Framework
Term

LTV (Lifetime Value)

The total gross profit a business expects from a single customer over the entire duration of their relationship. LTV is the upper bound on how much you can spend to acquire that customer (CAC) and remain profitable.

LTV (Lifetime Value, sometimes CLV for Customer Lifetime Value) measures how much profit a single customer is worth over their entire relationship with the business. It's the ceiling on what you can spend to acquire that customer (CAC) while still running a profitable business.

The standard LTV formula

For a subscription business:

LTV = ARPU × Gross Margin × Average Customer Lifetime

Where:

  • ARPU — average revenue per user per period (typically per month)
  • Gross margin — revenue minus cost-of-goods (hosting, support, payment processing), as a %
  • Average customer lifetime1 / churn rate

LTV calculator: worked example

A SaaS product has:

  • ARPU = $50/month
  • Gross margin = 80%
  • Monthly churn rate = 5% → average lifetime = 1/0.05 = 20 months

LTV = $50 × 0.80 × 20 = $800 per customer

If CAC is $250, the LTV/CAC ratio is 3.2× — healthy. The CAC payback period (250 / (50 × 0.80) = 6.25 months) is also healthy.

If churn drops to 3% monthly, lifetime rises to 33 months and LTV jumps to $1,320 — a 65% LTV increase from a 2-point churn reduction. This is why churn dominates LTV math.

LTV/CAC benchmarks

LTV/CAC RatioInterpretationImplication
Below 1×Losing money on every customerStop acquiring until economics fix
1–3×MarginalSustainable only with low churn + expansion
3–5×HealthyStandard SaaS target
Above 5×Best-in-classEither under-investing in growth or genuinely category-leading

Above 5× is sometimes a signal you're under-spending on acquisition — the business is leaving growth on the table.

Why the formula is approximate

1/churn overstates lifetime because it assumes churn is constant. In reality, customers who survive the first 3 months churn much more slowly than new ones (the "smile curve"). More sophisticated LTV calculations use cohort-based retention curves rather than a single average churn rate.

For early-stage companies with fewer than 12 months of data, any LTV calculation is largely guess. Use it directionally; don't over-interpret the precision.

What LTV is good for

  • Setting CAC ceilings — LTV/CAC ≥ 3× is the standard target
  • Comparing customer segments — enterprise LTV might be 10× SMB LTV, which informs where to direct acquisition spend
  • Pricing decisions — a price increase that doesn't change churn rate increases LTV proportionally
  • Justifying expansion investment — when NRR > 100%, LTV grows even without new acquisition

What LTV is bad for

MisuseWhy it fails
Absolute revenue forecastsToo many compounding assumptions
Justifying high CAC in early-stage companiesChurn data isn't reliable; LTV is fiction
Comparing across business models10-year B2B contract LTV isn't comparable to 12-month consumer subscription LTV
Single-period LTV at consumer scaleHigh-churn consumer apps have lifetimes too short to support traditional LTV math — use cohort revenue instead

How to grow LTV

In order of leverage:

  1. Reduce churn — every 1pt churn reduction at 5% baseline grows LTV by ~20%
  2. Expand existing customers — upsells, seat expansions, add-on modules (drives NRR > 100%)
  3. Increase ARPU — pricing changes (less risky for new customers than existing)
  4. Improve gross margin — hosting efficiency, payment fees, support automation

Related

  • CAC — the cost side of the unit-economics equation
  • Churn — the biggest LTV lever
  • NRR — net revenue retention; when > 100%, LTV grows from existing customers alone
  • Unit Economics — the broader framework LTV fits inside
  • Cohort Analysis — the right way to measure lifetime

See also

Nearby terms

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