Franki
Social Conversion Loop
Overview
Franki is a social discovery platform connecting users with local experiences and rewarding them for participation and sharing.
Led end-to-end product strategy and interaction design to increase first purchase conversion through community-driven discovery and booking.
Process
The Problem
User research revealed a critical activation gap: many users completed onboarding but failed to make their first purchase.
This signaled a breakdown between:
Discovery
Trust
Value perception
Ease of booking
The business goal was clear: increase first purchase rate without increasing reward costs .
Framing the Opportunity
I began by mapping potential friction points:
Misalignment between onboarding interests and surfaced content
Lack of clarity around rewards and credits
Perceived difficulty of booking
Limited social proof in the decision moment
Early problem framing and hypothesis mapping
Strategic Direction
Instead of simply optimizing the booking flow, I reframed the problem:
Activation depends on social confidence, not just financial incentive.
Credits motivate while community converts.
I defined three core pillars:
Community discovery before purchase
Contextual social proof at booking
Post-purchase reinforcement to strengthen the loop
End-to-End Flow Design
I designed a complete purchase flow integrating community at multiple moments:
Discovery feed driven by onboarding signals
Search + map exploration
Experience detail view with social signals
Reward clarity before payment
Post-booking engagement loop
End-to-end user flow integrating community touchpoints
Mid-Fidelity Exploration
I prioritized speed and iteration to validate structure before investing in polish.
The wireframes explored:
Community feed variations
Search vs browse behaviors
Map-based discovery
Reward messaging hierarchy
Social proof placement
Post-booking prompts
Key Decisions
1. Community Before Incentive
The feed prioritizes real user experiences over transactional prompts.
This builds trust before asking for payment.
2. Reward Transparency at Decision Moment
Instead of hiding credits in microcopy, I elevated:
Credits earned
How they apply to future bookings
How sharing increases reward
This reframes the purchase as progress within a loop.
3. Friction Reduction in Booking
Clear breakdown:
Experience details
Payment transparency
Credits applied immediately
Confirmation feedback
Outcome
Product Outcome
The final design integrates community signals across the purchasing journey rather than isolating them in a feed.
The system creates a loop:
Discover → Book → Earn → Share → Influence → Discover …
This increases:
Social confidence
Perceived value
Engagement after purchase
Incentive alignment with business goals
Conversion Strategy Impact
The design addresses first purchase friction by:
Increasing relevance through onboarding-informed feed
Surfacing peer validation at booking
Reinforcing reward visibility
Reducing perceived booking complexity
Even modest improvements in first purchase rate would materially impact growth given the marketplace model.
What I Would Validate Next
Does visible peer attendance increase booking intent?
Do credit previews increase conversion?
Does map-based discovery outperform feed-first?
Does post-booking credit animation increase sharing behavior?
A/B testing and cohort tracking would focus on:
First purchase rate
Time to first purchase
Credit redemption rate
Share rate after experience
