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For a 360-Degree View of the Customer, Combine Active and Passive Observability

Mehdi Daoudi
Catchpoint

Digital businesses don't invest in monitoring for monitoring's sake. They do it to make the business run better. Every dollar spent on observability — every hour your team spends using monitoring tools or responding to what they reveal — should tie back directly to business outcomes: conversions, revenues, brand equity. If they don't? You might be missing the forest for the trees.

As technologists, it's our ability to master the technical complexity involved in delivering successful applications that got us where we are. Yet, focusing too narrowly on technology can sometimes lead us astray. It's not uncommon, for example, for businesses to devote hundreds of hours to inching their digital storefront up in search engine rankings, even as customers struggle with basic functions on the site.

How can you avoid these kinds of pitfalls?

By always keeping a laser focus on the most important aspect of a digital business: the experience of users.

To capture a comprehensive customer view, businesses use a variety of tools, including Real User Monitoring, or RUM (which measures real user interactions), and active observability (simulating synthetic interactions to test the site's response). Too often though, these approaches aren't tied together in a strategic or intentional way. Instead, they exist in silos — sometimes owned by totally different teams — each providing only a partial, fragmented view.

Let's take a closer look at how you can ensure that real and synthetic observability strategies work together to measure what matters most.

Navigating Complexity

The basic goal of prioritizing user experience seems straightforward. Why then do so many businesses struggle to effectively measure it? Because modern digital applications have grown enormously complex.

A typical website now encompasses content and services from literally hundreds of sources: third-party data centers and servers, Domain Name System (DNS) and content delivery network (CDN) providers, load-balancers and site accelerators, social sharing widgets, tracking tags, and more. Problems with any of these elements can disrupt the user experience. That's to say nothing of all the variables on the user's end, such as issues with devices, browsers, and Internet Service Providers (ISPs).

To understand the health of a digital business, you need to observe all these elements and many others. So, modern digital businesses use both real and synthetic monitoring to measure different aspects of how users experience a site. To synthesize them into a holistic observability strategy, however, you need to understand exactly what each perspective shows you — and what it doesn't.

Inside Real User Observability

Real User Monitoring uses code placed on a website or mobile app (typically, the navigation timing API in browsers) to transmit performance metrics around engagement. This data can help you better understand your users — how they get to your site, from which markets and devices, which pages they access most, and more.

This type of observability can play a key role in linking digital interactions with core business metrics. For example, RUM can measure things like:

■ How many customers abandon the site when performance drops by 25%? How about 50%?

■ How do fluctuations in performance levels correlate with conversion rates?

■ When I make changes to my application (adding a new data center, changing CDN provider) what effects do they have on traffic, conversions, and other metrics?

Real user data can be particularly valuable in tracking longer-term trends. By correlating performance data with shopping cart abandonment, bounce rates, time spent on specific pages, and more, you can identify which metrics correlate most strongly with business outcomes. You can then use these insights to identify areas for improvement and prioritize investments towards activities with the most direct impact on revenues.

While RUM insights can be extremely valuable, however, you can't assume they're showing a complete picture of user experience. For example, if DNS issues prevent users from accessing your site, real user metrics won't show you that's happening.

Additionally, passive monitoring tools like RUM, are, well, passive. Anything you do in response those insights is, by definition, reacting to problems after they've already affected customers.

Getting Active

Active observability complements real user monitoring by taking a proactive approach to measuring system health. With active observability, you can continually poke and prod your application by generating synthetic user behavior — on any part of your site, 24x7, from any geography you choose.

Active observability fills in the gaps in passive monitoring, allowing you to spot potential issues before they affect your customers and revenues. It also offers:

Flexibility: Test whatever you want, however you want, from wherever you choose, as often as you choose — without having to wait for real users.

Visibility: Synthetic monitoring measures from the outside-in, capturing performance of both your own systems and third-party elements (DNS, CDNs, ISPs) at every step in the user journey. This also means that, when you detect a problem, you can quickly pinpoint the source.

Validation: With the ability to generate any kind of user behavior, from anywhere, you can measure the performance impact of prospective changes before they go to production.

Business intelligence: Active observability can help you benchmark your performance against the competition, as well as track performance of your digital partners (like DNS or CDN providers) and make sure they're living up to their service-level agreements.

Building Holistic Visibility

Both real and active tools play important roles in a digital observability strategy. To achieve true 360-degree visibility into the customer experience, however, you need to synthesize them within a single strategy. If you're approaching observability strategically, you'll use RUM to understand how real users interact with your site, so you know what to test. And you'll use synthetics to proactively, continually test those components and interactions that have the biggest impact on business outcomes.

Together, these approaches will provide ongoing insights to guide how you invest development and engineering resources — and then validate the effects of those investments. Effectively, you create a continuous feedback loop of measure, respond, and measure again. You end up with much deeper visibility into the customer experience. More important, you have a strategy driven not by technology, but by real-world business concerns.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

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For a 360-Degree View of the Customer, Combine Active and Passive Observability

Mehdi Daoudi
Catchpoint

Digital businesses don't invest in monitoring for monitoring's sake. They do it to make the business run better. Every dollar spent on observability — every hour your team spends using monitoring tools or responding to what they reveal — should tie back directly to business outcomes: conversions, revenues, brand equity. If they don't? You might be missing the forest for the trees.

As technologists, it's our ability to master the technical complexity involved in delivering successful applications that got us where we are. Yet, focusing too narrowly on technology can sometimes lead us astray. It's not uncommon, for example, for businesses to devote hundreds of hours to inching their digital storefront up in search engine rankings, even as customers struggle with basic functions on the site.

How can you avoid these kinds of pitfalls?

By always keeping a laser focus on the most important aspect of a digital business: the experience of users.

To capture a comprehensive customer view, businesses use a variety of tools, including Real User Monitoring, or RUM (which measures real user interactions), and active observability (simulating synthetic interactions to test the site's response). Too often though, these approaches aren't tied together in a strategic or intentional way. Instead, they exist in silos — sometimes owned by totally different teams — each providing only a partial, fragmented view.

Let's take a closer look at how you can ensure that real and synthetic observability strategies work together to measure what matters most.

Navigating Complexity

The basic goal of prioritizing user experience seems straightforward. Why then do so many businesses struggle to effectively measure it? Because modern digital applications have grown enormously complex.

A typical website now encompasses content and services from literally hundreds of sources: third-party data centers and servers, Domain Name System (DNS) and content delivery network (CDN) providers, load-balancers and site accelerators, social sharing widgets, tracking tags, and more. Problems with any of these elements can disrupt the user experience. That's to say nothing of all the variables on the user's end, such as issues with devices, browsers, and Internet Service Providers (ISPs).

To understand the health of a digital business, you need to observe all these elements and many others. So, modern digital businesses use both real and synthetic monitoring to measure different aspects of how users experience a site. To synthesize them into a holistic observability strategy, however, you need to understand exactly what each perspective shows you — and what it doesn't.

Inside Real User Observability

Real User Monitoring uses code placed on a website or mobile app (typically, the navigation timing API in browsers) to transmit performance metrics around engagement. This data can help you better understand your users — how they get to your site, from which markets and devices, which pages they access most, and more.

This type of observability can play a key role in linking digital interactions with core business metrics. For example, RUM can measure things like:

■ How many customers abandon the site when performance drops by 25%? How about 50%?

■ How do fluctuations in performance levels correlate with conversion rates?

■ When I make changes to my application (adding a new data center, changing CDN provider) what effects do they have on traffic, conversions, and other metrics?

Real user data can be particularly valuable in tracking longer-term trends. By correlating performance data with shopping cart abandonment, bounce rates, time spent on specific pages, and more, you can identify which metrics correlate most strongly with business outcomes. You can then use these insights to identify areas for improvement and prioritize investments towards activities with the most direct impact on revenues.

While RUM insights can be extremely valuable, however, you can't assume they're showing a complete picture of user experience. For example, if DNS issues prevent users from accessing your site, real user metrics won't show you that's happening.

Additionally, passive monitoring tools like RUM, are, well, passive. Anything you do in response those insights is, by definition, reacting to problems after they've already affected customers.

Getting Active

Active observability complements real user monitoring by taking a proactive approach to measuring system health. With active observability, you can continually poke and prod your application by generating synthetic user behavior — on any part of your site, 24x7, from any geography you choose.

Active observability fills in the gaps in passive monitoring, allowing you to spot potential issues before they affect your customers and revenues. It also offers:

Flexibility: Test whatever you want, however you want, from wherever you choose, as often as you choose — without having to wait for real users.

Visibility: Synthetic monitoring measures from the outside-in, capturing performance of both your own systems and third-party elements (DNS, CDNs, ISPs) at every step in the user journey. This also means that, when you detect a problem, you can quickly pinpoint the source.

Validation: With the ability to generate any kind of user behavior, from anywhere, you can measure the performance impact of prospective changes before they go to production.

Business intelligence: Active observability can help you benchmark your performance against the competition, as well as track performance of your digital partners (like DNS or CDN providers) and make sure they're living up to their service-level agreements.

Building Holistic Visibility

Both real and active tools play important roles in a digital observability strategy. To achieve true 360-degree visibility into the customer experience, however, you need to synthesize them within a single strategy. If you're approaching observability strategically, you'll use RUM to understand how real users interact with your site, so you know what to test. And you'll use synthetics to proactively, continually test those components and interactions that have the biggest impact on business outcomes.

Together, these approaches will provide ongoing insights to guide how you invest development and engineering resources — and then validate the effects of those investments. Effectively, you create a continuous feedback loop of measure, respond, and measure again. You end up with much deeper visibility into the customer experience. More important, you have a strategy driven not by technology, but by real-world business concerns.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

The Latest

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...