Vela Surf Forecast App
As a surfer myself, I often witnessed beginners struggling to decipher complex weather forecasts to find the perfect surf spot. This inspired me to create Vela, a surf forecasting app that offers personalized recommendations based on individual abilities and preferences.
Exploring the Problem Space
Existing surf forecasting platforms like Magicseaweed and Surf-Forecast overwhelm users with raw, non-personalized data.
While experienced surfers may navigate these tools with ease, beginners and occasional surfers struggle to interpret the information and make informed decisions.
After five rounds of user interviews I defined four core problems to solve
Simplicity and Clarity
67% of users expressed difficulty in finding clean conditions and understanding forecasts, indicating a need for clearer, more straightforward information presentation.
Personalization and Context
100% of users highlighted the lack of personalized forecasts, especially for longboarders, and the need for detailed spot descriptions, including tide and swell size.
Efficiency
100% of users check forecasts multiple times a day, indicating a demand for quick, efficient decision-making tools.
User-Friendly Design
67% of users struggled with navigation, particularly with finding the filter feature, underscoring the need for a more accessible interface.
Problem Statement
"How might we provide surfers with clear, personalized, and actionable recommendations so they can confidently choose the best surf spot for their needs?"
Solution
Vela is a surf forecasting app designed to simplify the decision-making process for surfers of all levels. By combining personalized filters, intuitive navigation, and accessible design, Vela empowers users to find the perfect surf spot quickly and easily.
Defining Needs and Pain Points
Based on my research data, I created an affinity map that I turned into a User Persona to guide all following design decisions.
Structuring the Solution
I began with low-fidelity sketches to explore layout ideas and user flows. These sketches evolved into mid-fidelity wireframes, which I used to create a clickable prototype for testing.
Sitemap Overview
A card sorting exercise with six participants helped me design intuitive navigation, ensuring users could easily find features like the spot filter.
Validating my Designs
Usability testing with six participants revealed key pain points:
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Home Screen
33% of test participants tried using the search bar to find spots rather than the spot map, missing the opportunity to use the filter, one of the core features.
I changed the spot map to be the new home screen to avoid this issue.
Severity: Medium
Filter Items
12% of participants voiced confusion when seeing the filter items displayed in two columns. I revised the design to clearly structure the filter settings.
Severity: Low
Spot Filter
66.7% of participants had trouble finding the spot filter so I moved it to a more obvious location on the screen.
Severity: High
Login Screen
33% of participantstried logging in with social sign up options. By visually separating the two options, I could exclude this error completely.
Severity: Low
Final Product
Key Features
Personalized Recommendations
Users can set filters based on their skill level, board preference, and wave type to receive tailored spot suggestions.
Map-Based Navigation
The home screen features an interactive map, allowing users to explore nearby surf spots and view real-time conditions.
Simplified Forecasts
A side-by-side comparison of current and ideal conditions helps users quickly see whether a spot is suitable.
Accessibility
Vela adheres to WCAG standards, with high-contrast text, clear labels, and error prevention mechanisms.
Outcomes
75% task completion rate
Users successfully completed key tasks, such as setting filters and finding surf spots.
Positive feedback
Test participants praised the simplicity of the map-based home screen and the clarity of the forecast display.
Reflection
Designing Vela was an amazing experience that taught me the importance of usability testing and iteration... And to believe in the process. By listening to users and addressing their pain points, I was able to create a solution that is both functional and inclusive.
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