Leboncoin

User research

Understanding where trust breaks down in the journey

On Leboncoin, the trust problem isn't technical, it's a readability problem. I conducted exploratory interviews and analyzed community forums to understand where exactly trust breaks down in the journey.

Marc and Sophie embody two sides of the same problem. By cross-referencing their feedback with community forums, a pattern emerges: the problem isn't security, it's its visibility. Trust signals exist in Leboncoin's data (history, responsiveness, disputes, secure payment usage) but none are synthesized into a readable indicator for the buyer.

This insight refocused the design question: it wasn't about creating a new security system, but making the existing one visible. The question became: what mechanism transforms existing behavioral data into a readable trust signal for Sophie, without adding friction for Marc?

The badge and its criteria

An indicator calculated from already existing data

The answer: a verified seller badge, automatically calculated from data already captured by Leboncoin. Four criteria, zero manual verification.

These four criteria are already measurable by Leboncoin without any additional data. The badge requires no manual action from the platform, it is calculated automatically.

The badge alone is a static signal. For it to change behaviors, it must create an incentive: sellers adopt secure payment to earn the badge, which generates the data that feeds the badge.

This incentive mechanism is what distinguishes the badge from a simple cosmetic label. To visualize and validate it, I designed its integration into three touchpoints of the existing journey.

The virtuous loop

A cycle where each transaction strengthens trust

The badge is not a cosmetic label, it's a behavioral lever that aligns the interests of the buyer, the seller and the platform.

Product impact

What the badge changes for buyer, seller and platform

Without real data available on a concept, the challenge was to demonstrate that the badge integrates without friction and creates a measurable incentive. The prototype validates the journey and impact is read through the behavioral levers activated.

Without real metrics, impact is measured by the levers activated. Every additional secure transaction is a data point captured, a seller retained, and a buyer reassured.

This concept demonstrates that a trust problem can be solved at scale without redesigning the experience, by aligning the incentives of all three parties: buyer, seller, platform. To validate this hypothesis, the next step would be testing the badge in real conditions on a high-volume category and measuring its impact on conversion rate and secure payment adoption.