AI Recommendation Engine Boosts E-Commerce Sales

Client

A leading online fashion marketplace with over 1 million monthly active users.

Challenge

The platform experienced high bounce rates and low average order values. Customers were overwhelmed by an extensive product catalog, resulting in decision fatigue, cart abandonment, and missed purchase opportunities. Existing recommendation tools lacked the depth of personalization required to drive meaningful engagement.

Solution

The company integrated an AI-powered recommendation engine that analyzed:

• Real-time browsing behavior
• Purchase history
• Demographic and preference data

Personalized recommendations were delivered seamlessly across:

• Homepage
• Product detail pages
• Email campaigns
• Checkout screens

The AI continuously refined recommendations using feedback loops, improving relevance and accuracy as user interaction data increased.

Results

• 28% increase in total sales
• 19% boost in average order value
• 15% reduction in cart abandonment rate
• Higher repeat purchases and improved customer satisfaction

Key Benefits

• Highly personalized shopping experiences across all customer touchpoints
• Faster product discovery with reduced decision friction
• Increased cross-selling and upselling opportunities

Impact Quote