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SaaS LTV Calculation: How to Calculate Customer Lifetime Value for a B2B SaaS Company

Calculate SaaS LTV for B2B SaaS with cohort, gross margin and NRR adjustments, a worked example, and how to use LTV in CAC and budget decisions.

Ishan ManchandaIshan ManchandaNov 9, 2026
SaaS LTV Calculation: How to Calculate Customer Lifetime Value for a B2B SaaS Company

On This Page

  • SaaS LTV Calculation: How to Calculate Customer Lifetime Value for a B2B SaaS Company
  • How do you calculate lifetime value for a B2B SaaS company?
  • The six steps
  • Why gross margin belongs in the formula
  • The inputs at a glance
  • What data do you need before you calculate SaaS LTV?
  • Fields to pull and who owns them
  • Why does the basic SaaS LTV formula overstate value?
  • The error changes direction over time
  • Three common mistakes
  • How do you calculate LTV by cohort or customer segment?
  • A worked example with illustrative inputs
  • Segmentation rules
  • How do you calculate LTV when net revenue retention is above 100%?
  • The capped-horizon method
  • Which retention benchmark to trust
  • Pricing model changes the answer
  • How should LTV inform attribution and acquisition budgets?
  • Use LTV and CAC payback together
  • Connect LTV to the attribution model
  • Set thresholds from segment numbers
  • Who is this LTV method not for?
  • Frequently Asked Questions
  • What is a good LTV:CAC ratio for B2B SaaS?
  • Should LTV be based on revenue or gross margin?
  • Should LTV use logo churn or revenue churn?
  • How do you calculate LTV with less than 12 months of data?
  • What is a good net revenue retention rate for B2B SaaS?
  • Conclusion

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Last updated: Nov 9, 2026

SaaS LTV Calculation: How to Calculate Customer Lifetime Value for a B2B SaaS Company

By RevOps for B2B SaaS Editorial Team. Last updated: November 4, 2026.

SaaS LTV calculation is the process of estimating the gross profit a B2B SaaS customer will generate over the life of the account, usually by dividing margin-adjusted revenue per account by a churn rate. The formula is simple. Trusting it is harder.

In ChartMogul's analysis of 35,512 customer cohorts, 28.3% had actual revenue that differed from the predicted LTV by more than 50% (ChartMogul, 2026). That gap matters because LTV sets acquisition cost thresholds and pipeline targets, which feed the attribution decisions that revenue operations (RevOps) owns. This guide shows how to calculate LTV, split it by cohort, handle net revenue retention above 100%, and use it in budget decisions.

Key Takeaways

  • SaaS LTV is ARPA × gross margin ÷ churn rate in its basic form, and ChartMogul calls that basic formula "overly optimistic".
  • A blended LTV hides segment differences: ChartMogul found 74% of the cheapest signup-MRR quartile still active after 12 months, against 45% of the most expensive (ChartMogul, 2026).
  • When net revenue retention is above 100%, the churn-based LTV formula breaks, so a B2B SaaS team should use a capped 24 to 36 month cohort horizon.
  • LTV for B2B SaaS budget decisions should be compared with fully loaded CAC by segment and paired with CAC payback.

How do you calculate lifetime value for a B2B SaaS company?

Customer lifetime value (LTV) is the gross profit a customer account is expected to generate before it churns. The basic B2B SaaS formula is ARPA × gross margin ÷ churn rate, but ChartMogul warns that "The basic LTV formula produces an overly optimistic result." (ChartMogul, 2026). Treat it as a starting estimate, then adjust it.

Finance and RevOps colleagues reviewing a handwritten LTV formula on a whiteboard
Finance and RevOps colleagues reviewing a handwritten LTV formula on a whiteboard

The six steps

  1. Pick the account unit. Use paying accounts, not logos or seats.
  2. Calculate ARPA. ARPA (average revenue per account) is monthly recurring revenue divided by the number of paying accounts.
  3. Apply gross margin. Multiply ARPA by subscription gross margin so LTV measures profit, not revenue.
  4. Choose the churn rate. Use monthly revenue churn, or 1 minus gross revenue retention converted to a monthly rate.
  5. Divide. LTV = ARPA × gross margin ÷ monthly churn rate.
  6. Check the result by cohort. Repeat steps 2 to 5 for each segment before using the number in any budget.

Why gross margin belongs in the formula

Revenue-based LTV ignores the cost of serving the account, so it overstates profit whenever gross margin is below 100%. Apply the same margin assumption in every segment so comparisons stay fair.

The inputs at a glance

InputDefinitionTypical source
ARPAMonthly recurring revenue ÷ paying accountsBilling system
Gross margin(Subscription revenue − cost of delivery) ÷ subscription revenueFinance
Revenue churnRecurring revenue lost to cancellations and contraction per monthBilling system
Fully loaded CACSales, marketing, onboarding and customer success cost to win one accountFinance and customer relationship management (CRM)

What data do you need before you calculate SaaS LTV?

Calculating SaaS LTV for a B2B SaaS company requires five inputs: average revenue per account, gross margin, a churn rate, a cohort definition and a fully loaded customer acquisition cost (CAC). Gross revenue retention (GRR) is the cleanest churn source, and Aleph's 2026 benchmark shows median GRR fell from 88% to 84% (Aleph, 2026).

Aleph's commentary on its 2026 report puts the trend plainly: "Median GRR fell to 84% in 2025, down from 90% just three years prior." (Aleph, 2026). Any LTV built on an older churn assumption is likely too high.

Fields to pull and who owns them

FieldWhere it livesOwner
Start date and plan type (monthly or annual)Billing systemFinance
Contract value at signup (ACV)CRM closed-won recordRevOps
Segment, price tier and industryCRM account recordRevOps
Acquisition channel and campaignCRM, tied to the Google click ID (GCLID) or equivalentRevOps and Marketing Ops
Expansion and contraction by monthBilling systemFinance
Onboarding and customer success costGeneral ledgerFinance

The channel field is the one most teams are missing. A 2026 audit of 104 Google Ads accounts published by GrowthSpree found 91% had no Google click ID reaching the CRM (GrowthSpree, June 2026). Without that link, LTV cannot be joined to the channel that produced the customer.

Why does the basic SaaS LTV formula overstate value?

The basic SaaS LTV formula overstates value because it blends customers with different retention into one average. In ChartMogul's analysis of 35,512 cohorts, 28.3% had actual revenue that differed by more than 50% from the LTV predicted at formation (ChartMogul, 2026). Churn assumptions also go stale quickly.

Printed cohort retention table with pen marks on a desk beside a laptop
Printed cohort retention table with pen marks on a desk beside a laptop

The error changes direction over time

ChartMogul's dataset covers 3,331 company accounts from Q1 2020 to Q4 2024. LTV was calculated at cohort formation from blended ARPA and trailing six-month logo churn, then compared with actual revenue. The median error moved from -2.4% at 12 months to +6.9% at 24 months and +14.4% at 36 months (ChartMogul, 2026). The formula errs one way early and the other way later, so one point-in-time LTV is unreliable.

Line chart: Median error of formula-based LTV prediction vs actual revenue, by months after cohort formation. Highest: 36 months at 14.4%.
Line chart: Median error of formula-based LTV prediction vs actual revenue, by months after cohort formation. Highest: 36 months at 14.4%.

Source: ChartMogul (The SaaS LTV Report, 2026), 2026

Three common mistakes

  1. Using logo churn for revenue decisions. A lost small account and a lost large account count the same. Use revenue churn or GRR.
  2. Ignoring gross margin. The result is revenue, not profit.
  3. Blending monthly and annual plans. ChartMogul's retention report found median NRR is 10 to 20 percentage points higher for annual plans than for monthly plans (ChartMogul, 2025). Keep those cohorts apart.

How do you calculate LTV by cohort or customer segment?

Cohort LTV is the LTV calculated separately for a group of customers who share a signup period, price tier, plan type or acquisition channel. ChartMogul found 74% of the cheapest signup-MRR quartile were still active after 12 months, against 45% of the most expensive quartile (ChartMogul, 2026).

Customer cards sorted into two groups on a table by price tier
Customer cards sorted into two groups on a table by price tier

The report's author summarises the pattern: "Lower-paying customers often survive longer than higher-paying ones" (ChartMogul, 2026). A blended LTV therefore tends to overvalue high-priced segments.

A worked example with illustrative inputs

The inputs below are hypothetical round numbers chosen to show the arithmetic. They are an illustration, not benchmarks. Both cohorts assume an 80% gross margin and the same CAC. The blended column is revenue-weighted: total MRR ÷ total accounts for ARPA, and (A MRR × A churn + B MRR × B churn) ÷ total MRR for churn.

Metric (illustrative)Cohort A (low price)Cohort B (high price)Blended
Paying accounts501060
Monthly recurring revenue$20,000$20,000$40,000
ARPA$400$2,000$667
Monthly revenue churn2%4%3%
LTV (ARPA × 0.8 ÷ churn)$16,000$40,000about $17,800
Fully loaded CAC$6,000$6,000$6,000

Divide each LTV by its CAC. Cohort A recovers its acquisition cost less than three times over. Cohort B recovers it more than six times over. The blended figure lands close to three times, which looks acceptable. Yet Cohort A holds most of the accounts and sits below that line. A budget set on the blended figure would treat both cohorts the same, and would misprice every channel that feeds only one of them.

Segmentation rules

  • Cut cohorts by price tier, plan type (monthly or annual), industry and acquisition channel.
  • Do not split so far that a cohort has too few accounts to show a stable churn rate.
  • Treat AI add-on products separately. ChartMogul's AI-native sample shows products under $50 a month with 23% GRR and 32% NRR, against 70% GRR and 85% NRR above $250 a month (ChartMogul, 2025). That sample is a directional illustration, not a classic B2B SaaS benchmark.

How do you calculate LTV when net revenue retention is above 100%?

Net revenue retention (NRR) is the share of a cohort's starting recurring revenue still billed after churn, contraction and expansion. When NRR is above 100%, the churn-based LTV formula breaks because the implied lifetime has no end. Use a capped 24 to 36 month horizon of realised cohort revenue instead. Median NRR was 102% in 2025 data (Aleph, 2026).

Analyst sketching a capped 36 month revenue curve on paper
Analyst sketching a capped 36 month revenue curve on paper

The capped-horizon method

  1. Take the cohort's monthly recurring revenue for each month since signup.
  2. Multiply each month by subscription gross margin.
  3. Sum the result up to a fixed cap of 24 or 36 months.
  4. Optionally discount later months so distant revenue counts for less.
  5. Report the cap and the discount rate next to the number.

Use realised revenue where it exists and a stated projection only for the months that have not happened yet. The cap keeps expansion from inflating LTV without limit.

Which retention benchmark to trust

Benchmarks differ because the samples differ. Pick peers by pricing model, deal size and stage.

SourcePopulationMedian NRR
Aleph x Benchmarkit, 2026342 B2B SaaS and AI-native companies, self-reported (230 reported NRR)102%
SaaS Capital, 2026Bootstrapped private B2B SaaS, $3M to $20M annual recurring revenue (ARR)103% (GRR 91%)
ChartMogul, December 2025About 2,700 B2B SaaS companies, billing data82%

The first two are survey medians. The third comes from billing records. The benchmark you choose changes the LTV you defend to the board.

Pricing model changes the answer

Aleph's 2026 benchmark puts usage-based companies at 108% median NRR and seat-based companies at 98% (Aleph, 2026).

Horizontal Bar chart: Median net revenue retention by pricing model (2025 data). Highest: Top quartile at 110%.
Horizontal Bar chart: Median net revenue retention by pricing model (2025 data). Highest: Top quartile at 110%.

Source: Aleph x Benchmarkit (2026 SaaS & AI Performance Benchmarks), 2026

For bootstrapped companies, SaaS Capital reports median GRR of 91% and NRR of 103%, with the 90th percentile at 100% GRR and 117.9% NRR (SaaS Capital, 2026). Use these to sanity-check your own inputs.

Lollipop chart: Bootstrapped B2B SaaS ($3M-$20M ARR): retention medians vs top performers. Highest: 90th pct NRR at 117.9%.
Lollipop chart: Bootstrapped B2B SaaS ($3M-$20M ARR): retention medians vs top performers. Highest: 90th pct NRR at 117.9%.

Source: SaaS Capital, 2026

How should LTV inform attribution and acquisition budgets?

LTV informs attribution and budget by setting the ceiling on what each channel or segment can pay to acquire a customer. A blended LTV applied to every channel hides weak segments, so compare segment LTV to fully loaded CAC and lead with CAC payback, which Aleph reports improved from 18 months to 16 months at the median (Aleph, 2026).

Finance lead and marketing lead discussing acquisition budget over printed pages
Finance lead and marketing lead discussing acquisition budget over printed pages

Use LTV and CAC payback together

CAC payback is the number of months of gross profit needed to recover the cost of acquiring a customer. LTV:CAC is the ratio of lifetime gross profit to acquisition cost. Payback is measured, while LTV:CAC is a projection. For cohorts under 12 months old, lead with payback.

Connect LTV to the attribution model

A channel-level LTV:CAC is only as good as the attribution behind it. If last-touch attribution gives branded search credit for deals other channels created, the channel CAC is wrong and so is the ratio.

Audit data (GrowthSpree, June 2026, 104 audited Google Ads accounts): 91% had no Google click ID reaching the CRM and 89% ran default attribution. After a 90-day attribution fix, the share of closed-won deals traced to a campaign went from 0% to 67%.

Review the attribution software options once click IDs and stages reach the CRM.

Set thresholds from segment numbers

  • Paid acquisition: set the maximum cost per sales-qualified lead (SQL) by working back from segment LTV, a target ratio and the stage conversion rates in B2B SaaS sales conversion benchmarks.
  • Customer success: fund by segment GRR and NRR, not the company average.
  • Pipeline targets: convert segment LTV and CAC into the pipeline coverage each segment needs.

Who is this LTV method not for?

The cohort and capped-horizon LTV method suits B2B SaaS teams with at least 12 months of billing history. Teams with younger cohorts should lead with CAC payback and show LTV:CAC only as a projection, the practitioner position in 2026 trade commentary (Mostly Metrics, 2026).

  • Very early companies. With few accounts, a cohort split produces noisy churn. Use payback and state assumptions openly.
  • Teams without billing-to-CRM links. Without an account ID shared by both systems, channel LTV cannot be calculated.
  • Companies with one price tier and one channel. A blended figure is less misleading, though still worth checking against actual cohort revenue.
  • Anyone treating LTV as a forecast. ChartMogul's error data shows it is an estimate that moves with the cohort.

Frequently Asked Questions

What is a good LTV:CAC ratio for B2B SaaS?

No single LTV:CAC ratio is reliable for every B2B SaaS company, because the ratio is a projection built on churn assumptions that go stale. ChartMogul's 2026 cohort analysis found predictions often miss actual revenue by wide margins (ChartMogul, 2026). Pair the ratio with CAC payback and review it by segment.

Should LTV be based on revenue or gross margin?

LTV for B2B SaaS should be based on gross margin, not revenue, because revenue ignores the cost of serving the customer. A revenue-based figure overstates profit whenever gross margin is below 100%. Use subscription gross margin and keep the same margin assumption in every segment comparison so the ratios stay fair.

Should LTV use logo churn or revenue churn?

LTV for B2B SaaS should use revenue churn, ideally gross revenue retention (GRR), because logo churn treats a small account and a large account as equal. Median GRR fell from 88% to 84% in Aleph's 2026 benchmark (Aleph, 2026). Use logo churn only as a secondary check when revenue data is unavailable.

How do you calculate LTV with less than 12 months of data?

A B2B SaaS company with less than 12 months of data should lead with CAC payback and show LTV:CAC only as a projection, the practitioner position in 2026 trade commentary (Mostly Metrics, 2026). Use realised gross margin per account, state the churn assumption openly, and replace it with measured cohort retention once 12 months of billing history exist.

What is a good net revenue retention rate for B2B SaaS?

Median net revenue retention for B2B SaaS ranges from 82% to 103% depending on the dataset. Aleph's 2026 survey reports 102% (Aleph, 2026), SaaS Capital reports 103% for bootstrapped companies (SaaS Capital, 2026), and ChartMogul's billing data shows 82% (ChartMogul, 2025). Pick peers by pricing model, deal size and stage.

Conclusion

SaaS LTV works as a decision input only when it is built by cohort, adjusted for gross margin and tested against realised revenue. The takeaways:

  • Start with ARPA × gross margin ÷ churn, then treat the result as an estimate.
  • Split LTV by price tier, plan type and channel before setting any budget.
  • Cap the horizon at 24 to 36 months when NRR is above 100%.
  • Choose retention benchmarks that match your pricing model, deal size and data source.
  • Pair LTV:CAC with CAC payback, and fund channels on segment numbers, using the attribution model guide to check the channel data behind them.

One funnel. One set of definitions. One number everyone trusts. To work through your LTV inputs, CRM fields and attribution setup with a RevOps expert, Meet with an expert.

Ishan Manchanda

Written by

Ishan Manchanda

Ishan Manchanda is co-founder of GrowthSpree, a B2B SaaS marketing consultancy founded in 2017 that has managed $60M+ in ad spend across 300+ B2B SaaS companies. He focuses on demand generation, go-to-market strategy and pipeline growth, and has been featured in Silicon Valley Times, SaaS Mag and the Unbounce podcast.

Nov 6, 2026

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