Cohort LTV Analysis

Tracking & Analytics

Cohort LTV (Lifetime Value) analysis tracks how much revenue you earn from groups of customers who converted in the same month. This helps you understand the long-term value of your traffic sources and optimize for profitability over time.

Heatmap

The cohort heatmap shows revenue accumulation over time. Each row represents a monthly cohort (customers who first converted that month), and columns show their cumulative revenue in subsequent months:

  • Month 0: Revenue during the first month after conversion

  • Month 1: Cumulative revenue through the second month

  • Month 2+: Continued revenue accumulation over time

Darker cells indicate higher cumulative revenue. This staircase pattern (older cohorts have more columns) shows how long-term value develops over time.

Tip: Italic values with an asterisk (*) indicate partial month data. The current month is always incomplete.

AFS (Average First Sale)

AFS measures the average revenue generated within the first 24 hours of a customer's initial conversion. This metric is crucial for understanding immediate monetization:

  • High AFS: Strong initial offers, good upsells, or high-ticket products

  • Low AFS: May need stronger front-end offers or better audience targeting

AFS is calculated as: Total first-24h revenue ÷ Number of first conversions. It only counts revenue from conversions that happened within 24 hours of the customer's first click.

Why 24 hours? This aligns with ad platform attribution windows and ensures you're measuring the immediate impact of your traffic quality.

CAC (Customer Acquisition Cost)

CAC shows how much you spent to acquire each customer in a cohort. This is calculated by matching your ad spend with conversion attribution:

  • CAC lower than AFS: You're profiting on Day 1

  • CAC higher than AFS but lower than LTV: You'll profit over time

  • CAC higher than LTV: You're losing money on this cohort

CAC is calculated using the cvadid parameter to attribute ad costs to conversions. Make sure your tracking URLs include cvadid for accurate cost attribution.

Profitability Analysis

Compare AFS vs CAC to understand your breakeven point:

  • AFS > CAC: Profitable on first sale (ideal for scaling)

  • AFS ≈ CAC: Breaking even on acquisition, profit comes from repeat purchases

  • AFS < CAC: Requires strong LTV curve to become profitable

Track the Month column where cumulative LTV exceeds CAC to know your payback period. Shorter payback = faster reinvestment potential.

Filtering

Use segment filters to analyze cohorts by traffic source, geography, or any V1-V5 parameter:

  • V1-V5 parameters: Compare LTV by campaign, ad set, or creative

  • Country: Identify which markets have best long-term value

  • Device: Compare mobile vs desktop customer value

  • Referrer: Analyze by traffic source domain

This helps identify which segments have the best unit economics and deserve more budget allocation.

Best Practices

  • Wait for complete data: Month 0 data is most reliable after the month ends

  • Compare cohorts monthly: Look for trends in AFS and LTV curves

  • Use cvadid: Ensure accurate CAC by passing ad IDs in tracking URLs

  • Segment analysis: Break down by traffic source to find your best-performing campaigns

  • Focus on payback period: Know how long it takes each cohort to become profitable

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