System and method for assisting the buying and selling of property

• US 7,016,866 B1
• Filed: 11/28/2000
• Issued: 03/21/2006
• Est. Priority Date: 11/28/2000
• Status: Expired due to Term

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Sdn. Bhd. (Accenture PLC)
• Inventors: Chin, Wei Min, Nyeoh, Kok Tih, Liang, Mily, Chia, Suad Hooi
• Primary Examiner(s): NGUYEN, CUONG H
• Application Number:
  US09/722,341
• Time in Patent Office: 1,939 Days
• Field of Search: 705 26- 28
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

The invention provides systems and methods for assisting the buying and selling of properties. The invention serves as a single point of contact for sellers, buyers, negotiators and third party service providers in the real estate market, offering a forum for identifying needs, presenting solutions and accessing a suite of real estate tools and services.

An application architecture preferably includes resource applications, transaction applications, appointment management applications, advertising applications, and operations applications. A technical architecture preferably includes hardware that supports the application architecture, such as web servers serving web pages that serve as an online interface between the application architecture and the users. A business operation solution preferably includes independent but interacting product and content management functions, customer service functions, negotiator acquisition and management functions, operations support functions, marketing functions, alliance formation and management functions, technology operations functions, and back office support functions.

A method preferably includes providing an online interface that sellers can use to provide information regarding properties they wish to sell, that can be used to publish the property-for-sale information to many buyers, and that buyers can use to provide information regarding properties they wish to buy. The method further includes selecting a property for recommendation to the buyer and providing the online interface for recommending the property to the buyer. The method further includes facilitating a negotiation between the seller and the buyer as necessary to effect a closing of a transaction between the seller and the buyer for the property.

Claims

1. A method of profiling a user of a system for assisting the buying and selling of properties, comprising:

providing at least one of a customized recommendation and a customized opinion to the user based on the character profile score, wherein assigning the character profile score comprises;

passing a relative weightage preference of a demographic weightage through the demographic weightage to determine a preferred demographic weightage for a plurality of character types;

passing a relative weightage preference of a property weightage through the property weightage to determine a preferred property weightage for the plurality of character types; and

adding the preferred demographic weightage for each of the plurality of character types to the preferred property weightage for each of the plurality of character types to determine the character profile score.

2. The method of claim 1, further comprising:

receiving data associated with a plurality of character types; and

receiving data associated with a plurality of character attributes and divided into character attribute subsets.

3. The method of claim 2, wherein:

the character types include at least one of yuppie, expatriate, young family, established family, teenager, elderly, and none; and

the character attributes include at least one of age, income range, marital status, number of children, and nationality.

4. The method of claim 2, wherein the user is a seller and the customized recommendation is a recommendation to sell a property.

5. The method of claim 2, wherein the user is a buyer and the customized recommendation is a recommendation to buy a property.

6. The method of claim 2, wherein assigning the character profile score comprises:

receiving questionnaire answers from the user;

mapping the user in the character profile matrix using the questionnaire answers; and

calculating the character profile score.

7. The method of claim 6, wherein the questionnaire answers comprise demographic data, preferred neighborhood data and preferred property type data.

8. The method of claim 1, further comprising:

tracking at least one online action of the user to obtain user habit information; and

re-assigning the character profile score using the character profile matrix and the user habit information.

9. The method of claim 8, wherein the online action is at least one of a property search, a profile search, a property price search, a change to a list of favorite properties, a request to view detailed information regarding the property, a request for an appointment to visit the property, and applying for a loan.

10. The method of claim 1, wherein providing at least one of a customized recommendation and a customized opinion to the user based on the character profile score comprises:

defining a plurality of recommendation object attributes divided into a plurality of recommendation object attribute subsets;

defining a recommendation object profile matrix representing the likelihood that a person of at least one of the character types will fit into at least one of the recommendation object attribute subsets;

assigning a recommendation object profile score to the user using the recommendation object profile matrix and the character profile score; and

providing the customized recommendation to the user based on the recommendation object profile score.

11. The method of claim 10, wherein:

the recommendation object is at least one of a property, a tool, a new project listing, an article, a pricing index, a promotion, a sorting preference, and a home furnishing; and

when the recommendation object is a property, the recommendation object attributes comprise property attributes that include at least one of neighborhood, property type, buildup area and number of rooms.

12. The method of claim 10, wherein assigning the recommendation object profile score comprises:

mapping the user in the recommendation object profile matrix using the character profile score; and

calculating the recommendation object profile score.

13. The method of claim 12, wherein:

mapping the user in the recommendation object profile matrix comprises passing the character profile score through the recommendation object profile matrix to calculate recommendation object attribute fit scores indicating, for each character type, the likelihood that the user would desire each of the recommendation object attributes; and

calculating the recommendation object profile score comprises;

adding the recommendation object attribute fit scores for each property attribute to calculate recommendation object attribute fit total scores; and

adding the recommendation object attribute fit total scores to calculate the recommendation object profile score.

14. The method of claim 13, wherein providing the customized recommendation comprises:

ranking the recommendation object profile score with the other recommendation object profile scores;

selecting a number of high-ranking recommendation object profile scores; and

recommending to the user a recommendation object associated with at least one of the high-ranking recommendation object profile scores.

15. The method of claim 8, further comprising redefining the character profile matrix using the user habit information.

16. A method of profiling a user of a system for assisting the buying and selling of properties, comprising:

generating, using a computer program, a character profile matrix representing the likelihood that a person of at least one character type will fit into at least one character attribute subset;

assigning, using a computer program, a character profile score to the user using the character profile matrix;

providing at least one of a customized recommendation and a customized opinion to the user based on the character profile score;

wherein assigning the character profile score comprises;

passing a relative weightage preference of a neighborhood weightage through the neighborhood weightage to determine a preferred neighborhood weightage for each character type;

passing a relative weightage preference of a property type weightage through the property type weightage to determine a preferred property type weightage for each character type; and

adding the preferred neighborhood weightage for each character type to the preferred property type weightage for each character type to determine a property weightage indicating a relative degree of property preference similarity of the user to each of the character types.

17. A computer program product, tangibly embodied in an information carrier, for executing instructions on a processor, the computer program product being operable to cause a machine to:

generate a character profile matrix representing the likelihood that a person of at least one character type will fit into at least one character attribute subset;

assign a character profile score to the user using the character profile matrix;

provide at least one of a customized recommendation and a customized opinion to the user based on the character profile score;

pass demographic data through a demographic matrix of the character profile matrix to calculate a demographic weightage indicating a relative degree of demographic similarity of the user to each of a plurality of character types;

pass preferred neighborhood data through a neighborhood matrix of the character profile matrix to calculate a neighborhood weightage indicating a relative degree of demographic similarity of the user to each of the character types;

pass preferred neighborhood data through a neighborhood matrix of the character profile matrix to calculate a neighborhood weightage indicating a relative degree of neighborhood preference similarity of the user to each of the character types;

pass preferred property type data through a property type matrix of the character profile matrix to calculate a property type weightage indicating a relative degree of property type preference similarity of the user to each of the character types;

pass a relative weightage preference of the neighborhood weightage through the neighborhood weightage to determine a preferred neighborhood weightage for each character type;

pass a relative weightage preference of the property type weightage through the property type weightage to determine a preferred property type weightage for each character type; and

add the preferred neighborhood weightage for each character type to the preferred property type weightage for each character type to determine a property weightage indicating a relative degree of property preference similarity of the user to each of the character types.

18. A computer program product, tangibly embodied in an information carrier, for executing instructions on a processor, the computer program product being operable to cause a machine to:

generate a character profile matrix representing the likelihood that a person of at least one character type will fit into at least one character attribute subset;

assign a character profile score to the user using the character profile matrix;

provide at least one of a customized recommendation and a customized opinion to the user based on the character profile score, wherein a instructions to assign the character profile score comprises instructions to;

pass a relative weightage preference of a demographic weightage through the demographic weightage to determine a preferred demographic weightage for a plurality of character types;

pass a relative weightage preference of a property weightage through the property weightage to determine a preferred property weightage for the plurality of character types; and

add the preferred demographic weightage for each of the plurality of character types to the preferred property weightage for each of the plurality of character types to determine the character profile score.