Bilheteria Digital: a ticketing platform that goes beyond checkout · drevasconcellos

In short

• Company: Bilheteria Digital (BD), a ticketing platform
• When: January to September 2026
• My role: Mid-level Product Designer, from research to final screens, plus the coded prototype, built with Claude Code
• Team: a B2C PM, the Head of Product and the Product Director; in the first three months, another designer worked with me on research
• Result: I built the prototype in less than 1 month, and it became the MVP that went to production.

Context

BD wanted to rebuild its consumer ticketing platform. Buying a ticket had a lot of friction and relied on an inefficient operation that was hard to scale.

The bet was for the platform to stop being just the place where you pay for a ticket and become a place to discover events, connecting fans, artists and promoters.

My role

I was a Mid-level Product Designer at BD. In the first three months, another designer worked with me on the research and the benchmark. After that, I did the persona, wireframes, final screens and coded prototype on my own. Day to day, I worked with the B2C PM, the Head of Product and the Product Director.

Process

1. Research: where people discover events

The research had two fronts: desk research, from January to March, and workshops with employees and stakeholders from marketing, operations and sales.

• a benchmark of 14 ticketing platforms, in Brazil and abroad, comparing audience, business model, interface, pros and cons;
• a CSD matrix, to separate certainties, assumptions and doubts;
• before starting, criteria to know when the research was enough: we could move on once the hypotheses were specific, testable and tied to interface decisions.

The numbers showed that discovery happens outside ticketing platforms:

• 89.9% of people hear about events from stimuli outside the platform;
• only 10.2% actively search for events, usually when they want to go out but don’t know where;
• friends are the main source of recommendations (36.1%), and WhatsApp is the main channel for inviting them;
• 20% of fans want to be notified about presales from artists they like.

In other words: people arrive with the event already chosen and only use the platform to pay. And that checkout-only model is losing profitability.

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2. Definition: hypotheses, persona and MVP

I turned the findings into 12 hypotheses in an “if… then… because…” format. One of them: if event discovery happens inside the platform, purchase intent goes up, because today people discover elsewhere and only come in to pay.

The persona is Beatriz, 29, who buys on her phone and decides on the spot, after seeing the event on social media or hearing about it from a friend. She wants to buy fast without a complicated sign-up, be sure the ticket is official, and see the total price before paying, with no surprise fees.

That defined the MVP: sell tickets from event discovery to the ticket on the phone, designed mobile first and for high traffic. The information architecture and user stories covered authentication, discovery, event page, checkout, my tickets (with transfers and cancellations) and my account.

3. Wireframes and final screens

I designed the wireframes in Figma with shadcn/ui, a component library that is easy to customize and scale, and works well with generative AI. Then I applied BD’s visual identity and designed the screens in light and dark mode.

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Some decisions came straight from the research: the home page opens with discovery (“what to do today”, categories, popular searches); the event page has like, share and how many people are interested; and checkout shows every fee in the summary, before payment.

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4. Coded prototype, with AI

Once the wireframes were validated, I brought the Figma screens into Claude Code and built the working prototype on my own, in less than 1 month. That let the product and tech team use the real platform before it existed, which was key to validating the product and improving the experience.

At handoff, two developers reviewed and cleaned up the code, which went to production.

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Results

The prototype became the MVP and went to production. Shortly after, the company went through strategic issues and shelved the project to focus on other priorities.

User testing was planned for September, but it didn’t happen: the Product team was dissolved that month. The next steps were mapped out, such as an artist page and dashboard, gamification, streaming integration and adding tickets to the phone wallet.

What I learned

Prototyping in code with AI shortened the path from Figma to production: instead of describing the experience, the team got to use it.