Evaluate Paid Campaign Effectiveness

Business Context

FitMeal, a subscription meal-planning app, ran a 4-week paid marketing campaign across Meta, Google Search, and influencer partnerships to drive new paid subscribers. Marketing spend increased from $120,000 in the prior month to $210,000 during the campaign, and leadership wants to know whether the campaign was actually effective or just generated more low-quality traffic.

Metric Scenario

During the campaign month, impressions were 18.4M, clicks were 412,000, landing page visits were 356,000, account sign-ups were 42,700, free trials started were 12,900, and paid subscriptions within 14 days were 4,180. The prior month had 11.2M impressions, 255,000 clicks, 221,000 landing page visits, 31,500 sign-ups, 11,400 free trials, and 4,050 paid subscriptions on lower spend. Blended CAC rose from $29.60 to $50.24, while Day-30 retention for campaign-acquired users is projected at 61% versus 72% for the previous month. The CMO asks whether the campaign improved business outcomes, which channels performed best, and whether to scale, cut, or redesign the campaign.

Requirements

1. Define the primary metric or set of metrics you would use to evaluate campaign effectiveness.
2. Decompose performance across the acquisition funnel and identify where efficiency improved or worsened.
3. Compare volume growth versus quality of acquired users, including retention and CAC trade-offs.
4. Explain how you would segment results by channel, audience, device, geography, and creative.
5. Recommend whether FitMeal should continue, reallocate, or pause spend, and specify guardrail metrics.

Data Available

• ad_spend_daily: date, channel, campaign_id, ad_set_id, spend, impressions, clicks
• landing_page_sessions: session_id, user_id, timestamp, source, device_type, country, bounce_flag
• signup_events: user_id, signup_time, campaign_id, source_channel
• trial_events: user_id, trial_start_time, trial_plan, trial_to_paid_flag
• subscription_events: user_id, subscription_start_time, plan_type, revenue_amount, refund_flag
• retention_cohorts: user_id, acquisition_channel, day_7_active, day_30_active