AI-Powered Virtual Try-On for Amazon Luxury Store
This product introduces a virtual fitting room and AI-driven outfit recommendations for an Amazon online store, improving the shopping experience and boosting customer engagement.
Amazon Luxury Stores is an online shopping platform that sells fashion and beauty products from luxury brands.
This project incorporating AI recommendations and virtual try-on, has significantly transformed the shopping experience, providing users with a dynamic and engaging way to explore and interact with fashion products.
3D mode
AI conducts intelligent searches, generates virtual avatars based on user-uploaded data, and provides intelligent outfit recommendations.
Picture Mode
The two fitting modes can be freely switched. In the photo mode, user can upload their own photos for virtual try-ons, providing a broader range of visual effects.
Problem Overview
Based on user surveys, it was found that users spend no more than 5 seconds viewing a product from the Amazon luxury store. Approximately 30% of the 2000 shoppers surveyed are willing to consider making a purchase, indicating low user intent and engagement.
Business Opportunity
Utilizing AI for personalized recommendations and VR applications in online shopping can significantly influence consumer purchasing decisions and enhance interactivity.
User Research
Based on 70+ surveys and interviews with 5 users who are current or former Amazon shoppers with experience in buying clothing and fashion brands online, I found that most consumers perceive offline shopping as secure due to sizing issues and concerns about product accuracy.
User comfort with adopting new technology is shaped by perceptions of value, enjoyment, informativeness, and overall consumer experience, affecting their purchase intentions.
Ideation—Breaking Down Data
I conducted an affinity mapping process to analyze research data, grouping data points into categories and distilling key insights. Users desire to efficiently view fitting effects based on their data and receive personalized recommendations.
HMW enhance AI-powered virtual try-on systems to leverage personalization for individual user preferences?