Can a real estate firm that focuses on small towns use big data? The biggest promise of big data is targeted advertising. Have you ever wondered about targeting your advertising to different lifestyle groups, because in the end, with the home, comes a host of other daily practices: gardening, horses, going to school; and these daily life considerations weigh heavily in home buying. In selling a home, you want to find the person whose lifestyle most closely matches what that home or property has to offer. In selling vacant lots for semi-truck parking, I suddenly wish all my friends were truckers so I could get insight into what their companies are looking for~ how do I get to know this demographic if I don’t personally? For Renee Morrison’s listing in Palisade, the person who wants to grow Red Zinfandel grapes needs to know about the opportunity, and for the hunting camp on Divide Creek, the right paterfamilias will be the interested buyer. On the Western Slope finding a buyer can be like finding a needle in a haystack because you first have to find people who already do or can imagine their lifestyle here rather than an urban center. In addition, the particular demographic groups that enjoy living here have very specific tastes, and are pursuing different lifestyles. Are our ads reaching the RV retirees, the climbing guides with young families, the fifty-something sportsman, and the soccer moms? Advertising in the usual outlets gets the word out to the real estate community, but how can we target different ads to different lifestyle niches? How can we use all the data collected constantly on social media, the mls, and in our contact files to find those friends of friends who absolutely dream of living outside of Silt or even in Mack, or Hotchkiss or Meeker? The special buyers that want a particular kind of rural Colorado dream home or commercial property because they know that these are great places to be.
Inman Blog Article “How Big Data Improves the Real Estate Industry” observes that big data has helped real estate agents in the obvious way of providing the comparables. Real estate investors are interested in which economic and demographic variables predict real estate spending and market potential in a specific area so they can accurately predict the worth of units in a new development. Appraisals are another obvious way data helps the real estate industry. This Dataeconomy article notes that the availability of data improves the speed and accuracy of appraisals, which determine the speed of so many other related decisions in a transaction. This Location Inc Article covers the same territory.
This QuickenLoansBlogPost has some more specific ideas for realtors, about how to optimize targeted markets with easy tools at your fingertips, like emails and facebook ads. This article from PromptCloud discusses the way gaining feedback on the home is a contribution data collection methods have made to helping realtors. Of course, there is rarely a blog article without a pitch at the end, and prompt cloud tries to sell you on something called web scraping for real estate, but this is just basic data management you are probably already doing yourself. Is a milennial good at exporting to xlm or csv and then compiling those files going to come up with more insights about your market when they don’t live near it? Not sure.
Geospatial data seems like the most interesting use of big data, not about people who already live in a certain area, but to target people who are indicate they are considering moving there. It is probably worthwhile to investigate the data you can already export from the mls syndicators, and merging data files if you can export the same file type out of multiple sites.
Don’t forget to check out the amazing Western Slope and Roaring Fork Valley properties for sale by our Cheryl&Co agents when you are done thinking about data and just want to look at some real estate.