Learn How Real User Monitoring Can Transform Your Digital Strategy

In today’s digital landscape, where more than 4.9 billion people are connected to the internet, the quest for optimal performance in online services has never been more critical for businesses. Tools like Real User Monitoring (RUM) emerge as essential solutions, enabling companies not only to track the technical performance of their applications but also to deeply understand how users interact with their services in real time.

This detailed and immediate monitoring not only prevents potential service failures but also optimizes the user experience, leading to an increase of up to 15 to 20% in operational efficiency and customer satisfaction, as highlighted in recent studies, such as research by Gartner.

Real User Monitoring is an evolution in the field of application monitoring, allowing for a deep understanding based on real data of how end-users interact with a system. In this article, we’ll cover the concept of Real User Monitoring, its benefits, implementation challenges, the best tools and practices, and the importance of data security and privacy. An essential read for anyone looking to transform their digital strategy.

What is Real User Monitoring?

Real User Monitoring (RUM) is a monitoring technique that collects data directly from the interactions of end-users with a website or application. Unlike synthetic monitoring approaches, where automated scripts simulate user interactions, RUM observes and records actual user actions in real time, providing valuable insights into user behavior, application performance, and, consequently, the quality of the experience offered.

Through RUM, it is possible to monitor various aspects of the user experience, including:

• Page load times: Measures the time it takes for pages to fully load in the user’s browser.
• Error rates: Detects and records errors that users encounter while navigating the application.
• User engagement: Analyzes how users interact with the application, which features they use most, and where they encounter difficulties.
• Geographic performance: Assesses how the user’s geographic location affects their experience due to factors like network latency.

This data allows development, operations, and marketing teams to better understand how different factors impact the end-user experience and make proactive adjustments to improve customer satisfaction and optimize application performance.

What Are the Main Tools and Techniques Used in Real User Monitoring?

It is difficult to say which Real User Monitoring tool or technique is the most accurate, but all the ones we will mention are widely recognized and positively evaluated in different usage contexts. The choice of RUM tool or technique depends on your company’s specific requirements, such as infrastructure complexity, the need for integration with other tools, and monitoring objectives. Success in implementing RUM often depends more on proper configuration and efficient integration with other data analysis techniques than on the choice of a specific tool.

Below are some of the main tools and techniques associated with real user monitoring.

New Relic Browser

New Relic Browser is one of the most popular RUM tools, offering detailed monitoring of application performance directly in the user’s browser, allowing you to visualize page load times, identify performance bottlenecks, and monitor JavaScript errors in real time.

• Key features: Response time monitoring, performance analysis by geographic location, JavaScript error detection.
• Strengths: Highly popular for its ease of use and integration with other New Relic solutions, intuitive interface, and detailed user interaction monitoring capabilities.

Dynatrace

Dynatrace offers a performance monitoring platform that includes RUM as part of its comprehensive solution. It enables real-time monitoring of all user interactions with the application, providing detailed insights into the customer experience.

• Key features: User session monitoring, real-time traffic analysis, performance tracking by device and browser.
• Strengths: Widely used in large organizations due to its ability to provide comprehensive and integrated application monitoring, including RUM. Integration with APM and artificial intelligence for automatic problem detection.

AppDynamics

AppDynamics is a robust RUM solution that integrates with its Application Performance Monitoring (APM) platform. It provides a holistic view of application performance and its impact on end-user experiences.

• Key features: End-to-end transaction tracking, user session analysis, performance monitoring by browser and device.
• Strengths: Used in large organizations for its ability to provide comprehensive and integrated application monitoring, including RUM. Integration with APM and AI for automatic problem detection.

Google Analytics (Complemented with RUM)

While better known for its traffic analysis capabilities, Google Analytics can be complemented with custom scripts to perform RUM. This approach allows monitoring user experience and understanding how performance affects user behavior.

• Key features: User session monitoring, real-time traffic analysis, performance tracking by device and browser.
• Strengths: Widely adopted for its affordability and familiarity with the Google Analytics interface, good integration with web analytics data, although it requires custom configuration for RUM.

Catchpoint

Catchpoint is a tool focused on performance and digital experience monitoring, with a robust RUM module. It provides a clear view of how performance affects user experience in different geographic locations and on various devices.

• Key features: Real-time monitoring, customizable data visualization, user experience analysis by location and device.
• Strengths: Preferred by companies needing detailed performance and availability monitoring in different geographic regions, with strong geographic latency monitoring and real-time performance capabilities.

Which of These Tools Should You Use?

For large organizations with complex infrastructures, tools like Dynatrace and AppDynamics are often considered more reliable due to their ability to integrate RUM with Application Performance Monitoring (APM) and other advanced features.

If you are looking for ease of use and integration with other monitoring or analytics platforms, New Relic Browser and Google Analytics are popular and reliable choices. For companies requiring detailed regional monitoring, Catchpoint is often considered one of the best, especially for global businesses.

When it comes to techniques used in real user monitoring, the most popular are:

JavaScript Injection

One of the most common techniques for implementing RUM involves injecting JavaScript scripts directly into the web application’s code. These scripts collect performance data and user interactions, such as page load times, clicks, and navigation. Most RUM tools use this technique to collect data directly from the user’s browser, allowing for real-time monitoring.

Session Analysis

Session analysis involves monitoring and recording complete user sessions, allowing development and support teams to see exactly how users are interacting with the application. Tools like Dynatrace and AppDynamics use this technique to track and analyze user behavior, identifying specific issues affecting the user experience.

Monitoring Web Vitals

Web Vitals are a set of metrics created by Google that measure essential aspects of the user experience, such as the time to the first contentful paint (FCP) and interactivity (First Input Delay – FID). RUM tools often monitor these metrics to ensure the application meets the necessary performance standards for a good user experience.

Monitoring JavaScript Errors

Collecting and monitoring JavaScript errors in real time is essential for understanding issues that may be affecting the user experience, such as failures in rendering page elements or broken interactions. Tools like New Relic Browser capture JavaScript errors, allowing teams to quickly fix issues affecting users.

User Geolocation

Monitoring performance based on the geographic location of users is important for understanding how factors such as network latency and distributed servers impact the experience. Tools like Catchpoint offer geolocation features, enabling detailed analysis of performance by region.

How Can Real User Monitoring Benefit Businesses?

By identifying performance bottlenecks and allocating resources more efficiently, Real User Monitoring helps companies optimize their operational costs. This is especially important in large organizations, where reducing inefficiencies can result in substantial savings. RUM also helps avoid unnecessary infrastructure spending by focusing on specific areas that truly impact the user experience.

Below are some of the key benefits of RUM for businesses, along with practical examples of how it can be applied.

Improving User Experience

RUM provides a detailed real-time view of user behavior, allowing for quick identification of performance issues such as slow loading times and page errors. This results in a smoother user experience and consequently increases customer satisfaction. For example, an online store notices that users are frequently abandoning their shopping carts. Using RUM, the company discovers that the issue is excessive loading time on the payment page, causing frustration and drop-offs. By optimizing this page, the company reduces abandonment rates and increases conversions.

Reducing Operational Costs

RUM helps identify performance issues before they affect a large number of users, enabling the IT team to resolve problems proactively and collaboratively. This reduces the costs associated with technical support and revenue loss due to downtime or poor performance. A practical example: a video streaming platform uses RUM to monitor service quality in different regions. By identifying that users in certain areas are experiencing excessive buffering due to network latency, the company adjusts its content delivery strategies, improving service quality without the need for extensive technical support interventions.

Data-Driven Decision Making

RUM provides valuable data on how users interact with an application or website, allowing companies to make more informed decisions about where to invest resources for improvements. For example, a SaaS software company uses RUM to monitor the frequency and behavior of users in different parts of its application. They discover that a specific feature is rarely used, and when it is, users face performance issues. The company decides to discontinue this feature and redirect resources to improve the more popular parts of the application, resulting in greater user satisfaction and better ROI.

What Are the Main Indicators That Can Be Analyzed with Real User Monitoring?

A Gartner study shows that 70% of digital business initiatives in large organizations will require Infrastructure and Operations (I&O) leaders to report on digital experience metrics by 2025, a significant increase compared to less than 15% in 2020. The research demonstrates the growing importance of monitoring performance and user experience indicators, especially in large companies, to ensure operational effectiveness and customer satisfaction.

Indicators monitored through Real User Monitoring provide a detailed view of how users interact with an application or website in different contexts. Below are the main indicators that can be analyzed with RUM:

Time to First Byte (TTFB)

Measures the time it takes for the user’s browser to receive the first byte of data from the server after a page request.

• Importance: A high TTFB can indicate performance issues with the server or network, negatively affecting the user experience.
• How RUM Helps: Monitors TTFB in real time, allowing companies to identify and resolve latency issues before they affect a large number of users.

First Contentful Paint (FCP)

Measures the time from the start of page loading until any content (text, image, etc.) is rendered on the screen.

• Importance: An important indicator of how quickly users perceive that the page is loading, impacting their first impression.
• How RUM Helps: Monitors FCP in different contexts, helping optimize the initial content load to improve the user’s perception of performance.

First Input Delay (FID)

Measures the time between the user’s first interaction with the page (e.g., clicking a button) and the moment the browser responds to that interaction.

• Importance: A high FID can result in a frustrating experience, as the user may perceive the page as slow or unresponsive.
• How RUM Helps: Allows monitoring FID to identify and resolve interactivity issues, especially on mobile devices where these problems tend to be more common.

Cumulative Layout Shift (CLS)

Measures the total sum of all unexpected layout shifts that occur during page loading.

• Importance: Unexpected layout shifts can lead to a poor user experience, where elements move unexpectedly, causing incorrect clicks or making reading difficult.
• How RUM Helps: Monitoring CLS with RUM helps companies identify and minimize these shifts, improving the visual stability of the page.

Session Abandonment Rate

Measures the percentage of users who abandon the session without significantly interacting with the page.

• Importance: A high abandonment rate may indicate problems with site speed, usability, or even content.
• How RUM Helps: Correlates the abandonment rate with other indicators, such as loading time or page errors, helping to identify the underlying causes and take corrective action.

What Are the Best Practices for Implementing Real User Monitoring?

Effective implementation of Real User Monitoring requires a strategic approach involving clear objective setting, careful tool selection, and integration with other monitoring practices. By following these best practices, companies can ensure that RUM provides valuable insights. Here are some best practices for implementing RUM in an application or website:

Define Clear Objectives

Before starting implementation, it is necessary to define what you want to achieve with RUM. This may include improving page load times, reducing abandonment rates, optimizing the user experience on mobile devices, among others. In practice, it is essential to identify the key success metrics (KPIs) that will be monitored and use these metrics to guide the configuration and interpretation of RUM data.

Choose the Right Tool

As mentioned earlier, there are several RUM tools available, each with its own characteristics and capabilities. The choice of tool should be based on the defined objectives, the size of the application, and the complexity of monitoring needs. Therefore, evaluate different RUM tools (such as New Relic, Dynatrace, or Google Analytics with custom RUM) to find the one that best aligns with your goals and existing infrastructure.

Implement Gradually

Implementing RUM gradually allows the IT and development teams to better understand the data collected and make adjustments as needed without negatively impacting site performance. Therefore, start with RUM implementation on a critical part of the site or application and, based on the results, expand monitoring to other areas.

Monitor Specific Metrics

Avoid monitoring all possible metrics; instead, focus on the metrics most relevant to your objectives, such as page load times, First Input Delay (FID), or Cumulative Layout Shift (CLS). Do not forget to set up alerts and reports for key metrics and keep the focus on those that most impact the user experience and business results.

Analyze Data by Segments

Different user segments (e.g., by device, geographic location, browser) may have different experiences when interacting with the application. Therefore, use data segmentation to identify specific issues that may be affecting a particular group of users. This helps implement targeted fixes and optimizations.

Conduct Tests in Production Environments

Since RUM collects data from real users, it is important to ensure that the implementation does not negatively affect application performance in production. Before launching the full implementation, conduct tests in a production environment to ensure that RUM functions correctly without impacting the user experience.

Continuously Review and Adjust

The effectiveness of RUM depends on continuous reviews and adjustments based on collected data and changes in business objectives. Whenever possible, conduct periodic reviews of RUM data and adjust the implementation as needed to address new challenges and opportunities.

Educate the Team

It is essential that the entire team involved understands how RUM works and how to interpret the data collected. Provide training and workshops for IT, development, and marketing teams, ensuring everyone is aligned with the objectives and knows how to use RUM data to improve the application.

How to Ensure Privacy and Security in Real User Monitoring?

Real User Monitoring collects data directly from user interactions with an application or website, raising important privacy and security concerns. A notable case was the data breach of British Airways. In 2018, the company was fined £183 million by the UK’s Information Commissioner’s Office (ICO) after a data breach exposed the personal and payment information of approximately 500,000 customers.

The breach was partly attributed to failures in implementing monitoring scripts, including RUM, which allowed hackers to intercept users’ payment data. This incident underscored the critical importance of ensuring that any RUM implementation follows best security and privacy practices, such as data encryption and proper access control, to prevent such breaches from occurring.

Below are the key strategies to ensure privacy and security in real user monitoring:

Compliance with Privacy Regulations

Data protection regulations, such as the GDPR (General Data Protection Regulation) in Europe and the CCPA (California Consumer Privacy Act) in the United States, establish strict requirements on how user data can be collected, stored, and used.

• User Consent: Ensure that users are aware of the RUM data collection and obtain explicit consent, especially for data that may be considered sensitive.
• Clear Privacy Policy: Update your company’s privacy policy to include information about the use of RUM, detailing what data is collected, how it is used, and how users can manage their preferences.
• Legal Analysis: Consult the legal team to ensure that RUM implementation complies with all applicable data privacy laws.

Data Anonymization

Anonymizing collected data is an effective way to protect user privacy by ensuring that personal information cannot be linked to a specific individual.

• IP Masking: Mask or truncate IP addresses to prevent direct identification of users.
• Exclusion of Personal Data: Avoid collecting directly identifiable personal data, such as names, email addresses, phone numbers, or other sensitive information.
• Data Hashing: Use hashing techniques to encrypt data before storing it, ensuring that even if the data is compromised, it cannot be easily reversed to its original form.

Access Control and Data Security

Data collected by RUM must be protected against unauthorized access and security breaches. This includes implementing strict access controls and robust security practices.

• Encryption: Use encryption to transmit and store RUM data. This helps protect data from interception during transmission and unauthorized access at rest.
• Role-Based Access Control (RBAC): Implement RBAC to ensure that only authorized users have access to RUM data, limiting access based on the needs of their specific roles.
• Audit and Logs: Keep detailed records of who accesses RUM data and when, facilitating security audits and incident investigations.

Data Minimization

Collecting only the data strictly necessary to achieve RUM’s objectives is a fundamental practice to reduce risks associated with privacy and security.

• Selective Collection: Configure RUM to collect only the metrics and information essential for performance and user experience analysis. Avoid collecting excessive or irrelevant data.
• Limited Retention: Establish data retention policies that limit the time RUM data is stored. Delete or anonymize old data that is no longer needed.

Transparency with Users

Being transparent about how users’ data is collected and used is crucial for building trust and maintaining compliance with privacy regulations.

• User Information: Inform users about the use of RUM through consent banners, cookie notifications, and dedicated sections in the privacy policy.
• Opt-Out Option: Provide users with the option to opt-out of having their data monitored by RUM, respecting individual preferences.

How to Combine Real User Monitoring with Other Data Analysis Techniques?

Integrating Real User Monitoring with other data analysis techniques can provide a more comprehensive and in-depth view of application performance and user experience. A Gartner survey notes that companies that combine RUM with other techniques, such as Synthetic Monitoring and Digital Experience Monitoring, report a significant improvement in visibility and control over user experience, resulting in a 15 to 20% increase in operational efficiency. Here are some ways to combine RUM with other data analysis techniques:

RUM + Application Performance Monitoring (APM)

APM focuses on monitoring application performance from the backend, including servers, databases, and APIs. By combining APM with RUM, it is possible to correlate backend performance data with end-user experiences.

• Root Cause Diagnosis: If users are experiencing slowdowns or errors, APM can help identify if the issue is related to the server, database, or application code.
• Comprehensive Optimization: By combining RUM (user experience) with APM (technical performance) data, it is possible to optimize both the interface and the backend to improve the overall user experience.

Practical example: An e-commerce site notices that the checkout page is slow for many users. While RUM identifies an increase in loading time, APM reveals that a database query is taking longer than expected. With this information, the team can optimize the query and improve the checkout page’s performance.

RUM + Session Analysis and Heatmaps

Session analysis and heatmaps provide visual insights into how users interact with a page, showing where they click, scroll, and which areas they ignore. When combined with RUM, this offers a complete view of how performance issues affect user interaction.

• Friction Identification: Combining RUM with heatmaps allows you to identify whether frustration areas (such as unregistered clicks or excessive scrolling) are related to performance issues.
• Usability Improvement: Combined insights help optimize content layout and navigation experience, considering both performance and user behavior.

Practical example: A heatmap shows that many users repeatedly click on a button without a response. RUM indicates that there is a delay in the button’s response time due to a slow JavaScript script. With this data, the company can fix the script and improve the button’s usability.

RUM + Predictive Analysis

Predictive analysis uses machine learning techniques to predict future behaviors based on historical data. Integrating RUM with predictive analysis can help forecast how performance changes may impact user experience and business outcomes.

• Proactive Problem Prevention: Anticipate performance issues before they affect users, allowing proactive fixes to be implemented.
• Resource Optimization: Predict when traffic spikes may cause performance issues and adjust infrastructure resources as needed.

Practical example: Based on RUM data, predictive analysis suggests that a traffic increase during a marketing campaign could lead to significant performance degradation on the site. The company can then increase server capacity or optimize content before the campaign.

RUM + User Feedback

Direct user feedback, such as satisfaction surveys and reviews, can be combined with RUM to provide additional context to performance data.

• Deep Impact Understanding: Correlate performance data with user perception of the experience, offering insights into how technical performance is impacting satisfaction.
• Better Prioritization: Prioritize fixes and improvements based on perceived user impact, maximizing resources and ROI.

Practical example: Users report that a specific page seems “slow.” RUM confirms that the loading time is longer than expected. By combining these insights, the technical team can focus on optimizing this page to improve user satisfaction.

RUM + A/B Testing

A/B testing involves comparing two or more versions of a page or feature to determine which performs better. Combining RUM with A/B testing allows understanding how changes in technical performance impact the test results.

• Impact Validation: Check if performance improvements result in better user behavior and conversion rates.
• Data-Driven Optimization: Adjust the user experience based on real performance and interaction data rather than assumptions.

Practical example: During an A/B test of a new checkout page, RUM reveals that version B has significantly lower loading time. Web Analytics shows that this version also has a higher conversion rate, validating that the performance improvement is directly correlated with better business results.

Combining Real User Monitoring with other data analysis techniques allows for a more complete understanding of the user experience and application performance. This integrated approach helps companies identify and resolve issues more effectively, optimize the user experience, and make more informed and targeted business decisions.

Success Stories

Netflix: Optimizing Streaming Experience

Netflix needed to ensure a high-quality streaming experience for millions of users worldwide, especially during traffic peaks. They faced the challenge of monitoring performance on different devices, networks, and geographic regions. Netflix implemented a RUM solution to monitor streaming quality in real time, including metrics such as buffering time, latency, and perceived video quality by users. They were able to quickly identify specific issues, such as latency in certain regions or devices facing performance difficulties.

By optimizing content delivery based on RUM data, Netflix significantly reduced buffering time for its users, resulting in a smoother viewing experience. The improved experience also led to increased customer satisfaction and higher user retention, especially in markets where network latency was previously an issue.

Airbnb: Improving Mobile User Experience

Airbnb faced challenges in ensuring a consistent user experience on its mobile platform, especially considering the diversity of devices and networks used by its customers worldwide. The company used RUM to monitor its mobile application’s performance in real time, collecting data on page load times, API performance, and user interactions, segmenting this data by device, operating system, and location.

With the insights provided by RUM, Airbnb was able to identify and optimize parts of the application that were negatively impacting load times, especially on older mobile devices. Performance improvements led to a faster and smoother user experience, resulting in increased conversions, with more users completing bookings.

In an increasingly competitive digital environment, being data-driven is not just a strategic advantage but a necessity to ensure operational excellence and customer satisfaction. Data-driven decisions allow companies to quickly identify improvement opportunities, optimize resources, and deliver a superior user experience. Objective stands out as an expert in this field, providing solutions that turn data into actionable insights. Contact our experts and find out how we can help you.