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Customer Lifetime Value Calculator.

A customer lifetime value calculator measures the total revenue you expect to earn from a single customer over the course of your relationship. Enter your average monthly revenue per customer, monthly churn rate, and optional gross margin to compute LTV using three models: simple, retention-based, and predictive. The calculator shows how each model produces a different figure, compares your result against published SaaS benchmarks segmented by annual contract value, and computes your LTV to CAC ratio if you provide your customer acquisition cost.

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LTV
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Simple LTV Model

LTV = ARPA (monthly) x Average Customer Lifespan (months)

Average Revenue Per Account per month

Average number of months a customer stays
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How to Use

Get Started in 3 Steps

Step 01

Enter Customer Revenue and Churn Inputs

Input your average monthly revenue per customer and monthly churn rate. The calculator uses these two values to compute retention-based LTV. Add gross margin and a discount rate if you want the predictive model output.

Step 02

Select Your LTV Model

Choose between simple, retention-based, and predictive models. Each model uses different inputs and produces a different LTV figure. The calculator shows all three side by side so you can compare the impact of each assumption.

Step 03

Review LTV, Benchmarks, and LTV:CAC Ratio

See your LTV broken down by model, a benchmark comparison by ACV range, and the LTV to CAC ratio if you enter your customer acquisition cost. The ratio tells you whether your unit economics support your current growth rate.

How It Works

Under the Hood

This calculator implements three progressively more sophisticated LTV models. The simple model multiplies average monthly revenue per customer by average customer lifespan in months, where lifespan is derived directly from churn rate as the inverse of monthly churn. This model treats all revenue as equivalent regardless of when it is collected and ignores the cost structure of the business.

The retention-based model uses the formula LTV = (average monthly revenue per customer) divided by (monthly churn rate). This is mathematically equivalent to the simple model when lifespan is defined as the inverse of churn, but it makes the relationship between churn and LTV explicit. Reducing monthly churn from three percent to two percent raises the LTV multiplier from 33x to 50x monthly revenue, a fifty percent increase from a single percentage point improvement.

The predictive model extends the retention-based formula to include gross margin and a discount rate. Gross margin is applied as a multiplier so the result reflects profit contribution rather than gross revenue. The discount rate converts future cash flows to present value using monthly discounting, recognizing that a dollar received in month thirty-six is worth less than a dollar received today. This model is the most conservative because it reduces LTV for revenue that arrives far in the future.

Benchmark comparisons use published data from OpenView and KeyBanc segmented by annual contract value. The LTV to CAC ratio is computed by dividing the selected LTV model output by your blended CAC input. A ratio of three or above is typically the threshold for healthy unit economics, while ratios below two suggest the business is spending too much relative to the value it retains from each customer.

FAQ

Frequently Asked Questions

What is customer lifetime value and how is it calculated?
Customer lifetime value is the total revenue a business expects to earn from a customer over the entire duration of their relationship. The simplest model multiplies average revenue per customer by average customer lifespan. A retention-based model divides average monthly revenue per customer by the monthly churn rate, which captures how churn compresses the time a customer stays active. A predictive model layers in gross margin and a discount rate to express LTV in present-value terms, accounting for the fact that revenue collected years from now is worth less than revenue collected today. Each model increases in accuracy and complexity. Most SaaS companies start with the retention-based formula because it only requires two inputs, churn rate and monthly revenue, and produces a figure that closely matches historical cohort data.
What is a good LTV for a SaaS company?
The most widely used benchmark is the LTV to CAC ratio rather than LTV in isolation. A ratio of three to one or higher is generally considered healthy, meaning each customer generates at least three dollars of lifetime value for every dollar spent acquiring them. Top-quartile SaaS companies achieve ratios above five to one. In absolute terms, LTV benchmarks vary significantly by market segment. SMB-focused products with high churn and low ACV often see LTV between two thousand and eight thousand dollars. Mid-market products typically range from fifteen thousand to fifty thousand dollars. Enterprise contracts can push LTV above one hundred thousand dollars because contract values are larger and churn rates are lower. Compare your LTV against peers at a similar ACV and churn profile for the most meaningful insight.
What is the difference between simple and predictive LTV models?
Simple LTV multiplies average revenue per customer by average customer lifespan in months. It is easy to calculate but treats all customers as identical and ignores the time value of money. Retention-based LTV divides monthly revenue per customer by the monthly churn rate, which is mathematically equivalent to simple LTV when lifespan is derived from churn but makes the churn dependency explicit. Predictive LTV goes further by applying a gross margin multiplier to express only the profit component of lifetime value, and then discounting future cash flows to present value using a monthly discount rate. This makes predictive LTV the most conservative and theoretically correct figure, but it requires additional inputs and is more sensitive to assumption changes. For early-stage companies with limited cohort history, the retention-based model usually provides the best balance of accuracy and practicality.
How does churn rate affect customer lifetime value?
Churn rate is the single most powerful lever in the LTV formula because it determines average customer lifespan. In the retention-based model, LTV equals monthly revenue divided by monthly churn rate. A company with two percent monthly churn has an average customer lifespan of fifty months, while a company with five percent monthly churn has an average lifespan of only twenty months. Halving your churn rate more than doubles LTV because both lifespan and cumulative revenue increase together. At very low churn rates, small improvements have outsized impact: reducing monthly churn from one percent to half a percent doubles expected lifespan from one hundred to two hundred months. This compounding effect explains why enterprise SaaS products with sub-one-percent monthly churn routinely show LTV figures ten to twenty times higher than high-velocity SMB products with similar contract values.
How can I increase my customer lifetime value?
The four highest-impact strategies are reducing churn, expanding revenue per account, improving onboarding, and implementing proactive customer success programs. Reducing churn directly extends the lifespan over which you collect revenue. Even a one-percentage-point reduction in monthly churn can increase LTV by thirty to fifty percent depending on your starting churn rate. Revenue expansion through upsells, cross-sells, and seat additions increases average revenue per customer without requiring new acquisition spend, boosting LTV on existing accounts. Structured onboarding that drives customers to their first value milestone within the first thirty days correlates strongly with twelve-month retention. Finally, proactive customer success outreach to accounts showing early disengagement signals can prevent churn before it shows up in the data. Combining these levers compounds their impact because higher retention and higher revenue per account multiply each other in the LTV formula.
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