SaaS LTV:CAC Benchmark Calculator

This calculator estimates your SaaS customer lifetime value (LTV), CAC payback period, and LTV:CAC ratio, then compares your results to commonly cited benchmarks. Use it to quickly check whether your unit economics are moving in the right direction and how efficiently you turn customer acquisition spend into long-term value.

Key SaaS unit economics this tool calculates

• Customer lifetime value (LTV) – estimated gross profit you earn from an average customer over their lifetime.
• LTV:CAC ratio – how many dollars of lifetime value you generate for every dollar spent acquiring a customer.
• CAC payback period – how many months it takes to recover your customer acquisition cost from gross profit.

Benchmarks shown here are directional, not prescriptive. They are useful for discussion, fundraising, and planning, but you should adapt them to your specific segment, ACV, and go-to-market model.

Formulas used in this SaaS LTV:CAC calculator

The calculator uses a simple steady-state model based on ARPA (average revenue per account), gross margin, and monthly churn.

1. Monthly gross profit per customer

First, we estimate the average gross profit you earn per customer each month:

Here, ARPA is your average revenue per paying customer per month, and gross margin is the percentage of revenue left after direct costs (such as hosting, support tied directly to usage, third-party tools directly required to serve customers).

2. Customer lifetime value (LTV)

We approximate customer lifetime using monthly churn and assume churn is constant over time:

LTV is then calculated as:

3. LTV:CAC ratio

The LTV:CAC ratio compares what you expect to earn from a customer against what you spend to acquire them:

Where CAC is your fully loaded customer acquisition cost per new customer, including marketing, sales, and related overhead allocated per acquisition.

4. CAC payback period

The payback period tells you how many months it takes to recover CAC from gross profit:

How to interpret your LTV, LTV:CAC, and payback

The right targets depend on your stage, ACV, and growth strategy, but many SaaS teams use the following ranges as a starting point:

These benchmarks are broad guidelines. Early-stage, niche, or enterprise SaaS may sit outside these ranges for good reasons.

Worked example

Suppose your SaaS business has the following metrics:

• ARPA: $100 per month
• Gross margin: 80%
• Monthly churn: 3%
• CAC per customer: $600

Step 1: Monthly gross profit per customer:

$100 × 0.8 = $80

Step 2: Estimated customer lifetime in months:

1 ÷ 0.03 ≈ 33.3 months

Step 3: LTV (gross profit basis):

$80 × 33.3 ≈ $2,664

Step 4: LTV:CAC ratio:

$2,664 ÷ $600 ≈ 4.4:1

Step 5: CAC payback period:

$600 ÷ $80 = 7.5 months

Interpretation:

• LTV:CAC of about 4.4:1 is above the commonly cited 3:1 benchmark, suggesting efficient acquisition relative to value.
• A 7.5-month payback is fast, which is favorable for cash flow and may justify more aggressive growth investment.

Who should use this calculator and how often

This tool is designed for:

• Founders and CEOs assessing whether their go-to-market engine is sustainable and investor-ready.
• Growth and marketing leaders comparing channels, campaigns, and cohorts on LTV and payback.
• Finance and RevOps teams building budgets, setting CAC targets, and stress-testing growth plans.

Revisit your numbers monthly or quarterly using consistent time periods for ARPA, churn, and CAC so you can see trends rather than one-off snapshots.

Assumptions, limitations, and notes

• Constant churn assumption: The model assumes churn is stable over time. In reality, churn may be higher early in the customer lifecycle and lower for long-tenured customers.
• No explicit expansion revenue: The calculator does not separately model upgrades, seat expansion, or pricing increases. If expansion is material, your true LTV may be higher than this estimate.
• Average-based view: Results are based on averages (ARPA, churn, CAC). Individual cohorts, segments, or channels can perform very differently.
• Gross margin focus: LTV is calculated on a gross profit basis, which is more relevant for unit economics than pure revenue, but it still ignores fixed costs like product and G&A.
• Benchmarks are generalized: The benchmark ranges above come from widely used SaaS rules of thumb, but what is "good" depends heavily on ACV, sales cycle length, funding strategy, and market dynamics.

This tool is for educational and planning purposes only. It should support, not replace, detailed financial modeling and cohort analysis.

Why LTV and CAC Matter for SaaS

Software‑as‑a‑service businesses live or die by unit economics. You can have an exciting product, a growing user base, and positive buzz, but if the dollars you spend to acquire customers are not recovered through long‑term gross profit, growth becomes fragile. LTV (customer lifetime value) and CAC (customer acquisition cost) are the two core measures used to check that fragility. They are simple enough for early‑stage founders, but they are also the metrics investors, boards, and growth teams return to again and again because they condense the whole go‑to‑market machine into a few ratios.

LTV is the gross profit you expect to earn from a customer over the time they remain subscribed. CAC is the fully loaded cost required to win that customer in the first place. Put together, the LTV:CAC ratio answers a deceptively basic question: for every dollar we spend on acquisition, how many dollars of gross profit do we get back over the customer’s life?

If the ratio is too low, your business is effectively buying revenue at a loss. If the ratio is too high, you may be under‑investing in growth, leaving market share on the table. The right target depends on segment, growth stage, and sales motion, but the logic is universal. This calculator helps you compute your baseline unit economics and place them in context.

Key Inputs in Plain English

The calculator uses four inputs that are available to most SaaS operators:

• Average revenue per customer per month (ARPA/ARPU). This is subscription revenue actually collected, averaged across paying customers.
• Gross margin. The percentage of revenue remaining after direct service costs (hosting, support tied to delivery, third‑party usage fees). LTV should be based on gross profit, not top‑line revenue.
• Monthly churn rate. The share of customers who cancel in an average month. Churn is the main driver of lifetime length.
• CAC per customer. Your total sales and marketing spend in a period divided by new customers acquired in that period.

The Formulas Behind the Calculator

At a high level, lifetime value is the gross profit per month multiplied by the expected number of months a customer stays. If churn is stable, expected lifetime in months is approximately the inverse of churn. The simplest SaaS LTV model is:

Where ARPA is a dollar amount per month, gross margin is a decimal (for example 0.80 for 80%), and monthly churn is also a decimal (0.03 for 3%). If your churn is 3%, the expected lifetime is about 1 / 0.03 ≈ 33.3 months. A customer paying $100 per month at 80% gross margin yields roughly $80 of gross profit each month; over 33 months the LTV is about $2,666.

The LTV:CAC ratio is then:

Finally, many SaaS teams track the CAC payback period—how long it takes to earn back acquisition cost through monthly gross profit. That is:

Worked Example

Imagine a B2B SaaS product selling to small agencies. Your metrics look like this:

• ARPA: $120 per customer per month
• Gross margin: 78%
• Monthly churn: 2.5%
• CAC: $900 per customer

Step 1: compute gross profit per month: $120 × 0.78 = $93.60.

Step 2: compute expected lifetime: 1 / 0.025 = 40 months.

Step 3: LTV = $93.60 × 40 = $3,744.

Step 4: LTV:CAC = $3,744 / $900 = 4.16.

Step 5: Payback = $900 / $93.60 = 9.6 months.

In plain terms, each new customer costs about $900 to win, and over a typical lifetime you earn roughly $3,744 of gross profit. You recover CAC in about ten months, and every acquisition dollar returns a bit more than four dollars over the life of the customer. That is generally a healthy SaaS engine.

How to Interpret Your Results

Benchmarks are not laws, but they are useful guardrails. The LTV:CAC ratio is most informative when paired with payback period. A company can have a decent LTV:CAC ratio but still be cash‑strained if payback takes too long. Similarly, a very fast payback can justify a lower ratio if you are in a land‑grab market.

Payback benchmarks vary by motion:

• Self‑serve / PLG. 3–6 months is common because acquisition is largely marketing driven.
• Inside sales / SMB. 6–12 months is typical.
• Enterprise sales. 12–18 months is acceptable if retention is high and contracts expand.

Common Pitfalls When Using LTV:CAC

Even though the formulas are simple, it is easy to mislead yourself if the inputs are not consistent:

1. Using revenue instead of gross profit. LTV based on revenue exaggerates value for low‑margin products.
2. Mismatching time windows. CAC from one quarter and churn from another can distort the ratio if the business is changing quickly.
3. Ignoring expansion and contraction. For products with strong upsells, net retention may be a better driver than logo churn. This calculator focuses on a baseline, not a full cohort model.
4. Counting one‑time onboarding costs in margin but not in CAC. Decide where those costs live and be consistent.
5. Using early churn for mature cohorts. New cohorts often churn faster than older ones; choose a churn rate appropriate for the customers you are acquiring today.

Limitations and Assumptions

This calculator intentionally uses a compact model to stay useful for a broad audience. It assumes:

• Churn is steady over time and follows an exponential survival curve.
• Gross margin is stable across the customer lifetime.
• ARPA is an average that already reflects discounts and plan mix.
• CAC is fully loaded with the costs required to acquire the customers reflected in churn and ARPA.

Real businesses are messier. If your churn changes sharply with tenure, if customers expand materially, or if you have several distinct segments with different economics, a cohort‑based LTV model will be more accurate. Still, the baseline LTV:CAC ratio here is a good first check and a shared language for strategy discussions.