Abstract: Offers and optimization have co-existed since long and industry has several solutions to address this need. However, identifying the right customer to target offers, assigning the right offer only when customer requires it and presenting offers even on long tail product is crucial to a successful offer assignment. Present application provides systems and methods that creating potential segments where in each user fits into any of the segments based on purchase history, navigation/behavior through e-commerce portal, demographics, and look-ahead scores. When a trigger is received in real-time, the system generates optimal real-time product recommendations for the users by eliminating popularity bias, based on his/her most recent product clicks in the e-commerce portal using a recommender system.

Abstract: Offers and optimization have co-existed since long and industry has several solutions to address this need. However, identifying the right customer to target offers, assigning the right offer only when customer requires it and presenting offers even on long tail product is crucial to a successful offer assignment. Present application provides systems and methods that creating potential segments where in each user fits into any of the segments based on purchase history, navigation/behavior through e-commerce portal, demographics, and look-ahead scores. When a trigger is received in real-time, the system generates optimal real-time product recommendations for the users by eliminating popularity bias, based on his/her most recent product clicks in the e-commerce portal using a recommender system.