How to calculate LTV (customer lifetime value): formulas and worked examples

The standard LTV calculation is average revenue per account per period, times gross margin percentage, divided by the churn rate for the same period. A customer paying $900 a month at a 75% gross margin, with 1.5% of customers leaving each month, has a lifetime value of 900 × 0.75 / 0.015 = $45,000. Customer lifetime value is gross profit, not revenue, and it is only useful next to what the customer cost to win.

The LTV formula

LTV = ARPA × Gross margin % / Churn rate

Expected lifetime = 1 / Churn rate

ARPA is average revenue per account. All three inputs must be for the same period: monthly ARPA with monthly churn, or annual with annual. Dividing by churn is the same as multiplying the period's gross profit by the expected lifetime, so the formula reads as "gross profit per period × number of periods the customer stays."

David Skok's LTV and CAC formulas give the same structure, with the lifetime example "If the Monthly customer churn rate is 3%, then the Customer Lifetime will be 1/0.03 which is 33 months." In Excel, with ARPA in B2, gross margin in C2 and churn in D2:

=B2*C2/D2

Expected lifetime is =1/D2.

The inputs and where they come from

Use customer churn, not revenue churn, in this form: it counts how many accounts leave, which is what sets the expected lifetime. The difference between churn, renewal and retention rates is set out in renewal rate, retention rate and churn rate, and churn has the one-line definition.

Worked example: three segments

Monthly figures, in USD, for one SaaS company with 440 active accounts. LTV in G2 is =B2*C2/D2; lifetime in E2 is =1/D2.

Mid-market, step by step: 900 × 0.75 = 675 of gross profit a month. Divided by churn, 675 / 0.015 = 45,000. Expected lifetime is 1 / 0.015 = 66.7 months, and 675 × 66.7 = 45,000 again.

The enterprise lifetime of 125 months is more than ten years, longer than most contracts have existed. See the cap under "Where it goes wrong."

LTV against CAC

LTV means little until it is set against customer acquisition cost. With a CAC of 15,000 for a mid-market account and 4,000 for an SMB account:

Mid-market returns three times its acquisition cost; SMB 2.3 times. Skok's SaaS Metrics 2.0 puts the best SaaS businesses at "a LTV to CAC ratio that is higher than 3". That is a rule of thumb, and his definitions add that it assumes LTV without a gross margin adjustment and a gross margin of 80% or higher. On gross-profit LTV, as here, 3.0 is a stricter bar.

A discounted LTV

The simple formula treats a dollar in year five like a dollar today. The discounted form from Gupta and Lehmann's "Customers as assets" (Journal of Interactive Marketing, 2003) is:

Discounted LTV = Margin per period × Retention rate / (1 + Discount rate − Retention rate)

It assumes margin arrives at the end of each period, and only from customers still retained at that point. Use annual figures. For the mid-market segment:

8,100 × 3.4 = 27,540. With a discount rate of zero the same formula gives 8,100 × 0.85 / 0.15 = 45,900, close to the simple 45,000; discounting at 10% takes off 40%. Monthly churn of 1.5% compounds to 83.4% annual retention, so 85% is slightly generous. In Excel, with margin in B2, retention in C2 and the discount rate in D2: =B2*C2/(1+D2-C2).

LTV without a subscription

Distributors and manufacturers rarely have a churn rate: customers do not cancel, they stop ordering. Measure from purchase history instead:

LTV = Average annual gross profit per customer × Expected relationship years

A distributor whose customers bring an average of $18,000 of gross profit a year and keep buying for 6.5 years on average has an LTV of 18,000 × 6.5 = $117,000. Both inputs come from the sales ledger: gross profit by customer by year, and the span from first to last order for customers who have stopped. Customer lifetime value from the ledger works the method in full, including how to decide when a customer has stopped.

The check

Two checks prove the segment figures.

LTV × accounts is plausible against total gross profit. Each segment's LTV times its accounts is the gross profit the current base is expected to deliver:

15,200,000 is 68.8 months of today's gross profit of 221,000 a month. If your accounts have never stayed anywhere near that long on average, the churn input is too low.

Segment LTVs weighted by accounts give the blended figure. 15,200,000 / 440 = 34,545. Computing one LTV from blended inputs gives a different answer: blended gross profit per account is 221,000 / 440 = 502 and blended churn is 10.96 lost accounts / 440 = 2.49%, so 502 / 0.0249 = 20,164. The weighted figure is the one that adds back to the segments; the blended-input figure is not an average of anything.

Where it goes wrong

• Revenue instead of gross profit. At 900 a month and 1.5% churn, revenue LTV is 60,000 against 45,000 of gross profit LTV, a third too high.
• Absurd lifetimes from very low churn. 0.2% monthly churn is a 500-month, 41-year life. Cap the horizon, for example at five years: the enterprise LTV capped at 60 months, =B2*C2*(1-(1-D2)^60)/D2, is 133,843 rather than 350,000.
• Mixed periods. Monthly ARPA divided by annual churn gives an LTV twelve times too small; annual ARPA with monthly churn, twelve times too large.
• Ignoring expansion and contraction. Accounts that grow are worth more than flat ARPA says, and accounts that shrink are worth less; gross retention and net retention measures both.
• One blended LTV. It hides segments with very different churn, as the 34,545 against 20,164 above shows. Measure churn by cohort first: how to build a cohort retention table in Excel.

LTV by segment and cohort

Covirage computes churn, retention and gross profit per customer and cohort from the uploaded billing and ledger files, then LTV by segment, with every input shown beside the result. Its deterministic tools do the arithmetic and the external AI model only explains it. See Covirage for SaaS sales teams to compute LTV by segment from your own billing export. To compare LTV with what it cost to win the customer, see the LTV to CAC ratio, and for the per-customer view around both, see unit economics.