08/12/2025
✨ What if Sephora could predict customer satisfaction before a product even hits the shelves? ✨
In this analytical project at Canadian University Dubai, we used real consumer behavior patterns, regression models, and sentiment insights to understand what truly influences satisfaction with Sephora’s makeup products.
From shade-match accuracy to formula performance and brand perception metrics — this study reveals how data can help forecast buying decisions and refine product strategies at scale.
This full research, analysis, and presentation were developed and delivered by Ameena Ashfaque, highlighting how predictive analytics can transform the future of beauty innovation.
Sephora — here’s a glimpse of how your next big trend can be predicted with data.
Watch the full video to see the insights unfold.
| Sephora Consumer Satisfaction Analysis | Sephora Makeup Analytics | Predictive Modeling Beauty Industry | Customer Behavior Insights Cosmetics | Beauty Product Performance Data | Sephora Data-Driven Strategies | Consumer Sentiment Analysis Makeup | Canadian University Dubai Analytics Project | Beauty Industry Predictive Analytics |
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