Product Usage Analytics: A Guide for Product Teams

Product usage analytics enable product teams to make informed product development decisions to deliver a better customer experience, drive customer success, and boost their satisfaction.

From the article, you’ll find out about:

• The difference between product usage analytics and marketing analytics.
• The main benefits of product usage analytics.
• How to collect and analyze product usage data.
• Key metrics to track.
• How to harness the power of product analytics to improve customer experience.

With that out of the way, let’s dive right in!

What is product usage analytics?

Product usage analytics is the practice of tracking and analyzing how users interact with a digital product.

This involves tracking user behavior inside the product, for example, how many users use it, how often, which features they use, or how they navigate through the product.

This data can then be used to improve the product, develop better user onboarding experiences, and optimize the overall customer experience.

Product usage analytics vs. marketing analytics

Product usage analytics and marketing analytics focus on different aspects of product performance.

As mentioned, product usage analysis focuses on customer behavior in-app to better understand their pain points, needs, and preferences. Its aim is to identify ways to improve the product, optimize user experience, and drive user engagement.

Marketing analytics, on the other hand, concentrates on assessing the effectiveness of marketing efforts. It involves analyzing data related to customer acquisition, conversion rates, marketing channels, and ROI. Its key objective is to optimize marketing activities and allocate resources effectively to drive customer acquisition and retention.

To achieve their objectives, both kinds of analytics use different tools and data sources and track different metrics.

What are the benefits of product usage analytics?

Product usage analytics enable teams to drive product growth by improving their ability to make informed decisions and providing insights into how to optimize the user journey so that they can achieve their objectives more easily.

Facilitate product managers to make data-driven product decisions

Tracking product usage provides product managers with the most objective insights into user behavior in-app.

Armed with such insights, they don’t have to rely on guesswork and hunches when making product decisions.

By knowing how different users interact with different aspects of the product, they can effectively prioritize initiatives that will deliver the most value to customers and evaluate the effectiveness of the changes once implemented.

Increase conversions at important customer journey stages

Product usage analytics offers product teams valuable insights into how users progress along the customer journey.

Understanding what actions users complete at different stages of the user journey, how long it takes users to reach subsequent stages, and where they get stuck allows them to optimize relevant touchpoints and boost conversions.

Improve retention rates and customer lifetime value

Optimizing the customer journey means that they can experience the product value and adopt it in less time. That translates into higher user satisfaction which also leads to improved customer loyalty and retention.

Increasing retention rates is the most obvious way to boost customer lifetime value. It’s not the only one, though. Product usage analytics can help teams identify PQLs (product-qualified leads in the PLG parlance) and drive account expansion through upsells and cross-sells.

How to measure product usage data?

Modern analytics tools enable product teams to easily track various aspects of product usage without writing a single line of code.

Track feature usage to analyze user behavior

Tracking product usage allows you to identify how many users utilize a feature and how often.

Thanks to that, your product team can identify the most valuable features you need to prioritize in the future and those you might need to sunset. Feature usage data can also shed light on issues with the onboarding process, which get in the way of smooth feature discovery.

With tools like Userpilot, you can start tracking feature usage by simply tagging them from the Chrome extension. Apart from clicks, you can also tag hovers and text infills for a more complete picture. And once that’s set up, you can visualize the data for easy analysis in graphs and heatmaps.

Set up event tracking at important stages in the user journey

Events are all user’s actions inside the product. These could be individual interactions or combinations of them. We call the latter custom events.

One way to leverage event tracking is to optimize the user journey inside the product. To do so, you need to identify the key actions that indicate that the user has progressed to the next stage.

For example, using certain features once could be an indication of their activation, whereas using a specific feature a number of times over a period of time could mean feature adoption.

Next, you need to tag each of the events in the same way you do with features and analyze the data for insights.

Trigger customer surveys to gauge usage frequency

Another way to collect product usage data is through surveys.

In-app surveys are easy to create and you can use trigger them for specific user segments at a specific time. For example, you could trigger them contextually at a moment when the user engages with a feature.

Surveys could offer valuable insights both directly and indirectly. Apart from the actual user responses, the response rate could be a good indication of user engagement and loyalty.

A word of warning, though. Asking users about their product or feature usage isn’t always reliable, so it’s best to use this method in conjunction with quantitative methods like feature or event tracking.

Important product usage metrics to track

What exactly is on your product usage analytics dashboard depends on your focus or goals. However, I don’t know of product teams that wouldn’t track the metrics below.

Number of active users

The number of active users is an engagement metric that is an indication of customer satisfaction. If your customers use the product regularly, it’s a sign it delivers value (and users know how to realize it).

Teams normally track:

• Monthly Active Users (MAU) – the number of unique users that engage with your product in a month.
• Weekly Active Users (WAU) – the number of unique users that interact with the app in a week.
• Daily Active Users (DAU) – the number of unique users that engage with the product at least once a day.

What DAU, WAU, or MAU good figures are, depends on your product and the user segment. For example, a freelancer is likely to use accounting software once a month, whereas an account will do it daily.

Activation rate

Activation rate is the percentage of the total number of users who signed up over a period who achieved the activation milestone.

The metric is important because it shows you how effective your user onboarding is.

If your users fail to reach the activation stage or it takes a lot of time, it’s an indication of friction that stops them from experiencing the product value. This will eventually lead to user churn.

Feature adoption rate

Feature (or product) adoption tells you how many users are likely to have incorporated the feature into their workflows and use it as a go-to solution to their problems.

We calculate the feature adoption rate by dividing the number of the feature’s monthly users by the total number of logins over a period of time and multiplying it by 100.

Tracking the metric can help you identify how valuable users find the feature so that you can make informed decisions about their future development. It can also help you identify ways to improve user onboarding.

Retention rate

The customer retention rate tells you how many customers keep using the product (and paying their fees). It helps teams assess how well the product satisfies user needs. If they are satisfied and see it as a good value for money, they have no reason to leave.

To calculate the retention rate, deduct the number of users acquired during the period from the number of users at the end of the period and divide it by the total number of users at the beginning of the period.

How to leverage product usage analytics to improve the customer experience?

Now that we know how to collect product usage data and the metrics to track, let’s look at a few specific ways you can use it to make your product better.

Identify friction points in the customer journey

Product usage analysis can help you create frictionless user experiences.

While a little bit of friction might be desirable, for example, to qualify some leads, unnecessary friction slows down users on their way to activation and adoption.

The product analytics tool that you need to discover friction is funnel analysis.

The funnel is a visualization of user progress from one stage of the journey to another. As users drop out, the funnel chart bars representing subsequent stages get narrower. If there’s a big drop in conversions from one stage to another, you will see it immediately. That’s your friction point.

To identify the root cause of friction, look closer at product usage at the difficult stage. Carry out Paths/Journeys analysis and study user session recordings and heatmaps for granular insights.

Create detailed user segments to personalize experiences

Thanks to product usage analytics, teams are able to create accurate user segments based on their in-app behavior. For example, you could create segments based on whether users have engaged with a specific feature or reached a milestone.

Segmenting your user base allows you to tailor their experiences to their unique needs and the stage in the customer journey they’re at.

For instance, you could customize the onboarding experiences for new users to help them discover only the key features that are relevant to their use cases. For more advanced users, on the other hand, you’d focus on improving the discovery of more complex functionality.

In this way, you increase the chances of them adopting the product and converting to paid customers. Personalization also helps you build stronger customer relationships and increase their loyalty.

Optimize the onboarding process for new users

Analyzing the product usage of existing users allows teams to optimize the onboarding experiences for new customers.

How so?

Tracking the product interactions of the most successful users, for example, those who require the least time to adopt the product enables you to identify the most effective behaviors and paths.

You can then tweak the in-app onboarding flows to guide users with similar use cases along the most optimal paths and increase their activation and adoption rates.

Identify and target users receptive to upsell messages

With product usage analytics, you can also single out the users who are ready to upgrade to the paid or higher plans.

You could do it by analyzing the actions of users leading up to their conversions. Next, you could bundle them up into custom events, and track which users complete them.

If your engagement or adoption tool offers event-based triggering, you could automatically target such users with contextual upsell messages to drive account expansion.

Conclusion

Product usage analytics are an indispensable tool for product teams aspiring to build products that deliver on their value proposition and delight customers.

If you want to see how Userpilot can help your team extract actionable product usage insights and act on them, book the demo!