Company Context

FitTrack is a subscription-based mobile fitness app with 12M monthly active users and a freemium model. It has strong brand awareness in guided workouts, but growth has slowed: new user acquisition remains healthy while paid conversion and 8-week retention have plateaued.

Problem

The CEO has asked the product team to identify the single best near-term growth opportunity for the next two quarters. Existing product analytics show three possible areas: (1) a large drop-off after onboarding, where only 42% of new users complete their first workout in week 1; (2) weak conversion from free to paid, with only 3.8% of active free users starting a trial each month; and (3) poor retention among casual users, where 8-week retention is 24% versus 51% for users who set a goal in their first session.

The team has some data, but it is incomplete. Quantitative dashboards explain where users drop, but not why. Prior user interviews suggest users join FitTrack for different jobs: building a routine, losing weight, training for a specific event, or finding short workouts that fit a busy schedule. Leadership wants a recommendation grounded in both user research and product data, not intuition.

Deliverables

1. Explain how you would combine user research and product data to identify the best growth opportunity.
2. Define the user segments or jobs-to-be-done you would investigate first and why.
3. Prioritize the top growth opportunity and propose 1-2 product bets to pursue.
4. Define how you would validate the opportunity before committing major engineering resources.
5. Specify success metrics and decision criteria for moving from discovery to execution.

Constraints

• You have 6 weeks for discovery and recommendation.
• Only one cross-functional squad can work on the chosen opportunity in the next half.
• Research budget supports at most 25 user interviews and one survey wave.
• Analytics instrumentation is reliable for funnel events, but weak for qualitative intent signals and cross-device behavior.