LTV in SaaS: Calculation, Mistakes, and Healthy Benchmarks

Lifetime value (LTV) is the single most-abused metric in SaaS. Founders use one formula. Investors expect another. The actual answer — what a customer is really worth — requires a third.

This guide covers the three LTV formulas you will encounter, when to use each, the four mistakes that inflate LTV by 2–5x in most spreadsheets, benchmarks across SaaS segments, and how LTV connects to pricing and retention decisions that actually move the number.

What is LTV?

Customer Lifetime Value (LTV) is the total revenue, or gross profit, you expect to earn from a customer over their entire relationship with your product.

That is the concept. The math is where it gets contentious, because three different formulas exist — each more honest than the last, each producing materially different numbers from the same data.

The Three LTV Formulas

Formula 1: Simple LTV (avoid past pre-seed)

Simple LTV = ARPU ÷ Monthly churn rate

Where ARPU is average revenue per user per month and churn rate is monthly customer churn.

Example: ARPU $100, monthly churn 2%, LTV = $5,000.

This is the formula most founders use. It is also wrong for two reasons:

1. It treats revenue as profit (ignores COGS).
2. It assumes churn is constant over time — it almost never is.

Use it only for: napkin math, pre-launch, very early stage when no other data exists.

Formula 2: Gross-margin LTV (acceptable for fundraising)

Gross-margin LTV = (ARPU × Gross Margin) ÷ Monthly churn rate

Same as above, but multiplied by gross margin to convert revenue into gross profit.

Example: ARPU $100, gross margin 80%, monthly churn 2%, LTV = $4,000.

This is the formula most investors expect to see at seed and Series A. It is defensible, comparable across companies, and captures real customer value (gross profit, not gross revenue).

Use it for: investor decks, financial models, unit economics calculations, and LTV:CAC ratios at seed stage — see CAC explained.

Formula 3: Cohort-based / NPV LTV (correct)

NPV LTV = Σ (Monthly gross profit × Retention probability × Discount factor) across all months

Sum across all months: gross profit per customer in month N, multiplied by the probability of retention to month N, discounted to present value at your discount rate.

This is the formula a CFO or a serious VC analyst will build. It uses actual cohort retention curves (not assumed constant churn), accounts for time value of money, and reflects the reality that retention curves typically flatten — customers who survive year 1 churn far less in year 2 than the year 1 average would suggest.

Use it for: Series A+ fundraising, board reporting, pricing decisions, valuation work, anything where the number actually drives a decision.

Calculate cohort-based LTV in CashQuil →

When to Use Which Formula

Stage	Formula	Why
Pre-launch / pre-seed	Simple or gross-margin	No cohort data yet
Seed	Gross-margin	Investor expectation, defensible
Series A	Gross-margin + early cohort data	Cohort data starts to matter
Series B and beyond	Cohort-based / NPV	Required by sophisticated VCs
Internal pricing decisions	Cohort-based	Real decision impact
Board reporting	Cohort-based	Trend over time matters

The honest take: if you are past 12 months post-launch and you are still reporting simple LTV, you are either avoiding the truth your cohort data tells you, or you do not have the cohort data — and both are problems an investor will surface within 15 minutes of diligence.

Four Mistakes That Inflate LTV

Mistake 1: Constant churn assumption

Simple LTV math assumes 2% monthly churn means the average customer stays 50 months. In reality, churn is rarely constant. Most SaaS sees high early churn (months 1–6) and lower late churn — the retention curve looks like a hockey stick laid on its side.

If you compute LTV from average month-1-through-month-12 churn but the curve flattens after month 6, you will understate LTV. If the curve never flattens, you will overstate it dramatically. Both happen. Both are wrong.

The fix: use actual cohort retention curves, even if imperfect. An imperfect cohort curve beats a perfect-looking constant churn assumption.

Mistake 2: Confusing revenue churn with logo churn

ARPU divided by churn — which churn? If you have meaningful expansion revenue from existing customers, your revenue churn is lower than your logo churn. Sometimes it is negative (net revenue retention above 100%). Using revenue churn in the LTV formula when you have expansion gives you a much higher — and arguably more accurate — number than using logo churn.

The fix: be explicit. Report "LTV using net revenue churn" or "LTV using gross logo churn." Never just "LTV." A VC will ask which churn you used. Knowing the answer is the bare minimum.

Mistake 3: Ignoring discount rate

A dollar of profit in month 60 is worth less than a dollar in month 1. Simple LTV math treats them as equal. For SaaS with 5-year+ LTV horizons, ignoring the discount rate can inflate LTV by 20–40% versus an NPV calculation at a 15% discount rate.

The fix: at Series A and beyond, use NPV-based LTV with a discount rate that reflects either your WACC or VC return expectations (typically 20–30% for early-stage).

Mistake 4: Using ARPU at the wrong point

If you compute LTV using current-month ARPU but your customers expand revenue 30% over their lifetime, you understate LTV. If you compute LTV using projected expanded ARPU but most customers churn before the expansion realizes, you overstate it.

The fix: model ARPU as a cohort-level trajectory, not a point estimate. Month 1 ARPU is rarely month 24 ARPU for the same cohort.

LTV Benchmarks by SaaS Segment

These benchmarks are gross-margin LTV (formula 2), which is the most comparable across companies.

B2B SaaS

Segment	Gross-margin LTV	Healthy LTV:CAC
SMB (ACV under $5k)	$2,000–$15,000	over 3:1
Mid-market (ACV $5k–$50k)	$20,000–$200,000	over 3:1
Enterprise (ACV $50k+)	$200,000–$2M+	over 4:1

B2C SaaS and consumer subscriptions

Pricing tier	Gross-margin LTV
$5–$15/mo	$50–$300
$15–$50/mo	$200–$1,500
$50–$200/mo	$500–$5,000

The benchmarks are wide because retention varies enormously by segment, motion, and product stickiness. A workflow tool with daily-active usage and 95% gross retention will have 4–5x the LTV of a tool with 70% retention at the same price. Same revenue, very different businesses.

LTV:CAC Ratio — The Headline Number

LTV:CAC over 3:1 is the rule of thumb cited everywhere. The fuller story:

• Under 1:1 — you are losing money on every customer
• 1:1 to 3:1 — sub-scale economics, investable only with a strong improvement trajectory
• 3:1 to 5:1 — healthy, fundable
• Over 5:1 — either great, or you are underinvesting in growth and leaving market share on the table

Read more: CAC/LTV Ratio: What Investors Actually Want to See

How LTV Connects to Pricing and Retention

Two levers actually move LTV: ARPU and retention. Both are pricing decisions in disguise.

Pricing decisions that raise LTV

• Annual prepay discounts — raise retention by 20–40% versus monthly
• Tier upgrades with feature-based price walls
• Usage-based pricing components (expansion built into pricing model)
• Multi-product attach (sells related products, raises ARPU per customer)

Retention decisions that raise LTV

• Onboarding rigor — months 1–3 churn dominates total customer-lifetime churn
• Customer success motion — especially for mid-market and enterprise
• Product depth — more workflows mean more switching cost
• Contract structure — annual contracts retain roughly 2x better than monthly across most SaaS segments

A 10% lift in retention typically lifts LTV by 15–25%, because retention compounds. A 10% lift in ARPU lifts LTV by 10%. Retention is the higher-leverage lever, almost always.

This is the practical reason cohort-based LTV matters: it is the only formula that correctly captures the impact of retention improvements. Simple LTV cannot.

Where LTV Lives in a Financial Model

In a proper SaaS financial model, LTV is not a single cell — it is an output of:

1. Cohort retention curves (multiple cohorts, monthly retention rates)
2. ARPU trajectory by cohort (initial ARPU plus expansion over time)
3. Gross margin assumptions (stable or improving)
4. Discount rate for NPV calculation

If your model has a single hardcoded LTV number, it is a guess, not a model. If your model derives LTV from constant churn and current ARPU, it is closer to a guess than a model.

CashQuil builds cohort-based LTV automatically from your retention assumptions and ARPU model, across multiple scenarios, with full XLSX export so you can hand the model to an investor or your CFO.

Start free →

Next Steps

If you are calculating LTV for an investor conversation:

1. Report gross-margin LTV as your primary number — not simple LTV.
2. Show the calculation method explicitly — formula used, churn type (revenue vs logo), time horizon.
3. If you have 6+ months of customer data, include a cohort retention chart, even if it is messy.
4. Pair LTV with CAC payback period — they answer different questions and both matter.

The right LTV number is not impressive on its own. The right LTV calculation is. Investors notice the difference within the first five minutes of looking at your model.

---