Analytics (Al,ML) Services AI-Driven Recommendation Platform

About the customer – Customer is one of the top 4 Credit card company in the world

Customer Challenge

  • Create a recommendation model for cross-sell/up-sell recommendations for 80+ Million users
  • Performance requirements of 300-350 TPS
  • Create a Multi-Touch Attribution Model (MTA) for channel optimization
  • Integrate Data from 10+ different sources for building both models

NucleusTeq Solution Approach

  • Developed  a product recommendation engine that personalizes recommendations for 80 million customers
  • Created a high availability big-data platform where the recommendation engine processes the data
  • Created high availability API infrastructure to address the high TPS requirement
  • Created a graphical model for MTA

Outcomes Delivered

  • Savings of millions of dollars in promotional expenses
  • Increased Net New Conversions from  2% to 7%
  • Increase Upgrade Conversions from 8% to 14%
  • Model for channel budget allocation led to increase in ROI


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