Calculate the real LTV of your SaaS customers from monthly churn, ARPU and gross margin. Find out if your CAC is sustainable with LTV:CAC and payback ratios.

Cohort Retention Calculator

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Project how a cohort of customers decays over time and the cumulative revenue it generates at 3, 6 and 12 months. Compare cohorts to detect product-led changes.

Advanced simulators

Subscription Pricing Strategy

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Simulate the impact of price changes on subscriptions.

Sector context

Whoever runs an SMB SaaS lives at the intersection of three tensions: MRR is growing but churn grows faster, CAC climbs each quarter, and burn eats runway before LTV materializes. The product can be excellent and still bleed money if the monthly cohort doesn't offset the cancellation of the cohort from six months ago. Every pricing, package, and onboarding decision hits multiple cohorts simultaneously, and effects only show with a 3–9 month lag. The SaaS simulators make that cycle visible: cohort retention, CAC payback, burn rate, runway, and MRR projection under different churn assumptions.

Key metrics

Indicators an SMB operator in the sector should know before modeling decisions.

MRR (Monthly Recurring Revenue)

Recurring revenue normalized monthly. The sum of all active subscriptions. The growth velocity of net MRR (new + expansion − churn − contraction) is the master metric.

Net revenue churn

(Revenue churn − expansion) / period MRR. Negative net churn (expansion > churn) is the SaaS holy grail: the business grows without acquiring new customers.

LTV / CAC ratio

A healthy ratio is 3.0 or more. Below 2.0 indicates a structural problem; above 5.0 suggests you can invest more aggressively in acquisition without breaking unit economics.

CAC payback period

Months for a customer to repay their own CAC via recurring margin. For SMB SaaS 12–18 months is reasonable; under 12 months releases significant working capital.

Burn multiple

Net burn / net new ARR in the same period. Under 1.0 is exemplary efficiency, 1.0–2.0 is good, >3.0 suggests growth depends excessively on burning capital.

How to pick the right simulator

If you're in growth mode and need to project MRR for 12–24 months, the MRR projection simulator models cohorts month by month with net retention. If churn is the worry, the churn rate simulator detects early signals, and the cohort retention simulator shows where in the customer lifecycle you're losing them. To defend CAC to a committee or investor, the CAC vs LTV simulator computes payback and ratio. If you sell SaaS with variable usage (not flat fee), the subscription pricing simulator models package, add-on, and overage combinations. For infrastructure, the capacity planning simulator sizes servers against expected growth. And if you're fundraising or managing runway, the burn rate simulator projects remaining months under different spend assumptions.

Practical example

Hypothetical case in US dollars. Plug your real numbers into the simulator to validate your own scenario.

A B2B SaaS startup has $42,000 USD MRR with 280 customers ($150 USD average ARPU). Current CAC $1,200 USD, monthly churn 4.5%, expansion 1.8% (net −2.7%). Computed LTV: ARPU × gross margin / churn = $150 × 0.85 / 0.045 = $2,833 USD. LTV/CAC: 2.36. CAC payback: $1,200 / ($150 × 0.85) = 9.4 months. The simulator models an onboarding improvement that reduces churn to 3.5% monthly (LTV rises to $3,643 USD, ratio 3.04) and a price adjustment lifting ARPU 8% (LTV $3,933 USD, payback 8.7 months). After the change, sustainable growth allows investing more in CAC without breaking the model: the simulator shows they can spend up to $1,800 USD/customer and keep payback under 12 months.

Common modeling mistakes

Traps we see when reviewing sector planning. Avoid them before closing your own model.

Confusing gross with net churn

If you lose 6% revenue monthly but gain 2% in expansion, your net churn is 4%, not 6%. Telling an investor 'churn is 6%' when net is 4% understates your trajectory.

Computing LTV with un-stabilized churn

In young cohorts (under 12 months) churn is understated because customers haven't had time to cancel. Use cohorts of at least 18 months for credible LTV.

Assuming flat CAC as you scale

The first 100 customers came in organically; the next 1,000 demand ads. CAC tends to grow with scale, not stay flat.

Reporting MRR without discounting aggressive discounts

If you discount 30% in year one to close deals, month-1 reported MRR isn't comparable to sustained MRR. Model effective MRR (post-discount) and contractual MRR separately.

Scope and limitations

SaaS simulators model individual cohorts then aggregate them. They don't capture network effects (when winning customer #100 changes the value proposition for #101) or dynamic competitive responses (a competitor cutting price aggressively). For strong pricing decisions (billing-model change, enterprise package launch) pair this with small-cohort A/B experiments before applying to the whole portfolio.

Read the methodology →Directional results: they do not replace certified accounting, tax, legal, or financial advice in your jurisdiction.

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The simulators with the most adoption in the sector. Each tackles a different business question.

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