LTV (Lifetime Value)

What is lifetime value (LTV)?

Lifetime value (also called LTV, CLV, or customer lifetime value) is the projected total revenue a business will earn from a single customer account from their first purchase to their last. It's a forward-looking estimate, not a historical fact — built on average revenue per customer, retention rate, and sometimes gross margin.

LTV matters because it determines how much a company can afford to spend acquiring customers. If a customer's LTV is $45,000 and it costs $15,000 to acquire them (CAC), the unit economics work — the business earns $3 for every $1 spent. If LTV drops to $10,000, the same $15,000 CAC destroys value.

For B2B SaaS companies at the $5-30M ARR range, LTV is the metric that connects retention strategy to financial performance. A 10% improvement in retention rate doesn't just reduce churn — it increases LTV by 15-30% because each customer generates revenue for additional months. This is why NRR improvements have an outsized impact on company valuation.

LTV is sometimes confused with ARR per customer. ARR per customer is a snapshot of what the customer pays now. LTV projects what they'll pay over the entire relationship — which includes expansion, contraction, and the time until churn.

Why LTV matters for operators

LTV sets the upper bound on customer acquisition spending. Every marketing budget, sales hiring plan, and channel investment decision should be filtered through LTV. Without it, companies either overspend (acquiring customers that never return the investment) or underspend (missing growth opportunities where unit economics are strong).

The consequence of ignoring LTV is most visible in channel allocation. A company might scale its highest-volume acquisition channel aggressively — only to discover that customers from that channel have 40% lower LTV than customers from organic or referral sources. The channel looks productive but destroys long-term value.

A typical $8M ARR SaaS company discovers that LTV varies 3-5x across customer segments when they first calculate it by cohort. Enterprise customers with $50K+ ACV might have 5-year LTV of $200K. SMB customers at $5K ACV might have LTV of $8K (high churn, low expansion). The blended average hides the segment economics that should drive strategy.

LTV formula

Simple LTV:
LTV = ARPA / Churn Rate

Where:
- ARPA = Average Revenue Per Account (monthly or annual)
- Churn Rate = Monthly or annual customer churn rate

Example:
- ARPA: $2,500/month
- Monthly churn rate: 2.5%

LTV = $2,500 / 0.025 = $100,000


Margin-adjusted LTV (more accurate):
LTV = (ARPA x Gross Margin %) / Churn Rate

Example:
- ARPA: $2,500/month
- Gross Margin: 78%
- Monthly churn rate: 2.5%

LTV = ($2,500 x 0.78) / 0.025 = $78,000

What each component means:

• ARPA: The average monthly (or annual) revenue per account. Use the number that matches your churn rate period.
• Churn Rate: Monthly or annual — must match the ARPA period. Use revenue churn, not logo churn, for the most accurate LTV.
• Gross Margin: Including gross margin gives you LTV in profit terms, not revenue terms. More useful for LTV:CAC calculations.

LTV benchmarks by segment

Sources: SaaStr 2025 Benchmark Report, Bessemer Cloud Index 2025, KeyBanc SaaS Survey 2025.

Common mistakes when calculating LTV

1. Using a blended LTV for all customer segments

Enterprise and SMB customers have dramatically different LTV. Blending them into one number makes both segments invisible. Calculate LTV by segment, by acquisition channel, and by cohort. The variance will surprise you.

2. Ignoring expansion revenue in the LTV calculation

The simple formula (ARPA / Churn) assumes revenue per customer stays flat. In practice, expansion revenue from upsells and seat growth increases ARPA over time. If NRR is 120%, customers are generating 20% more revenue each year. Ignoring this underestimates LTV by 30-50%.

3. Projecting LTV from early-stage data

LTV estimates based on 6-12 months of data are unreliable. Customers who survived the first 6 months behave differently than the full cohort. At minimum, use 18-24 months of cohort data before trusting LTV projections for strategic decisions.

4. Using logo churn instead of revenue churn

Logo churn (% of customers lost) and revenue churn (% of revenue lost) can diverge significantly. If small customers churn at 5% but large customers churn at 1%, the logo churn overstates the revenue impact. LTV should use revenue churn rate.

5. Not margin-adjusting LTV when comparing to CAC

Comparing revenue-based LTV to fully-loaded CAC overstates the ratio. If LTV is $100K but gross margin is 70%, the profit-based LTV is $70K. The CAC comparison should use the margin-adjusted number.

How Fairview tracks LTV automatically

Fairview's Operating Dashboard calculates LTV by connecting your CRM subscription data with payment history (Stripe) and retention metrics. LTV is segmented by customer cohort, acquisition channel, and plan type — so you see which segments generate the most long-term value.

The Margin Intelligence layer applies gross margin to LTV automatically, so the LTV:CAC ratio reflects true profit — not just top-line revenue. When LTV trends shift, the Next-Best Action Engine surfaces the driver: "LTV for Q1 cohort is 22% below Q4. Monthly churn for this cohort is 1.8 points higher — investigate onboarding completion rates."

→ See how the Operating Dashboard works

LTV vs ARR per customer

ARR per customer tells you what a customer is paying now. LTV estimates what they'll pay over time. For strategic decisions (how much to spend acquiring customers), LTV is the right metric.

FAQ

What is LTV in simple terms?

LTV is the total revenue you expect to earn from a customer over the entire time they stay with you. If a customer pays $500/month and stays for 3 years, their LTV is $18,000. It helps you determine how much you can afford to spend acquiring each customer — and whether your business model works.

What is a good LTV:CAC ratio for SaaS?

A healthy LTV:CAC ratio is 3:1 to 5:1. Below 3:1, you're spending too much to acquire customers relative to what they're worth. Above 5:1, you may be underinvesting in growth — the unit economics could support more aggressive acquisition spending.

How do you increase LTV?

Three levers: reduce churn (customers stay longer), increase ARPA (customers pay more through upsells, seat growth, or price increases), and improve gross margin (you keep more of each dollar). The highest-ROI lever is usually reducing early-stage churn — the first 90 days determine whether a customer becomes long-term or short-lived.

What's the difference between LTV and CLV?

LTV and CLV (customer lifetime value) are the same metric. LTV is more common in SaaS. CLV is more common in e-commerce and DTC. Some companies use LTV for revenue-based calculations and CLV for profit-based (margin-adjusted) calculations, but this distinction isn't standard.

How often should you recalculate LTV?

Quarterly for strategic planning. Monthly for monitoring trends by segment. LTV should be recalculated whenever churn rates, ARPA, or expansion patterns shift meaningfully. A 2-point increase in monthly churn changes LTV by 20-40% — significant enough to alter acquisition strategy.

Can you calculate LTV for a new company?

Approximately. With 6+ months of data, you can estimate LTV using early churn rates and ARPA. But treat it as directional, not precise. LTV models become reliable after 18-24 months of cohort data. Until then, track CAC payback period as a more observable proxy.

Related terms

• CAC (Customer Acquisition Cost) — Total cost of acquiring a new customer
• LTV:CAC Ratio — Ratio of lifetime value to acquisition cost; health check for unit economics
• Churn Rate — Percentage of customers or revenue lost in a given period
• NRR (Net Revenue Retention) — Revenue retained from existing customers after expansion and churn
• CAC Payback Period — Months required to recover customer acquisition cost

Fairview is an operating intelligence platform that tracks LTV by cohort, channel, and segment automatically — alongside CAC payback and contribution margin. Start your free trial →

Siddharth Gangal is the founder of Fairview. He built cohort-level LTV tracking because blended averages hide the segment economics that should drive every acquisition decision.