InvestorLoft Awarded Best New Real Estate Investor Tool Of 2008

INTRODUCING INTELLIGENT PROPERTY SEARCHES
Eighty seven percent of all house searches begin on the Internet. The Web hosts thousands of real estate search sites with millions of listings and little to distinguish site A from site B. The typical property search, especially for an investment property, results in more questions than answers.
   
YESTERDAY — ANALYSIS PARALYSIS
The standard search identifies properties by their physical characteristics, such as a single-family home, duplex, number of bedrooms and bathroom, location and price. The result is a list of addresses. Then, investors slog through the listings and may identify the one or two properties that may be appropriate. If not, they repeat the process.

Then the analysis begins. The investor considers price, financing, expected income and expenses to calculate returns to make an intelligent buy or no buy decision.

The search is more complex if they are looking for an appropriate property for a 1031 exchange or self-directed IRA portfolio.
   
TODAY — SEARCH GENIUS
InvestorLoft stands this model on its head. It allows investors to create a profile based on their requirements (deposit amount, credit capacity, return goals, etc.), and produces a short list of properties that meet those requirements.

InvestorLoft surpasses current systems in other ways, too. Suppose you’re looking for a positive cash-flow rental to add to your investment portfolio. You have created a list of properties using your requirements, such as return expectations and calculated possible deposit to loan(s) ratios. Then, what if the asking price is not a market price? What are the real market rents?

InvestorLoft uses two proprietary pricing engines.
1. A discrete automated valuation model (AVM) to arrive at a comparable expected property strike price (comp). It also displays results from the three most popular home pricing sources: Zillow, CyberHomes and Eppraisal.
2. Another valuation function allows investors to compare rental data to their own comparison model. InvestorLoft gathers public rent data and further refines typically fuzzy rent data and provides more accurate rental income estimates for more precise investor goal analysis.
Other purchase fees and operational expenses are derived from the listing data or from current market data and known expense models, like homeowners’ association fees, insurance and taxes.

InvestorLoft’s ground-breaking system filters properties based on investors’ criteria and delivers a short list of properties that meet investors’ needs. The resulting short list eliminates hours and days of number crunching to find and model an appropriate investment property.
   
EMPOWER THE EXPERTS?
A major miscue of many Internet real estate implementations is to sideline industry professionals and propose a new real estate trading model. The industry is not likely to adopt an automated system that excludes professionals.

Wall Street is a perfect example of automation for the right reason. Stock trading volume outgrew human capacity. When computer-aided trading arrived, professionals and staff saw it as a welcome solution that eased drudgery and expanded business.

Many Internet real estate automation tools tried to gain acceptance by replacing professionals. They started with the theory that “smart customers can buy and sell real estate and eliminate the dreaded and expensive middleman.” Great idea — if real estate was simply a commodity.
Cutting out the people most likely to use it is like shooting oneself in the foot. To succeed with an Internet application, the technology must reflect industry culture. InvestorLoft has mastered the culture elegantly.

Instead of excluding professionals, the best real estate Internet tools assist the professional to provide better service. InvestorLoft does more than leverage the professional real estate agent, lender, appraiser, 1031 exchanger, self-directed IRA custodian or other service provider skills; it ensures the value of their role.

NO FISHING ALLOWED
One of the reasons professional real estate associations were formed was to set practice standards and protect members. Real estate professionals and brokers fear constantly that someone will steal their clients. The other fear is that someone will then “fish upstream” and take away prospective clients as well. This is also true for 1031 exchangers, self-directed IRA custodians and anyone who derives revenue from a successfully served real estate or investor customer.

Understanding this sensitivity, InvestorLoft developed a technique called Refer Safe that attaches account ownership of any referral to the source of that referral. For example: 1031 exchange companies frequently have customers with little time to find and close on a qualified property. Miss the date; pay taxes prematurely. With InvestorLoft, a 1031 intermediary can refer clients with two assurances; they will quickly find a qualifying property, and a client will never be exposed to a competing qualified intermediary while on the site. The same is true for all other service providers like real estate agents, brokers and lenders.

COMMISSIONS ASSURED MEANS ADOPTION ASSURED
To place a listing on InvestorLoft.com the vendor of the property must be an owner/principal of the property or a licensed real estate agent representing the seller or a buyer. This maintains industry co-broke and referral fee conventions and protects professionals. This guarantee stimulates business. This also means that fly-by-night deals will not enter this environment.

“Empowering versus ostracizing professionals has already proven to generate phenomenal viral market growth for InvestorLoft.com,” says president Walter Charnoff. “Each real estate professional brings an average of ten investors to participate in our site. The glorious problem we have now is we do not have enough listings. The great news is that every time we explain our Refer Safe and co-broke requirements, investment-appropriate inventory follows.”

The industry-leading brokerages who have committed their listings to InvestorLoft bring thousands of independent real estate agents, and tens of thousands of real estate investors selling or seeking property, to the InvestorLoft community.
Charnoff sees the majority of these professional or investor members as future self-directed IRA investors, if they are not already. “The implication is that today the $1.6 trillion (as of 2006) that investors have in self-directed IRAs have never had a better opportunity to get into long-term investment real estate at the lowest market prices with highest cash returns,” says Charnoff.

“AMAZON EASY” GAME CHANGER 
Who wouldn’t use an intelligent investment search engine that is as easy to use as Netflix or Amazon, saves time, keeps and serves clients better, and protects commissions?

InvestorLoft’s management team and employees have been to this movie before. The roster consists of former financial planners, real estate investors and licensed real estate professionals. Charnoff was a registered investment advisor and head of a successful Bay Area financial advisory firm that served demanding Silicon Valley investor clients. He is an inventor of patent-pending marketing technology for investment practices who founded and led other successful technology companies that cater to the financial services and real estate sectors.

“This vast market is grossly underserved,” says Charnoff. He saw that the way of selecting investment real estate was completely backwards. If investors know their investment goals, why not search for the answer, not the question.

InvestorLoft is changing the game by offering smart solutions.    

Because of their innovation, Personal Real Estate Investor Magazine awards InvestorLoft “Best New Real Estate Investor Tool of 2008.