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E-commerce Product Recommendation Engine

Draft
Recommendation Systems

An AI system that analyzes customer behavior, purchase history, and product attributes to provide personalized product recommendations.

e-commerce
recommendations
personalization
retail
Created by James Thompson on May 5, 2025, 11:30 AM
Last updated on May 5, 2025, 11:30 AM
Business Objectives
  • Increase average order value by 15%
  • Improve conversion rate by 20%
  • Enhance customer engagement and retention
  • Reduce cart abandonment by 25%
Success Criteria
  • Recommendation click-through rate >10%
  • Conversion rate from recommendations >5%
  • Customer satisfaction with recommendations >80%
  • System response time <200ms
Key Tasks
  • Analyze customer browsing and purchase history
  • Identify patterns and preferences in customer behavior
  • Generate personalized product recommendations
  • Adapt recommendations based on real-time behavior
  • Provide explanations for recommendations
Technical Requirements
  • Integration with e-commerce platform
  • Real-time data processing capabilities
  • Scalability to handle peak traffic periods
  • Privacy compliance for customer data
Associated Models (0)

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