How important are your user engagement metrics?
Well, let’s say you have a newsletter building tool with 3 million users and your competitor has 800,000.
Seems pretty great right?
Source: Google Playtime EMEA 2017
But it turns out; Scenario 1 has a bit of a problem. Nobody is using the core feature.
However, the competitor-the one with 800,000-has majority of their users sending out the newsletter (using their core feature).
6 months later, you might still be at 3 million, and your competitor at 5 milion.
Source: Google Playtime EMEA 2017
User engagement can be the difference between exponential growth and hitting a brick wall. You need to focus on the right metrics.
Some metrics will show if you are currently doing well, projected to do well soon, and if you’re correctly steering the wheel in the right direction long term.
In this article, we will be doing an overview of what user engagement metrics are, how to find your user engagement metrics, common mistakes in measuring user engagement, and of course, a big list of metrics.
In the end, we will summarize the five key user engagement metrics you should be tracking for product-led growth.
Table of Contents
- What Are User Engagement Metrics?
- How To Find And Measure User Engagement Metrics
- Key Mistakes in Measuring User Engagement
- What Are the 5 Best Metrics for Measuring User Engagement?
- User engagement metrics are the data points to measure your users’ interactions with your product.
- You can find your user engagement metrics by figuring out the positive and negative behavior in your product, benchmarking this behavior with your power users and power features, then measuring it through cohorts and your product analytics tool.
- The most common mistakes companies make in measuring user engagement are attributing daily active users with only their login frequency. Not establishing an optimal session time and guiding users to reach it. Focusing too much on their initial conversion rate and not enough on retention.
- Our top 5 user engagement metrics are core action use, stickiness, NPS score, activation rate, and product adoption percentage.
What Are User Engagement Metrics?
First, let’s define user engagement. User engagement is the frequency and the quality of your user’s interactions with your product.
The more positive interactions they have, the more likely they will turn into long term customers and become product advocates.
User engagement metrics are the data that you can measure based on these interactions.
Let’s see how to find and measure your own user engagement metrics!
How to Find And Measure User Engagement Metrics
So, of course, we started with a super general definition of user engagement metrics, but it is your job to decide what engagement means to you.
By watching your users’ behavior in your product analytics tool, user session recordings, and user interviews, you will see some patterns emerge.
Some actions would have led to a positive experience where customers just realized your product’s value (Aha! moment). Others would be key actions where you could consider them activated (activation point) and on the verge of becoming customers.
What you want to track and focus on improving are the rates that your users perform these actions.
On the flip side, you will also notice negative behavior that lead to customers leaving your product. This might be multiple logins but very little session time. It could also be removing information, silencing notifications, or not engaging with any secondary features.
These actions you want to monitor and keep at low levels. Above all else, these will contribute directly to your churn rate. If you want to get real-time product insights, use our advanced user analytics features. Get a demo today!
Once you have defined these actions for your product, you want to combine them with other complementary metrics like session length and intervals, login frequency, NPS score, and time in the app.
Here is a step-by-step process to finding your user engagement metrics and how to measure them.
1. Define the positive behavior within your product that leads to higher engagement.
Some examples in different products are:
- Linking accounts
- Importing data
- Performing core actions like sending out emails
- Integrating the product with your tech stack
2. Define the negative behavior
Red Flags to take note of in most products are:
- Removing team members
- Downgrading their plan
- Deleting their profile
- Numerous logins with very little session time.
3. Identify your Power Users and Power Features
Once you figure out the positive and negative behavior in your app, it is time to figure out who your ideal user is.
Your ideal user or power user is in your product regularly because it helps them get their job done better than any other solution they have tried. They are valuable resources to tap when looking for product feedback.
These users will swear by a specific feature of yours or the so-called power feature. You will find the more users who engage with this feature, the more they realize your product’s value.
Once you identify your power users, you will have a specific persona based on their role, behavior, and interests to create your product around. You will also know your key differentiating factor from the competition and should try to get every user to test it out.
4. Learn from these rates and compare them with your other user engagement metrics
So now you know what positive behavior you want to encourage, what you want to avoid, and who you are building your product for.
A great way to track and measure your progress in fostering this behavior is by using retention and action cohorts.
A cohort is essentially a chart focused on two data points. A retention cohort would be measuring the session frequency and the time after a new user signs up.
An action cohort tracks key feature use compared to daily active users (DAU), WAU (weekly), and MAU (monthly active users). This means you can look at the percentages of your user base who used a certain product feature during a given period of time (1, 7, or 30 days). DAUs would have used a feature during the last day, while WAUs are the users who used it during the last seven days, and so on.
By tracking what features people use when they start with your product, you can discover the features that make people stick around, the features used most frequently by your most active users, and which features may need more attention.
You will also find out which features make people close their browser tab with anger.
Cohorts are a useful tool for comparing various feature usage metrics to even onboarding and general metrics like logins and time in-app.
They are also helpful in avoiding common mistakes in measuring user engagement. Let’s see what these are in the next section.
Mistakes in Measuring User Engagement Metrics
Measuring user engagement is not all sunshine and rainbows. It takes a lot of trial and error to figure out the metrics that make sense for your product.
Here are three common mistakes when applying user engagement metrics.
What you want to avoid is mischaracterizing who is activated and who is just window shopping.
Let’s go back to the newsletter app from the example in the introduction. They had 3000 users and were acquiring users at a steady pace. Each new user had multiple daily logins, so they put all of them into their DAU category.
You can’t go wrong with hundreds if not thousands of daily active users, am I right?
The number of logins doesn’t tell you much about user engagement because many users can boot up your app, get frustrated, and peace out.
None of the users are getting any value out of your product at the end of the day and will likely find another solution in the next couple of days, hours, or minutes.
To categorize your DAUs, you should see if they engage with your core features and how much time they spend in your app.
The way you can track this is through a tool like Userpilot, where you can tag your core features and measure how much of your user base actually engage with them.
Don’t stop at tracking how much time they spend in the app. Knowing if they complete the onboarding flow is also an important indicator if the time they spend in the app is actually valuable or just a “hello, goodbye”. To learn more about how you can do this through Userpilot, book a demo today!
So the newsletter app from above may have messed up on measuring their DAUs, but session duration was one metric they were confident about initially.
Many users would spend a half-hour in their product designing their newsletter with all the tools available. The problem was that few ever actually sent it out.
However, their competitor found that their users’ average session duration was one hour to fully import their templates or design a new one, including all the necessary information and then to send it out.
In your user engagement metrics, you should be creating a target session duration for how much time it actually takes to complete your core action. You can then optimize your product experience to show users everything they need to know to complete that core action within that time frame.
Obviously, it depends on the product. A task manager might have an average session duration of 15 minutes, while a CRM might be 30 minutes.
First, you want to follow your power users to see how much time they spend in your app. They understand your product the best and reveal how long the optimal time is to get value.
Source: Userpilot.com-Create and test out tooltips for each user segment to optimize their session duration. No coding required! Find out how with a free call today.
Conversion Rate vs Retention Rate
The last mistake we will mention applies more to early-stage startups or companies with an established product looking to increase their annual revenue.
Every founder is fixated on their paid trial conversion rate because more customers mean more money.
However, according to Retently, 80% of your company’s future revenue comes from just 20% of your existing customers!
Surprisingly, the first newsletter app had a pretty decent conversion rate at around 14%. This was likely due to their interactive walkthrough with videos.
But after users did convert, they usually only stuck around for a month.
Their competitor, however, was more focused on retaining the users they acquired even if their conversion rate was at a lower 10%.
They used a high-touch model with multiple onboarding emails from sales and customer success. An onboarding experience through the product and an optional onboarding with a customer success rep that users could sign up for.
We do a lot of that too:
The point is, by focusing on educating users as much as possible, offering numerous resources, and staying in touch throughout the trial period, they lifted their overall user engagement metrics.
Each user had a unique relationship with the product that fit their use case and made it that much harder to leave.
You need a well-balanced process that shows users the value initially and supports them through the product experience so that they continue to receive value as they use it.
Now that we have gone through the common mistakes in user engagement metrics, it’s time to get to the moment you have all been waiting for: the best metrics for measuring user engagement.
The 5 Best User Engagement Metrics
We aren’t here to show you a giant list of metrics for you to scroll through and not have any takeaways from. Instead, we will show you all the metrics that we measure for user engagement at Userpilot and then give you our top 5.
- Created a segment
- Created a goal
- Tagged a feature
- Installed a jv code snippet
- Installed Chrome Extension
- Invited a Developer
- Created an experience
- Activated the NPS
- Invited a teammate
- Created a checklist
- Activated the Resource Center
- Retention rate
- Number of opened support tickets
- Number of scheduled success calls
- Churn rate
- DAU, WAU, and MAU
- Time spent in-app
- Customer Satisfaction
- MRR, ACV, and ARPU
- MQLs, SQLs, PQLs
As you can see, most of the metrics that we measure focus on the interactions with our core and secondary features. We believe that measuring a 60-40 mix between your core actions and general user behavior makes the most sense for mid-market products.
We keep a close eye on the usage of our core features because they are critical in helping our users improve their conversion and retention rates.
Depending on how many features you have in your product and the problem you are trying to solve, you may find that different ratios work better. Each product needs to rely on a unique set of metrics to truly understand its engagement.
Other blogs will talk about the top 14 or 28 metrics and never actually get to user engagement metrics’ true purpose: to create a better product for your users.
Below, these are the 5 main metrics you need to get a baseline read on your engagement and ultimately try to improve to reduce churn, increase conversion and retention.
User Engagement Metric #1 – Core Action Use
Core action use is part of your most important user engagement metrics. It will demonstrate if your product is simple enough for anyone to pick up and start receiving value or need more guidance.
Measuring how often users click or use one of your key features is helpful; however, you can also get creative with how you read into their activity.
Here are three ways to dive deeper into core action use:
- The mean number of key actions per user: This is the average number of times a user performs a key action or uses a core feature. For example, “On average, users sent out 3.5 newsletters last month.” This average lets you categorize healthy and unhealthy behavior in your users. If they didn’t meet the average monthly core action total, it might be a sign they are disengaged and could use a follow-up with a customer service rep.
- The average time between each key action per user: This is tracking the time between using a specific key feature or service. The more you reduce this average time, the longer users will stay in your product and the more value they will get out of it. You can get lower averages through product experiences like tooltips, modals, or interactive videos.
User Engagement Metric #2 – Stickiness
Stickiness is your daily active users divided by your monthly active users or DAU/MAU.
By performing this equation, you are left with a percentage that lets you know how often users are coming back to your app. For example, you may have 2000 daily active users and 5000 monthly active users. That means you have a stickiness percentage of 40%.
This is a typically low percentage for simple B2B or B2C products. Their overall goal is to have the same number of MAUs as DAUS. In other words, have their entire user base getting value from their product all day, every day.
If you have a more complex product, this stickiness rate might be good because users don’t need to log in every day and engage.
User Engagement Metric #3 – NPS
When people talk about NPS, many may think it is a metric only applicable to surveying your customers.
But it can also be beneficial for products with longer free trials (14+ days) to understand their users’ opinions during their free trial experience.
It starts by asking with an in-app survey, “On a scale of 1-10, how likely would you recommend this product?”
Let’s say 100 people answer it. Next, tally up the responses into three categories.
- 50 respond with 9 or 10, so they fall into the promoter category and qualify as 50%.
- 30 respond with 7 or 8, fall in the passive category, and qualify as 30%.
- 20 respond with less than 6, so they fall in the detractor category and qualify as 20%.
Now, subtract the percentage of detractors from the percentage of promoters.
50% – 20% = 30%
So your NPS score is 30!
The average NPS score will vary by industry, so there are different benchmarks you want to hit. By surveying your users before it comes time for them to pay up, you can figure out what is working and what needs to be improved.
You may find information or uncover bugs that you never noticed, and as long you have a score above your industry average, you know you are on the right path.
Track your NPS score responses and launch your own in-app surveys with just a click of a button. Find out how easy it is with a free product consultation.
User Engagement Metric #4 – User Activation Rate
As much as we want to give you a definite answer on what a good activation rate is, unfortunately, it is impossible to create a solid SaaS benchmark.
The actions and experiences are too varied. Specific in-app events need to happen for a specific persona to get the benefits of your product.
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.
User activation rate is the number of users activated divided by the total number of new users who signed up in a given period of time, divided by 100%.
How do you improve this metric?
Create branched user experiences leading straight to your key activation points. This is easily achievable through interactive walkthroughs where a user has to complete an action to move to the next stage of onboarding.
It is also more engaging than doing a complete overview of the product and expecting the user to follow a predesigned path and remember everything.
User Engagement Metric #5 – Product Adoption Rate
This metric measures what percentage of your users engage with all your features.
Strong user engagement can be shown through your core action use, but adoption measures the number of unique features being used. This can be defined as the depth of their engagement and is a useful indicator for which users will eventually become power users or product advocates.
For example, if you have a social media scheduler and a customer has used 2 of 5 total distinct features in the past month, that account would have a 30-day Adoption rate of 40%.
But someone who used all of those features would have a 30-day Adoption rate of 100%.
Low adoption rates mean that users are using the product in a concentrated way, while high adoption rates mean that users are using the product more broadly. It can also mean that you have different personas with different jobs to be done (goals).
A great way to understand product adoption rate is goal setting. With Userpilot, you can set goals for each of your features and even activation points.
You can then track how much of your user base engages with each feature and calculate your overall product adoption rate for each segment.
Ready to set goals for your feature use and track exactly how many users engage with them? Let us show you how to get real-time data!
Wrapping Up: User Engagement Metrics
There are tens if not hundreds of metrics that you might want to focus on in your product. However, don’t get too caught up trying to measure every action that a user takes. You might spend more time watching than actually improving your product.
High user engagement is your gateway to conversion and most importantly, retention. If you are unsure of where to begin, do an internal audit of your features and user behavior. You will start to see trends and be able to pick the metrics that make the most sense for you!