Swipe Files - 📂 Your SaaS metrics are lying to you

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When you're in scale-up mode and you have KPIs to hit... the pressure is on to deliver demos and signups. And it's a lot to handle: multi-channel strategy, remarketing, landing pages, email sequences, revenue ops, conversion rate optimization.

42/Agency, founded by my friend Kamil Rextin, has worked with companies like Sprout Social, Klue, Qwilr, Uptick, Onfleet, and many more to help them with all things demand generation. They're always my top agency recommendation for specializing in SaaS demand gen. Go read some spicy takes on freemium, "inbound marketing", and category creation and then schedule a free consultation.

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In my time as the Head of Growth at Baremetrics I probably reviewed over 500 accounts personally.

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

And after all that time, I came to realize that there are many ways your SaaS metrics are actually lying to you...

Let's explore a few deceiving realities:

1. Higher growth = higher churn.

It's not uncommon to see higher churn when you're growing more since churn is concentrated to the beginning of the lifecycle, usually within the first 3 months of subscribing.

Just because you're growing doesn't mean churn is low.

Unfortunately, higher growth means you're likely acquiring a lot of new customers, and not all of them will be a good fit at the end of the day.

This freaks people out when they start growing quickly. They turn off acquisition channels and try to figure out how to stop churn.

But really it's all par for the course and totally normal.

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

Reactivation rate is the rate of cancelled customers returning and signing up as paying customers again.

The thing is, some customers are just finicky. They sign up, use your app for a while, cancel, and come back, and maybe even repeat that process a few times.

So your reactivation rate effectively acts as a discount to your churn rate.

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

3. LTV isn't real.

Lifetime value is a concept for measuring the average amount you can expect each customer to spend with you.

This works great 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, which recurring charges and a product line with a wide range of price points... LTV is useless.

Today, SaaS LTV is calculated as ARPU / User Churn.

This makes too many assumptions:

• Averages lie, especially with SaaS having a wide range of price points that can skew ARPU much higher or lower than the most common price point customers choose.
• User churn is simply a proxy to estimate how long a customer is likely to stick around, but it's a very rough estimate that's capped at a fixed time frame.

4. Payback period should be based on ARPC.

VCs love to talk about the magic acquisition formula of CAC:LTV. It's "best practice" to have a CAC:LTV ratio of 3:1 or greater.

What is trying to get at is payback period.

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

Since we just established that LTV is a sham, we can't use CAC:LTV to calculate a payback period.

Instead, I propose payback period to be based on ARPC (average revenue per customer).

At the end of the day, all you need to know is (1) how quickly you can recoup CAC and (2) how much cash you need in order 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 at the end of the day.

6. Attribution: First touch vs Last touch vs Multi-touch

Most analytics tools, especially Google Analytics, orient around a last-touch attribution model.

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

Similarly, "First touch" means that the very first customer touchpoint that lead to a conversion gets all the credit as a marketing channel.

Both are flawed, which is why "Multi-touch" 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.

—Corey

p.s. do you want to be able to compare your marketing metrics with other SaaS companies? Fill out the State of SaaS Marketing Survey →​

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