user ID “a”. To do. In addition, Roh proposes a 1LDK type room and garage, assuming he is single and owns a car.

When the guess database 54 (FIG. 7) is stored in the storage unit 5 and the server 4 further includes the analysis unit 10, it is possible to cause the server 4 to analyze the user's tendency and output it. That is, the analysis unit 10 sorts the aggregated data in FIG. 9 in descending order of the aggregated point number, and acquires the tendency of matching users with reference to the guess database 54. The sorted aggregated data and the ranking of the item attributes in the guess database 54 may be exact matches, or may be a forward match in which only the first few item attributes match. What is necessary is just to set on the server 4 collectively.
The tabulation unit 8 tabulates the sum of the number of browsing requests and the weighting value after the user leaves the site of the server 4, but instead adds the corresponding weighting value for each browsing request to the tabulation data. It may be designed to do.

Embodiment 2
In the real estate transaction support system according to the second embodiment, the server 4 further includes a measurement unit 11 and a calculation unit 12 as shown in FIG. The measurement part 11 measures browsing time and browsing time. The calculation unit 12 is designed to add a predetermined value to the weighting value belonging to the corresponding item every time the browsing time exceeds a certain value (for example, 5 minutes). For example, when the browsing time of the “primary and junior high school” web page by the user exceeds 5 minutes, the same number of values are assigned to the weighting values of the “child support” attribute and the “school attendance” attribute belonging to the “primary and junior high school” item in FIG. The number of points is 6 and 4 respectively.

  The computing unit 12 is also designed to add a predetermined value to all weight values corresponding to a predetermined item according to the viewing time. For example, when the browsing time is between 9:00 am and 5:00 pm, it is assumed that the housewife is browsing, and the point number 1 is added to all the weight values corresponding to the “super” item.

  The operation of the system 1 will be described with reference to the flowchart of FIG. When the user accesses the URL of the server 4, the web page distribution unit 6 identifies the user ID and reads the web page 51 a (top page) from the real estate property database 51 and distributes it to the client device 2. At the same time, the calculation unit 12 acquires the browsing time from the measurement unit 11 and adds the number of points according to the browsing time.

Similar to the first embodiment, corresponding web pages are distributed in response to a user's browsing request (click), and the storage unit 7 records the number of browsing requests (clicks) for each web page. The measurement unit 11 resets for each click and starts measuring the browsing time. When none of the browsing times exceeds a predetermined value (for example, 5 minutes), the number of browsing requests and the weighting value (the value including the added value when added according to the browsing time) is the same as in the first embodiment. Are multiplied to create aggregated data. When the browsing time for a certain web page exceeds 5 minutes, a predetermined value is added to the weighting value belonging to the item that designates the web page, and then multiplied by the number of browsing requests, thereby generating aggregate data.
According to this embodiment, since the aggregated data is created in association with the browsing time and the browsing time, the user's tendency can be analyzed with high accuracy.

Embodiment 3
In the real estate transaction support system according to the third embodiment, as shown in FIG. 12, in addition to the configuration of the second embodiment, the server 4 includes a collation unit 13, an analysis result database 55, a proposal master table 56, and a sales technique master table 57. Is provided.

  The analysis result database stores combinations of item attributes sorted by the analysis unit 10 as shown in FIG. 13 in association with specific user IDs. The proposal master table 56 stores various combinations of item attributes shown in FIG. 7 in association with sales methods as shown in FIG. This correspondence relationship is not one-on-one, but a plurality of sales methods are associated with one combination of item attributes. The sales method consists of a number of conditions such as the floor plan of the property proposed to the user, the presence / absence of a parking lot, the contents of surrounding facilities, the visit time, and the payment method. The sales method master table 57 is a table in which codes are assigned to these sales conditions, and the sales method recorded in the proposal master table 56 is the code. The collation unit 13 collates the combination of item attributes in the proposal master table 56 with the combination in the analysis result database 55, and acquires a matching sales method for each user.

  For example, when it is determined in the analysis unit 10 that the target user is a family who supports a child who is attending school and uses a train as in the combination number 1, the two sales methods are compared as shown in FIG. 14. 13 gets. The sales representative outputs this information and makes an appointment with the user on a weekday morning, visits a property with a station and school nearby without parking in 4LDK, and a school and park nearby with parking in 5LDK Suggest a property. In addition, since the browsing time is concentrated in the daytime as illustrated in the second embodiment, as a result of adding the number of points to all the weight values corresponding to the “super” item, the item attribute “housewife” is the head of the combination. In the case of visiting, the collation unit 13 acquires a sales method for visiting a property having a supermarket within walking distance in the daytime. As a result, even an inexperienced sales person can conduct sales activities with a high contract rate.

Embodiment 4
In the real estate transaction support system according to the fourth embodiment, as shown in FIG. 15, the server 4 includes a review unit 14, a business result database 58, and a statistical result database 59 in addition to the configuration of the third embodiment.

  As shown in FIG. 16, the sales result database 58 stores the sales method for each user acquired by the collation unit 13 and the sales results of the sales staff for the specific user in association with each other. In the figure, in the business result field, point 1 indicates that the contract has been completed, and point 0 indicates that the contract has not been completed. The sales result is input by a salesperson through an input unit (not shown) such as a keyboard and a mouse. The statistical result database 59 collects business results and stores statistics for each item of the sales method. FIG. 17 is an example of this, and when statistics were taken on the item “scheduling”, in the case of combination number 2, 5 proposals were concluded with a proposal including a 5LDK floor plan, 1 was concluded with 4LDK, and there was no contract with 3LDK. It is shown that.

  The review unit updates the proposal master table 56 based on the statistical result database 59. For example, as shown in FIG. 17, when the statistical result that the 3LDK sales result total value is 0 for the combination number 2 is repeatedly obtained, all of the proposal master tables 56 in FIG. Records are automatically deleted. Thereby, a contract rate can be raised further.

It is a figure which shows schematic structure of the real estate transaction support system of Embodiment 1. It is a figure which shows the top page stored in the real estate property database. It is a figure which shows the web page of a link destination. It is a figure which shows the link relationship of a web page. It is a figure which shows an item attribute database. It is a figure which shows a person in charge database. It is a figure which shows a guess database. It is an operation | movement flowchart of the real estate transaction support system of Embodiment 1. It is a figure which shows total data. It is a figure which shows schematic structure of the real estate transaction support system of Embodiment 2. It is an operation | movement flowchart of the real estate transaction support system of Embodiment 2. It is a figure which shows schematic structure of the real estate transaction support system of Embodiment 3. It is a figure which shows an analysis result database. It is a figure which shows a proposal master table. It is a figure which shows schematic structure of the real estate transaction support system of Embodiment 4. It is a figure which shows a business result database. It is a figure which shows a statistics result database.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Real estate transaction support system 2 Client apparatus 3 Communication network 4 Server 5 Storage part 51 Real estate article database 52 Item attribute database 53 Person in charge database 54 Guess database 55 Analysis result database 56 Proposal master table 57 Sales method master table 58 Sales result database 59 Statistics Result database 6 Web page distribution unit 7 Accumulation unit 8 Total unit 9 Output unit 10 Analysis unit 11 Measurement unit 12 Calculation unit 13 Verification unit 14 Review unit

Claims (7)

In response to a request from a client device of a specific user, the system distributes real estate property information from a server via a communication network, and the server includes:
Each property consists of a plurality of web pages linked to each other, and each web page is one or more of still images and / or videos, and symbols, icons, marks among the appearance, interior view, view, floor plan and surrounding facilities of the property. And a real estate property database that displays items for specifying browsing of information different from the still image and / or the moving image, which is one or more types selected from the specified coordinate range;
An item attribute database in which a plurality of item attributes each indicating the characteristics of the user and a weighted value of the item attribute are stored for each item;
In response to a browsing request from the client device, the corresponding web page is extracted from the real estate property database and distributed to the client device; and
An accumulation unit for accumulating the number of browsing requests for each web page and for each user;
A real estate property transaction support system comprising: a totaling unit that totalizes a product of the accumulated number of browsing requests and the weighting value for each item attribute to create totalized data. Furthermore, a measuring unit for measuring the browsing time and browsing time for each web page,
The system according to claim 1, further comprising: an arithmetic unit that adds a predetermined value to the weighting value belonging to the corresponding item every time the browsing time exceeds a certain value. Furthermore, a measuring unit for measuring the browsing time and browsing time for each web page,
The system according to claim 1, further comprising: an arithmetic unit that adds a predetermined value to all weighting values corresponding to a predetermined item according to browsing time. Further, a person-in-charge database storing the ID of the specific user and the ID of the person in charge of selling the property,
The system in any one of Claims 1-3 provided with the output part which outputs the said total data for every salesperson ID with reference to a person in charge database. And a guess database that stores various combinations of prioritized item attributes in association with user trends,
The system according to claim 1, further comprising: an analysis unit that sorts the aggregated data and acquires a tendency of matching users with reference to the guess database. Furthermore, the analysis result database which stored the combination of the item attribute sorted in the said analysis part corresponding to ID of the said specific user,
A proposal master table that stores various combinations of prioritized item attributes in association with sales methods;
The system of Claim 5 provided with the collation part which collates the combination of the item attribute in the said proposal master table, and the combination in the said analysis result database, and acquires the matching sales method for every user. Further, a sales result database that stores the sales method for each user acquired by the collation unit and the sales result of the sales person corresponding to the specific user,
Statistics result database that aggregates sales results and stores statistics for each item of sales method,
The system of Claim 6 provided with the review part which updates a proposal master table based on the said statistics database.

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