AI-driven recommendation service that forecasts homeowner’s intention to sell a property.
Client
Real estate technology startup automating the process of home selling for the agents.
Objective
Client was looking to build an AI-driven recommendation service that forecasts homeowner’s intention to sell a property for a given geographical market in order to generate leads for the agents.
Solution
Our data science team reviewed both public and private data sources, analyzed and labelled the data, selected the proper algorithm, and finally built the Machine Learning model that generates home sales predictions. Then our software engineering team wrapped the model into a cloud-based microservice API and integrated the solution with the client’s platform.
The service offers the following features:
Multi source data fusion: location, sales transaction history, property listings, census data on county level, etc.
Integration with 3rd party GIS services to fetch, process and visualize the data
Classification and labeling of the documents based on the predefined rules
Propensity modeling: predicting “intention to sell” probability for any given property
Predicting seasonal market trends for defined area
Result
Our AI-powered recommendation engine serves as a secret sauce of the client’s real estate platform. It gives the platform a major competitive edge and allows to generate qualified leads at a fraction of a typical market cost.
