Product engagement metrics are a crucial success indicator for product managers. With the right usage statistics at hand, product teams can better understand how customers navigate and find value in your product.
But how do you effectively track product engagement?
In this article, you’ll learn:
Having thousands of paying customers doesn’t necessarily make a SaaS business successful. If your customers barely touch your product, you probably aren’t solving the problem your user needs help with.
Measuring user engagements helps product managers give direction to their product roadmap in a more data-driven way. For example, they can spot product opportunities and improvements in the glimpse of an eye. Below are only a few examples.
Product engagement metrics take the prejudice out of product management. It shows real user behavior without the bias of user interviews. And because you’re measuring day in, day out, the insights are more substantial compared to shorter user testing experiments.
In addition to product teams, customer success teams will easily assess the overall health of their user base.
With these insights, customer success managers can take action immediately when customer engagement changes and avoid unhappy users or even churn
Ultimately, product and customer success teams will make better decisions, leading to a better customer experience and higher customer satisfaction.
The term ‘product engagement’ seems straightforward at first. But in reality, product engagement takes on different meanings for every SaaS product.
What you consider an engaged user, isn’t necessarily an engaged user for another SaaS product. Every product has its own definition of engagement. Although you can use many benchmarks and guidelines, it’s completely up to you to decide.
Below are a few pointers to help you identify engagement.
How you define ‘product engagement’ depends on your business. It’s a good idea to align on what defines success first, before tracking any metrics.
Below, you’ll learn the most common metrics tracked by product teams. You can use product analytics software like Heap, Pendo, or Amplitude to track actions and events in your product.
Daily active users (DAU) refers to the number of product users who are active on your app on a daily basis. Some product teams prefer to use monthly (MAU) or weekly active users (WAU). Your choice depends on how often a typical user logs in. This metric is great for monitoring the overall engagement of your user base.
Product managers can also combine multiple metrics.
Product adoption rate measures how many new product signups end up becoming active users of your product. You can calculate the adoption rate for your entire product, or for a specific feature.
Feature adoption rate is useful to understand which features of your platform are driving usage. After a product launch, they are a great success metric.
Product and feature adoption metrics are good indicators of the added value a product delivers. Activating clients is an ongoing struggle for SaaS products, yet an important goal. Now, you can fully understand which parts of your application activate your users.
If your adoption rate is low, you may want to investigate the cause more deeply. Sometimes, the cause lies beyond the product, like marketing strategy or onboarding. For example, you may be targeting the wrong people, or perhaps have a suboptimal onboarding process.
Many businesses will define an active user as a person who logged into your platform. However, you may want to measure more meaningful actions on key events in your platform.
For example, think of an email marketing platform. User A sends out a monthly campaign and returns every week to check performance. User B sends out a weekly campaign and checks performance once a week. They would both be weekly and monthly active users, while their level of engagement is very different.
You can measure key events separately. Or you can change your definition of ‘active users’ to reflect important actions.
Product stickiness measures how well you’re bringing users back to your platform. Stickiness is the ratio between daily and monthly active users. The more active users are returning to your product, the better.
If your product wasn’t built for daily or weekly usage, you can tweak this formula to your own needs. For example, measure recurring users versus unique users.
Formula: DAU / MAU
The Product Engagement Score (PES) measures how product users are interacting with your product. The score combines the previous metrics into a single score:
The product engagement score is the average of these three ratios. This metric is a great strategic metric, because it shows a comprehensive view of product engagement.
Formula: Adoption rate + Stickiness rate + Growth rate / 3
This metric tracks the average amount of time a user spends on your product during a single session. Usually, a longer session duration means more user engagement. However, depending on the job to be done, long sessions could also mean users get stuck. As mentioned earlier, your product’s context will shape how you look at these metrics.
Week 1 engagement measures how your users interact with your product within the first week. This metric is particularly useful for measuring product adoption with new users. You can also use week 1 engagement as a measure for new feature adoption.
Usage during the first week is a crucial metric to understand how fast users find value in your product. The faster they get to the aha-moment, the more usage, and the less likely they will churn.
Retention rate measures how many users are still actively using your product after a specified period of time. For example, if your product has 6,000 users today, how many still return after 6 or 12 months?
You can choose the timeframe depending on your business needs. With regards to customer activity, this formula works with daily, monthly or weekly active users. It’s a great way for product and customer success teams to understand longer-term engagement and anticipate churn risk.
Formula: Users at the end of specified time period / Users at the beginning of specified time period
Churn rate measures how many users stopped using your product after a specified period of time. Customer success can use churn rates to spot long-term trends in user behavior. When churn rates rise, interviewing your churning customers helps you identify gaps in your product experience. Although, regardless of churn rate, tracking churn reasons is always a good idea.
Formula: Churned customers in a specified time frame / Total customers in the same timeframe
Now it’s time to put all these user engagement metrics to good use. Product managers and customer success managers should use them to take the right actions to improving their product.
Here are a few tips to start making more effective use of product usage data.
Once you have these metrics in place, you can also start experimenting with new strategies to boost product engagement. Below are a few experiments to test.
Most product managers use product engagement metrics for internal operations to improve their product. However, exposing usage statistics to your product users can also provide tremendous value for customers. Unfortunately, it is an overlooked strategy in product development.
For example, video communication platform 24sessions uses engagement data to prove that video meetings save their users up to 20 minutes, compared to face-to-face meetings. All by exposing relevant product engagement metrics to their users.
Innovative SaaS companies share these insights through intuitive embedded analytics. It provides even more value to clients from within the interface of your own SaaS product.
Product engagement metrics will help you improve your product experience, add business value, and turn your users into ambassadors.
To set yourself up for success, don’t forget these two important notes when you start measuring product engagement.
Considering to take your product offering to the next level with client-facing reporting? Our team of embedded analytics experts are ready to help. Book a demo of Cumul.io to understand how your customers can benefit from your product data.