Referral and Subcription for fAIshion

fAIshion.AI’s revamped referral and subscription programs give users monthly credits for try-ons and size recommendations, while Plus subscribers unlock premium features and expanded access. By rewarding users who invite friends with stackable bonuses and discounts, we saw referral activity rise by 30% and subscription opt-ins significantly increase. These changes, along with clearer CTAs and seamless upgrade flows, improved platform retention and satisfaction, making it easier for both free and premium users to experience the full value of fAIshion.AI.

| Team

Myself

2 Designers

3 Engineers

Data Analysts

| My Role

Product Manager

| Timeline

Jun - Nov 2025

Background and Challenges

fAIshion.AI needed to increase user retention and monetize its growing base. The original app had no incentives to invite friends or upgrade, resulting in slow growth and a lack of recurring revenue.

Role and Team

As Product Manager, I led strategy and execution for the referral and subscription features, working with both engineering and design teams.

Research and Discovery

Key Features/Improvements

I reviewed cohort retention data and surveyed users to understand what would motivate referrals and upgrades. I benchmarked successful programs in similar apps to validate core mechanics.

Process and solutions

We mapped out referral flows for inviting friends and tested different incentive structures. For subscriptions, I defined tiers and perks, working closely with the team to design seamless upgrade and management journeys. Rapid prototyping allowed us to quickly iterate based on early feedback.

Easy-to-use referral system with instant rewards for both referrer and invitee

Subscription tiers offering enhanced AI recommendations, exclusive styles, and faster try-on credits

Clear in-app messaging and upgrade CTAs integrated into every major touchpoint

Reflection & Learnings

This project taught me the importance of aligning incentives with user values and making upgrade flows frictionless. Data-driven iteration and quick prototyping were key to launching features that users actually wanted. Next, I plan to add social leaderboard mechanics and experiment with limited-time offers to further boost engagement.