Product Analytics

Why product usage data is the key to unlocking user insights

Harsh Patel

Today’s digital economy relies heavily on software products that make generating and collecting data easier than ever before. In fact, the total number of publicly available mobile apps is estimated to be around 9 million, with each app generating tons of data on the behavior of each of its users.

But, of all the data created across the entire user journey, product usage data is arguably the key to unlocking user insights. In fact, in a Mixpanel survey of over 1,000 participants, almost 80% of respondents said that they used analytics primarily to understand product usage—and for good reason. “In every software product, there are usage patterns that point us toward the core outcomes that are important to your customers,” says Wes Bush, founder of the Product Led Institute “Product-led companies continually track and monitor these usage patterns to understand whether users are accomplishing what they set out to.”

Simply stated, no other type of data can help you understand what your users do, and why they do it. 

What is product usage data, and why is it so important?

Product usage data is data generated by in-product user interactions (everything from ‘sign up’ to ‘watch video’, and ‘add to cart’). It tells you who the end-user of your product is, as well as when and how they’re interacting with it.

What makes product usage data so essential is the volume of insights it drives across the entire user experience, and how actionable these insights can be for nearly every team in an organization—from product, to marketing, sales, customer success, and more. Ultimately, analyzing product usage data can help product teams surface clear opportunities for user, product, and business growth.

Perhaps most importantly, product usage data is objective. Much more so than things like user interviews and surveys, which —while incredibly valuable when used in tandem with product usage data—can only show you what users say they do, and not what they actually do. This is one of the biggest reasons why many products fail to innovate, as we learned in our State of Product Analytics report earlier this year.

How can product usage analytics help improve user experience?

So how, exactly, does analyzing product usage data help improve your product’s user experience? Well, it depends on what part of the user experience you’re trying to move. Let’s take a look at a few use cases to see what product usage analytics can accomplish.

1. Increasing user engagement

Product usage data can tell you what parts of your product users love and interact with the most, and how deeply they engage with your product.

Identify events that lead to higher engagement (or churn)

Product usage data can show you which events engage users more than others, so you can highlight them to users. For example, Viber surfaced that users found group chats highly engaging and subsequently made creating them easier, leading to a 10% increase in engagement on their chat platform.

With product usage analytics, you can identify events that correlate with high engagement, as we demonstrate in this Signal report in Mixpanel.

Understand how engaged different user segments are

Creating cohorts with product usage data allows you to understand who your power users are, which users are likely to become power users, and which users are at risk of churning. You can then nudge them in the right direction to increase their engagement.

Cohorts can help you identify users that can potentially turn into power users, as shown in this demo cohort in Mixpanel.

Use in-product user actions to drive messaging

Product usage data can help you identify which users to message and when, so you can sync that data with third-party messaging tools, and increase engagement by sending promotions or offers via in-app messages or emails.

Cohorts can also be used to target specific users for messaging based on their activity, like this example cohort in Mixpanel.

2. Improving retention

Although engagement and retention go hand in hand (an engaged user is less likely to churn), understanding how your product gets used also allows you to improve retention.

Understand user workflows to eliminate friction

Product usage data lets you analyze user flows to locate points of friction, so you can improve your product to optimize your users’ experience.

Analyze user flows to locate points of friction that cause drop-off. This example in Mixpanel shows that an experiment is causing users to drop off, which may mean that improving or removing the experiment can improve your user experience.

Identify user actions or attributes that correlate with retention

Correlating product usage to user retention enables you to nudge users towards actions that might cause them to retain more.

For example, the Australian real estate website Domain found that school-related property searches correlated strongly with retention. They then created more school-related features and found users of those features retained two times more.

Certain user events correlate highly with retention. In this example from Mixpanel, enrolling in Bill Pay correlates with 2nd-week user retention, which indicates that promoting this feature to new users might improve new user retention.

Break down retention data for better insights

Breaking down data by properties like browser, acquisition channel, or operating system enables you to find out which users retain better, and what to focus on for the rest.

Breaking data down often provides more insights. This Retention report in Mixpanel breaks down retention data by users of Touch ID to reveal that users of the feature are retained better. Promoting this feature may increase the number of users for it, which can in turn improve the login experience and increase usage frequency and retention.

3. Boosting adoption

It goes without saying that product usage data can tell you how much your users interact with new products and features, but using this data can result in increased adoption of these features.

Recognize feature popularity and adoption

Seeing how often a feature is used helps you identify what feedback to collect so you can improve the feature, and increase adoption. That’s how Seelk improved adoption of their logistics app by 120% within just a few weeks.

This Mixpanel Insights report shows that the Channel and Integration creation features aren’t being used as often as before, which means they should be the focus of customer feedback.

Identify which users are most likely to use specific features

Product usage data can tell you which users would enjoy a feature most, based on their previous activity, so you can expose your new features to the right users and with the right message — exactly what Sunrun did to improve adoption of their mySunrun app by 50%.

The cohorts report in Mixpanel can be used to identify users that can find value in certain features based on their in-product activity, as shown in this example in Mixpanel.

Understand if your A/B tests and feature launches are successful

Product usage data can show you if your product changes are affecting users as intended, so you can prioritize resources on what works based on data and facts. Although this won’t improve adoption of current features, it helps you launch the right features which will get adopted faster in the future.

Mixpanel’s Impact report can show you the causal relationship between a feature launch and key metrics. This example shows that the new “Authenticate” feature caused adopters to publish ~27% more integrations than non-adopters.

4. Optimizing conversion

Product usage data also helps you improve conversion rates in your product. This can be anything from someone completing your product onboarding guide or tutorial, to upgrading their plan.

Mixpanel product marketing manager Anya Pratskevich wrote an in-depth article about using product data to improve conversion rates that shows you how to achieve this.

Product usage data is powerful if you’re able to leverage it

We just shared a lot of different ways to improve your user experience with product usage data. But none of it matters if you’re not able to use it. That’s where a dedicated product analytics tool comes in. Teams that leverage one have the ability to analyze product usage data without a data expert, run exploratory analysis, and make actionable data visible across teams, so every person at their company is set up for success.

And while marketing analytics and business intelligence tools are essential parts of a modern tech stack, they’re not built for analyzing product usage data. The former won’t give you the depth of data you need to understand what users are doing in your product after they land on your sign up page, and the latter requires an outsized investment of time and resources for the same result. Sure, it’s tempting to use one tool to do both, but that’s the analytics equivalent of killing two birds with one small thermonuclear device — possible, but not very practical.

If you’re interested in learning more about product analytics, sign up for Mixpanel and take it for a spin. You can explore the platform with a variety of publicly available sample datasets, and see if it’s right for you.


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