UX Analytics 101: How to Collect and Use User Data in SaaS (+Best Tools)


What does the term UX analytics stand for? How do you perform UX analysis for SaaS and make data-driven decisions?

This article will guide you through every important aspect of collecting and utilizing user behavior data to drive product growth.

You will learn how to spy on users’ experiences in real time and turn insights into a data-driven design that will help to improve activation and customer retention rates.

Let’s dive in.


  • UX analytics refers to analyzing how the users engage with your product UI and their overall experience while using the product.
  • Always use both UX analytics quantitative and qualitative data for better insights.
  • In-page UX analytics data tracks click data and tells you exactly which features your users are engaging with.
  • User journey and funnel analytics tools show you at which steps in the user flow friction and churn happen.
  • Use heatmaps to identify what’s dragging customer attention on the UI and what’s ignored.
  • Session replays let you fully understand the way users engage with your product and capture friction points.
  • For effective UX analysis, categorize and tag all data points to turn qualitative data into quantitative data and uncover patterns.
  • Prioritize bug fixing and updates based on what will lead to the biggest outcomes. Break down all problems into four categories: blocker, critical, medium, and low.
  • Use story mapping before designing and coding the final solution to visualize potential user flow and put brainstormed ideas on paper.
  • After updating the product, run A/B-tests and NPS surveys to catch and refine minor drawbacks.
  • If you’re looking for an all-in-one UX analytics tool, Userpilot is the one to go for. It allows you to tag features, conduct funnel analysis, analyze heatmaps, and add feedback widgets to the UI. Book a demo to learn more.

What is UX analytics?

UX analytics stands for user experience data and it’s all about gathering and interpreting data about user behavior on a website or in-app by tracking actions like:

  • Moves of a cursor(mouse) within web pages
  • How many times the user clicks on the button
  • How fast do users get to an “Aha!” moment
  • How much time do customers need to complete specific tasks

It enables you to spot friction points in the user journeys and make it seamless to optimize conversion rates and customer experience with your product.

Qualitative data analytics vs. Quantitative data analytics

There are two methods of user research — qualitative and quantitative. They complement each other and can not be substituted.

Quantitative analytics is all about quantifying the experience in numbers. Good or bad, neutral, very bad, etc. But it doesn’t tell you the why behind it.

Qualitative UX data analytics tells the logic of the user experience with a web app. If simplified, qualitative UX research data help product managers figure out the answer to why some users interact with your product in a particular way.


Qualitative data analytics vs. Quantitative data analytics

There are three popular methods of doing qualitative UX analysis:

  • One-on-one customer interview
  • Customers’ observation (session replays)
  • Open-ended surveys

All together, UX analysis using both types of data enables you to make data-driven design decisions to reduce churn and create an unforgettable user experience.

Why is it important to track UX analytics data?

If you want to make product updates that matter to users and lead to revenue growth, you must remove friction in the user flow and build the best experience.

Therefore, you need the data to rely on —quantitative (to spot how frequently and where customers encounter issues) and qualitative (to get answers to why users find it difficult to interact with concrete product features).

Below we’ll go through three common use cases where UX analytics data helps.

Identify issues in the user journey and reduce exit rates

Product bugs and hard-to-navigate UIs are one of the main reasons customers abandon your app.

UX analysis helps you to anticipate and reduce friction points in your product.

By implementing heatmaps, session replay, or open-ended surveys, you understand where the users get stuck and why. Act on those insights and you will reduce exit rates.

Inform design decisions and improve the product based on insights

If you don’t understand where friction happens, how do you know what should be fixed?

There’s a saying, “what gets measured gets managed.

Use quantitative data visualization to find actionable insights on problematic areas and prioritize the next sprints accordingly.

Identify bugs with ”rage clicking” tracking

In short, rage clicking is when a user desperately clicks in the same spot on the website (or in-app), expecting something to happen that isn’t happening. It’s a straight indicator of a bug or bad UI.

Seize such moments and fix the nature of rage clicking to prevent users from abandoning your product.

How to collect user behavior analytics data?

Here’s how to find repetitive problems in UX, how to map user behavior and unravel pain points, and how to perform usability testing.

In-page web analytics UX tools

Having measured and compared how many times users click on some UI elements in a product, such as filters or specific buttons, we grasp the level of likability of one or the other feature.

“Okay, but how to actually track that?” — you may ask me.

Use Userpilot feature tagging. This allows you to select any UI element on a website or web app without writing any code and then track the number of clicks, directly inside the dashboard.

Feature tagging in Userpilot

Feature tagging in Userpilot

User journey and funnel analytics tools 

If customers run into bugs, misleading UX, broken links, or other obstacles that slow down their progress, they’re likely to churn. As product managers, we must be aware of such issues in real-time to fix them ASAP.

That’s when funnel analytics tools come into play.

They gather the number of users who completed important steps in the user flow day in, and day out and highlight potential gaps.

While Google Analytics can help with funnel analysis, we recommend an advanced web analytics tool like Userpilot. The funnel analysis feature helps in analyzing user behavior across the customer journey. It helps you spot friction and where users drop off from the journey.

Unlike other analytical tools, you can act on the insights with Userpilot’s engagement features. Book a demo to learn more.

Funnel analysis in Userpilot

Funnel analysis in Userpilot

User feedback widget tools 

There’s a category of widgets designed for continuous user feedback collection. We call them the “always-on” widget.

Usually, it’s a small icon floating on the UI that lets users give feedback on specific features or experiences whenever they feel like that.

Feedback widget in Userpilot

Feedback widget in Userpilot

What’s cool is that you can bond unique one-question surveys with different product pages and receive very precise feedback.

Using tools like Userpilot, you can embed these into your product without the need to code them from scratch.

A survey that appears after clicking on the widget button on Userpilot.

A survey that appears after clicking on the widget button on Userpilot

Heatmaps analytics tools 

I love heatmaps a lot. Let me explain why.

When designing a site, we anticipate user experience and try to adjust color patterns, the place of every element, illustration, etc., to deliver value to the end-user. But how do we know what UI elements on our website are indeed drawing attention?

To figure it out, you can use Userpilot’s heatmaps.

Userpilot empowers product teams through feature heatmaps, enabling visualization of user interactions with product elements for improved customer experience.

Its main features include tagging for monitoring user interactions (clicks, hovers, text inputs), analyzing heat maps by user segments to enhance personalization, and tracking interaction changes across time periods for effective insights.


Userpilot heatmap analysis

Session recordings analytics tools

Then there are the session replays you can use.

Record user sessions in real-time to replay them and analyze user engagement with your product at different steps through their journey.

You can spot rage-clicking, broken links, misleading marketing messages, insufficient product hints, etc.

These help to understand the why.

Hotjar is the best UX analytics software for this purpose.


Hotjar session recording analytics

Usability testing tools

Usability testing is more about in-person interactions with a group of customers or individuals.

Use this to get in-depth insights into how customers experience a product and what should be changed to accelerate activation or facilitate product adoption.

Literally, product managers watch how a user is engaging with their product, ask leading questions, and document every little detail.

You can also conduct usability tests remotely through tools like Maze.

Usability testing in Maze

Usability testing in Maze

Questions that UX analysis help answer

Before we move further and find out how product managers utilize collected data, let’s double-check our findings. An effective UX analysis will unlock insights into:

  • How do users expect to interact with your site or app?
  • How easy is it for users to switch between the most used features?
  • What’s the shortest path to value?
  • What are the friction points in the user journey?
  • What’s the most used part of the product, and how do users engage with it?
  • Are there any bugs deteriorating the user experience?
  • Which user behavior is correlated with power users?

If we’re all set and have answers to all these questions, let’s jump to the next chapter.

Steps to performing a UX analysis after collecting UX data

Once you’ve collected the user behavior data, how do you act on those insights?

Here are six essential steps to get from unstructured data points to an updated roadmap and feature release plan, using the data.

1. Identify main issues using qualitative user research data

Although it sounds simple and obvious, it’s hard to apply. Imagine how many data sets you will gather by recording sessions and analyzing heatmaps and answers from the “always-on” widget.

Not to drown in the ocean of data, identify big issues using quantitative data, and then get insights from qualitative analysis data to understand the main reasons for churn. Check important milestones in the journey and:

2. Organize and tag issues

Let’s say that our goal is to optimize the conversion rate to signups. To this moment, once a user clicks on “Create an account,” we ask them some qualification questions like company name, headcount, industry, role, etc.

For some reason, new registrations have been dropping for a week.

Our first step to cracking it is to identify the issue. Next, look at session recordings or heatmaps to understand customers’ flow.

Plus, launch in-app surveys when a user moves the mouse to close the tab. Ask them why are they abandoning the page and offer help.

As soon as we have completed the qualitative analysis, let’s turn it into a quantitative one. To do that, create categories and tags so we can calculate and prioritize issues:

  • Category: signups, activation, upgrading
  • Tag 1 (what’s wrong): link, button, content
  • Tag 2 (outcomes): hesitation, exit, anger

If you want to identify patterns and anticipate churn, try using NPS surveys and tag recurring themes in responses.

NPS survey tag analytics, Userpilot

NPS survey tag analytics in Userpilot

3. Check for recurring issues using qualitative data

The NPS survey report above is not only for identifying an issue at the moment but also for recognizing recurring or more complex issues that are causing friction.

As illustrated, users are complaining about missing features. If something was fixed before and complaints are still piling up, we need to get another round of watching session recordings or conduct in-person usability testing.

4. Prioritize fixes

This is the most tricky point for product managers. Would you add bug fixes for 100 user requests to the next sprint or 123 requests for a new feature, or maybe three different bug-fixing requests with lower numbers?

Remember one thing: bugs appear every time in different features. Sure thing, we have to fix them all but prioritizing goes a long wait to save your resources.

I recommend dividing all bugs into four categories:

  • Blockers: a problem that blocks the full functionality of the product — it must be solved instantly.
  • Critical: the issue makes it impossible to use a decent part of a feature. For instance, we can create a report but cannot filter it.
  • Medium: inconveniences that will irritate users long term and cause them to churn.
  • Low: customers are annoyed by minor issues that don’t expose experience.

5. Brainstorm solutions using story mapping

Story mapping is a way of visualizing a potential user path. Once we combine quantitative and qualitative data, we pinpoint the problem.

The next step is to look at the whole picture and how exactly a new feature or bug fix will affect the product experience. Story mapping helps us glimpse into the future and anticipate a user path, breaking it down into activities.

Eventually, we create a skeleton (draft) for UX design and development that will fix the problems we uncovered.

6. Implement and test

It’s time to build a new feature and test it in the wild. There are three essential steps for seamless product updates:

  1. Code the solution users are waiting for.
  2. Launch in-app surveys to measure customer satisfaction.
  3. Analyze collected data and refine launched features in the next sprints.


Don’t neglect to conduct UX analysis if you aim to build a product that customers will love.

Want to get started with UX analytics? Get a Userpilot Demo and see how you track feature usage using feature tagging, launch in-app surveys to collect feedback data, and more.

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