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Customer Lifetime Value

Customer Lifetime Value
Calculation.

Updated

The CLV calculation that's right for you depends on what decision you're trying to inform. A finance team modeling 5-year revenue needs a different calculation than a marketer setting next month's ad budget. Both can be right, neither is universal. For most Shopify subscription stores, two methods cover the vast majority of needs.

Method 1: Formula-based (fast, approximate)

CLV = ARPU ÷ Monthly Churn Rate

Average revenue per user per month, divided by the percentage of subscribers who cancel each month. If your ARPU is $30 and your monthly churn is 5%, average tenure is 20 months and CLV is $600.

For a profit-adjusted view: CLV = ARPU × Gross Margin ÷ Churn Rate. Same example with 60% margin: $360 gross profit per customer.

Strengths: fast, easy to update, good for benchmarking and quick decisions.

Weaknesses: assumes constant churn (rarely true — early-tenure churn is usually higher), assumes constant ARPU, doesn't capture cohort dynamics.

Method 2: Cohort-based (slow, accurate)

Track a real signup cohort and observe their cumulative revenue at 30, 90, 180, 365, 730 days. Sum the curve to get observed CLV.

  • Strengths: reflects actual behavior, captures churn curves and seasonality.
  • Weaknesses: slow — you need 12 to 24 months of cohort data before the calculation stabilizes.

Best practice: use formula-based CLV for ongoing operations, and validate against cohort data once a quarter. When the two disagree significantly, trust cohort data and investigate why the formula is off.

Common calculation mistakes

  1. Counting only voluntary churn. If your churn rate excludes failed-payment cancellations (involuntary churn), your CLV will be inflated. Real churn includes both.
  2. Mixing customer types. A $20/month entry-tier and a $100/month premium-tier customer averaged together produce a misleading CLV. Calculate by tier, then weight.
  3. Using monthly cohort data without enough history. A 60-day cohort can't tell you 18-month CLV. Extrapolate carefully and label your numbers as estimates.
  4. Ignoring reactivation. Customers who return after a lapse extend effective tenure. Simple formulas miss this; cohort data captures it.

What "good" CLV depends on

Always relative to CAC. The healthy benchmark is CLV at least 3× CAC. A $600 CLV is excellent if CAC is $100, marginal if CAC is $200, and unsustainable if CAC is $400. The absolute dollar amount means little without the ratio.

Frequently Asked Questions

What's the easiest way to calculate CLV?

ARPU ÷ monthly churn rate. $30 ARPU and 5% monthly churn gives CLV of $600. It's the fastest and most-used formula for subscription businesses, accurate enough for almost all day-to-day decisions.

Should I include margin in my CLV calculation?

If you're comparing to CAC, yes — both numbers should be on the same basis (gross profit). For top-line revenue discussions, gross revenue CLV is fine. Just make sure your team knows which version is on the screen, because they can differ by 30 to 60%.

How accurate is formula-based CLV?

Roughly within 20–30% of actual cohort behavior for most stable subscription businesses. The biggest source of error is treating monthly churn as constant when early-tenure churn is usually higher. Validate against cohort data quarterly to catch drift.

How long does it take to calculate CLV accurately from cohort data?

12 to 24 months for stable observations. Earlier than that, you're extrapolating from partial data. Most stores compromise — they use formula-based CLV for daily operations and validate against cohort data once enough history accumulates.

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