Diagnose Marketing Funnel Performance

Business Context

FitPulse is a subscription fitness app that spends heavily on paid acquisition across Meta, Google, influencer partnerships, and email reactivation. In the last month, marketing spend increased from $800K to $1.0M, installs grew from 120K to 150K, but paid subscription revenue only increased from $540K to $555K.

Metric Scenario

The CMO wants a structured analysis to determine whether marketing is attracting low-quality traffic, whether onboarding is underperforming, or whether retention is weakening. Current topline metrics are: click-through rate fell from 2.8% to 2.4%, install-to-signup conversion fell from 62% to 55%, signup-to-trial start improved from 40% to 44%, trial-to-paid conversion fell from 32% to 25%, and 30-day retention for newly acquired users dropped from 28% to 22%. CAC increased from $44 to $61, while estimated 90-day LTV declined from $96 to $78.

Requirements

1. Define the primary KPIs you would use to evaluate marketing effectiveness across acquisition, conversion, engagement, and retention.
2. Decompose the decline in marketing efficiency to identify the largest driver(s) of weaker revenue output.
3. Explain how you would distinguish a channel-mix issue from a product onboarding or retention issue.
4. Recommend 3-4 actions the marketing and product teams should take based on the data.
5. Identify guardrail metrics to ensure short-term conversion gains do not hurt long-term user quality.

Data Available

• ad_campaign_performance: date, channel, campaign_id, impressions, clicks, spend, installs
• app_signup_funnel: user_id, install_date, signup_date, trial_start_date, paid_date, acquisition_channel
• user_activity_daily: user_id, activity_date, workouts_completed, session_count, minutes_active
• subscription_events: user_id, plan_type, renewal_date, cancellation_date, revenue_amount
• user_profile: user_id, country, device_type, signup_cohort, acquisition_channel