If my LTV to CAC ratio slips, I can see the problem before revenue tells the story in plain English. Baremetrics helps because it puts the core numbers in one place, but I still need to read them with care.
A clean dashboard can still hide a messy formula, and a polished ratio can hide weak economics. I measure it by checking the right inputs, matching the same time window, and keeping the result beside churn and MRR. Then I decide whether growth is buying real value or just burning cash.
Table of contents
- The logic behind the LTV to CAC ratio
- Where Baremetrics gets the numbers
- My step-by-step process in Baremetrics
- How I read the LTV to CAC ratio
- Common mistakes that warp the number
- Conclusion
- FAQ
The logic behind the LTV to CAC ratio
I start with the simplest version of the formula, LTV divided by CAC. For a clean formula reference, I keep Wall Street Prep’s LTV/CAC guide nearby. It matches the math I use in Baremetrics, where LTV is based on ARPU divided by churn rate, and CAC is total acquisition costs divided by new customers.
If LTV is $2,000 and CAC is $500, the ratio is 4:1. That means I get four dollars of lifetime value for every dollar I spend to acquire one customer.
I don’t treat that number like a medal. I treat it like a pressure gauge, because the reading is only useful when the inputs are clean.
A nice-looking ratio can hide bad inputs. If churn is off, the whole number tilts with it.
Where Baremetrics gets the numbers
Baremetrics gives me the revenue-side inputs, so I start with ARPU and churn. I keep essential SaaS metrics for tracking churn close when I check those numbers, because churn drives the entire result.
Here is the simplest way I keep the pieces straight:
| Part | What I use | My check |
|---|---|---|
| LTV | ARPU and churn rate | Same segment and date range |
| CAC | Total acquisition costs and new customers | Every cost I count is included every time |
| Ratio | LTV divided by CAC | I compare like with like |
The ratio falls apart fast if I mix a monthly LTV with a quarterly CAC. It also gets muddy when I compare different customer groups. Self-serve and enterprise should not share the same number unless I want a blurry answer.
I also pay attention to what I call acquisition cost. If I count paid media, then I count it every time. If I include sales labor, I keep that rule consistent too. The math is simple, but consistency does the heavy lifting.
My step-by-step process in Baremetrics
I keep the process plain so I can repeat it month after month.
- I open the main revenue view and confirm the customer segment. If I am looking at SMB accounts, I do not mix in enterprise deals.
- I check ARPU and churn first. Baremetrics uses those numbers to build LTV, so any spike or dip deserves a second look.
- I gather acquisition costs from the same period. Paid search, agency fees, and sales labor only belong in CAC if I always count them that way.
- I divide LTV by CAC. That gives me the ratio I can compare across months, plans, or cohorts.
- I pin the result to a dashboard view. I like to keep it inside building a custom SaaS metrics dashboard so I can watch it next to MRR and churn.
That last step matters more than it sounds. A ratio buried in a spreadsheet gets ignored. A ratio next to the rest of the business turns into a real signal.
How I read the LTV to CAC ratio
A good LTV to CAC ratio in SaaS is often around 3:1 or higher. I use Burkland’s 3:1 benchmark note as a loose floor, not a law. Market, margins, and sales motion all shape what makes sense.
| Ratio | My read |
|---|---|
| Below 1:1 | Acquisition is costing too much |
| Around 3:1 | Healthy for many SaaS teams |
| 5:1 or higher | Strong, but I check for underinvestment |
I do not stop at the ratio itself. I also look at churn, payback, and how much spend is fueling growth. A high ratio can still mask a slow pipeline. A low ratio can be fine for a company pushing hard into a new market.
The ratio is best when it helps me answer one question: is the business buying customers at a price that makes sense? If the answer feels shaky, I look at the inputs before I blame the formula.
Common mistakes that warp the number
I see the same errors over and over when this metric looks wrong.
- I mix time windows. A monthly CAC against a lifetime value built from a different period gives me a false read.
- I compare different customer groups. A self-serve cohort and an enterprise cohort should not share one ratio.
- I let churn drift. If churn changes and I do not notice, LTV changes fast too.
- I forget hidden acquisition costs. Agency fees, sales labor, and ad spend can all belong in CAC.
- I trust one month too much. Small samples can make the ratio swing hard.
When I want to sanity-check the inputs, I cross-reference essential SaaS metrics for tracking churn before I trust the result. That keeps me from building a neat answer on top of a loose foundation.
Conclusion
Baremetrics makes the ratio easy to measure, but the real work is in the inputs. I want one LTV formula, one CAC definition, and one time window.
When those pieces stay aligned, the number tells me whether growth is buying value or just buying noise. That is the read I trust.
FAQ
What formula does Baremetrics use for LTV?
I use ARPU divided by churn rate. If I change the churn definition, I change the result, so I keep it consistent.
What counts as CAC in my Baremetrics ratio?
I count total acquisition costs divided by new customers. That usually includes every acquisition cost I choose to track, not only ad spend.
What is a good LTV to CAC ratio for SaaS?
Around 3:1 is a common benchmark. Higher can be fine, but I still check whether churn is rising or growth spend is too low.
Why does my Baremetrics ratio look different from a spreadsheet?
The formula is usually not the problem. The time range, segmentation, or cost inputs are often what changes the answer.
