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Machine Learning Analytics

Implemented machine learning analytics to improve the results accuracy and increase conversion rates

Challenges

  • The client wanted to provide an easy to use tool for realtors to analyze their end customers and increase conversion ratio under the line of businesses Buy, Sell, Rent, Lease, Break-Lease, Renew-lease.
  • They wanted to bring the power of machine learning into their analytics application in order to improve the accuracy of the results and reduce the gaps between onsite and marketing people

Solutions

  • Designed and developed predictive analytics and self-service predictive analytics workflows blending third party and own datasets
  • Implemented customer segmentation using ML models which helps realtors in identifying target customers group for a better conversion ratio
  • Implemented self-serviced ML models which allowed realtors to have personalized reporting
  • Developed machine learning models to get propensity of the customer to buy/sell property
  • Developed workflow to refresh predictive algorithms on-demand basis without any manual efforts

Tools & Technologies

Python, scikit learn, AWS, MySQL, Java

Key benefits

  • Improved customer experience by giving more control through self-service predictive analytics
  • Increased prediction accuracy
  • Enabled realtors to engage effectively with each persona type, thus enabling a superior customer experience
  • Helped realtors in redirecting marketing efforts and campaigns in the right direction (focusing on the top 2% of prospects who are most likely to buy in a particular month) instead of reaching out to all the prospects
  • Machine Learning pipeline helped them to build predictive models for new realtors quickly