At a glance
Team: Solo Project Time: 15 Weeks (Spring-Summer 2024) My Role: Service Designer
Tools Used: Figma, Google Suite, ChatGPT, Autodesk Sketchbook
Key Methods: survey, diary study, SWOT analysis, Blue Ocean strategy, Wizard-of-Oz testing, ‘The Grid’ (strategic business model framework)
The Challenge: About 85% of NFL fans live outside their team’s market, and their engagement drops off significantly in the off-season.
What I did: Ran an 88-person survey and 10-day diary study to design, prototype, and price a year-round fan community service backed by a tested business model.
The Result: In testing, participants trusted the Fan Level placement, 5 of 6 said they would pay for the service (3 at $5/month or more), and indicated they would use it daily.
For a closer look at the project and methodologies:
Project Summary
Holding season tickets gave me front-row access to my team's operational cadence and its blind spots. While local engagement is tied tightly to the team calendar, millions of remote fans remain completely disconnected from the community year-round.
Why it matters: Out-of-market fans struggle to access games and feel disconnected from their community. This leads to a massive drop in engagement during the off-season, resulting in lost revenue opportunities for the league.
The Concept: FanTowns is a dedicated social networking and educational platform designed to solve the engagement crisis facing the 85% of NFL fans who live "out-of-market." As a gamified service ecosystem that bridges the gap between casual viewing and die-hard fandom, FanTowns combines hyper-local community building with a "Learning Center" to increase Football IQ. By incentivizing daily interaction through Fan Points, Rankings, and Trivia, the platform keeps fans active year-round, converting off-season lull into deep brand loyalty.
Working solo: As the only designer, I owned every stage of the project, from research and concept development to the business model canvas and the final pitch. In practice, that meant:
Finding the opportunity: I connected off-season engagement to fan spending using industry data.
Designing the service: I developed FanTowns as a niche platform for the 85% of fans who live out-of-market.
Building the business model: I projected $76.5M/year based on a 15% market capture and a tested subscription price (in testing, 5 of 6 participants said they would pay a monthly subscription fee for the service: 1 at $10, 2 at $5, and 2 at $3-$5).
Designing for daily use: I created the "Fan Levels" system to bring fans back every day, driving daily retention and long-term user loyalty.
Research & Discovery
To understand the problem space, I utilized a mixed-methods approach combining quantitative and qualitative data.
Quantitative Survey: I surveyed 88 NFL fans about their off-season habits and appetite for more content, then recruited six respondents for a diary study.
Key Insight: While all fans desire more engagement, out-of-market fans expressed a significantly higher urgency for connection than hometown fans.
Longitudinal Diary Study: To move beyond what fans wanted to how they felt, I conducted a 10-day diary study with six participants from the initial survey. Tracking their responses to the same set of daily questions revealed the consistent lack of meaningful touchpoints during the off-season.
Ecosystem Mapping: I conducted secondary research to map the current Service Ecosystem and Value Exchanges, identifying where the current NFL model fails to capture value from displaced fans.
Analysis & Strategy
Following the research phase, I utilized affinity mapping to synthesize the raw data. Distilling the findings, I was able to extract 3 key insights:
1. Fans, especially those living out-of-market, are unhappy with the quantity and quality of off-season content and engagement opportunities with their teams.
2. Fans are seeking a closer connection and better understanding of the game, the business, and the people within football to enhance their viewing experience.
3. Being able to connect with a community of like-minded fans and watch your team play is important, but often-times difficult, especially for fans who live out-of-market.
During this analysis, I identified a critical viability constraint: directly acquiring premium NFL content (player interviews, behind-the-scenes footage) would be cost-prohibitive for a startup service.
To carve out a unique space in a crowded marketplace, I utilized a Blue Ocean Strategy analysis. This framework helped me identify an uncontested market segment where I could increase engagement without competing directly with major broadcasters for costly content rights.
Guided by this analysis, I established four strategic pillars to ensure the solution addressed unmet user needs while remaining business-viable:
Strengthen Fandom: Facilitate the journey from casual viewer to die-hard fan, deepening emotional investment and advocacy.
Increase Football IQ: Lower the barrier to entry for a complex sport. By increasing user understanding of strategy and nuance, we increase their appreciation and long-term retention.
Grow the Fan Base: Create a frictionless "onboarding" experience for new fans, helping them acclimate to the sport and join existing communities.
Support Local Communities: Provide the digital infrastructure and tools necessary for local fan groups to organize, grow, and thrive.
Ideation & Synthesis
To maximize creative output, I leveraged a hybrid brainstorming approach. I combined human-centered ideation sessions with Generative AI (ChatGPT) to stress-test my "How Might We" questions. This process produced over 200 concepts ranging from practical UI fixes to "blue sky" service innovations.
I then distilled this volume down to 20 core value propositions and tested their validity using SWOT analyses and mapping them to ‘The Grid’ to ensure they met both business goals and user needs.
To select the features for the initial launch, I plotted these concepts on an Impact vs. Effort Matrix. This framework allowed me to balance technical feasibility against user value, separating critical MVP features from "nice-to-have" additions for the future roadmap.
The Solution
FanTowns is a new social networking platform dedicated to and designed specifically for NFL fans.
With FanTowns, fans can find and stay connected with local fan communities, more easily navigate those communities with a proprietary Fan Level system, and access a library of information to help them learn more about the sport they love during a time of year where little to no meaningful content is produced about their team, all on a platform that encourages continual, year-round interaction.
With an initial placement exam to test incoming fans’ football knowledge, Fan Levels sort fans into rookie, veteran, all-pro, and H.o.F. levels based on how well they know the NFL.
These Fan Levels will be integrated throughout the platform, helping distinguish FanTowns from its competitors by allowing fans to navigate communities more easily. Fans can use this system to find other fans on their level or find fans on a different level to learn more about football or help bring a new fan into the fold.
Fans are encouraged to engage with the platform through a set of daily questions designed to help fans learn more about the game of football and the history of the NFL and that offer opportunities for fans to earn Fan Points and progress along the path towards becoming a Hall of Fame level fan.
These Fan Points also fuel the Fan Rankings, allowing fans to see where they stack up individually among other fans - filterable by team, group, and location - as well as where the Fan Groups they have joined stack up against other team’s Fan Groups in their area, and eventually other fan groups of their team around the country or the world!
Finally, for new fans or fans who just want to learn the basics or more seasoned fans who want to brush up on their football knowledge, the Learning Center provides a great resource for information about the rules and strategy of NFL football.
Testing
I utilized the Testing Table and Test Cards from Strategyzer to set up and organize the prototype testing and results. This brought focus to the testing methods and helped me establish which metrics I would use to determine whether this service concept might be a success.
I ran 6 participants through a Wizard-of-Oz style placement exam to give them an initial Fan Level placement before moving the users through the rest of the prototype and collecting their feedback.
Testing results indicated a high level of trust in the initial placement exam to sort fans appropriately. 5 of 6 participants said they would pay for the service (3 at $5/month or more), and they expected to use it at least once a day.
Next Steps
Based on feedback from concept testing, a larger emphasis is needed on player, team, and league history. Including player, team, and league history in the initial placement exam, daily questions, and the learning center will allow a broader array of fandoms to be taken into account throughout the service. As the service is developed, the focus should start with the initial offering, which should include the Fan Levels system, daily trivia questions, fan and fan community rankings, the Learning Center, user profiles, fan community pages, event pages and planning, and discussion threads.
This initial offering would be launched in major cities with NFL teams to establish a strong user base. As the user base grows, the service can develop more features like learning modules, an AI “assistant coach”, and fan challenges. We can also establish partnerships with industry professionals and local venues to host fan events and challenges. Down the road, as the service gains market leverage, we can look to partner with the NFL and NFL teams, establish virtual meet and greets with fans, players and personnel, and fan “bar takeovers” for fan community watch parties.
Reflection
Running this project alone meant owning every decision, from who to survey to what to cut from the MVP. Without a team to test my thinking against, I learned to let the research do that job and come back to the data whenever I felt too sure of an idea.
The diary study taught me the most. What fans said they wanted on day one was often different from what they kept coming back to by day ten. A survey captures what people think they want; watching behavior over time shows what actually holds their attention. It changed how I plan research, and I now pair a quick survey with a longer look at behavior whenever I can.
Using ChatGPT in ideation taught me where AI helps and where it doesn’t. It was great for volume, pushing me past my first ideas to more than 200 concepts. But deciding which 20 were worth pursuing, and which MVP was viable, still took judgment grounded in the research.
The constraints made the concept better. Because premium NFL content was out of reach for a startup, I had to look elsewhere for value, and found it in community and learning, which fans valued more than I expected.
If I took FanTowns further, I’d test with a larger, more varied group of fans. Six testers gave me a promising signal, not proof, and I’d want to know whether willingness to pay holds up across different kinds of fans.