Business Context

FitTrack, a consumer fitness app, is launching a new AI-powered workout planner in the US. Leadership has committed $1.5M in launch spend over the first quarter and wants a clear measurement framework to decide whether the launch is succeeding beyond download volume.

Metric Scenario

In the first 30 days, the launch generated 120,000 landing-page visitors, 36,000 app installs, 24,000 account sign-ups, 15,000 users who completed onboarding, 9,000 users who created their first workout plan, and 5,400 users who completed at least one workout. By Day 7, 2,700 of those users were still active, and by Day 30, 1,350 remained active. Of the activated users, 1,800 started a free trial and 540 converted to paid at $19.99/month. The GM asks: which metrics should be treated as primary launch KPIs, how should they be defined, and how would you diagnose weak points in the funnel?

Requirements

1. Define the north star metric and 5-7 supporting launch KPIs for this product.
2. Separate metrics into acquisition, activation, engagement, retention, and monetization.
3. Identify the most important leading indicators in the first 30 days versus lagging indicators.
4. Decompose the launch funnel to show where the largest drop-offs occur.
5. Recommend what metrics should be segmented and monitored weekly after launch.

Data Available

• landing_page_events: visitor_id, campaign_id, source, device_type, timestamp
• app_installs: user_id, install_timestamp, platform, campaign_id
• signup_onboarding_events: user_id, signup_timestamp, onboarding_step, completed_flag
• workout_plan_events: user_id, plan_created_timestamp, workout_type, recommendation_source
• workout_sessions: user_id, workout_start, workout_end, completion_flag
• subscription_events: user_id, trial_start_date, conversion_date, plan_type, monthly_price
• user_profiles: user_id, country, age_bucket, acquisition_channel