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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 decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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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

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...