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, leveraging AI as a part of the journey to help curate and create content that will keep customers engaged.
The solution: Create a content-driven approach to serving products to our customers, emphasizing product features and use cases over price.
These collections would be accessible on the homepage feed through a specialized banner like this one here featuring Badminton Fashion:
Result: After launching this project, we now feature thousands of hobby and interest-based collections on Wish. To date, these collections have contributed to an overall growth in GMV by 34%.
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.