Business Context

BrightCart is a DTC subscription commerce company selling household essentials through its website and mobile app. Over the last two quarters, paid acquisition spend increased while finance reported weaker unit economics, and leadership wants to know how the data team should tie analytics priorities directly to CAC and LTV.

Metric Scenario

In Q1, BrightCart spent $2.4M on acquisition and added 30,000 new customers, implying blended CAC of $80. In Q2, spend rose to $3.0M and new customers increased to 33,000, pushing CAC to $91. At the same time, projected 12-month LTV fell from $210 to $185 because 90-day repeat purchase rate declined from 42% to 36%, average order value dropped from $58 to $54, and gross margin stayed near 48%. The CEO asks whether the data strategy should focus on channel mix, onboarding, retention, or pricing, and what metrics should be monitored weekly versus quarterly.

Requirements

1. Define CAC and LTV precisely for this business, including numerator, denominator, and time horizon.
2. Explain how you would connect data strategy decisions to improving these two metrics.
3. Decompose the CAC increase and LTV decline into the most likely drivers.
4. Identify leading indicators that predict future CAC and LTV movement.
5. Recommend a metric framework and dashboard for marketing, product, and finance stakeholders.

Data Available

• ad_spend_daily: channel, campaign, impressions, clicks, spend, attributed_signups
• orders: customer_id, order_id, order_date, revenue, discount_amount, gross_margin
• customer_profiles: acquisition_channel, signup_date, geography, device_type, subscription_status
• retention_cohorts: cohort_month, repeat_purchase_rate_30d, repeat_purchase_rate_90d, churn_rate
• web_funnel_events: landing_page_view, signup_start, signup_complete, first_purchase