Data Science Techniques for Real Estate
As discussed in RealWorld 2018 sessions
Most people won’t argue with you about the importance of data. There are more data sources now than ever before, and we know we need to tap into them—but collecting the right metrics, interpreting properly and translating into business decisions that improve results is another story.
Savvy property management professionals are bridging this gap by stepping into the role of the data scientist, no lab coats or beakers required. At RealWorld 2018, RealPage’s own data scientist Rich Hughes led data-driven experiments and put numbers to the test in “Data Science Techniques for Real Estate.” Hughes challenged attendees to rely on statistical evidence, rather than conjecture, when evaluating real estate decisions.
The proof is in the numbers
We can speculate all day, but numbers have power and convey truth. How are you evaluating your performance data? How well do you understand your market conditions and competition? Are you getting the right types of leads? The answers to each of these questions can be uncovered using data science.
As any good scientist knows, a thorough process needs to be followed when performing an experiment. Hughes recommends following the scientific method—hypothesizing, testing, analyzing and revising— when evaluating the key drivers of performance in multifamily.
Putting data to the test
Hughes led hands-on experiments during the session, walking through several commonly-held conjectures in multifamily to debunk the myths. These included:
“Mandatory Renters Insurance negatively impacts revenue performance”-Hughes shared insights into a RealPage study, which analyzed leasing data for 156 communities nationwide. Led by Hughes, the study compared the revenue performance of properties that mandate renters insurance against the performance of similar properties that did not in the same markets, sub-markets and ZIP codes. Based on the stat...