Creating personalized discovery experiences with AI
Wish revolutionized discovery shopping, but competition has crowded the space with feed-based experiences.
To set ourselves apart, we imagined a content-led approach that leveraged AI to curate and create content that would keep customers engaged.
Solution: A content-driven approach to serving products, emphasizing product features and use cases over price.
These collections were accessible on the homepage feed through specialized banners, such as a featured “Badminton Fashion” collection.
Result: After launch, we featured thousands of hobby- and interest-based collections on Wish. These collections contributed to an overall 34% growth in GMV.
As the lead UX Writer for this project, I was tasked with optimizing our approach to UX writing for interest-based collections and micro collections. The collection’s content ask consisted of:
My goal was to create content that provided context for the micro collections, serving as the guideline for future AI-generated content collections. Additionally, I would begin engineering AI prompts that can generate engaging content for products within the collection.
Timeline: Initially, the project managers asked for a one-week turnaround for 250 collections. As the sole UX writer on the project, I made it clear that with content generation and reviews from legal and localization, the work would take at least 3-4 weeks to complete. For context, I delivered content for 160 collections in 3 weeks before instituting AI.