Location, location, location.
It’s the oldest real estate adage in the world. And how can you develop the clearest possible understanding of a location for your customers and other data users? How can you convey a property’s true value, potential and limitations?
Data, data, data.
Watch the Ground Truth: Improving the Real Estate Customer Experience with Higher-Quality Data on-demand now. In just a half hour, you’ll learn how investment in the right data sets can help improve your data strategy — then improve your business.
Free data abounds, published by private companies and government agencies. You know this. Surf over to the local school district web site, and you can tell which catchment area a house sits in. A maps app on your smartphone can pinpoint how close a property is to local museums, community pools, shopping centers and other amenities and points of interest.
But from our experience providing data to some of the largest real estate businesses in the world, Pitney Bowes knows that industry professionals often find two problems with free data: its age and its interoperability.
In the data industry, free data often means “dirty data.” It comes with no guarantee: the onus is on you to ensure its accuracy. And even if you do find an accurate-when-written boundary-based data set, things change. Boundaries move. Populations increase and schools narrow their catchment areas. A community pool closes and a condo tower rises in its place. Free data is not updated often enough to keep up with the pace of change.
Stale data makes for unhappy customers. Do you want to face a developer who learns, after purchasing a few hundred acres, that only half his planned community now sits in a desired school attendance zone? Or a homeowner who, shortly after moving in, learns they are technically not within a trendy neighborhood, but only one block from a less-desirable one? Real estate will always be a word-of mouth business, and these customers’ dissatisfaction will cost you.
Interoperability is a second headache. Premium data is sold in established computing formats and languages: MapInfo TAB, GeoJSON, Shapefile, and WKT. Free data sets often come in nonstandard formats, with nonstandard data fields. For example, formatting of names and address may vary: John Q. Smith’s information may alternately appear as “John Q. Smith, 456 12th Street,” “Smith, John Q., 456 Twelfth Street,” or “John Smith, 465 Twelfth St.” Real estate companies often spend enormous amounts of time validating and standardizing free data for “like to like” comparisons, and for interoperability with internally held data.
Good data grows business. Bad data stymies it. But not all data sets — even premium data sets — are created equal. And the risk of implementing bad data sets its significant: it takes a lot of time to rip out incompatible or inaccurate data and start over.
To improve your real estate business, you need to find data that is professionally curated, comprehensive, regularly updated, and built out with professional GIS rigor. Only then can you build a data strategy that helps you:
- Improve property insight
- Use hard evidence to bolster your recommendations to buyers
- Help sellers set the most competitive asking prices possible
- Avoid the customer dissatisfaction and damage to reputation that can arise from recommendations based on inaccurate or out-of-date-data
Your competitors are already honing their data strategies. Don’t be left behind. Register now for The Ground Truth to learn how to make the best data decisions for your real estate business. And don't forget to watch the webinar on-demand.