Business Case Studies & Business Publications

DIY Zillow

Lichtendahl, Kenne...

Case

DIY Zillow

Lichtendahl, Kenneth C. Jr.; Boatright, Benjamin; Andrasko, Joe

QA-0931 | Published December 14, 2021 | 9 pages Case

Collection: Darden School of Business

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This case examines a realtor’s attempt to improve an online residential real estate website’s mapping and home estimation features. With the help of a data scientist, the two professionals work to create an interactive map that provides greater filtering capabilities and improved school boundary views, allowing clients to easily locate homes in their desired school districts. In addition to the visualization enhancements, they also build a simple predictive model for forecasting a home’s current value. These forecasts can be used to evaluate properties on the market by comparing a home’s listed price to the estimated value from the model.

This case can be used to (1) demonstrate data collection and data processing; (2) introduce the “unit of observation” and the “unit of analysis” concepts; (3) teach the training and deploying predictive models; and (4) discuss how to build visualizations that utilize geographic information such as shapefiles.