Curious to know what the user activation benchmarks are for SaaS? Activation – the elusive pirate metric that’s notoriously hard to measure – also has the biggest impact on SaaS revenue. A 25% increase in activation results in a 34% boost in MRR over 12 months.
Wondering why, how you stack against other SaaS businesses, and how to boost your activation rate?
Spoiler warning: the answers will surprise you.
In the following post, I’m going to discuss how to define activation for your SaaS, why it matters so much, and how to improve it.
Finally, I’ll comment on an industry benchmark study on activation rates in B2B and B2C SaaS conducted by my colleague – Aazar Ali Shad.
Let’s dive straight in!
- What is user activation?
- Why is activation important in SaaS?
- What is the impact of activation on revenue in SaaS?
- What is user activation rate? How to calculate user activation rate [formula]
- Challenges with calculating user activation rate
- What are user activation rate benchmarks in B2B vs B2C SaaS?
- How to improve your user activation rate in SaaS
- Final thoughts
- Activation is a nebulous metric and every business has to define it for itself. It is loosely defined as the point when your user actually gets the benefits of your product.
- Activation has the largest impact on MRR from all the pirate metrics. A 25% increase in activation translates into a 34% increase in MRR over 12 months.
- You need to operationalize activation for your business by looking at key activation events – the actions a new user must do to get value. It will vary from product to product, from one persona to another, and even from one use case to another use case.
- That’s why coming up with an ‘industry standard’ is almost always impossible, as you will be comparing apples to oranges (unless you’re comparing to the activation benchmark for your direct competitors).
- Comparing your own activation rates over time, however, can be a great way to see which user segment needs more help through onboarding.
- Creating and A/B testing ‘corrective’ experiences is the best way to improve your activation rate over time.
What is user activation?
User activation is the moment when your user performs the key events in your product that allow them to experience the value of your product for their use case. Unlike the ‘AHA! moment’ – which is the moment your user realizes the value of your product, but not necessarily obtains the benefits of it yet (e.g. your potential user can have an ‘AHA! moment when reading your blog or seeing a screenshot of your dashboard on your website) – user activation is tied to activation events and key results.
Simply put – your user needs to actually do the things that give him the results they want to get from your product.
For example: a small business owner, let’s call her Jenna, who promotes her business on social media on their own notices that she is spending more and more time on that. Frustrated, she googles ‘How to save time posting on social media’ and stumbles upon a case study of a similar business owner, who reduced his time on social media marketing by 2 hours per week, saving a whole working day per month, by using a social media scheduling tool.
Jenna experiences and ‘AHA! Moment’ now.
She signs up for the free trial, links her social media accounts, and schedules post for the whole period of 2 weeks within just one hour. She can then relax and forget about social media for the whole fortnight, immediately saving 4 hours of her time. She gets the benefits of the tool and becomes an ‘activated user’.
But the activation for another user, e.g. an agency user who is well-versed in social media marketing – would be different.
You can probably already see what’s the problem here – activation will be operationalized differently not only in every business and product, but also within the same product for different use cases and personas!
I will soon tell you a personal anecdote about how we were musing what activation rate actually means for us not so long ago with our CEO…which is another case in point that activation is so elusive and hard to measure!
But first, let’s answer another fundamental question: if it’s so hard to measure then why bother at all?
Why is activation important in SaaS?
Well, let that thought sink in: if activation is the point where your user performs the key actions that are prerequisites for obtaining the value of your product, without activation, there won’t be anything next.
No value, no money. As simple as that. To make my case more compelling, look at the numbers below.
From all the ‘Pirate Metrics’, activation has the biggest impact on MRR in a 12 month period:
What is the impact of activation on revenue in SaaS?
From the table above you can quickly infer that if a 25% increase in activation contributes to a 34% increase in MRR in 12 months, activation affects MRR by the factor of x 1.34 – compared to x1 for acquisition and only x 0.3 for referrals.
How to define and measure user activation?
Now, this is the tricky part.
There’s no ‘universal’ measure of activation as – as I mentioned earlier – the activation events will differ from business to business, product to product, persona to persona, and use case to use case.
So you need to define:
What in-app events need to happen for a specific persona to get the benefits of your product.
Then, you count how many people have performed these in-app events in a specific period of time.
Let me give you an example:
If you have an email marketing tool, you may get several types of users who come to your tool with different jobs to be done. Let’s take two of them:
1) A blogger who is just starting out and wants to use your tool to collect subscribers on their blog;
2) An e-commerce store owner who is switching from another tool for cost-effectiveness and is bringing in 10,000 subscribers, so they can send newsletters to them.
For the first persona: the key activation events will be:
- Creating their first signup form
- Embedding it on their blog
- Collecting their first subscribers
For the second persona, they will be:
- Uploading their email list
- Creating their first newsletter
- Sending their first newsletter to their email list
That’s why Convertkit, an email marketing tool for creatives, actually asks its users if they have used another tool before:
But sometimes, the situation may not be that clear-cut… let me give you our example in Userpilot.
Userpilot has a tricky situation when it comes to its activation rates – much trickier than an email marketing tool. One reason is that it’s a digital adoption platform consisting of three complementary products (user analytics, user engagement experience builder, and user sentiment – in-app microsurveys) and catering to very different personas.
Traditionally, we assumed that an activated user is one that has performed the following activation events:
- Creating at least one experience flow
…but when we actually sat down to look at the real data of the new users from our free trial (in an attempt to check if the users from self-serve trial signup or the demo had a higher activation rate) the real data threw us off:
– there was a whole lot of users who installed the js code and had several web sessions looking at the analytics, but didn’t build any experiences…
– then there were users who built several experiences, and had a number of web sessions, but have not installed the js code (meaning they couldn’t access their user analytics or deploy the experiences to their app). 🤷♀
Both groups could actually get value from the product at this point…
This illustrates how careful you need to be in deciding what actually counts as activation for you.
Sorry for the bummer – but I simply can’t give you a straightforward answer on how to calculate activation in your business.
What is user activation rate? How to calculate user activation rate [formula]
And this is actually the fairly simple part.
User activation rate is the number of users that activated (reached the key activation points and performed the key activation events we’ve discussed above) divided by the total number of new users who signed up in a given period of time, divided by 100%.
In other words, how many out of each 100 new users activated in a given time point.
But easy as it sounds, there’s a catch…
Challenges with calculating user activation rate
Now, while calculating the rate you still need to remember to split the calculation by all the different personas and jobs to be done.
As you remember from the email marketing tool example above: the activation point will differ for each persona.
So before calculating your rate – you need to make sure you’ve separated your new users into cohorts by the different personas, and calculate the rates separately for each cohort.
This can actually be helpful in designing better in-app experiences aimed at improving activation – the more granular your view, the more accurately you can address the problem.
E.g. if you see that a certain group of users is lagging behind in terms of activation rate, you can address that group first by e.g. working on improving their onboarding experience.
What are user activation rate benchmarks in B2B vs B2C SaaS?
Considering all we’ve said above – can we even talk about any industry benchmark in relation to user activation?
A good friend of mine and a former colleague in Userpilot, Aazar Shad, really wanted to conduct a survey on user activation benchmarks in SaaS.
“Bro! You can’t create a benchmark for something that is defined differently in every business!” – I told him.
‘It’s like comparing apples to oranges.’
He went on to collect the data nevertheless, and while there’s no statistical value in them (I like to quantify things, what can I say…) – the responses people gave are still interesting in that you can see how difficult measuring activation is for SaaS.
Aazar collected 22 responses so far, asking the respondents i.a. whether they were B2B or B2C, what their lead-gen model was (freemium, free trial, demo etc.), what was their activation rate and how they measured it.
Here are a few interesting preliminary insights:
First of all – the wide distribution of activation rates suggests there’s actually no leitmotif here (59% of the respondents were B2C).
Some didn’t really know:
In conclusion: too many variables, not enough data to draw conclusions.
Which I think will be the case for any activation benchmark study – so be careful about click-baity headlines from SaaS gurus who claim they know.
And be careful about comparing your apples to other people’s oranges.
If something can’t be uniformly defined, how can it be effectively compared?
I know I know. Now you know my headline was super click-baity. But I feel I had to do it for the greater good 😉
How to improve your user activation rate in SaaS
Having said that – should you throw your hands up in the air in despair, and resign to nihilistic thought that ‘what doesn’t get measured, doesn’t get improved?’
It may sound like a motivational-guru mantra but… you just shouldn’t compare yourself to others. You should compare yourself (now) to yourself (yesterday.)
While you can’t effectively say how you compare to an ‘industry standard’ (because there’s no standard) you can still measure and improve your own benchmark!
Now that you know (or not…) how to define your activation, you can measure and improve it over time with bespoke in-app experiences, and set your own goals (And hey, Userpilot is exactly for that! Get on a call with us to see how to start!)
For instance, here’s what goal tracking for one of the activation events of a social media scheduling app:
As you can see, you can set a goal for the metric and track your progress towards the goal, while manipulating it with various in-app experiences and experiments.
Now, let’s talk a bit more what you can do to manipulate yours 😉
Know your user persona and their JTBD well
Well, as I mentioned earlier – in order to improve your activation rate, you first need to define activation well.
And to do that – you need to actually understand your persona and the different jobs they have that need to be done in your tool.
While user journey mapping and user persona templates are a topic for a whole different post – you may want to check out the linked articles to learn more about how to define your personas accurately to create your own internal user activation benchmarks for them.
Create branched user experiences leading to the Key Activation Points Only
I know I harp on about it all the time – you can’t have a traditional product tour and expect your users to activate. Showing them how to do STEP 4 before they’ve even taken STEP 1 is a surefire way to overwhelm them. The GIF below from an email marketing tool provides a good case in point:
Instead of a product tour overwhelming your users, create an interactive walkthrough that will push the users to adopt the key activation points.
Make sure that the goal of each step in your walkthrough is set to a custom event – the activation event you want the user to achieve.
Only that way you will know if the particular experience has actually contributed to a higher activation rate. See the example of an interactive walkthrough below.
STEP 1: Urging the user to link a social media account with a series of tooltips:
STEP 2: Getting the user to write and publish their first post:
Now, the interesting part comes in between: in order to see STEP 2, the user needs to have completed STEP 1: we know that by checking which custom event has happened and which has not.
That way, you can effectively measure how many people completed each of the key activation events.
All the experiences above have been built in Userpilot.
Now, it’s time to see if tweaking the experiences actually moves the needle.
Measure, A/B test and iterate
Now that you have created a bunch of experiences to improve your activation metrics, it’s time to see how much each of them actually contributes to the increased activation rates.
The easiest way to do it is by A/B testing your experiences against null or split testing the different versions against each other.
Userpilot allows you to do that by simply ticking this option in the experimentation part of the experience settings:
Activation is a nebulous metric and every business has to define it for itself. Moreover, it will vary from product to product, from one persona to another, and even from one use case to another use case. That’s why coming up with an ‘industry standard’ is almost always impossible, as you will be comparing apples to oranges (unless you’re comparing to the activation benchmark for your direct competitors). Comparing your own activation rates over time, however, can be a great way to see which user segment needs more help through onboarding. Creating and A/B testing ‘corrective’ experiences is the best way to improve your activation rate over time.