Why Activation is the Most Important Pirate Metric

5 minute read

If you work at a growing SaaS company, you probably think you have a pretty good understanding of the startup “pirate” metrics. You can probably recite them—acquisition, activation, retention, referral, and revenue—and you might even remember where they come from (thank you Dave McClure).

But how deep is your understanding of these metrics? Do you know which ones you're overlooking—and what that's costing you?

Most small-but-growing SaaS companies focus first on acquiring users and getting them into the funnel. Then, they focus on retaining those users and turning them into loyal, long-term customers. But they're missing that second A in McClure's AARRR—activation

Helping brand new users start using the product successfully has huge downstream effects. In order to understand how best to optimize your customer journey, you need to understand exactly how much activation effects your growth.

We Built a Model to Compare the Pirate Metrics

The order of the original pirate metrics resemble a freemium revenue model—McClure put revenue after retention and referrals, like freemium apps do.

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But nowadays a free-to-paid revenue model is more popular. By this, we're referring to the model where companies offer a free trial and then convert users to paid plans. Often, subscription SaaS users are acquired through some form of free plan or free trial. Then, monetization happens when these users sign up for paid subscription plans and become paying customers.

Our model reflects this by placing revenue right after activation.

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The good news for pirates is that our rearranged model leaves the ‘AARRR’ acronym unharmed.

Since activation comes right after acquisition and right before revenue, it's an incredibly important metric to measure and optimize. Activation, or the moment when a customer achieves the product's promised value, reflects how efficiently you're spending money to acquire customers. A higher activation rate means better efficiency. Activation also directly determines revenue, because you need to be able to show free trial users the value of the product in order to convince them to pay for it.

With this in mind, we built a calculator to model the impact each metric has on MRR after 12 months. This is to demonstrate the sustained effects of improvement in each metric because for subscription businesses, percentage improvements have compounding impact over time. For example, a 10% increase in customer retention will be a much bigger improvement in customers retained when you have 10,000 customers than when you have 100.

We chose to calculate MRR rather than ARR. This is because for small businesses, it's useful to keep a pulse on the more frequent, incremental changes in business activity since small changes can make a big difference.

You can download this calculator for yourself and start exploring the pirate metrics here.

Here's a look at the calculator:

To model each metric’s impact on MRR, we'll first calculate what the MRR after 12 months would be with each pirate metric set at an industry benchmark:

  • Acquisition: 5,000 free trial users/month
  • Activation: 30% of users successfully use the product
  • Revenue: $100/customer/month
  • Retention: 97% monthly customer retention
  • Referral: 22% of users referring each month

Then, one by one, we'll improve each pirate metric by 25%, and calculate the affect that has on MRR after 12 months. Again, that’s: 

The percent difference in revenue between:
benchmark of metric vs.
benchmark of metric + 25% lift

Let's put this into context with some hypothetical numbers to model how these different metrics can impact your bottom line.

Some notes about our methodology

The purpose of this model is to allow you to conceptualize how each of these different metrics has a direct impact on your bottom line. 

That said, our model is a simplified representation of a hypothetical, small but growing SaaS company. In reality, these estimates won't exactly model any one company, because each company is unique and its growth is affected by many factors. 

In this model, we're imagining that we can control all of those other factors and isolate each pirate metric one by one, though in a real company these changes wouldn't happen in a vacuum and would likely influence one another.

It's also important to note that the relative importance of each metric will change depending on your company and your stage of growth. For example, if you already have a massive customer base, percentage increases in retention will have much bigger effects than the same incremental increase in a smaller customer base. Because we're using a percent difference as the equalizer, the relative importance of each metric is not absolute.

However, if your SaaS business roughly fits into the parameters that we describe for our benchmarks, these estimates will show you just how important each metric is to your company's growth so you can start optimizing your customer journey more effectively. 

We highly encourage you to put your own business metrics into the calculator as the benchmarks and calculate exactly how much improving each pirate metric will improve your bottom line. 

Let's take a closer look at each of these metrics so you can start putting our model to use for your company.

Acquisition Sets the Funnel Size in Terms of Users

In our model, acquisition measures the number of users entering your free trial. For our acquisition benchmark, let’s plug in 5,000 free trial sign-ups. 

5,000 is a made-up number, but for your calculations, you can either use data on your monthly free trail sign-ups or estimate sign-ups if data isn't available. According to a study of SaaS companies by Alex Turnbull, CEO and founder of Groove, about 8.4% of traffic converts to a trial on average.

Using our estimate of 5,000 free trial sign ups, we'll calculate how a 25% lift on our acquisition benchmark impacts 12-month MRR after one year:

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As you can see, the 25% lift in acquisition (top right cell) resulted in a 25% lift in MRR (bottom right cell). It makes sense that these lifts are equal because acquisition determines the size of your funnel.

Therefore, if you 10x acquisition, you’ll 10x your MRR. And that’s pretty uninteresting. Don’t worry though—other metrics have a higher impact on MRR.

Activation is the Upstream Bottleneck

Activation takes place when users first achieve the value you promised. It’s calculated as a percent of activated users out of total acquired users.

As a benchmark for activation rate, we’ve chosen 30% based on the sad reality of mobile app onboarding and our experience working with companies on their onboarding

You can use this benchmark for your own calculations, or pull data on your monthly percentage of activated users. Activation can have a different meaning for each product depending on that product's aha moment. Make sure you define exactly what determines an activated user, so you understand the data that you're looking at.

Here’s how activation impacts MRR:

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A 25% increase in activation yielded a 34.3% lift on MRR after 12 months. It turns out the metric you've been overlooking can give you outsized returns. Tweet

Surprised? I was. But in our free-to-paid model, activation directly determines how much revenue is coming in the door.

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That makes activation an important upstream metric that impacts not only revenue from new users but also recurring revenue from existing users.

One more note—remember that in our simplified model, we're not calculating the effects that increases in one metric might have on others. In reality, increases in activation would likely result in increases in retention and referrals as well. This would make the increase in MRR even greater.

Revenue Sets the Funnel Size in Terms of Dollars

In our model, revenue represents the ACV, or average contract value, that a user pays per month. To keep things simple we set revenue at $100, to model a mid-sized subscription contract for an SMB SaaS company. In your own calculations, you can directly input your average contract value for the revenue benchmark.

By doing this we can calculate the impact revenue has on MRR:

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As you can see here, a 25% lift in revenue corresponds to a 25% lift in MRR. 

In our funnel, revenue serves a similar function as acquisition. Both metrics are fixed numbers, not percentages like the other pirate metrics. They have similar one-to-one impacts on the bottom line. Acquisition sets the size of the funnel in terms of numbers of users, and revenue sets the funnel size in terms of dollars.

Retention is the Downstream Bottleneck

Retention measures the number of users continuing to pay for your product month over month. Retention is typically a much higher percentage than activation because it’s easier to get users to maintain a habit than to start one. 

We're using a 97% benchmark on monthly retention for SMB companies observed by Redpoint VC Tomasz Tunguz and affirmed by Point Nine Capital VC Clement Vouillon. If you have monthly customer retention data for your own company, you can input this metric as the benchmark in the calculator.Let’s calculate the impact a 25% lift would have on MRR:

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It may seem odd that we’re experimenting with a 121.3% retention rate, but it’s actually possible to have a retention rate greater than 100% or net negative churn. That’s because most products encourage users to upgrade and spend more, so their contract size grows over time.

The effect of retention on MRR is most similar to that of activation—they're both percentage-based bottlenecks. They can grow or shrink the size of the funnel.

However while retention yielded a 31.0% increase in MRR, activation yielded a 34.3% increase. Though that's splitting hairs in our hypothetical model, it goes to show that the often overlooked metric of activation can have as much or more of an impact on your bottom line as metrics like retention, which most SaaS companies focus on more. 

In our model, payment occurs at activation. If payment was occurring at the retention cohort, activation would have less of an impact on revenue. If your business uses a free-to-paid model, you can try this out with your own data to see the relative differences in activation improvement and retention improvement.

Referrals Are Icing on the Cake

Referrals measure the percentage of current users who successfully bring new users into your funnel. That means we measure referral as a percentage of your entire existing user base—not just your new users.

We did some math based on referral benchmarks, and found 22% to be a good referral rate benchmark for successful SaaS companies. You can also substitute your own referral rate for the benchmark if you have this data.

So let’s calculate the impact of a 25% lift on our referral benchmark:

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As you can see, a 25% lift off of our referral benchmark resulted in a 7.4% MRR increase. This is a bit underwhelming.

For growth people that believe that viral loops are the holy grail, this might come as a shock. I was surprised the first time I saw the results of this calculation. So I ran it again with a 100% increase for the same referral benchmark. Doubling the number of referrals resulted in a similarly underwhelming lift of 38.2% and has changed my perception of the value of referrals.

When It Comes to Growing MRR, Activation Reigns Supreme

Here’s a table to compare the impact each metric has on MRR with a 25% lift—the bottom right cell in the tables above:

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 In our model, a 25% lift in activation increased MRR by:

  • 9.3% more than the same percentage increase in acquisition
  • 3.3% more than the same percentage increase in retention

These values are dependent on the benchmarks we chose in our hypothetical, simplified model. But when comparing each pirate metric's impact on MRR, it's clear that activation has huge downstream effects on your bottom line. If you're still overlooking this metric, you're missing out on revenue and opportunities for growth.

These findings are hugely important to the way experts in growth should view their user journeys. Each pirate metric is not equal in their impact—and they should not be treated as such.

For the most effective growth, product teams should focus on optimizing activation and begin to watch the huge improvements in business that start to unfold.

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