Have you ever launched a feature only to see users drop off unexpectedly? Traditional analytics might reveal what happened, but not why.

Real user monitoring (RUM) bridges that gap by tracking every click, scroll, and frustration signal—such as rage clicks or slow load times—allowing you to identify where users struggle. For product managers, this isn’t just data; it’s the key to transforming disconnected user journeys into seamless experiences.

Tools like Userpilot’s product analytics offer real user monitoring to help you gather detailed insights into each user session, ensuring you address the right issues at the right time.

But first, let’s learn more about real user monitoring.

What is real user monitoring?

Real user monitoring is a method of collecting detailed, real-time data on user interactions within your app. It captures everything from button clicks and form submissions to users’ time on specific tasks.

Think of it as a high-resolution lens that shows where users thrive or struggle during their sessions.

For example, real user monitoring can reveal that 30% of mobile users abandon a registration form because it takes 8 seconds to load, or that a poorly labeled button causes repeated rage clicks.

But not all tools deliver equal visibility.

Ideally, you’d track every user action without sampling or guesswork. However, many platforms sacrifice depth for scalability, relying on partial data or assumptions.

For instance, a basic tool might sample 10% of user sessions and extrapolate trends, missing critical friction points. Robust real user monitoring solutions, like Userpilot, capture 100% of interactions, ensuring you see the full picture: every hesitation, every bottleneck, and every Aha moment.

This distinction matters because partial data risks skewed insights. However, comprehensive real-user monitoring ties user experience (UX) flaws directly to business outcomes, like fixing a checkout flow costing you $50k/month in lost revenue.

How is real user monitoring different from synthetic monitoring?

While real user and synthetic monitoring are used to measure website and app performance, they differ significantly in their approach and use case.

• Tracking method: Synthetic monitoring simulates user behavior (e.g., bots testing a checkout flow at 2 AM). It’s like rehearsing a play in an empty theater: useful for catching expected performance issues, such as server downtime. Real user monitoring, however, observes real users in real-time, exposing unexpected friction. For example, it flags rage clicks when a promo code field fails on mobile devices.
• Use case: Use synthetic monitoring to proactively test scenarios, like simulating Black Friday traffic spikes. It’s great for establishing performance baselines. Real user monitoring, on the other hand, diagnoses real-world problems. Let’s say users in Brazil experience slow load times due to a CDN issue; RUM detects this, while synthetic scripts (running from a predefined location) might miss it entirely.

Benefits of real user monitoring

RUM transforms raw interactions into actionable insights directly impacting your product’s success. It enables you to drive better business outcomes in the following ways:

Improve UX by addressing real pain points

RUM tracks actual user interactions to help you identify pain points in real-time. This way, you can make timely adjustments.

For example, you might discover that users on iOS devices abandon their carts 3x faster than Android users because of a hidden lag during payment processing. Or, session replays could show that 40% of new users rage-click a non-interactive element, mistaking it for a button.

In each case, you know what pain point to solve to reduce friction and improve your UX.

Resolve issues faster with contextual insights

Traditional debugging relies on vague user reports (“The app is slow!”). Real user monitoring eliminates the guesswork by showing you where and why problems occur. This visibility allows you to prioritize which performance issues to fix first and resolve them before they escalate.

Let’s say your Net Promoter Score (NPS) metrics drop suddenly: RUM data might reveal that a recent update caused JavaScript errors for Chrome users, leading to broken workflows. With real-time alerts and granular segmentation (e.g., filtering by browser, location, or device), you can diagnose issues in minutes, not days.

Make data-driven decisions that align with business goals

You can use real user monitoring to adopt a data-driven analysis approach because it turns abstract user behavior into measurable metrics. With this data, you can create a comprehensive view of how your users are interacting with your product.

For example, if your goal is to improve upselling, RUM can track how often users interact with premium feature prompts, and see where they drop off. Or, you can discover that simplifying your project dashboard (based on low engagement metrics) retains more customers.

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How to set up real user monitoring in 5 steps

Setting up RUM doesn’t have to be complicated. The key to setting up RUM is to break the process into manageable stages so you can focus on what matters most: gathering accurate, real-time insights about how users interact with your product.

Define clear objectives

Implementing a goal-setting framework is the first step to ensuring your real user monitoring efforts yield actionable insights.

A goal-setting framework offers a structured approach to establish and achieve your goals.

Ask yourself which metrics matter most to your team. It may be conversion rates, user satisfaction, or something else entirely. If, for instance, your onboarding flow has high drop-off rates, make it a priority to track relevant user behavior.

Next, focus on the most impactful performance metrics and user journeys—such as registration processes, onboarding flows, or core feature adoption—to have a clear roadmap of what to monitor and improve. This helps you avoid data overload and stay focused on business objectives.

Choose a holistic RUM solution

Select a real user monitoring tool that does more than track basic events. Most tools already do that.

Basic event tracking involves capturing button clicks or page loads in real-time, but that data alone isn’t always enough to understand why users abandon a crucial workflow.

Look for a solution that pairs “in the moment” monitoring with features like session replays so you can reconstruct user actions and understand the full context of their experience.

A session replay feature helps you see where users struggle or drop off, giving you deeper insight into the “why” behind each event.

Insert the code snippet to track in-app events

You can manually insert code snippets to track specific in-app events. But this approach often fails to capture the entire user journey.

Instead, choose a tool with auto-capture capabilities that automatically records all user interactions with your product. So that you can track every click, form fill, and navigation path automatically.

Userpilot’s autocapture feature helps you streamline data collection and gain comprehensive insights into user interactions. This means you can focus on analyzing user journeys to uncover friction points and increase engagement, rather than spending valuable time writing and maintaining code.

Visualize the collected data through dashboards and reports

Effective dashboards combine session recordings with various report types to reveal actionable trends.

For example, funnel reports can pinpoint drop-offs like a 40% exit rate at “Step 3: Payment Details” in your signup flow. Pair this with session replays to see why users leave: maybe a hidden loading spinner or a confusing form field.

Analyzing these visual insights lets you quickly identify where users struggle and correlate these patterns with performance issues.

Make data-driven decisions to optimize the user experience

Prioritize fixes by focusing on issues affecting the largest segments of your user base.

For example, if real user monitoring reveals that 20% of mobile users abandon a checkout flow due to a laggy address autofill feature, fix that first; not a niche bug impacting 0.5% of users.

Pairing quantitative data with contextual solutions helps you get the entire picture. Let’s say users skip a key feature because it’s buried in your UI: add in-app guidance like a tooltip or interactive walkthrough to drive product adoption.

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