This project explored product-level engagement and category strategy for Sephora’s digital storefront using a cross-sectional dataset of 600+ SKUs. The team conducted K-means clustering to identify product personas, correlation analysis to assess relationships among pricing, popularity, and satisfaction, and ANOVA to evaluate how features like exclusivity and rating varied across categories.
Recommendations included prioritizing emotionally resonant segments for loyalty and content campaigns, repositioning high-rated but low-visibility products, and expanding exclusive digital-first launches in high-performing categories like skincare and fragrance.