Let's talk product engagement metrics.

Not exactly the sexiest topic, but if you're in the business of running a SaaS product, it's an important one none-the-less (and if you're in that business, you have to think it's kind of sexy, right?).

Whenever defining and crafting any metric, it's essential to start with the questions you are looking to answer. And when it comes to product engagement, there are several of these questions.

Of course, the ultimate question you want to answer when it comes to product engagement is - Is anyone using my product or not?!?!

To answer that question, sure, you could just look at active users. How many users are logging in daily, weekly, monthly. But that's pretty shallow - pretty weak. And not good enough for this blog, frankly. Product engagement is not a one-dimensional phenomenon. It's multi-dimensional and if you want to understand those dimensions, you need to dive deeper. You need to ask more questions.

And if you'd like to dive with us - to discover the more specific questions you should be asking as well as the metrics that will help answer those questions - then stick around. That's exactly what this post will do.

Four key questions to define good product engagement metrics

Here are the key questions we think you should be asking when it comes to measuring your product engagement.

  • How much are my users using my product?
  • How often are they using my product?
  • How deep is their feature usage? How many of my features are they using?
  • How far along are they from getting value from product?

Each one of these questions explores a different dimension of the engagement story. And the metrics that are derived from these questions fill in the plot.

Four key product engagement metrics

The following represent the key product engagement metrics that we think help you tell a complete, holistic story about how users are engaging with your product.

But before I get into the specific metrics, a quick note on our approach to metrics in general.

A word about metrics

We have a strong bias toward actionable metrics, not only in this post, but in general. Of course, looking at any these metrics at a global-level (meaning aggregated across your entire user-base) is important for understanding broad trends and overall health of your product, but these global metrics aren't necessarily that actionable. We are much more interested in metrics that can be computed right down to the individual user and account-level. This is when they become actionable - when they can then be used to triggered automated messages or important signals for your teams to take specific actions.

That is why, as you read out the engagement metrics covered in this post, you should think about them both at the global and, more importantly, at the user/account level.

With that said, here are our list of key product engagement metrics:


product engagement score - Sherlock

A product engagement score is a calculation created to answer the question, How much is a user or account using my product? In our opinion if you HAD to use only one metric to measure engagement with your product, it would be this one.

At its fundamental level, a product engagement score is an aggregate count of how many times a user or account uses your key features in a defined time period. These aggregated counts should then be ranked and normalized so that they can be expressed in a scale (between 1-100, for example) that everyone can understand. Almost like a credit score for your users.

When each of your users and each of your accounts have a weekly engagement score, you will immediately be able to identify your power users, your churn threats, and everyone in-between. A good engagement score goes well beyond whether or not a user is simply "active" (ie - simply logged in) and will expose how much every user is engaging.

Crafting a proper product engagement score is not a simple task, but it is worth it. You can find the steps necessary in this post (or if you would rather go the easy route, this is for which Sherlock was built).

FREQUENCY (the How Often)

Frequency is a metric that answers the question How often a user or account is using my product?

Ideally, this is a metric that is calculated with more granularity than "daily/weekly/monthly". For example, you want frequency to tell you how many days in the last week a user or account has been active. Account A has been active 5 of the last 7 days, while Account B has been active 2 of the last 7.


An Adoption rate metric allows you to answer the question How deep is a user or account's feature usage? Are they primarily focused on one of your features or are they diving deep, hammering away at all your key features?

A simple Adoption rate metric can help you understand this. This is basically a percentage of features used - [Total number of features used] divided by [Total number of features in the product]. Account A has adopted 75% of your features, Account B has only adopted 25% of your features.

You'll want to look at this calculation over specific time frames. You'll want to calculate Adoption rate over the past 7 or 30 days (recent adoption), but you'll also want to know all-time.

  • An account with a high, all-time Adoption rate, but a low, recent Adoption rate has tried attempted to go deep on your feature set, but maybe didn't find much of it valuable. Maybe they need more training? (or maybe you need to improve those existing features before building any new ones)
  • An account that has low all-time and recent Adoption rate may be using your product to solve a very specific problem, or it may they may not be aware of all the beautiful features you offer. Better product marketing? 
  • An account that has both a high, recent Adoption rate AND a high, all-time Adoption rate is an account that is really embracing your full product offering. Brilliant - go get that case study!


An Activation rate metric helps you answer the all important question How far along is a user or account to getting value from my product? Otherwise known as Activation. An Activation rate is an essential metric for driving go-to-market processes for both trial or newly paid accounts.

Activation rate is a calculation expressed as a percentage, measuring how many of the 5, 6, 7 things that a new account needs to do to become activated has completed. So, for example, if a new account needs to complete these actions to become activated:

  • Account created
  • Invited 2+ team members
  • Created project
  • Uploaded 2+ files
  • Created 3+ calendar events
  • Created 1+ tasks
  • Completed 1+ tasks

...then the Activation rate will be the percentage of those items that have been completed. Finished 2 of 7? That's an Activation rate of 39% Complete 5 of 7? That's an Activation rate of 71%.

This is a key metric for building a PQL process and driving an effective onboarding program for your users.

BONUS: Three other key metrics

While the above represent what we consider core engagement metrics, there are a few others that are important in order to (a) give more context to your engagement metrics; and/or (b) to make your engagement data even more actionable. They answer the following questions:

  • How long has a user or account been using your product?
  • When were they last active?
  • How many of their users are active (an account-specific metric)?

TENURE (the How Long)

How long has a user/account been using your product? Have they a new account (Tenure of less than 30 days)? Or a mature account that has been using for over three years?

This is an important metric to track for all your users and account mostly because it will help drive your GTM actions around the account. For example, you if you have a new account (Tenure less than 30 days) with a low Activation rate, then you know you need to push them toward getting to that first value. If however, you have a more mature account (Tenure of 8 months) with a low Adoption rate, then you need to help them find value in the features they have yet to explore.

As you build a proper signaling system for your customer base, this metric will be key for defining the right signals you want to implement and for driving the right action off of them.

LAST ACTIVE (the When)

It's very important to know when a user and account was Last Active with the product. There are many actions that can be triggered based on this metric. An account that hasn't been active in 15 days is a concern. One that hasn't been active in over 30 days is a problem (*you can even use this metric to forecast forward looking churn).


Active user percentage is a very important metric for SaaS businesses that sell to accounts (which means all of us). This is especially true for those of us who sell seat licenses. For example, you will want to know if an account with a high Engagement score has one user driving all the usage or if it is spread evenly across multiple users. This is a metric you will want a good handle on for your larger accounts as a drop in Active user percentage is a bad sign - especially heading into a renewal.

We hope this overview of the key engagement metrics that should be driving your operation was helpful. Sherlock was built to make it easy to calculate and take action on all of these metrics. If you are interested, you can sign-up for a demo here.

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