Real estate search portals are consistently trying to offer the best, most unique information to their users and search engines. As the 5th largest portal in the US, Homes.com collects a massive amount of anonymous data from on-site user behavior, however data at the scale of hundreds of millions of interactions is challenging to aggregate and summarize. With a comprehensive understanding of both the demand and supply sides of real estate availability, Homes.com can offer more personalized recommendations that better address user needs and inventory targeting.
We used data from user site searches as a proxy for housing demand, geo targeted to specific locations and cross referenced with listing availability (almost 3 million records) in each US market. Using this data, we created an adequate but valuable KPI that defines areas where housing demand might lead to fluctuations in pricing, and the velocity of those prices changes, based on the anticipated inventory of listings versus the real-time search behavior.