Hyper-Personalizer
An eCommerce recommendation system that analyzes real-time user behavior to serve highly personalized product suggestions, boosting conversion rates by 22%.
Project Details
A full breakdown of the features and modules delivered as part of this project.
Category
Retail
Year
2024
Duration
5 Months
Stack Size
5 Technologies
Key Features
6 ModulesGraph-database driven recommendation engine mapping user-product-session relationships.
Real-time user intent detection adapting suggestions within seconds of landing on any page.
Personalized homepage carousels, product detail cross-sells, and cart upsells.
A/B testing framework for continuously measuring and improving recommendation quality.
Cold-start model for new users leveraging demographic and referral data.
Back-office merchandising dashboard to manually pin or exclude products from recommendations.
Key Results & Impact
Measurable business outcomes delivered through this project.
Boosted overall site conversion rates by a staggering 22%.
Increased Average Order Value (AOV) by 18% through intelligent cross-selling.
Drove a 35% increase in click-through rates on personalized homepage carousels.
Reduced catalog search abandonment by actively surfacing relevant items.