Reducing the cognitive cost of contribution

Course Vaults is a web and mobile product for golfers to track and rate the courses they’ve played, a shared, player-driven rating system of courses around the world.

Instead of panels, critics, or curated rankings, it’s powered by everyday golfers. Each rating adds to a collective view of the course. Letterboxd for golf, designed and shipped end to end.

At the time of this work, the product had a few thousand users and over 75,000 courses added to player profiles, yet 28% of users never rated a single course. The issue wasn’t interest. It was effort.

Rating a course required too many decisions. Users were asked to:

• Recall granular details
• Complete a long intake form
• Understand the system before receiving value

I made a deliberate tradeoff: optimize for contribution speed, not data completeness.

If contribution felt easy and rewarding, the data graph could improve faster and ratings would naturally become more accurate over time. If it felt like work, the system would stall, and the data would take longer to reach its potential.

I reduced the rating flow to a one-page experience:

• Preserved the 1-10 score
• Removed supporting inputs to create a one-page experience
• Changed from full screen to modal view
• Included a slider so users could rate courses quicker

Inspired by Letterboxd, new users were immediately asked to rate familiar, nearby courses, eliminating search and decision paralysis.

• Cut empty profiles by more than two-thirds. New users with zero course ratings decreased from 28% to 8%, a 71% reduction.
• Users were able to build meaningful course diaries more quickly, confirming that reducing friction and showcasing the rating system early improved contribution.

• Reducing the cognitive cost of contribution solved the activation problem, but exposed a new constraint: onboarding became engaging enough to delay deeper product exploration.
• If contribution feels like work, the product is already broken, but onboarding must remain a bridge, not the destination.
• The overall course rating already captured most of the signal reflected in subcategory inputs; requiring that data upfront added friction without materially improving accuracy or the broader data graph.

Evaluate whether early rating contributions meaningfully increase deeper product exploration and long-term engagement.