I reviewed over 1,000 SaaS company analytics in my time as the Head of Growth at @Baremetrics.

I saw every size company, every growth rate, every churn rate, every ARPU...

And after all that, I came to a realization:

Your SaaS metrics are lying to you.

Here's how 👇

1/Higher growth = higher churn

Higher growth means a lot of new customers, and not all of them will be a good fit.

Which means churn.

This freaks founders out. They turn off acquisition channels and try to figure out how to stop it.

The reality is that its par for the course.

2/ You can have high churn if you have high reactivation rates

Some customers are just finicky.

They sign up, use your app for a while, cancel, and come back later.

If your monthly churn is 5% and your monthly reactivation rate is 1%, your "true" churn rate is 4%.

3/ LTV isn't real

It works if you're modeling off of one-time sales of a product line with a fairly standard set of prices.

But if you're modeling off of SaaS, with recurring charges and a wide range of price points... LTV is useless.

A SaaS LTV is calculated as ARPU/Churn.

4/ Payback period should be based on ARPC

VCs love to talk about how CAC:LTV.

It's "best practice" to have a ratio of 3:1 or greater.

What is trying to get at is payback period.

Payback period is how long it takes to recoup the cost of acquiring a customer.

We just established that LTV is a sham so we can't use it to calculate payback period.

Instead, I propose for it to be based on ARPC.

All you need to know is:

1) how quickly can you recoup CAC
2) how much cash you need to sustain acquisition costs at the current payback period

5/ Signups vs Trialing users vs Activated users

Most SaaS companies measure signups as their north star metric.

"Signups," meaning the total number of new users coming through the door.

But what if those signups aren't actually qualified users for your product?

What if those signups don't actually start using the product after they sign up?

What if those signups never start a trial to become a paying user?

This is why when you're projecting growth, you have to account for which metric actually leads to paying customers.

6/ Attribution: First touch vs Last vs Multi

Most analytics tools orient around a last-touch model.

"Last touch" means that the last customer touchpoint before a conversion gets all the credit.

"First touch" means the 1st customer touchpoint.

Both are flawed.

A "Multi-touch" approach is a much more accurate indicator of where and how to invest marketing dollars.

However, last touch is especially heinous since impulse purchases of SaaS are a very rare occurrence.

That's a wrap!

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