What is end user experience monitoring (EUEM)?

IT teams engage in application performance monitoring (APM) and network performance monitoring to evaluate the technical operations of their service, but understanding the end user’s point of view is key to analyzing the functionality of products and features. EUEM helps to make applications more reliable and efficient while providing a better user experience.

To gain a comprehensive understanding of the end-user experience, EUEM tools collect and aggregate data that relates to the entire user journey, including the performance of end-user devices, applications and networks. It is important to remember that an end user can refer to both an external customer who is using a product, application or feature as well as an employee.

End user experience management tools offer dashboards with real-time analytics that help IT departments gain end-to-end visibility into service delivery with capabilities for real-time performance monitoring, network connectivity monitoring, root cause analysis of performance issues and the automated remediation of those issues. 

With a stronger understanding of external customer and employee experiences with enterprise IT resources, organizations gain greater observability over business operations. This helps identify bottlenecks and other performance issues, monitor the productivity of remote work, offer better products and services and ultimately improve business outcomes, among other benefits.

EUEM is part of the greater digital experience monitoring (DEM) ecosystem. While DEM focuses on both application performance and user experience, EUEM prioritizes performance metrics and monitoring strategies—like network latency, application downtime, gateway monitoring, web application monitoring, device performance monitoring, regional monitoring and SaaS monitoring—that reflect the end user experience.

There are a number of end user experience management tools and approaches organizations can employ to monitor IT services. Such tools are designed to give IT departments the information needed to resolve issues on the back end and keep services running smoothly. This includes data on app usage and performance, network traffic and speeds, endpoint performance and more—all factors that ultimately influence the end user experience.

A platform that can combine active and passive monitoring approaches, as well as insight into application, device and network performance, helps construct a more comprehensive picture of the end user experience.

Real user monitoring logs real user interaction with an application, web page or service. This type of monitoring can give IT teams visibility into user behavior as well as page load times, the bounce rate—the number of users who leave a site immediately after landing on a page—the top pages or applications used and if any part of the business process is not functioning as expected. Real user monitoring leverages JavaScript code to trigger the collection of data based on set metrics.

An advantage of real user monitoring is that organizations are dealing with real data from real users. Compared to synthetic monitoring, real user monitoring might provide a more accurate representation of the user journey. On the other hand, because this method uses real-time data, organizations are often reacting to issues after the fact, rather than implementing proactive solutions that address hypothetical problems highlighted in synthetic monitoring tests.

Application performance monitoring tracks IT services through the performance of web applications, mobile apps and SaaS applications. APM tools help track metrics like error rates, downtime and response time. These metrics give service providers insights into application performance and availability and how quickly they are troubleshooting issues as they occur.

Synthetic monitoring allows IT teams to run automated tests of the services provided to maintain optimized performance. Unlike RUM, synthetic monitoring or synthetic testing does not rely on real users. Instead, it is used to create tests with different variables such as user geographic location, network types and different devices intended to simulate the engagement of unique users.

Synthetic monitoring is particularly useful in the development stage and can be used to test multiple scenarios that aid in the optimization of products before they are launched. Data collected from synthetic testing can be used to proactively identify performance bottlenecks that could impact user satisfaction.

Sometimes called endpoint monitoring, device performance monitoring pertains to the collection of data from various user devices including computers, on-premises servers, mobile devices and network connected devices such as medical equipment or manufacturing machinery. Endpoint monitoring is particularly important for monitoring issues like potential data breaches or other IT security risks on third-party devices used by internal or external customers.

End user experience is generally measured using metrics and monitoring solutions relevant to user experience and KPIs that track progress toward defined performance standards. EUEM products vary in their monitoring capabilities, but commonly monitored metrics include:

EUEM tools can monitor network latency, or the amount of time it takes for data to travel from one point to another across a network. Low latency networks have faster response times leading to more efficient application performance and a more positive user experience.

All businesses want to keep latency to a minimum, though it’s more crucial in certain industries and use cases than others. For example, organizations leading digital transformations will need to maintain low latency networks to maintain productivity among employees and customers throughout the transition.

Application outages can be caused by many factors, like network interruptions, coding errors, cloud vendor failures, scheduled updates or security breaches. In any case, extended application downtime can negatively impact user experience (to say nothing of lost revenue and clients). Monitoring the mean time to detection (MMTD), or the time it takes to detect an issue and the mean time to remediation (MTTR), the amount of time it takes to troubleshoot an error once it is detected, is crucial to minimizing downtime.

Bandwidth—a measure of the volume of data that can pass through a network at any given time—is an important metric when monitoring application performance. Unlike latency, which measures a system’s speed, bandwidth measures capacity. Organizations will want to ensure that their network has the capacity to handle traffic and user activity, particularly during times of peak use.

Understanding throughput is often even more valuable. While bandwidth measures possible capacity, throughput measures the average amount of data that actually passes through a network in a specific timeframe, taking into account the impact of latency. It reflects the number of data packets that arrive successfully and the amount of data packet loss.

Monitoring tools can keep track of network traffic and system storage, which allows IT teams to optimize systems and plan ahead to keep applications running efficiently, even during peak traffic periods.