SYSTEM AND METHOD FOR UTILIZING SENTIMENT BASED INDICATORS IN DETERMINING REAL PROPERTY PRICES AND DAYS ON MARKET

• US 20110251974A1
• Filed: 04/07/2010
• Published: 10/13/2011
• Est. Priority Date: 04/07/2010
• Status: Abandoned Application

• Current Assignee: ShowingTime.com, Inc. (Zillow Group, Inc.)
• Original Assignee: ShowingTime.com, Inc. (Zillow Group, Inc.)
• Inventors: Bi, Depeng, Woodard, Scott E.
• Application Number:
  US12/755,472
• Publication Number:
  US 20110251974A1
• Time in Patent Office: Days
• US Class Current: 705/348
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 50/16 Real estate

Abstract

A system and method for estimating the final sales price and amount of time required to sell a newly listed property based on the number of viewings that the property receives within a predetermined time of the properties listing. A model is constructed based on comparable properties, and the number of viewings that the newly listed property receives within the predetermined time period is compared to the number of viewings that properties within the model set received within the same time period after their respective listings. On-market days and percent of listing price are derived from this model.

Claims

1. A method of estimating the number of days that a real property is likely to be listed before a transaction occurs, said real property being listed at a particular price, and having been viewed a measured number of times within a predetermined time period after being listed, the method comprising the steps of:

accessing a listing and sales database containing a plurality of real property listings and transaction information for those real property listings, the transaction information including the number of days that a property was listed before a transaction occurred, and the number of times that a property was viewed within a predetermined time period after it was listed;

deriving a model relating the number of times that a property was viewed within said predetermined time period after it was listed to the number of days that it was listed prior to a transaction occurring; and

predicting the number of days that said listed property will be listed prior to a transaction occurring using said model and the measured number of times that said property was viewed within said predetermined time period after being listed.

2. The method of claim 1 wherein the step of deriving a model comprises a best fit exponential, and other regression methods, trendline analysis.

3. The method of claim 1 further comprising the step of accessing a web site access database relating a plurality of property web sites to a number of accesses for each of the plurality of property web sites, wherein said plurality of property web sites correspond to at least some of said plurality of real property listings, and wherein the step of deriving a model includes relating the number of times that a property web site was accessed to the number of days that a property was listed before a transaction occurred.

4. The method of claim 3 wherein a website is associated with said listed property and wherein said web site access database includes an entry relating a number of times that said listed property website was accessed within said predetermined time period after said listed property was listed, and wherein said step of predicting uses the number of times that said listed property website was accessed within said predetermined time period.

5. The method of claim 1 further comprising the step of accessing a lockbox access database relating a plurality of lockboxes to a number of accesses for each lockbox, wherein said plurality of lockboxes correspond to at least some of said plurality of real property listings, and wherein the step of deriving a model includes relating the number of times that a property lockbox was accessed to the number of days that a property was listed before a transaction occurred.

6. The method of claim 5 wherein a lockbox is associated with said listed property and wherein said lockbox access database includes an entry relating a number of times that said lockbox associated with said listed property was accessed within said predetermined time period after said listed property was listed, and wherein said step of predicting uses the number of times that said listed property website was accessed within said predetermined time period.

7. The method of claim 1 further comprising the step of accessing a key kiosk database, said key kiosk database including entries for one or more key kiosks, each of said entries relating a plurality of real properties to a number of key accesses, wherein said plurality of real properties correspond to at least some of said plurality of real property listings, and wherein the step of deriving a model includes relating the number of times that a key was accessed to the number of days that a property was listed before a transaction occurred.

8. The method of claim 7 wherein a key is associated with said listed property and wherein said key kiosk database includes an entry relating a number of times that said key associated with listed property was accessed within said predetermined time period after said listed property was listed, and wherein said step of predicting uses the number of times that said listed property key was accessed within said predetermined time period.

9. A method of estimating a percent of a listing price that a real property is likely to be sold at, said real property having been viewed a measured number of times within a predetermined time period after being listed, the method comprising the steps of:

accessing a listing and sales database containing a plurality of real property listings and transaction information for those real property listings, the transaction information including a listing price, a sales price, and a number of times that a property was viewed within a predetermined time period after it was listed;

deriving a model relating the number of times that a property was viewed within said predetermined time period after it was listed to the ratio of the sales price to the listing price; and

predicting a ratio of sales price to listing price for said listed property using said model and the measured number of times that said property was viewed within said predetermined time period after being listed.