A practical guide to product usage analytics

Imagine: you pour tons of time and energy into building a feature you think users will love. But weeks after launch, adoption is—disappointingly, frustratingly—still low. When you don’t have visibility into how users really interact with your product, you’re left guessing—which rarely leads to great decisions. That’s where product usage analytics gives you the clarity you need. It shows what users do, what they skip, and where they get stuck, so you can build smarter and improve faster.

In this guide, learn what product usage is and how to implement product usage analytics to make decisions that boost user satisfaction and drive business growth. 

Key insights

• Define what you want to improve (activation, retention, feature adoption) before choosing metrics—otherwise you end up with pretty dashboards that don’t drive decisions

• Users don’t stay on one device or platform, so your analytics shouldn’t either. Look for solutions that track behavior across web and mobile without creating data silos.

• Choose a tool that will help you turn insights into action quickly—your product usage data is meaningless if no one looks at or understands it

What is product usage analytics?

Product usage analytics is the process of tracking and analyzing data about how people use your product—what features they click on, how often they return, where they drop off, and what actions they take (or don’t take). 

Without usage analytics, you’re probably running your product strategy on gut feelings and a dash of wishful thinking. You might think users love that new feature you just launched, but product usage data shows that they scroll right past it. Product usage analytics helps you

• Identify valuable features so you can double down on what’s working

• Find user friction—like where users get stuck or stop engaging—and make changes fast

• Prioritize your product roadmap based on real user behavior (instead of an off-the-cuff suggestion in a meeting)

• Understand what drives retention, and find ways to keep customers coming back and increase customer lifetime value 

Product analytics vs. product usage analytics

People often use the terms ‘product usage analytics’ and ‘product analytics’ interchangeably, but they mean different things. 

• Product analytics is the big picture—it includes everything from who your users are to how they use your product and what their outcomes are

• Product usage analytics, our focus in this guide, is a subset of that term, focusing specifically on how users interact with your product—the clicks, flows, and actions inside the experience

A 6-step framework on how to implement product usage analytics 

Getting started with product usage analytics doesn’t need to be complicated. By following these 6 steps and choosing the right product analytics tools, you can start learning from your users’ behavior—and improving your product—faster than you expected. 

1. Choose the right tool for your team

Before measuring anything, you need a product analytics platform—one that fits how your team works and what your product needs.

The wrong choice could mean major setup headaches, confusing product analytics dashboards nobody uses, and data that’s, well, questionable at best. But the right choice means your team gets valuable insights they can actually act on—even without a master’s in data science. 🤓 Here’s what to look for when choosing a product usage analytics tool: 

• Easy implementation: skip platforms that require weeks of tedious manual event tagging. Instead, look for product analytics tools like Heap by Contentsquare that offer automatic data capture to get you up and running fast. 

• End-to-end journey visibility: you need to see how users move through your product across pages, devices, and sessions. Contentsquare helps you spot pain points, like frustration signals and drop-offs across the entire product journey. 

• Built-in insights: the best product analytics tools offer a variety of charts, graphs, and visualizations to help you turn numbers into insights. Some also help you decide what action to take based on your user data. (For example, simply ask Chat with Sense, our AI analytics assistant, to surface friction points or recommend next steps.) 

• Integrations with your existing stack: make sure your analytics tool plays nicely with the rest of your tech stack. For example, Contentsquare has native integrations with Optimizely and AB Tasty to connect product usage insights with A/B testing data.

• Ease of use: look for a platform that offers a user-friendly interface so anyone who influences the product experience—from marketers to product managers—feels comfortable accessing and using the data. (No more missing opportunities and bottlenecks while waiting for the data team!)

Make confident data-driven decisions with product usage analytics from Heap by Contentsquare

💡 Pro tip: choose a comprehensive, all-in-one platform to reduce SaaS sprawl and make it easier to access insights. For example, in addition to ticking all of the above boxes for product analytics platforms, Contentsquare is an all-in-one experience intelligence platform that offers 

• Experience Analytics tools like Heatmaps, Session Replay, and Journey Analysis that let you visualize how users interact with every page

• Experience Monitoring tools like Error Analysis and Speed Analysis to detect issues in real time

• Voice of Customer tools like Surveys and Interviews to hear directly from users

2. Set goals

Before diving into your data, take a step back and ask yourself, ‘What are we trying to improve?’

Because here’s the truth: while product usage analytics can show you lots of data, trying to track it all is a direct path to getting overwhelmed and shutting down. 🫠 (Sound a little too familiar? Check out our ebook on breaking free from analysis paralysis.)

Instead, your analytics should align with your business goals to ensure you measure what matters, not just what’s easy to count. 

Start by identifying your team’s focus:

• Want to increase activation? Analyze how new users engage with your product in their first session and which of their actions predict long-term success.

• Aim to boost customer retention? Find out what features or functionalities keep users coming back—or what drives them away before they even get started.

• Need to improve a specific feature? Discover how often people find and use it.

Sometimes, you may also align your goals with company values. For example, HelloSign, now known as Dropbox Sign, places a high value on customer experience, and they use this criterion to prioritize their goals. 

“Conversion rate is important to us because it’s important to our customers,” says Bill Farrell, the former Director of Product. “One of our core values is to make our customers shine, meaning we want to build products that let them shine in the eyes of their customers or within their organization.”

Heap by Contentsquare helped them spot an issue with conversions on their signer page for mobile users, which made them realize they needed to build a mobile-first version.  

3. Choose your metrics

Once you’ve set your objective, choose product usage metrics that reflect progress toward that goal and help guide your decision-making. 

This is worth clarifying—not all product analytics metrics are created equal. Vanity metrics might feel important, but they’re often too high-level or disconnected from outcomes—think total signups (without knowing how many users actually activated) or download counts (without tracking long-term user engagement). 

When in doubt, ask yourself if the metric could help steer your team toward an action. If the answer is no, let it go.

Here are a few metrics worth monitoring for product teams:

• Activation rate: the percentage of users who complete a key action that signals they’re getting value from your product

• Time to value (TTV): how long it takes a user to experience your product’s core benefit. If this takes forever, you lose people before they realize why they should care.

• Feature usage: how often people use specific features. This helps you uncover hidden gems worth promoting and expensive mistakes worth cutting.

• Engagement rate: how often and how deeply users interact with your product

• Churn rate: the percentage of users who stop using your product over a given period—the metric most likely to keep product teams up at night 

• Retention rate: the flip side of churn—how many users return after a set time

• Drop-off points: where users exit or abandon important flows, like onboarding or checkout. (These are neon signs pointing to your biggest problems—follow them!)

📱 What about mobile app metrics? More than 65% of website traffic comes from mobile. If you want to focus your efforts in this area, check out our mobile analytics metrics guide to learn the 7 most important metrics to track.

4. Define events

Once you know what you want to measure, you need to define events—the specific actions users take that help you progress toward your goals.

Many teams take an all-or-nothing approach to tracking—neither of which works. Track nothing, and you’re back to guessing. Track everything, and you’ll spend more time managing data than using it. 🫠

This time drain is even worse if you have to tag your events manually. Happily, Contentsquare offers Smart Capture, which automatically records every click, scroll, tap, and swipe. Plus, it works retroactively, so even if your goals change later, your data is still there.

Smart Capture takes care of event-tracking for you—no manual tagging required

When defining events to track, focus on moments that tell you whether your users are achieving  their goals—or getting stuck along the way.

• Activation signals, like ‘Completed onboarding’ or ‘Created first project’

• Engagement indicators, like ‘Used core feature’ or ‘Customized dashboard’

• Value moments, like ‘Generated first report’ or ‘Shared content’

• Friction points, like ‘Abandoned checkout’ or ‘Clicked help multiple times’

👉 A note about naming: keep it simple and consistent—messy naming results in messy insights. When your marketing team tracks ‘Started checkout’ and your product team tracks ‘Initiated purchase flow,’ they may (or may not!) be measuring the same thing. Set up simple, shared naming conventions for everyone to follow. (A basic spreadsheet works just fine.)

5. Collect usage data across web and mobile

Journeys aren’t linear, and users constantly bounce between devices. They may start exploring your product on mobile during their commute, continue on desktop at work, and check in again on their tablet before bed.

But some analytics platforms treat each touchpoint like a separate user—creating a major knowledge gap. For example, you might think mobile users have terrible conversion rates when they’re really just completing their journey on desktop. 

The solution is to use a single platform like Contentsquare to track every event across your tools and devices for a unified view of the whole user journey. 

This allows you to

• Understand how users move between devices

• Catch problems that only affect specific devices or browsers

• Figure out which touchpoints really drive conversions (instead of just crediting the last click)

The ability to collect omnichannel data is one of the reasons Product Manager Chelsea Heredia chose Heap by Contentsquare at Snapfish. Instead of piecing together data from multiple tools, she used the platform to see how customers switched between devices when creating photo projects. 

“Heap by Contentsquare’s omnichannel report enabled us to track how many customers were going to the saved projects in the app, tapping on a web project, going over to mobile web, and then ideally completing the project,” says Heredia. 💡 Pro tip: pipe all of that glorious unified behavioral data directly into your existing tech stack with Contentsquare’s Data Connect to create even more insights for your team. 

Data Connect lets you automatically export clean, structured behavioral data to your data warehouse (like Snowflake or BigQuery). There, you can blend usage insights with customer data and revenue metrics from other platforms, or power churn prediction models—all without begging your engineering team for help.

6. Analyze user behavior to gather actionable insights

Collecting product usage data is easy. Turning it into decisions that improve your product? That’s where you might get stuck. 

Start your analysis with a specific question that aligns with your goals and target metrics, like ‘Are users actually adopting our new feature?’ or ‘Where do people drop off during onboarding?’ (This is super easy with Chat with Sense—just type in your question in plain language and get insights in seconds.)

Then, segment your data by what matters—for example, first-time vs. returning users, or mobile vs. desktop—so you can tailor your product improvements to the people who need them the most.

The right tools help you dig deeper at this stage. Contentsquare’s Journey Analysis shows you how users move through your product (spoiler: it’s often messier than you planned). 

Next, go to Contentsquare Heatmaps to see where users collectively click, scroll, or hesitate—and jump into the Session Replay tool to watch real session recordings and understand the why behind user actions.

Chat with Sense (right) helps you analyze the journeys that users take through your product

Transform your product strategy with usage analytics 

Product usage analytics isn’t just about tracking clicks or counting sessions—it’s about finally understanding what your users do and using those insights to shape your product analytics strategy and build even better product experiences for customers.

Your users are already showing you exactly what they need—product usage analytics just helps you listen.

FAQs about product usage analytics