ALS(Alternate least square) ModelSuccessfully implemented a collaborative filtering recommendation system using the Alternating Least Squares (ALS) model, a matrix factorization algorithm, to provide personalized recommendations based on user-item interactions. Developed the recommendation engine for a customer base of 250k and product base of more than 50k which captures around 20% of the revenue, with 25% of user conversionsFTB ModelDeveloped a propensity model and provide a… Show more ALS(Alternate least square) ModelSuccessfully implemented a collaborative filtering recommendation system using the Alternating Least Squares (ALS) model, a matrix factorization algorithm, to provide personalized recommendations based on user-item interactions. Developed the recommendation engine for a customer base of 250k and product base of more than 50k which captures around 20% of the revenue, with 25% of user conversionsFTB ModelDeveloped a propensity model and provide a quantifiable score to the registrants indicating their probability to make first order in the next month . Successfully expanded the propensity model from 4 to 20 clients and later to all affiliate clients. Rigorously tested and validated, resulting in top deciles consistently outperforming default response rates(0.84%). Show less

Advocacy modelSuccessfully implemented a data-driven approach to segment customers into 7 distinct clusters enabling more personalized marketing strategies . This resulted in improved customer engagement and loyalty through targeted offers and promotionsRFM AnalysisImplemented RFM (Recency, Frequency, Monetary) analysis to segment customers into 4 clusters with RFM bands (1-4) for each parameter. Collaborated with cross-functional teams to translate RFManalysis results into… Show more Advocacy modelSuccessfully implemented a data-driven approach to segment customers into 7 distinct clusters enabling more personalized marketing strategies . This resulted in improved customer engagement and loyalty through targeted offers and promotionsRFM AnalysisImplemented RFM (Recency, Frequency, Monetary) analysis to segment customers into 4 clusters with RFM bands (1-4) for each parameter. Collaborated with cross-functional teams to translate RFManalysis results into personalized marketing campaigns . Show less