Meu Corre (“My Gig”) is a social impact entrepreneurship project I co-founded with Igor Dalla Vecchia, an old friend who was a PhD candidate studying on the relationship of Brazilian courier workers with platforms. I was the responsible for everything concerning the product, from Discovery, Strategy and Research to UX/UI Design and major technical decisions.
We successfully got funded with more than R$ 200k (~€33k) by FAPERJ, CNPq, and Fundo Brasil, important Brazilian research institutions. We also had access to almost 2 years of workshops and mentorship in topics such as business and product management. This allowed us to successfully launch the app on Google Play in April/2024 and we have been iterating on it with user feedbacks and planning on next steps.
Working on Meu Corre was one of those projects that really stuck with me. It pushed me to step out of my bubble, partner with so many different people, listen without judgment, and rethink what really impactful “solutions” actually look like.
The project was born out of our desire to build a tool to help address the challenges faced by delivery workers in Brazil. The idea initially emerged before the pandemic but gained momentum during it when delivery workers played a vital role in helping people stay at home while they were out on the streets, often in precarious conditions.
Delivery platforms often attract workers with promises of flexibility and entrepreneurship. However, the reality is much harsher, involving operational costs, financial unpredictability, lack of work rights and time for personal organization, not to mention serious health risks.
The project followed a user-centered design methodology since the beginning. Igor had been collecting data from various social media sources, from community posts in Facebook to chat groups in WhatsApp. This helped him notice the first patterns and draft some hypothesis we would build upon.
Right after joining the project I planned and conducted in-depth interviews with delivery workers from across Brazil to deepen that understanding. Our sample included both bicycle and motorcycle riders, different states, ages and genders. We wanted to have a clear picture of how a typical day for them looks like, and we focused on the challenges they faced. We also tried to understand their networks, consumption of content related to delivery, and their financial organization. Finally, we invited them to zoom out and understand how they got there and what were their medium and long term goals.
From these interviews we found out that their main pain points were:
To build a strong foundation to the following phases we took the opportunity to look around at what kind of applications these workers were using to support their work: maps apps, financial organization apps, social networks, etc.
I also took a close look at how the platform apps looked like. Even if we’re clearly not in the business of creating competition, these apps is our users’ universe and it was important we understand this shared vocabulary, both visual (how do they look? what kind of interaction patterns are most common?) and textual (what terms they use? how’s the tone of voice?). Often the worker’s-side app was completely different from the consumer-side app.
With the vast amount of data we gathered up to this point, I helped the team summarize all our findings using the Opportunity Solution Tree diagram. From this, we selected a few ideas we though were most promising and I’ve guided through a Design Sprint to better polish the ideas and have something tangible to test with real users.
Normally Design Sprints are done in an intense week of work, but since this was a sideproject for all of us, we made a longer version of the sprint that would last a whole month: each week corresponding to one of the days of the Design Sprint 2.0 format popularized by https://ajsmart.com/.
The winner concept was the “Financial Strava”, a kind of app that would merge the popular sports-tracking app Strava with the specificities of their work as delivery workers. The user would add their earnings and expenses to the app, which would help them track their daily and weekly goals and calculate some personal performance metrics.
What was amazing about this idea was the potential to understand their work at scale, which could be fed back to the workers as dashboards and reports to maximize their earnings: which platforms paid better and what were the best times to work.
The last week of the sprint was dedicated to run users tests with an interactive prototype.
Throughout the course of more than 1 year the project was continuously refined as we talked with more users, closed partnerships, developed business model ideas and started development with a software house we hired.
The final screens and features can be seen below. These were designed for our Google Play page:
After a [way too] long development phase where we faced thousands of issues, technical challenges and scope cutting, this MVP was successfully launched to the general public with zero known bugs on April of 2024 with several live events we coordinated with partner institutions as well as influential workers on YouTube.
Since June/2024 I’ve stepped down from the team to focus on other projects, but I still provide counseling, discuss strategy and contribute on big decisions.
Here are the main areas the project has been evolving since the launch and plans to continue in the near future:
Here’s a summary of the amazing results we’ve already achieved since the launch in April 2024:
Also we’ve been collecting amazing testimonials of people who has been using the app and expressing how it impacted their lives:
It’s really hard to summarize here in a few paragraphs how much I’ve learned and grew in almost 4 years of such an intense and different project, but here’s an attempt:
Challenging assumptions about user needs: Delivery workers’ challenges extend beyond simplistic assumptions about financial instability. Many workers lacked intuitive tools to track their income and expenses, which highlighted the gap between the tech-driven gig economy narrative of “freedom and entrepreneurship” and the daily, often chaotic reality of delivery work.
Data as empowerment for advocacy: The project reinforced our belief that structured data collection can shift the narrative about gig work from anecdotal complaints to evidence-backed advocacy. By providing delivery workers with actionable insights (such as the true cost of their earnings and platform-specific performance), the project underscored the potential for data-driven conversations about fair compensation, worker protections, and better working conditions.
Behavioral barriers to financial management: Even when workers recognized the importance of tracking their finances, psychological barriers often prevent consistent habits. Insights from user research revealed the need for ultra-simple interfaces with powerful features that didn’t just rely on rational arguments but tapped into behavioral nudges, such as goal tracking and positive reinforcement. Still, this is a highly complex challenge that even the biggest Fintechs in Brazil haven’t solved yet.
Otherness over empathy: Involving delivery workers in the testing and design process wasn’t just a “best practice” but a necessity since these were people with social backgrounds drastically different from ours. However, this collaboration presented challenges — balancing worker participation with their demanding schedules required creative approaches and deep respect for their time. Moreover, it highlighted the power imbalances inherent in design discussions and how those needed to be actively mitigated.
Working on Meu Corre was one of those projects that really stuck with me. It pushed me to step out of my bubble, partner with so many different people, listen without judgment, and rethink what really impactful “solutions” actually look like. The complete story is full of thousands of twists and challenges I had to skip here - but that’s where the best learning happened. More than just building an app, it was about building something we truly believed in, being full responsible for all of it outcomes, connecting with like-minded (or not) people, understanding their hustle, and figuring out how Design can actually make a difference in their lives.
This case study leveraged generative AI technologies to summarize and extract key insights from four years of extensive project documentation. It also helped me suggesting improvements to the writing. All AI-generated content was thoroughly reviewed and manually edited before publishing.
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