NextMark

The work behind the app was iterative and grounded in how resellers actually operate. I started with research into how people handle authentication and market data, and where the information overload sets in. That fed wireframes built around simplicity, guided actions and clear hierarchy. Several rounds of prototyping and testing later, onboarding and the dashboard felt obvious rather than clever.

The luxury resale market is exploding. We're talking about a $50B+ industry by 2025, growing 15% year over year. But here's the thing: counterfeit goods are increasing just as fast. For every authentic designer bag on the market, there are three fakes.

This creates a massive problem for resellers. They're the middle people between individual sellers and buyers, and their entire business depends on trust. One fake item can destroy their reputation, cost them thousands in chargebacks, or even get them banned from resale platforms.

When we started this project, the authentication landscape looked like this:

Manual authentication services: ship your item to a facility, wait 24-48 hours for results, pay $20-50 per item, and get a certificate back.

Early digital solutions: take photos yourself, upload to an app, wait 2-6 hours for "expert review", and get a yes/no answer with no context.

Both approaches had the same fundamental problem: they were too slow for the pace of reselling. One person we interviewed put it perfectly.

"I'm at an estate sale. I found a [designer] bag for $300. I need to know RIGHT NOW if it's real, because three other people are looking at it. If I have to wait 24 hours, I've already lost the opportunity."

Through our initial research, we identified three core user types:

Each group had different needs, but they all shared one thing: they needed speed, confidence, and context.

Before opening Figma, I wanted to understand what reselling actually looks like in real life: how people decide, how fast they move, and where things break. So the first two weeks were spent talking to users, watching their workflows, and validating what really matters to them.

We interviewed 12 resellers of different experience levels. The conversations were simple and honest. We asked them to walk us through how they pick items, how they verify authenticity, and what stresses them the most.

A few themes came up again and again:

These insights later shaped our design principles around speed, confidence, and community.

We also did 3 "ride-alongs" following resellers during thrift trips and at-home sorting sessions.

This is where everything clicked:

This told us exactly where the new experience needed to fit.

To make sure our interviews weren't outliers, we ran a short survey in online reselling groups (82 responses).

Understanding the landscape before defining our opportunity.

I looked at eight platforms: five direct authentication tools and three adjacent resale marketplaces. Less about comparing feature lists, more about what users had come to expect, where nobody was serving them, and where the app could be genuinely different.

Before jumping into wireframes, I mapped out the entire information architecture. With a small team and a tight timeline, I had to be strategic about where resources were allocated.

The guidelines that shaped every decision.

After our research, it became clear that users weren't just looking for an authentication tool, they were trying to make fast, informed, confident business decisions. To keep us aligned, I defined three design principles that served as our compass throughout the project.

Each principle acted as a guardrail whenever we had to make tradeoffs, ensuring the final product supported how resellers actually work.

The three-step onboarding flow introduces features progressively, starting with authentication basics and revealing market intelligence capabilities as users gain confidence with the core functionality.

Critical market data appears immediately upon scanning, with profit margins and market values prominently displayed before authentication details. This hierarchy ensures users understand the financial opportunity first.

The authentication process shows real-time progress with detailed confidence scores and verification steps. Community validation and transparent scoring build trust in the results.

The wireframes set structure before style: navigation, dashboard metrics and onboarding steps, so we could test whether the flow held up before anyone argued about colour. It let the team validate usability and tighten interactions early, while changes were still cheap.

Home is a quick read on how the business is doing: total profit, how many items you have authenticated, and how accurate you have been. Streaks, rank and tier sit alongside that, because the resellers we spoke to are competitive people and it turns out that helps. Underneath, Quick Scan, Bulk Mode and the Profit Calculator are one tap away, and the Live Feed and Trending Now show what is actually moving right now.

After launch, more people finished onboarding, got to their first scan faster, and hit fewer errors. The new features made it easier to make decisions on real data rather than instinct, and community participation and weekly activity both grew steadily. Onboarding completion rose 85%, time to first action fell 40%, error rate in bulk authentications dropped 15%, and weekly active users climbed 70%. Free-to-paid conversion lifted 28%.