The LTV to CAC ratio compares what a customer is worth over their lifetime with what it cost to acquire them: lifetime value divided by customer acquisition cost.
LTV:CAC = Customer lifetime value ÷ Customer acquisition cost
On the sample data below, six months come to 2.40×.
Why it matters
It is a one-number check on whether growth creates or destroys value. Below 1, every new customer loses money even if they stay as long as expected.
Worked example
The table shows the columns this metric needs from six months of a made-up subscription brand. Add each column up over the six months, then put the totals into the formula:
| Month | Revenue (net of discounts) | Cost of goods sold | Marketing spend | New subscribers | Subscribers at start of month | Subscribers who cancelled | Subscribers at end of month | MRR at end of month |
|---|---|---|---|---|---|---|---|---|
| 2026-01 | ₹4,12,000 | ₹2,26,600 | ₹96,000 | 120 | 800 | 40 | 880 | ₹1,95,500 |
| 2026-02 | ₹4,38,500 | ₹2,36,800 | ₹1,02,000 | 135 | 880 | 44 | 971 | ₹2,12,900 |
| 2026-03 | ₹4,71,200 | ₹2,59,200 | ₹1,18,000 | 150 | 971 | 52 | 1,069 | ₹2,30,000 |
| 2026-04 | ₹4,55,800 | ₹2,55,200 | ₹99,000 | 128 | 1,069 | 61 | 1,136 | ₹2,41,400 |
| 2026-05 | ₹5,02,300 | ₹2,71,200 | ₹1,24,000 | 160 | 1,136 | 57 | 1,239 | ₹2,60,400 |
| 2026-06 | ₹5,48,900 | ₹2,90,900 | ₹1,31,000 | 175 | 1,239 | 66 | 1,348 | ₹2,80,600 |
| Total | ₹28,28,700 | ₹15,39,900 | ₹6,70,000 | 868 | 6,095 | 320 | 6,643 | ₹14,20,800 |
₹14,20,800 ÷ 6,643 × (₹28,28,700 − ₹15,39,900) ÷ ₹28,28,700 ÷ (320 ÷ 6,095) ÷ (₹6,70,000 ÷ 868) = 2.40×
Add up first, then divide. Averaging the six monthly figures gives a slightly different answer, because it counts a small month the same as a large one.
Month by month
| Month | LTV to CAC ratio |
|---|---|
| 2026-01 | 2.50× |
| 2026-02 | 2.67× |
| 2026-03 | 2.30× |
| 2026-04 | 2.12× |
| 2026-05 | 2.49× |
| 2026-06 | 2.45× |
LTV:CAC calculator
How to read it
A high ratio is not automatically good: it can mean you are under-investing in growth. The useful question is how fast the acquisition cost is paid back.
Common mistakes
- Both inputs are estimates, and LTV is very sensitive to churn. Report the ratio with the assumptions behind it.
- Use the same customer definition and period for both sides.
- A blended ratio can hide a channel whose customers churn fast. Calculate it per channel when you can.
Calculate LTV to CAC ratio in Excel, SQL or Python
The quickest version, for the sample sheet laid out as in the CSV (headers in row 1, months in rows 2 to 7):
=SUM(AF2:AF7) / SUM(Z2:Z7) * (SUM(B2:B7) - SUM(C2:C7)) / SUM(B2:B7) / (SUM(Y2:Y7) / SUM(X2:X7)) / (SUM(G2:G7) / SUM(W2:W7))- LTV to CAC ratio in Excel and Google Sheets — per-month formula and zero-safe version
- LTV to CAC ratio in SQL — query by month and for the period
- LTV to CAC ratio in Python (pandas) — pandas script with expected output
Related metrics
See all business metrics, or the statistics methods that sit behind them.
Questions people ask
- What is LTV to CAC ratio?
- The LTV to CAC ratio compares what a customer is worth over their lifetime with what it cost to acquire them: lifetime value divided by customer acquisition cost.
- How do you calculate LTV to CAC ratio?
- LTV:CAC = Customer lifetime value ÷ Customer acquisition cost. For example, with six months of sample data: ₹14,20,800 ÷ 6,643 × (₹28,28,700 − ₹15,39,900) ÷ ₹28,28,700 ÷ (320 ÷ 6,095) ÷ (₹6,70,000 ÷ 868) = 2.40×.
- What is the LTV:CAC formula in Excel?
- With the sample data laid out as in the downloadable CSV, =SUM(AF2:AF7) / SUM(Z2:Z7) * (SUM(B2:B7) - SUM(C2:C7)) / SUM(B2:B7) / (SUM(Y2:Y7) / SUM(X2:X7)) / (SUM(G2:G7) / SUM(W2:W7)) gives the figure for the whole period. For one month, use =AF2 / Z2 * (B2 - C2) / B2 / (Y2 / X2) / (G2 / W2) and fill it down.
- What is a good LTV to CAC ratio?
- There is no figure that is right for every business: it depends on your products, prices and channels. A high ratio is not automatically good: it can mean you are under-investing in growth. The useful question is how fast the acquisition cost is paid back.
Check how stable it is
A metric moves for ordinary reasons as well as real ones. These methods separate the two: the spread shows what a normal month looks like, the moving average smooths it, the z-score flags a month that is out of line and the trend line shows the direction.
Guides
About the data on this page
The figures come from a small made-up dataset, printed above in full so you can check every number by hand. Download it as monthly.csv. The results are computed from those rows when the page is built, and the Excel formulas, SQL and Python on these pages are run against the same rows before publishing, so the code and the answers agree.
To get these numbers from your own data without writing formulas, try AnalyzeIt: ask in plain words and it shows the working behind every figure.
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