Choosing a place to live can be a challenging task because there are many factors to consider, such as cost of living, property size, amenities, transportation, safety, and more. Additionally, searching through real estate sites, neighborhood guides, and online forums can be time-consuming and often result in incomplete information.
Problem Statement: While there are platforms for real estate buyers and sellers, most of them focus on buyers with defined preferences and sellers who have experience listing their properties. These platforms often fall short in providing potential movers with comprehensive city data and making the listing process easier for sellers.
Solution: Polis is a platform designed to simplify the process of finding the ideal place to live. By asking users questions about their preferences and needs, it allows them to explore more than just property details and makes the experience more personalized.
Methodology: We applied the Lean UX methodology for this project, adjusting it to our class setting. This approach emphasizes rapid development, cross-functional teamwork, and a strong focus on user needs. Although only designers worked on the project, we followed Lean UX principles to guide our work.
This approach helped us gain a clear understanding of our users and their needs, align the user and business outcomes, and make decisions based on the validation of our assumptions. By continuously testing and improving our ideas, we ensured that the product added value to the user and business.
Over two sprints, each lasting three weeks, we translated our findings into a high-level interactive prototype that displayed the essential features and user flows of the platform.
We worked in two sprints, each beginning with a Design Week Zero, where we used the Lean UX Canvas to define our assumptions and create a Sprint Backlog. During Sprint Week 1, our focus was on building and testing MVPs through user research and usability testing. In Sprint Week 2, we refined our approach based on the information gathered in the first weeks. Finally, we had a week more to refine our prototype.
In this sprint, we began by creating the first Lean UX canvas in FigJam to declare our assumptions and create solutions that addressed the user and business outcomes. From these solutions, we developed hypotheses that we prioritized by how risky they were and used them as the foundation for our Minimum Viable Products (MVPs).
The Lean UX Canvas helped us define the business problem statement, solutions, outcomes, and testing methods. It allows teams to declare and test assumptions, while promoting a shared understanding throughout the project.
We began with the assumption that our product would help users find their ideal place to live by providing city data. Unlike existing products, we aimed to let users set preferences before exploring city details.
We created a primary proto-persona, Rose, whose goals shaped our solutions:
This process led to a hypothesis table based on insights from affinity mapping sessions of solutions. These hypotheses focused on business outcomes achievable through specific features that help user outcomes. We defined the MVPs we would build, to help us learn the most in the least time. As the team leader and main UX researcher, I oversaw the Lean UX canvas and developed the method for testing hypotheses, using spreadsheets with categorical variables to track and analyze user interview data.
During Week 1, we sketched initial drafts for the MVPs and gathered references for inspiration. As the team leader, I coordinated 2-day 15-minute stand-up meetings to identify the next tasks. At the end of the sprint, we held a 30-minute retrospective to evaluate the process and discuss improvements.
Before transitioning from FigJam to Figma, I created a style guide, including a color palette with primary, secondary, neutral, and semantic color variants and text styles using the Poppins typeface. I also built key components to maintain a cohesive design across all screens.
The first sprint backlog focused on developing filters, complete city data that prioritizes user preferences, an interactive map, and the ability to compare cities. After delegating tasks to start creating the MVPs, we conducted 3 user interviews. I created a structured interview guide, starting with broader questions about the participants’ experience with moving, finding a place to live and experience with existing tools, and moving to usability testing with questions about the MVPs. We tracked the aspects the participants liked about the features and areas for improvement using spreadsheets.
After the interviews, I led affinity mapping sessions to identify patterns from the interviews, helping us refine our understanding of user needs and improve MVPs. Some of the key insights included the types of filters users needed and their preference to limit options early in their search.
In Week 2, we discovered that our initial assumption about focusing on city data was incorrect. Users already had cities in mind and were more focused on finding properties. While they still wanted city data, property details were more important. This led us to shift focus to property search features alongside city data.
I continued leading 2-day stand-ups, and we conducted 3 more interviews. We tested higher-fidelity MVPs with participants, keeping a few features that still aligned with user needs while adapting to new insights.
At the end of the sprint, we had the retrospective meeting to discuss what went well, what could be improved, and next steps. We found that interviews were conducted quickly, prototyping started early, and components and the style guide were created ahead of schedule. We also managed schedules effectively and made quick decisions to keep the project on track. Some areas for improvement were being more realistic with deadlines, preparing more for testing, and ensuring more interactive prototypes were ready.
During Sprint 2, we revalidated our assumptions by going back to the Lean UX canvas and adjusting it to reflect the shift toward creating a real estate product. This led to adding a new set of features that were customized for real estate agents in addition to the original buyer persona. We updated our proto-personas to include both a buyer, Rose, and a real estate agent, Dexter, addressing the goals of both user types. We continued testing our assumptions with 6 user interviews and usability tests, refining our product to meet both personas’ needs.
In Week Zero, we made significant changes to our Lean UX canvas, shifting our focus to the real estate domain. We crafted a new business problem statement that incorporated both buyers and sellers, expanding the product’s scope. We introduced Dexter, a real estate agent, alongside Rose. Dexter’s goals included providing easy access to property information, managing buyer inquiries, and accessing market data. These changes led to updated user outcomes and new solutions. In our hypothesis table, we added both new and previous hypotheses, marking completed ones and highlighting discarded ones in red.
As the team leader, I set the specifications of MVPs and determined we would continue using spreadsheets to track their effectiveness.
In this sprint, we worked on a variety of features, including property listings, tour scheduling, the commute calculator, seller onboarding, notifications, a trending properties section, and more. I collaborated with my team to delegate tasks based on their skills. Since we had already developed some components from the previous sprint, the MVPs were higher fidelity.
We conducted three final user interviews, including one with a real estate agent, and I also updated the interview guides to reflect the MVPs we were testing. Considering our second persona, I created a separate guide for the real estate agent, focusing on their process when listing houses, tools used, and their experiences with them. The interviews helped refine the city data page and helped us learn that finding clients was an essential feature for agents.
We continued with the two-day standups and held affinity mapping sessions after each round of interviews to identify patterns and iterate on our designs.
In the final week, we conducted 3 usability tests. I created the tasks, asked participants to guide us through their thinking process, and prepared follow-up questions. One key finding was that real estate agents wanted more features in their dashboard, while buyers wanted the option to skip certain questions and view unfiltered listings. We also identified navigation issues that needed improvement.
After the usability tests, we spent a week finalizing the prototype in Figma, ensuring all interactions worked and the design system was applied consistently. As team lead, I focused on maintaining file hygiene and organization while overseeing all the frames. We completed 18 features across both sprints, leaving out 4 based on the validation process.
In our final retrospective, we reflected on what went well, such as meeting deadlines and building and testing MVPs, and what could have gone better, including helping participants understand Figma, especially during usability tests, and starting to work on some features earlier.
Polis was my first project using the Lean UX methodology, and it taught me a lot about the challenges and time constraints we face as designers when trying to deliver value quickly. If we had more time, I would have liked to conduct additional secondary research and competitive audits while we were working on the sprints to identify possible gaps we could address or opportunities for improvement. I also would have liked to interview more real estate agents to refine the seller flow. Some of the most important lessons I learned from the project were: