Build Me a website for real estate statistics using R

When picking a real estate agent to sell or lease a property, most owners engage an agent based on an established relationship or go with the agent that promises the highest price. More often than not, this selection process is detrimental to the lender and mortgagor in optimising the sales/leasing result for a property. Unlike applying for a loan, there is no formula or set of established acceptable metrics and parameters for determining whom the best real estate agent is to sell or lease a property…until now. My website, [login to view URL] is a decision engine to assist mortgagees and mortgagors by identifying who the best agent(s) are to sell or lease an asset, By The Numbers, using a location specific, geospatial market augmented sales and leasing metric algorithm with prescriptive and predictive attributes. In plain speak, it focuses on the jockey not the horse. [login to view URL] computes a few hundred thousand data sets a minute so that stake holders can make better informed decisions, using hard data to correlate, compare, rank, quantify, qualify and identify whom to engage when selling or leasing a property. [login to view URL] is data driven decision making. [login to view URL] is an adaptable platform for the financial service industry.