Case Study: RealtyAustin boosts email engagement with KUNGFU.AI’s recommendation engine

RealtyAustin - Customer Case Study

RealtyAustin, a real estate company, wanted to drive more traffic to its website and improve engagement beyond what SEO was delivering. KUNGFU.AI was brought in to build a recommendation engine that could personalize weekly email communications and help RealtyAustin compete more effectively with Zillow, Compass, and similar platforms.

KUNGFU.AI implemented a machine learning recommendation system using user clickstream data—such as viewed, saved, and dismissed listings—to generate personalized property suggestions. The solution used an autoencoder-based approach and also included “wild card” recommendations to broaden results beyond a buyer’s usual geography. The impact was strong: RealtyAustin saw an open rate of 32.5% and a click-through rate of 14.4%, outperforming common email marketing benchmarks, and the model remained stable in production with no major drift detected.

RealtyAustin