Climb Connect
Climb Smarter. Connect Stronger
Client
Type
Role
Solo
Year
What is Climb Connect?
Climb Connect is a mobile app designed to help climbers track performance, discover routes, and connect with climbing partners. The platform serves both weekend enthusiasts looking to improve their skills and experienced climbers seeking advanced analytics and community engagement.
What kind of problem are we tackling here?
Climb Connect's valuable features were buried and hard to find, leaving users frustrated and unable to discover tools that could improve their climbing experience and connect them with the community. This led to low engagement, poor retention, and users abandoning the app for simpler alternatives.
Target Users
Primary: Weekend climbing enthusiasts who want to improve their skills and find climbing partners but lack confidence navigating complex features.
Secondary: Advanced climbers who need sophisticated tracking tools and want to mentor others in the climbing community.
Research Insights
Through user interviews and app analytics, I discovered:
85% of users only used basic logging features despite wanting advanced capabilities
Users preferred detailed climbing data but couldn't find route discovery tools
Social isolation was a major pain point - users wanted partners but didn't know how to connect
Expert users wanted to share knowledge but had no clear pathway to do so
Solution Overview
I redesigned the app's information architecture around user goals rather than feature categories, implementing three key solutions:
1. AI Performance Tracking
Automatic climb analysis using smartphone sensors with personalized improvement recommendations.
2. Smart Partner Matching
Algorithm-based system matching climbers by skill level, location, and climbing preferences.
3. AR Route Discovery
Augmented reality overlays showing climbing routes and technique guidance through the phone camera.
Key Design Decisions
Progressive Disclosure: Revealed advanced features gradually based on user skill level to prevent overwhelming beginners while satisfying expert needs.
Community-Driven Content: Enabled expert users to contribute route information and technique tips, creating a knowledge-sharing ecosystem.
Contextual Guidance: Added in-app tutorials and hints triggered by user behavior rather than front-loading onboarding.
Results
60% improvement in feature discovery during user testing
Increased engagement with previously hidden social features
Positive user feedback on simplified navigation and community connection tools
Successfully bridged the gap between novice and expert user needs
Key Learnings
What worked: Progressive disclosure effectively served both user types without compromising functionality.
What I'd improve: Earlier prototype testing would have identified navigation issues sooner in the design process.
