Why user behavior signals are vital for product teams

To make the most impactful product changes—those that blow past your OKRs and your customers’ expectations—you need to know what your users truly need and how they feel when using your product. The challenge is to learn this without bias and at scale to get stakeholder buy-in.

The solution? Leveraging user behavior insights. In this guide, we cover:

• What are user behavior insights?

• The value of quantitative and qualitative data in user behavior insights

• Why it’s worth relying on user behavior insights for product changes

• Signals that reveal what users really want (and struggle with)

• How to make a case for a product change with user behavior insights

What are user behavior insights?

User behavior insights are a combination of quantitative and qualitative user data that help you understand the full experience people have in your product.

Simply put, as users move around your site or product, they leave traces and clues of what they need—and whether your product managed to fulfill that need. These traces are known as behavior analytics: the data that helps you understand how users behave and interact with your product or website.

Behavior analytics data is the pathway to user behavior insights.

User behavior insights are about the true experience users have in your product and how they feel about it, including:

• What they’re interested in and gravitate towards

• Where they get stuck and what leaves them frustrated

• What they ignore and don’t care about

And these insights can lead to product opportunities to create emotionally engaged users.

Helping users accomplish goals isn't a competitive advantage—it's table stakes. The true differentiator is having a deep understanding of your users; not just their usage or churn metrics, but how your product impacts them on a human level.

But going beyond hard data to understand users doesn’t mean you’re playing a guessing game. User behavior insights are, and always should be, unbiased, in context, and at scale so you can consistently make the right product decisions.

The value of quantitative and qualitative data in user behavior insights

Quantitative data can seem like the obvious place to start when getting buy-in for a product change. It’s hard, measurable data, like the number of task completions or clicks on a specific button or link.

Quantitative data answers the what. It shows you what’s happening in a way you can track over time and filter through different criteria. You can answer questions like:

• How long does a user take to complete a task?

• How does task completion vary between devices?

• How many people scroll below the fold of your app?

• What’s the conversion rate for users who visit your upgrade offer?

You can collect this data with PX tools like Mixpanel and Google Analytics, which are great for learning what your users go through in your product—but not what led to it or how it made them feel.

For example, users completing a task in 95 seconds isn’t inherently good or bad, and if that number grows, it’s impossible to tell why. For more context, you need to add qualitative data to the picture.

Qualitative data comes from subjective insight, including direct customer feedback (VoC) and insights from observing your users as they navigate your product.

Qualitative data answers the why. It reveals users' pain points, blockers, struggles, and motivations. It helps with questions like:

• Why are users suddenly taking 20 seconds longer to complete the task? Is there something misleading or distracting them?

• Which element on a page confuses users?

• When users don’t complete user onboarding, what do they focus on, and what do they ignore?

You can collect this data with tools like surveys and session recordings that allow you to observe hands-on user behavior. (More on this later.)

In short: quantitative data helps you identify issues and patterns in user behavior; qualitative data shows you why it happens and how it affects your users. You can’t have one without the other.

Why it’s worth relying on user behavior insights for product changes

You understand the concept of customer satisfaction: the act of meeting customer expectations in a way and timeframe they expect. It’s measured with quantitative metrics like Customer Satisfaction Score (CSAT) and Net Promoter Score® (NPS).

But then there’s customer delight: the practice of going above and beyond customer expectations. It’s about fostering an emotional connection and a sense of loyalty, which comes from creating products that are easy and enjoyable to use and provide more value than customers expect.

Delighted customers don’t leave. They also give hyper-useful feedback and become your product’s biggest advocates. They’re not just a joy to serve, but they directly impact your customer retention, revenue, and product success.

How to use behavior insights to create customer delight

Customer satisfaction is focused on ticking boxes—users complete tasks they use your product for, and your usage metrics align with industry standards.

If you make product changes based on hitting arbitrary numbers, you’re dismissing what your users truly need.

But customer delight is about proactively solving customer problems, celebrating their wins, and investing in resources to equip customers not just to complete tasks, but to have an excellent experience they want again and again.

When you make product changes to delight your users, you’re turning customers into product ambassadors.

Prioritizing customer delight (in action)

Let's say you're looking at product analytics for your email marketing app.

The app has a CTA button on the main dashboard for users to create a new broadcast email. Product analytics show the task completion rate from that CTA is low—the lowest across the entire product.

If you were only relying on quantitative data, you could start making assumptions: the button isn’t large enough; it isn’t the right color; the button copy needs spicing up.

You could make all those changes and still see a low completion rate.

But when you dig deeper with behavior insights to learn what users truly experience, you find that users often click the CTA to create a new email, then quickly leave to view the template library, the help center, and some of their previous emails—and that’s what makes their task completion rate from the main dashboard so low.

Seeing this allows you to make better changes: for example, you could make it easier for users to access the resources they need for their emails in a collapsible sidebar. Then they never have to leave their email editor, and can power through their campaigns faster and with more confidence.

Signals that reveal what users really want (and struggle with)

By now you know: user behavior insights unlock opportunities to delight customers with your product experience. But to learn what users truly crave, you need to know what to look for.

Here are some reliable user behavior signals:

Clicks and taps

Clicks and taps indicate what users interact with in your product. They show you what drives users to take action.

Standard link tracking in your website tracking or product reports only shows you how many times a specific link was clicked (and maybe the percentage of users that clicked it). What standard link tracking doesn’t show you is what else gets clicked on—or ignored—on each page.

This is where click tracking comes in. It shows you:

• The exact words users click in a link (what motivated them to click)

• Non-clickable elements they clicked on (what they think is a link, but isn’t)

• Elements they clicked on repeatedly (also known as rage clicks, often indicating user frustration or confusion)

Mouse movement

Mouse movements show you how users move their mouse on the screen as they navigate your product.

Users often follow their cursor with their eyes, making mouse movements a useful signal for what users focus on and what they ignore. This gives rich context to the time users spend on a page.

You can answer questions like:

• Are users ignoring an important element (e.g. a CTA button) because another element (e.g. an embedded screenshot) is more prominent?

• In what order do users focus on elements on the page? I.e. which elements are the most and least viewed? Is it a different order than the one you intended?

• What do users focus on on pages with high exit or bounce rates?

Scrolling

Scroll tracking refers to monitoring how far down users scroll in your product. It answers the question: are users reaching key elements of a page?

Let’s say you launch a 6-step user onboarding sequence that takes new users through key features. You learn that 75% of all drop-offs happen after the fourth step, which is significantly more than the previous steps.

Without scroll tracking, your assumption could be that step four needs better copy or an embedded video. But with a scroll map, you might learn that a UX issue pushed the suggested user action below the fold, and most users never know it’s there.

The fix is easy, and the result is massive: more happily onboarded users and a shorter path to their Aha! moments.

Navigation and page progression

The closest you can get to being in your users’ shoes is watching them move between the pages and features of your product.

Session replays (aka session recordings) make this possible.

You can watch individual sessions to understand product experience and navigation on a truly individual level, including mouse movements, clicks, taps, and scrolling for the entire session.

You’ll learn about:

• U-turns, which happen when users land on a page and immediately click the back button

• Sections they spend a lot of time on

• Rage clicks, which happen when users repeatedly click on the same element

• What happens right before dropping off or an unexpected action

• The order in which they move towards their goal with your product

• Bugs, issues, and elements that confuse users or block the user journey

In-context user feedback

Many behavior signals will tell you everything you need to know about a user's success, frustration, confusion, or indifference. But when they don't, you can rely on contextual user feedback.

User feedback gives people a way to share their product experience in their own words. It helps you answer questions like:

• Why is a user about to leave your site?

• What are they looking for after logging into your app? (And did they find it?)

• What's stopping users from using certain product features?

• What’s stopping them from completing a key step in your product?

It’s about asking the right questions at the right time, including closed-ended and open-ended questions at specific points in the user journey.

How to make a case for a product change with user behavior insights

Once you make the success and delight of your customers your goal, you and your PM team need a powerful toolkit to track the right signals and user behavior insights so you can make your case and get buy-in for product updates.

You’ll need tools that collect:

• Quantitative data, like product analytics tools, surveys for user ratings, and heatmaps

• Qualitative data, like product experience insights tools, open-ended surveys, lab usability testing, and session recordings

  Hotjar (👋 that’s us!) is a user behavior and product experience insights software that helps you empathize with and understand your users.

Learn what your users need and how they feel with:

• Heatmaps

• Session Recordings

• Surveys

• Incoming Feedback

To get complete stakeholder buy-in, you’ll need unbeatable proof of a problem or opportunity you discovered—and a proposed solution. Here’s a framework you can use:

1. Step 1:

   identify a pain point users experience within your product, a gap in your product features, or a success metric you want to improve

2. Step 2:

   find the connection between how users feel inside your product and a business outcome, like revenue or conversion rates

3. Step 3:

   map out potential results for the customer and the business if you were to make a change based on what you learned in the first two steps

Here are two examples of scenarios you can build:

Scenario #1

1. On average, 550 people fail to complete a certain task every month (you learn this using product analytics, heatmaps, and session recordings)

2. Among the people who churned in the recent months, 25% mentioned the struggle with that task as their reason to cancel (you find this out using qualitative post-cancellation surveys)

3. If you fix the issue stopping users from completing that task, you could recover $16,000 lost monthly revenue, and increase retention rate, customer delight, and referrals

Scenario #2

1. 55% of free trial users complete the 6-step onboarding they’re offered when first signing up

2. When the free trial expires and users are prompted to enter payment details, 60% of them convert into paying customers and the rest cancel; the majority (80%) of those that convert have completed onboarding (you learn this using product analytics)

3. Option 1: if you learn the reasons for onboarding drop-offs (through heatmaps, session recordings, and/or a feedback widget), you can make changes to increase onboarding completions and, as a result, conversions from free trial to paid users

4. Option 2: if you learn what detracts free trial users from converting (through in-app surveys), you can make changes that address unsolved pain points and increase conversion rates

The two scenarios above prove that you don't need to make assumptions about what users need from your product. You can ask them, observe them, and then create meaningful product changes that will delight them.