Personalizing the Shopping Experience
Increased Average Order Value (AOV) by 25% through intelligent real-time product recommendations.
Client
VogueVibe
Industry
E-commerce
Duration
4 Months
Services
2 Core
The Challenge
VogueVibe had a vast catalog but struggled with low conversion rates. Customers were overwhelmed by choices and often left the site without finding items they liked.
The Solution
We implemented a personalized recommendation engine that analyzes user behavior, browsing history, and real-time intent. By using a RAG-based approach, we were able to provide semantic product search and 'style-match' suggestions based on natural language queries.
The Impact
Conversion rates increased by 18% within three months. The average order value grew by 25% as customers found more relevant items. Customer retention also saw a 12% boost due to the improved relevance of marketing communications.