Depop
Rebuilding Community on Depop
Ariel, Robin, Anjolee, Emily
Context
What is Depop
Depop is a global secondhand fashion marketplace with over 43.5M users since 2011, driving the rise of resale culture.
The Challenge
Why Redesign Depop
As design lead, I selected Depop because I felt that its core identity of being a social, community-driven resale was underserved by its own product. The platform had the audience, but it lacked the infrastructure to activate them.
Where Does Depop Stand
We conducted a competitive analysis across six major resale platforms to understand where Depop's strengths could be extended and where structural weaknesses existed.
Depop stands out for its social media feel and the ease of shop setup, but lacks structured personalization across discovery and recommendations.
People’s Perception of Depop
To gauge people's attitudes toward Depop as well as their secondhand shopping habits and style inspiration process, we conducted surveys (92) and interviews (10) with college students.
Users rely on social connection for both purchase confidence and fashion inspiration.
- Users primarily seek fashion inspiration from people they feel personally connected to, such as friends and influencers
- Users hesitate to purchase from sellers they do not trust
Depop's marketplace is built around people, yet the platform does little to foster meaningful connections between them. By strengthening community and social trust, Depop could simultaneously improve fashion discovery and increase purchase confidence.
Users often hesitate to purchase on Depop due to a lack of trust in individual sellers. At the same time, most respondents turn to people they feel connected to, such as influencers or friends, for fashion inspiration.
- Community: More accessible points of interaction fosters community
- Streamlining listings: Sellers need a faster, guided listing flow. Buyers need structured condition and sizing data. Solving seller friction directly improves buyer confidence
- Personalizing discovery: Users preferred curated feeds from people and aesthetics they already followed—discovery was inherently social, not algorithmic.
Problem Framing
The research crystallized a specific strategic challenge:
How might we increase community engagement by personalizing discovery and streamlining the listing process?
This framing addressed two critical levers. For the buyer, personalized discovery makes purchases from unfamiliar sellers feel lower-risk by grounding them in trusted networks. As for the seller, streamlined listing reduces friction, thus increasing inventory supply and reinforcing network effects.
From there, we extracted key findings and translated them into insight statements to guide our design decisions and priorities.
Design Direction
With these insights as north stars, we mapped the information architecture to support both goals: a streamlined, transparent selling experience and a discovery layer grounded in community.
The information architecture structured:
- Home: general repository of what’s trending overall, as well as a more personalized daily edit where you can update your style preferences
- Explore: category and trend-based browsing for discoverability
- Add: step-by-step listing flow to reduce seller friction as well as a novel outfit builder capability
- Account: houses profile presence and also an archive of liked items and outfits
Prototype
Wireframing & Iteration
We moved quickly into lo-fidelity wireframes to pressure-test the IA against real user flows.
As a way to push boundaries, I had each member draw prototypes for every screen. I wanted to see everyone’s interpretation of the concepts to ensure that we weren’t limiting our ideations.
From there, we spent some time reviewing each others’ concepts and identifying key features to carry forward. Once we aligned on the direction for each page, we were ready to create low fidelity mockups.
Design Decisions
Each solution directly addressed a problem identified during wireframing. Rather than beautifying existing flows, we restructured them around our core insight: community trust drives conversion.
01: Home Feed
