Traditional methods for developing land and pricing new homes often miss the mark. The result? Missed profit. Our method uses seed models that are trained with your data, resulting in proprietary models that become your IP. With our approach, you get to keep your proprietary models and pay for model maintenance, refinement, and an ever growing dataset on a subscription basis.
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A Data Science Driven Approach
Our national home builder’s decision engine began with the cultivation of terabytes of data, including descriptions of the property itself (lot size, construction date, and number of bedrooms and bathrooms, among other factors), population characteristics, regional economic data, local crime statistics, price histories, local business characteristics, proximity to emergency services, local traffic flow data, and much more. These data points are combined from meticulously curated proprietary datasets. The final dataset contains over 145,000 newly constructed homes and 2.5 million parcels of undeveloped land with two thousand variables available for analysis.
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