Payback Cohorts

Why this matters

• Decide whether to scale, pause, or optimize a channel or campaign.
• Compare cohorts by channel, country, offer, or creative to see which recover CAC faster.
• Set budget guardrails (e.g., only scale campaigns with payback under 3 months).
• Explain performance to finance and growth teams in clear, time-bound terms.

Concept explained simply

Payback month is the first month where the cohort’s cumulative net contribution per acquired customer is greater than or equal to the CAC for that cohort.

Contribution = Revenue minus variable costs (e.g., cost of goods, payment fees, shipping, sales commissions). Use contribution, not gross revenue, because only contribution can pay back acquisition cost.

Mental model

Imagine a bucket labeled CAC. Each month, drops of net contribution fall into the bucket from that cohort. The payback month is when the bucket fills to the top. Different cohorts have different bucket sizes (CAC) and drip rates (retention, ARPU, margins).

Key definitions and formulas

• CAC per cohort = Total marketing spend to acquire that cohort ÷ Number of new customers in that cohort.
• Monthly contribution per cohort per acquired customer = (Cohort monthly revenue − cohort monthly variable costs) ÷ cohort size.
• Cumulative contribution per acquired customer up to month m = Sum of monthly contribution from month 0 to m.
• Payback month = The smallest m where cumulative contribution per acquired customer ≥ CAC per cohort.

Tip: What counts as variable cost?

Common inclusions: cost of goods/content, fulfillment/shipping, payment processing fees, refunds/chargebacks, sales commissions, variable support. Exclude fixed overhead unless it scales directly with orders.

Data you need

• Acquisition date and cohort key (e.g., acquisition month, channel).
• Cohort size (number of new customers in that cohort).
• Marketing spend tied to that cohort (or per-channel spend with proper attribution).
• Monthly revenue and variable costs generated by that cohort.

If you don’t have cost per order

Start with revenue × margin% as an approximation. Document the assumption and refine later with better cost data.

Step-by-step: Build a payback cohort

1. Define cohorts. Group users by acquisition month (e.g., 2025-03) and, optionally, by channel or campaign.
2. Compute CAC per cohort. Total spend that acquired the cohort ÷ cohort size.
3. Aggregate monthly contribution. For each cohort and each month since acquisition, sum contribution (revenue − variable costs).
4. Normalize per acquired customer. Divide monthly contribution by cohort size to get per-acquired-customer contribution.
5. Build cumulative contribution. Take a running sum by month 0, 1, 2, ...
6. Find payback month. The first month where cumulative ≥ CAC. If it never crosses, mark as "Not paid back" by horizon.
7. Compare cohorts. Visualize as a table or heatmap. Spot fast/slow payback groups.

Worked examples

Example 1: Subscription app (simple retention)

Cohort size: 100 users. CAC per acquired customer: $15. Net contribution per active customer per month: $5. Retention: Month0=100%, M1=70%, M2=60%, M3=50%, M4=45%.

Monthly contribution per acquired customer: M0 $5.00; M1 $3.50; M2 $3.00; M3 $2.50; M4 $2.25.

Cumulative: M0 $5.00; M1 $8.50; M2 $11.50; M3 $14.00; M4 $16.25.

Payback month: M4 (first month where $16.25 ≥ $15).

Example 2: E‑commerce (repeat orders, 30% margin)

Cohort size: 500 customers. Total CAC spend: $7,500 → CAC per customer: $15.

Average order value (AOV): $50. Margin: 30% → contribution per order: $15.

Repeat pattern per acquired customer: M0: 0.60 orders; M1: 0.30; M2: 0.20; M3: 0.15; M4: 0.10.

Monthly contribution per acquired customer: $9.00; $4.50; $3.00; $2.25; $1.50. Cumulative at M3 = $18.75 → payback in M3.

Example 3: Freemium SaaS (delayed monetization)

Cohort size: 1,000. CAC per customer: $8.

M0 revenue is $0 (trial). Net conversion starts M1 with $3 contribution per acquired customer, then M2 $2, M3 $2, M4 $1.5.

Cumulative: M0 $0; M1 $3; M2 $5; M3 $7; M4 $8.5 → payback in M4.

Interpreting results

• Faster payback reduces cash risk and lets you reinvest budgets sooner.
• Benchmarks vary by model. Many teams aim for 1–3 months on performance channels and accept longer for brand investments. Calibrate to your cash cycle and churn dynamics.
• When payback is slow, diagnose: high CAC, low retention, low margin, or delayed monetization.

Exercises

These mirror the exercises below. Do them in a spreadsheet or SQL, then compare your output to the expected results. Tip: Tiny rounding differences are fine; document assumptions.

• Exercise 1: Build a payback cohort in a spreadsheet from the mini dataset.
• Exercise 2: Write SQL to compute payback month per cohort.

• I computed CAC per cohort correctly (spend ÷ cohort size).
• I used contribution (revenue − variable costs), not revenue.
• My cumulative curve is non-decreasing and starts at month 0.
• My payback month is the FIRST month cumulative ≥ CAC.

Common mistakes and self-check

• Mistake: Using revenue instead of contribution. Fix: Subtract variable costs (COGS, fees, refunds).
• Mistake: Mixing activity date vs. acquisition date. Fix: Always group revenue by months since acquisition (0,1,2...).
• Mistake: Using blended CAC across all months. Fix: Use cohort-specific CAC, or channel-level CAC for that cohort.
• Mistake: Ignoring refunds/credits. Fix: Deduct in the correct month to avoid overstating early payback.
• Mistake: Counting trial users as acquired customers. Fix: Define cohort as paying customers or use separate trial-to-paid step.

Self-check routine

• Reconcile sums: Cohort-level monthly contribution should roll up to total P&L contribution for the same period (within known exclusions).
• Spot-check 5 users: their orders and costs land in the expected months-since-acquisition.
• Edge test: If month 0 contribution is greater than CAC, payback should be 0.

Practical projects

• Build a cohort payback sheet with slicers for channel and country. Add conditional formatting to highlight payback ≤ 3 months.
• Create a SQL view that outputs payback month per cohort, plus 6- and 12-month cumulative contribution per acquired customer.
• Scenario model: simulate +20% CAC or −10% margin and show how payback shifts.

Mini challenge

Your February paid social cohort has CAC=$18. Month-by-month contribution per acquired customer is: M0 $4.5, M1 $4.0, M2 $3.0, M3 $2.5, M4 $2.0.

1. Find the payback month.
2. What margin uplift (in $ per acquired customer per month from M1 onward) would make payback happen one month earlier?

Show a concise solution

Cumulative: M0 $4.5; M1 $8.5; M2 $11.5; M3 $14.0; M4 $16.0 → Not yet; need M5. Additional $2.0 at M4 would reach $18. To shift one month earlier (to M4), you need +$2.0 across months up to M4. If applied from M1 to M4 (4 months), +$0.50 per month per acquired customer would suffice (0.5×4=$2.0).

Who this is for

• Marketing Analysts and Growth Analysts who own channel reporting and budget recommendations.
• Product and Lifecycle Marketers needing retention-aware ROI tracking.
• Finance partners validating acquisition efficiency.

Prerequisites

• Comfort with spreadsheets (running sums, pivot tables) or SQL window functions.
• Basic understanding of CAC, contribution margin, and cohorts.
• Access to acquisition, revenue, and cost data (or sample data).

Learning path

1. Review cohort definitions and time indexing (month 0, 1, 2...).
2. Build payback in a spreadsheet for one cohort.
3. Generalize to multiple cohorts and channels.
4. Add contribution margin and refunds for realism.
5. Automate in SQL and schedule updates.
6. Layer scenario and sensitivity analysis on CAC and margin.

Next steps

• Extend to full LTV modeling beyond payback horizon.
• Add channel- and geo-level comparisons with confidence intervals.
• Combine payback with cash flow planning to set monthly budget caps.

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