Abstract:
A dynamic pricing system including a dynamic pricing unit including a memory and a processor, the processor of the dynamic pricing unit executing a program performing the steps of gathering a plurality of information on a unit of real property, gathering a plurality of information on a market where the unit of real property is sold, generating a first price for the unit of real property based on the gathered information on the unit of real property and market information, generating a second price and a third price based on the first price for the unit of real property, posting a portion of the plurality of property information and the first price for viewing by potential buyers on a first web site, posting a portion of the plurality of property information and the second price for viewing by potential buyers on a second web site, posting a portion of the plurality of property information and the third price for viewing by potential buyers on a third web site, monitoring each of the first, second and third web sites to determine the level of interest in the unit of real property at each of the first price, second price and third price, determining a final price based on the interest level of the web posting for the first price, second price and third price, posting a portion of the plurality of property information and the final price for viewing by potential buyers on a final web site.

Description:
FIELD OF THE INVENTION   
       [0001]    The current invention relates to a dynamic system using online tools for determining dynamically the value of any piece of real estate property, more specifically a system capable of determining the equilibrium market price of a piece of real estate property based on potential consumer reactions to sale offers. 
       BACKGROUND OF THE INVENTION  
       [0002]    As real estate markets mature worldwide, the importance of quick and easily available property valuation increases. Owners and investors in real estate review estimated valuations of properties to determine the ideal price to sell a property. Bankers and lenders also need efficient third party evaluation of real estate to help with lending refinancing. Owners of funds that include real estate assets also need to keep a close look on the value of their assets as ultimately the value of the fund closely depends upon the value of the underlying asset in the fund. Many methods of valuating property exist including reviewing tax and sales records of comparable properties, estimating cost per square foot based on the location of the property, and other methods. 
         [0003]    Ultimately, the value of any given piece of real estate property is the value a buyer is willing to pay for the property on any given day. One method of valuating a real estate property automatically involves a seller placing their product or service for sale, auction or lease on an Internet based web-site where a buyer or seller could then request, review and determine a proper price model based upon a mathematical algorithm calculating length of time on the market, number of inquiries and percentages of successful sales transactions based upon mapping the above equations against each other over time. For example, the owner of a real estate property who purchased on year 1 a given property must conduct an evaluation before listing the property on year 5 on the market of fear of underpricing the property. Often, a person will call a real estate agent, investigate as to increases of market in the region or even try to obtain online comparable properties sold recently in the area. Each of these methods are time extensive and costly. 
         [0004]    While these methods provide valuation methods for properties, they do not provide a reliable method of determining a real market valuation for a property without the need of external third party data and input. There is currently no system capable of determining with a great degree of reliability the current value of a property without extensive investigation. A need exists for a system that will allow a user to dynamically determine the real market valuation for a property using simply and available tools. 
       SUMMARY OF THE INVENTION  
       [0005]    A dynamic pricing system for real estate properties includes a dynamic pricing unit including a memory and a processor, the processor of the dynamic pricing unit executing a program performing the steps of gathering a plurality of information on a unit of real estate property, gathering a plurality of information on a market where the unit of real estate property is sold, generating a first price for the unit of real estate property based on the gathered information on the unit of real estate property and market information, generating a second price and a third price based on the first price for the real estate property unit, posting a portion of the plurality of real estate property information and the first price for viewing by potential buyers on a first web site, posting a portion of the plurality of real estate property information and the second price for viewing by potential buyers on a second web site, posting a portion of the plurality of real estate property information and the third price for viewing by potential buyers on a third web site, monitoring each of the first, second and third web sites to determine the level of interest in the unit of real estate property at each of the first price, second price and third price, determining a final price based on the interest level of the web posting for the first price, second price and third price, posting a portion of the plurality of property information and the final price for viewing by potential buyers on a final web site. 
         [0006]    In another example, the second price is higher than the first price and third price. 
         [0007]    In another example, the third price is lower than the first price and second price. 
         [0008]    In another example, the final price is a value between the first price and second price. 
         [0009]    In another example, the market information includes pricing information for a plurality of comparable units of real estate property having similar characteristics as the real estate property unit. 
         [0010]    In another example, the dynamic pricing unit performs the step of normalizing the pricing information of each of the plurality of comparable units of real estate property based on the property unit information. 
         [0011]    In another example, the dynamic pricing unit performs the step of gathering information relating to users viewing each of the first web page, second web page and third web page. 
         [0012]    In another example, the dynamic pricing unit performs the step of adjusting the final price based on the information relating to users viewing each web site. 
         [0013]    In another example, a dynamic pricing system includes a real estate property analysis unit configured to gather a plurality of information on a unit of real estate property, a market analysis unit configured to gather a plurality of information on a market where the unit of real estate property is sold, a real estate property analysis unit configured to generate a first price for the unit of real estate property based on the gathered unit of real estate property information and market information, generate a second price and a third price based on the first price for the unit of real estate property, a real estate property posting unit configured to post a portion of the plurality of real estate property information and the first price for viewing by potential buyers on a first web site, post a portion of the plurality of real estate property information and the second price for viewing by potential buyers on a second web site, post a portion of the plurality of property information and the third price for viewing by potential buyers on a third web site, monitoring each of the first, second and third web sites to determine the level of interest in the real estate property unit at each of the first price, second price and third price, a pricing analysis unit configured to determine a final price based on the interest level of the web posting for the first price, second price and third price, and post a portion of the plurality of real estate property information and the final price for viewing by potential buyers on a final web site. 
         [0014]    In another example, the second price is higher than the first price and third price. 
         [0015]    In another example, the third price is lower than the first price and second price. 
         [0016]    In another example, the final price is a value between the first price and second price. 
         [0017]    In another example, the market information includes pricing information for a plurality of comparable units of real estate property having similar characteristics as the real estate property unit. 
         [0018]    In another example, the real estate property analysis unit normalizes the pricing information of each of the plurality of comparable units of real estate property based on the real estate property unit information. 
         [0019]    In another example, the real estate property posting unit gathers information relating to users viewing each of the first web page, second web page and third web page. 
         [0020]    In another example, the pricing analysis unit adjusts the final price based on the information relating to users viewing each web site. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWING  
         [0021]    Details of the present invention, including non-limiting benefits and advantages, will become more readily apparent to those of ordinary skill in the relevant art after reviewing the following detailed description and accompanying drawings. 
           [0022]      FIG. 1  depicts a block diagram of an dynamic pricing system suitable for use with the methods and systems consistent with the present invention. 
           [0023]      FIG. 2  shows a more detailed depiction of the dynamic pricing unit. 
           [0024]      FIG. 3  shows a more detailed depiction of the computers. 
           [0025]      FIG. 4  depicts an illustrative example of the operation of the dynamic pricing system. 
           [0026]      FIG. 5  depicts an illustrative example of the operation of the pricing analysis unit gathering market information. 
           [0027]      FIG. 6  is an illustrative example of the operation of the property posting unit adjusting the price of the target property based on activity from various web postings of the property. 
           [0028]      FIG. 7  is an illustrative example of a website for the listing of property where the dynamic pricing model can be used according to an embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0029]    While various embodiments of the present invention are described herein, it will be apparent to those of skill in the art that many more embodiments and implementations are possible that are within the scope of this invention. Accordingly, the present invention is not to be restricted except in light of the attached claims and their equivalents. 
         [0030]    Described herein is a system for dynamically determining the real market value for a real estate property of product. The system determines an initial price based on information on comparable real estate properties or products, and posts the real estate property or real estate product at different prices via various web pages. The system then gauges interest in the real estate product or real estate property to determine the real estate market value of the real estate product or real estate property. 
         [0031]      FIG. 1  depicts a block diagram of an dynamic pricing system  100  suitable for use with the methods and systems consistent with the present invention. The dynamic pricing system  100  comprises a plurality of computers  102 ,  104 ,  106  and  108  connected via a network  110 . The network  108  is of a type that is suitable for connecting the computers for communication, such as a circuit-switched network or a packet switched network. Also, the network  110  may include a number of different networks, such as a local area network, a wide area network such as the Internet, telephone networks including telephone networks with dedicated communication links, connection-less network, and wireless networks. In the illustrative example shown in  FIG. 1 , the network  110  is the Internet. Each of the computers  102 ,  104 ,  106  and  108  shown in  FIG. 1  is connected to the network  110  via a suitable communication link, such as a dedicated communication line or a wireless communication link. 
         [0032]    In an illustrative example, computer  102  serves as a dynamic pricing unit that includes a property analysis unit  112 , a market analysis unit  114 , a property posting unit  116  and a pricing analysis unit  118 . The number of computers and the network configuration shown in  FIG. 1  are merely an illustrative example. One having skill in the art will appreciate that the dynamic pricing system  100  may include a different number of computers and networks. For example, computer  102  may include the property analysis unit  112  as well as one or more of the market analysis unit  114  and pricing analysis unit  118 . Further, the property posting unit  116  may reside on a different computer than computer  102 . 
         [0033]      FIG. 2  depicts a more detailed depiction of the computer  102 . The computer  102  comprises a central processing unit (CPU)  202 , an input output (IO) unit  204 , a display device  206  communicatively coupled to the IO Unit  204 , a secondary storage device  208 , and a memory  210 . The computer  202  may further comprise standard input devices such as a keyboard, a mouse, a digitizer, or a speech processing means (each not illustrated). 
         [0034]    The computer  102 &#39;s memory  210  includes a Graphical User Interface (“GUI”)  212  which is used to gather information from a user via the display device  206  and I/O unit  204  as described herein. The GUI  212  includes any user interface capable of being displayed on a display device  206  including, but not limited to, a web page, a display panel in an executable program, or any other interface capable of being displayed on a computer screen. The GUI  212  may also be stored in the secondary storage unit  208 . In one embodiment consistent with the present invention, the GUI  212  is displayed using commercially available hypertext markup language (“HTML”) viewing software such as, but not limited to, Microsoft Internet Explorer, Google Chrome or any other commercially available HTML viewing software. The secondary storage unit  208  may include an information storage unit  214 . The information storage unit may be a rational database such as, but not including Microsoft&#39;s SQL, Oracle or any other database. 
         [0035]      FIG. 3  shows a more detailed depiction of the computers  104 ,  106  and  108 . Each computer  104 ,  106  and  108  comprises a central processing unit (CPU)  302 , an input output (I/O) unit  304 , a display device  306  communicatively coupled to the IO Unit  304 , a secondary storage device  308 , and a memory  310 . Each computer  104 ,  106  and  108  may further comprise standard input devices such as a keyboard, a mouse, a digitizer, or a speech processing means (each not illustrated). 
         [0036]    Each computer  104 ,  106  and  108 &#39;s memory  310  includes a GUI  312  which is used to gather information from a user via the display device  306  and I/O unit  304  as described herein. The GUI  312  includes any user interface capable of being displayed on a display device  306  including, but not limited to, a web page, a display panel in an executable program, or any other interface capable of being displayed on a computer screen. The GUI  312  may also be stored in the secondary storage unit  208 . In one embodiment consistent with the present invention, the GUI  312  is displayed using commercially available hypertext markup language (“HTML”) viewing software such as, but not limited to, Microsoft Internet Explorer, Google Chrome or any other commercially available HTML viewing software. 
         [0037]      FIG. 4  depicts an illustrative example of the operation of the dynamic pricing system  100 . In step  402 , the real estate property analysis unit  112  gathers information on a specific real estate property (“target real estate property”). The information may be gathered via a web page displayed on a GUI  212  or  312  that requests specific information on the property including the address of the real estate property, number of bedrooms, total number of rooms, mechanical and electrical systems installed on the real estate property, lot size and any other information relating to the real estate property. The real estate property analysis unit  112  may also retrieve information on the real estate property from public records available such as tax records or deed records. The real estate property analysis unit  112  may identify the municipality where the property is located and electronically contact the municipality to request additional information on the real estate property. 
         [0038]    The real estate property analysis unit  112  may analyze and store documents pertaining to the real estate property that are retrieved from external sources. As an illustrative example, the real estate property analysis unit  112  may retrieve an electronic version plat of survey and calculate the dimensions of the lot where the real estate property resides using known document analysis techniques such as Object Character Recognition (“OCR”), line analysis or any other method of extracting data from a document. At a minimum, the real estate property analysis unit will gather the real estate property address, lot size, number of bedrooms, number of bathrooms, total number or rooms, and total square footage of the real estate property. The real estate property analysis unit  112  may gather additional information on the real estate property such as the schools associated with the real estate property address, crime reports for the area surrounding the real estate property or any other additional information on the real estate property. 
         [0039]    In step  404 , the market analysis unit  114  will gather information comparable to the information gathered on the target real estate property for the real estate market where the target real estate property resides. The market analysis unit  114  may gather information on real estate properties in the market having similar characteristics as the target real estate property such as the same lot size, same number of bedrooms or bathrooms, same square footage, or based on any other similar characteristic. The market analysis unit  114  also gathers sale and purchase information on each real estate property including the year and date of the last sale of a real estate property, the amount the real estate property was listed for and the amount the real estate property sold. 
         [0040]    In step  406 , the market analysis unit  114  generates a high value, low value and medium value for the target real estate property based on the real estate property information and the market information. The market analysis unit  114  may compare prior sales of similar properties to the target real estate property to determine the high, medium and low price points. As an illustrative example, the market analysis unit  114  may set the low price as the lowest price sold for a real estate property having the same or similar square footage, number of bedrooms and number of bathrooms. The market analysis unit  114  may also apply adjustment or weighing factors to compensate for differences in the characteristics of the real estate property. As another illustrative example, the market analysis unit  114  may increase a price by a predefined amount based on differences between the target real estate property and a comparable real estate property. In determining the low, medium and high prices, the market analysis unit  114  may require the low, medium and high prices be separated by a minimum amount of money to ensure the real estate properties are separated during searches. 
         [0041]    In step  408 , the real estate property posting unit  116  generates and displays separate web pages for the low, medium and high price for the target real estate property. Each web page includes the same images and description of the real estate property, but lists the real estate property for a different price. The web pages may be listed on the same website or on different websites. In one embodiment, the real estate property posting unit  116  stores a listing of property sales web sites and posts identical listings on each real estate property sales web site. In another embodiment, the real estate property posting unit  116  posts one web page on separate web sites and adjusts the pricing of the property between the high, low and medium price over a predetermined time period. 
         [0042]    In step  410 , the real estate property posting unit  116  monitors user activity for each of the posted web pages. The real estate property posting unit  116  may monitor and store the number of instances a web page is viewed, the number of e-mails sent concerning a posting, demographic information on the users viewing each posting or any other information relating to the users viewing each posting. In step  412 , the real estate property posting unit  116  gathers all information on each posting and analyzes the information relating to each posting. The real estate property posting unit  116  may assign a value to each posting based on the number of times a user viewed each posting, the demographic information on the person viewing each posting, the number of correspondence from users for each posting or any other information related to the posting. 
         [0043]    The value assigned to each posting represents the likelihood that the purchase price of the target real estate property is accurate. The value may be determined based on the both the quantity and quality of the interest shown in the posting. As an illustrative example, a posting that receives a large number of views and associated correspondence will receive a higher value than a real estate property receiving a smaller number of views. The real estate property posting unit  116  may also review the time period during which the real estate properties are viewed. As another illustrative example, a property that is viewed a number of times over an extended period would receive a higher value than a real estate property that is viewed a similar number of times immediately after the real estate property is posted. 
         [0044]    In step  414 , a new price for the target real estate property is generated using the values calculated for each posting. The new price may be the low price, medium price, high price or a value between the high price and low price. As an illustrative example, if the high price and medium price are assigned similar values, the real estate property posting unit  116  may calculate a target price between the medium price and high price. If the low price and high price receive the same or similar value, the target price maybe a value between the low price and the high price. 
         [0045]    In step  416 , the real estate property posting unit  116  posts a new web page for the target real estate property at the target price. In addition, the real estate property posting unit  116  may post additional postings for the real estate property with the value of the real estate property offset by a predetermined value. The real estate property posting unit  116  may analyze the new postings using the same criteria previously discussed. 
         [0046]      FIG. 5  depicts an illustrative example of the operation of the pricing analysis unit  118  gathering market information. In step  502 , the pricing analysis unit  118  performs a search of real estate property sales databases to identify properties having the same or similar characteristics as the target real estate property. As an illustrative example, the pricing analysis unit  118  may search a database listing real estate properties sold or currently for sale in the same geographical area as the target property. The pricing analysis unit  118  may search for real estate properties having the same or similar characteristics as the target real estate property such as real estate properties having the same or similar bedrooms or square footage. 
         [0047]    In step  504 , the pricing analysis unit  118  generates a list of identifying characteristics in the target real estate property. The identifying characteristics may be any defining characteristic of the real estate property such as the number of bedrooms, the total square footage of the real estate property, the number of garages or parking spots, the acreage where the property resides, the number of floors in the property or any other physical attribute of the property. The identifying characteristics may also include information on the community where the real estate property resides, including the ratings of the schools in the area, the crime rate in the area, the average income of the residents of the area or any other information relating to the market where the real estate property resides. 
         [0048]    In step  506 , the pricing analysis unit  118  identifies characteristics in the identified properties that correspond to each of the characteristics in the target real estate property. In step  508 , the pricing analysis unit  118  adjusts the market value of each identified real estate property based on differences between the identified real estate property and the target real estate property. As an illustrative example, the pricing analysis unit  118  may reduce the value of the identified real estate property if the identified real estate property is located on a lot having less acreage than the target real estate property. In determining the amount the value of the identified real estate property is reduced, the pricing analysis unit  118  may retrieve historical information on the approximate value of each characteristic. In the case of a real estate property with less acreage than the target real estate property, the pricing analysis unit  118  may determine the value of additional acreage to the overall value of a real estate property and adjust the value of the identified real estate property based on the historical information. The historical information may be stored in the memory  210  or secondary storage unit  208  of the dynamic pricing unit  102  or may be located external to the dynamic pricing unit  102 . 
         [0049]    In step  510 , the pricing analysis unit  118  determines weighing values for the target real estate property. The weighing values are determined by analyzing historical sales information on the market to determine specific real estate property characteristics that increase or decrease the value of the real estate property that may not be readily ascertainable by the structure of the real estate property alone. As an illustrative example, a real estate property located within walking distance of public transit may increase the value of a real estate property, while a real estate property located proximate to train tracks may reduce the value of the real estate property. To determine the increase or decrease in the value of the target, the pricing analysis unit  118  uses historical data to determine an increase or decrease in the sale of a real estate property based on a listing of predefined characteristics. The listing of predefined characteristics may be generated based on the geographical location of the property, information on users interested in the real estate property after the initial web posting, estimated demographic information of potential buyers or any other information relating to the value of the real estate property that is not readily apparent from just the structural description of the real estate property alone. 
         [0050]    In step  512 , the pricing analysis unit  118  determines the minimum value of the target real estate property based on the pricing of the identified properties. The minimum value may be the lowest adjusted priced of the previously identified real estate properties. In step  514 , the pricing analysis unit  118  applies weighing factors to the minimum value to determine an initial target price for the real estate property. In step  516 , the market analysis unit determines the medium price and high price by adding an incremental value to the target price. The incremental value may be a set predefined value or may be a percentage of the minimum value. As an illustrative example, the medium price may be fixed at $15,000 above the minimum price or 20% above the minimum price. 
         [0051]      FIG. 6  is an illustrative example of the operation of the real estate property posting unit  116  adjusting the price of the target real estate property based on activity from various web postings of the real estate property. In step  602 , the real estate property posting unit  116  posts web pages listing the target property for sale at a low price, a medium price and a high price. The postings may be on the same or different real estate sales web sites, such as realtor.com, Zillow.com or any other real estate sale web site. In step  604 , the property posting unit gathers information relating to each posting including, but not limited to, the number of views per hour, day, week and month, the duration each user spends viewing the web page, the number and content of each request for additional information on the property and any other information pertaining to the web postings. 
         [0052]    In step  606 , the real estate property posting unit  116  gathers information on the user&#39;s viewing the web postings including, but not limited to, the income of the user, the user&#39;s interest and hobbies, the age and marital status of the user or any other identifying information. The real estate property posting unit  116  gather this information directly or via an external source to provide information on the user. The information may be gathered using known web demographic applications such as Google Analytics. In step  608 , the property posting unit  116  determines the purchasing characteristics of each user based on the gathered demographic information. The purchasing characteristics may include a determination of whether a user&#39;s income would qualify them for a mortgage to purchase the target real estate property. The purchasing characteristics may also include an analysis of the types and prices of properties historically purchased by users with the same or similar demographic information. The historical purchasing information may be gathered and stored in the memory  212  of the dynamic pricing unit  102  based on prior activity on the web sites and deals brokered through the dynamic pricing unit  102 . 
         [0053]    In step  610 , the real estate property posting unit  116  determines the interest level of each user. The interest level of a user is determined based on their activity on the web posting including the number of times the user viewed the web posting, the number of correspondence initiated by the user concerning the web posting, and any other activity relating to the user&#39;s interaction with the web posting. The interest level of each user is assigned a score based on the user&#39;s interaction. The score and demographic information for each user is stored in the information storage unit  214 . 
         [0054]    In step  612 , the real estate property posting unit  116  generates a weighing factor based on the user information and interest level. In determining the weighing factor, the property posting unit  116  assigns a score to each of the demographic characteristics of the user including the income level, age, marital status, geographic location or any other demographic characteristic. Further, the real estate property posting unit  116  may assign a weight to the ability of the user to obtain a mortgage based on their income information. The real estate property posting unit  116  adjusts the weighting of each user based on the level of interest with the users with a higher level of interest having an increased weighted value. The real estate property posting unit  116  then determines an overall weighing factor based on the average of all the user&#39;s weighing factors. 
         [0055]    In step  616 , the real estate property posting unit  116  adjusts, via the pricing analysis unit  118 , the target price of the real estate property by applying the weighing factor from the web site. As an illustrative example, the target price may be set to the medium price posted on the web site. The user information may indicate that users with an income level well above the amount required to obtain a mortgage have indicated a strong interest in the real estate property. They pricing analysis unit  118  may apply a weighing factor generated by the real estate property posting unit  116  that increases the target price of the real estate property. In this way, the target price reflects not only the market price but also the demographic information of users showing interest in the target real estate property. 
         [0056]      FIG. 7  shows a possible embodiment of a website relying on the dynamic pricing technology. In this example, the page includes a world map showing active global listing inventory for property. Multiple different statistics associated with sale and listings are also given along with real time activity graphs. In this model, a user may click to scroll down and select a language of use, a currency, a country, a city, a category, a transaction, a size or even a price. The price for example will be determined using the dynamic pricing system described above. As shown, many other types of properties such as residential listings, commercial listings, vacation listings, private listings, new development listings, notes and debt listings, tax liens, and even portfolio listings can be used as property. 
         [0057]    In the present disclosure, the words “a” or “an” are to be taken to include both the singular and the plural. Conversely, any reference to plural items shall, where appropriate, include the singular. 
         [0058]    It should be understood that various changes and modifications to the presently preferred embodiments disclosed herein will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present disclosure and without diminishing its intended advantages. It is therefore intended that such changes and modifications be covered by the appended claims.