Activation: The Product Metric Everyone Thinks They Need But Can’t Seem To Define

June 30, 2022

I vaguely remember reading Dave McClure’s pirate metrics (circa 2007!) SlideShare when I started a new job at a startup and was struck by his “activation” metric—that is, the measurement of when users have a “happy” experience with the product.

For many businesses, especially at the time, activation seemed to be secondary to metrics that were closer to monetization, if it was measured at all, since most users weren’t having ANY experiences with the product. Fast-forward to the past few years, where product-led models have not only emerged, they’ve shown the market that it’s an excellent way to build a software company.

In a product-led motion, that first “happy” experience between a user and a product isn’t just a nice-to-have, it’s crucial. As a result, activation is having a moment.

Product Activation Definition

Who is using activation?

Product benchmarking data has shown that more businesses are adopting product-led models. However, there hasn’t been a significant increase in the number of businesses measuring activation—although the vast majority of standout product-led companies do.

The likely reason for this is that activation is highly specific to the product and individual user. External audiences like VCs are less likely to ask for activation numbers because they’re specific to the product and don’t make sense without a ton of context. Since no one is asking for activation numbers, very few founders and founding teams feel compelled to measure it.

Keep in mind that activation is binary–users can only activate once. Your number of activated users will only increase.That’s why it’s so common to see activation measured on a cohorted basis.

Defining user activation for your product

Activation is a beautiful metric because it’s a leading indicator. The right activation metric empowers growth, marketing, and sales teams to understand the impact of experiments they’re running.

User activation metrics for products

Say for example you have a sales cycle of 30 days, but your activation metric spans the first 10 days of a user’s journey. If you have the right activation metric–you’ll understand how well your experiments are performing three times faster than you would if you simply focused on conversion.

So how can you find your product’s activation metric? Keep it super simple. Make a list of all the key actions that users can take in your product. There shouldn’t be many, maybe 10 at the max. Make sure you ask customer-facing employees what they think activation should be, too.

Support reps, sales reps, and others spend all day talking to your users and trying to get them to find some value as well. Their insights are useful for this early list.

Once you have that list, get product usage information of all new users going back at least six months. You’ll want to understand if any of your potential metrics fall under all of the following conditions:

  • The potential metric is easily achievable by somewhat committed users (this means that around 40 to 50% of your users have taken this action).
  • Can be completed quickly (Quickly is subjective, and depends on the tool and the lift required to get started.) I typically recommend two weeks as the maximum amount of time.
  • Most importantly, prospective metrics should be directly correlated to a user’s propensity to convert.

Using activation metrics in real time

Here’s an example of a company undertaking this exercise. They looked at adding new users, using a specific feature, and getting positive responses to a survey as prospective activation metrics.

User Activation Framework

As you can see, all three of the prospective metrics could be easily achieved–all of them occurred with more than 40% of users.

Most of these could be completed quickly, but it did disqualify the feature usage metric, which typically occurred in the user population at a median rate of 60 days into usage.

The power of activation metrics in business performance

Finally, the true leader of the pack emerges with correlation to business performance–retention and conversion. The data shows that median counts of users added were the same for users that churned versus ones that converted. The same phenomenon occurred with feature usage. The behavior remains for users and their likelihood of conversion, too.

In this particular example, we selected the five-day timebox in order to increase the velocity of experimentation.

Median positive responses after signup

Using this framework keeps your team from adding too much complexity to the process. The crucial thing to remember is that the best activation metrics are ones that the whole team can rally behind. Weighted scores are wonderful for data teams, but they’re challenging for everyone at a business to understand if they’re making a significant impact on that score.

This framework helps keep the team focused.When a metric is subjective, there’s always someone who wants to have another opinion, to explore another feature. With this framework, you can test those hypotheses pretty quickly.

What does a good user activation metric look like?

A positive increase in activation can make enormous ripples across the rest of your business. The key thing to recognize is that it represents true value to the user. The more you attract users, the activation rate will decrease until you find ways for them to discover value.

One of the largest variables that go into activation rate is whether or not the product is collaborative—meaning that users must have another user in the product in order to unlock value. For collaborative uses, we typically see “good” rates of activation around 20%. For single-user products, or ones where collaboration isn’t necessary to unlock value, rates are typically around 40%.

Activation Rate Use Case from Product Benchmarks Survey

Given the fact that activation can decrease as your user base expands, it doesn’t come as a huge surprise that companies with more recurring revenue have smaller rates of activation on average.

User Activation rate by ARR from 2022 Product Benchmarks Survey

How can I put my activation metric to work?

Activation metrics aren’t just useful bits of data, they are also crucial signs of value and performance for all go-to-market teams. That also includes product. If you’re testing out a new onboarding process, make sure you understand what the baseline activation rates of older cohorts were prior to running your test. If your new onboarding process moves the needle, congratulations, you figured that out two to three times faster than you would have before those users converted.

Other ways successful teams use activation is in new user acquisition. If you’re curious about channels like TikTok, or Instagram, but have a limited budget to pay for advertisements on those platforms, activation could come in very handy.

When you have understood the baseline activation rate of prior cohorts, you can compare that to the new ones coming in through new channels. Ultimately, having those comparisons in mind can help you understand the return on investment of your new marketing channel spend way before that end-of-month meeting.

Activation is your product’s superpower

In the New User Journey, I always recommend that founders focus most on optimizing the value that their product provides users before expanding, eliminating signup friction, or driving demand.

I hope this framework helps you develop an activation metric that your team can get behind. If you have more in-depth questions, I’m always happy to chat. Feel free to reach out on LinkedIn or at [email protected].

VP of Growth<br>OpenView

Sam Richard is VP of Growth at OpenView, helping our portfolio accelerate top-line growth through establishing best practices and processes to support product led growth. At OpenView, Sam works closely with portfolio leadership teams to discover and implement the most impactful strategies for growth, including onboarding and retention optimization, expansion strategy, funnel optimization and channel/partner strategy.