Real Estate Revolution

Right now, real estate wholesalers have to spend a great amount of time and money towards finding potential motivated sellers in residential real estate markets. Wholesalers have to research potential sellers for the purpose of generating a mailing list to send out hundreds to thousands of letters to find the right person that is willing to sell their property. These lists are often vast with a low conversion rate - the current systems in place are costly, demanding, and inefficient.
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DataFlik provides a massive competitive advantage for real estate businesses by using AI-powered List Stacking and Predictive Modeling to focus marketing efforts on the owners that are most likely to sell and generate the highest return possible. NineTwoThree created a machine learning model that has the ability to generate a motivated sellers mailing list that is focused and has a higher degree of confidence as compared to traditional methods.

DataFlik had to provide a large amount of data to create an effective machine learning model. The real estate data needed to achieve the desired goal is extremely expensive. We had to prove that our proposed model will achieve its goal of generating an effective motivated sellers mailing list - without developing the full model - to justify the purchase of such data.
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Processing the data was another challenge, because producing fast results is technologically complicated and demanding due to the sheer volume and breadth of the data we received. It consists of millions of properties across the US and each individual property has about 1,700 data points. We had  to find a way to efficiently process the data in a timely manner to produce a working baseline.