Customer Lifetime Value & LTV:CAC Ratio Calculator
### Corporate Finance & Growth Marketing: Unit Economics & The LTV:CAC Ratio Customer Lifetime Value defines the total gross profit an enterprise captures from a single customer.
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📐 Formula
💡 Practical Example
For example, evaluating a SaaS company with \), \(75.0\%\text{ gross margin}\), \(15.0\%\text{ annual churn}\), \(\$350.00\text{ blended CAC}\), and \(10.0\%\text{ discount rate}\): Annual gross revenue is \(\$1,440.00\), with \(\$1,080.00\) in annual gross profit. Average customer retention is \}}\). The Simple LTV is \ (\(\mathbf{\$4,320.00\text{ Discounted DCF LTV}}\)). The \, achieving full CAC payback in 3.89 Months with +$6,850.00 in net lifetime profit per customer.
📖 About Customer Lifetime Value & LTV:CAC Ratio Calculator
Corporate Finance & Growth Marketing: Unit Economics & The LTV:CAC Ratio
Customer Lifetime Value defines the total gross profit an enterprise captures from a single customer relationship over its entire duration:
- Gross Margin Correction: Revenue-only LTV artificially inflates customer value; multiplying by gross margin isolate the true cash flow available to fund overhead, acquisition, and R&D.
- The 3:1 LTV-to-CAC Golden Rule:
- < 1.0x (Value Destruction): Company loses money on every acquired account.
- 1.0x to 3.0x (Sub-optimal): Weak capital efficiency; vulnerable to customer churn and cash flow crunches.
- 3.0x to 5.0x (Optimal Sweet Spot): The benchmark for venture-backed and high-performing private equity businesses.
- > 5.0x (Under-Invested): The business is leaving growth on the table and should accelerate marketing spend.
- CAC Payback Velocity: Measuring how many months of gross profit it takes to recoup initial marketing spend; top-tier SaaS companies target payback in 12 months or less.
How to Use This Calculator
Enter your Average Revenue per User (Monthly ARPU / Order Value ) (e.g. 120 (120/month subscription or average basket)), Purchase / Billing Frequency (Times / Year) (e.g. 12 (Monthly subscription = 12 | E-commerce: 2 to 6)), Gross Profit Margin (%) (e.g. 75 (SaaS: 70%–85% | E-commerce: 40%–60%)), Annual Customer Churn Rate (%) (e.g. 15 (15% annual churn = 6.67 year average lifespan)), Customer Acquisition Cost (Blended CAC ) (e.g. 350 (Sales + Marketing spend per new customer)), and Annual Cost of Capital / Discount Rate for DCF LTV (%) (e.g. 10 (Standard 10% discount rate for Net Present Value)). Results update instantly as you type — adjust any value to compare scenarios.
The Formula
SaaS \& E-Commerce Unit Economics \& Lifetime Value equations:
Annual Gross Revenue = ARPU × Purchase Frequency
Customer Retention Lifespan (Years): T = (1) / (Annual Churn Rate)
Simple Gross Margin LTV = (Annual Gross Revenue × Gross Margin) / (Annual Churn Rate)
Discounted Cash Flow (DCF) LTV = (Annual Gross Revenue × Gross Margin) / (Annual Churn Rate + Discount Rate)
LTV-to-CAC Ratio = (Gross Margin LTV) / (Customer Acquisition Cost (CAC))
CAC Payback Period (Months) = (CAC) / (Monthly Gross Profit per Customer)
Worked Example
For example, evaluating a SaaS company with , 75.0\% gross margin, 15.0\% annual churn, \350.00 blended CAC, and 10.0\% discount rate: Annual gross revenue is \1,440.00, with \1,080.00 in annual gross profit. Average customer retention is . The Simple LTV is \ (\4,320.00 Discounted DCF LTV). The \, achieving full CAC payback in 3.89 Months with +6,850.00 in net lifetime profit per customer.
Understanding Your Result
Marketing metrics are most useful as trends over time rather than isolated snapshots. Benchmark your result against your own historical performance first, then against industry averages. Attribution models (last-click vs. multi-touch) can produce dramatically different channel ROI figures — ensure consistent attribution methodology before making channel budget decisions. Statistical significance requires sufficient sample size: most A/B test decisions need a minimum of 1,000 conversions per variant for reliable results.
💡 Methodological Standards & Calculation Accuracy
- All calculations are performed client-side in your browser using verified, standards-compliant mathematical algorithms.
- Results are provided for educational and informational analysis; verify critical applications with certified domain specialists.
- Ensure input values are entered in consistent units matching the selector options to guarantee accurate outputs.
- Periodic recalibration is recommended whenever baseline assumptions, operating parameters, or external conditions change.
Results are for informational and educational purposes only. Always verify critical decisions with a qualified professional.