ML model scoring on CRM Data for Lead scoring optimization.

For a large Real Estate advisory company.

CLIENT & PROBLEM STATEMENT

  • Large Real Estate advisory company seeks lead scoring and optimization for sales efficiency on a live data processing basis.
  • Need for real-time, automated lead scoring using CRM data via APIs.

APPROACH

  • Established API connections with client’s sales CRM (MongoDB) to access lead data in real-time.
  • Developed an automated Machine Learning (ML) pipeline for continuous model training on historical lead data.
  • Implemented advanced ML algorithms to score incoming leads based on engagement, preferences, and financial indicators.
  • Created a scalable, event-driven architecture to process leads through the ML model instantaneously.
  • Established bidirectional APIs to send le
  • The incremental learning approach allowed the model to continuously improve based on incoming data, ensuring accuracy and relevance in real-time scoring.

SOLUTION & OUTPUT

  • Automated ML process adapts lead scoring models for optimal accuracy with new data.
  • High-value leads prioritised in real-time via API-driven CRM updates, boosting sales efficiency.
  • The model is now processing 3 million historical data points and scoring 100,000 incremental data points per month.
  • The system efficiently managed large volumes of data, enabling dynamic and responsive marketing strategies.
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