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The Importance of CX Observability for DevOps Teams: A $1 Billion Missed Opportunity

James Isaacs
Cyara

A company will thrive or go out of business based on its reputation. A brand's reputation is dictated by several different factors, but customer experience (CX) remains the most critical when it comes to customer loyalty, trust and ultimately, sales. Studies have shown that 96% of consumers say CX is a key factor in their choice of loyalty to a brand and 85% of buyers are willing to pay more for great CX.

Yet, every day, companies are missing CX "red flags" because they don't have the tools to observe CX processes or metrics. Even basic errors or defects in automated customer interactions are left undetected for days, weeks or months, leading to widespread customer dissatisfaction. In fact, poor CX and digital technology investments are costing enterprises billions of dollars in lost potential revenue.

You can't fix what you can't see. Without observability into critical data about CX quality, there will always be bugs and errors that live out in the CX system for far too long. These technical issues tamper with the reliability of the CX software, which is so integral to the customer journey now that most businesses are operating on a digital-first approach. Reliability has never been more important for enterprises as they navigate digital transformation, especially cloud migration and automation.

Cultivating Observability in CX Software

Even in today's digital economy, many companies are still missing the mark when it comes to creating a memorable and positive CX through digital and voice channels. Most of the gap can be solved, however, if businesses invest in increasing their observability of CX processes and insightful metrics such as call center data, churn rate and net promoter scores (NPS).

Investing in greater observability allows enterprises to better collect and analyze data on every component of a system, application and infrastructure — from performance to security to accessibility. This information allows DevOps teams to glean insights into the reliability of actions performed within a unique business environment, such as an interactive voice response (IVR) system or a contact center. While an observability approach has been quickly adopted by software development and engineering teams, the practice of observability is still lagging when it comes to CX-related systems and solutions.

Gaining Real-time CX Insights

The fact of the matter is that for even the best DevOps teams, flaws creep into production. While DevOps teams do their best to foresee and predict potential gaps, they need a little help. Automated testing early in the development cycle, and throughout the entire process, is a proven way to identify potential flaws and mitigate errors before it becomes a costly threat to customers' experience. This requires automation because the faster a data set can be analyzed, the more value it will deliver.

Automated CX testing solutions work by generating synthetic interactions — either a single or thousands — to test the customer journey from the outside-in, from the network through IVRs to digital apps and routing systems, all the way to agents at their desktops — engaging in systems just as a customer would. Testing elements such as connectivity, responsiveness, quality and functionality can help DevOps teams ensure quality is achieved throughout the entire CX development life cycle. You can then dictate what data should be collected, who will own and examine the data and why it matters in the business' unique context to ensure the information collected within the customer journey is useful and impactful for the organization.

Be a Champion for CX Success

While the virtues of improving CX through automated testing are well known, it is worth mentioning the importance of executives championing CX observability and making the investment to prioritize it. Considering the potential revenue lost annually due to poor CX, it is important for executives to champion CX improvement efforts. For CX digital transformation initiatives to succeed, they must be led by an executive leader who can assert the need to drive cultural change and strategic investments. Appointing an executive to this role will ensure that CX initiatives are not siloed from DevOps teams, but also from the rest of the enterprise, including sales, marketing, operations and more. The organization's digital transformation champion must have broad authority that covers budget, people and processes in order to be effective in their role.

Online and in-person CX will always play a key role in brand loyalty. In an increasingly digital age, the reliability of our brand's digital frameworks will play an undeniable role in achieving brand loyalty and reputation through positive customer experiences. With greater observability and automated testing capabilities, enterprises can be empowered to innovate faster and deliver higher-quality solutions that will improve customer interactions and solidify brand loyalty for years to come.

James Isaacs is President of Cyara

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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The Importance of CX Observability for DevOps Teams: A $1 Billion Missed Opportunity

James Isaacs
Cyara

A company will thrive or go out of business based on its reputation. A brand's reputation is dictated by several different factors, but customer experience (CX) remains the most critical when it comes to customer loyalty, trust and ultimately, sales. Studies have shown that 96% of consumers say CX is a key factor in their choice of loyalty to a brand and 85% of buyers are willing to pay more for great CX.

Yet, every day, companies are missing CX "red flags" because they don't have the tools to observe CX processes or metrics. Even basic errors or defects in automated customer interactions are left undetected for days, weeks or months, leading to widespread customer dissatisfaction. In fact, poor CX and digital technology investments are costing enterprises billions of dollars in lost potential revenue.

You can't fix what you can't see. Without observability into critical data about CX quality, there will always be bugs and errors that live out in the CX system for far too long. These technical issues tamper with the reliability of the CX software, which is so integral to the customer journey now that most businesses are operating on a digital-first approach. Reliability has never been more important for enterprises as they navigate digital transformation, especially cloud migration and automation.

Cultivating Observability in CX Software

Even in today's digital economy, many companies are still missing the mark when it comes to creating a memorable and positive CX through digital and voice channels. Most of the gap can be solved, however, if businesses invest in increasing their observability of CX processes and insightful metrics such as call center data, churn rate and net promoter scores (NPS).

Investing in greater observability allows enterprises to better collect and analyze data on every component of a system, application and infrastructure — from performance to security to accessibility. This information allows DevOps teams to glean insights into the reliability of actions performed within a unique business environment, such as an interactive voice response (IVR) system or a contact center. While an observability approach has been quickly adopted by software development and engineering teams, the practice of observability is still lagging when it comes to CX-related systems and solutions.

Gaining Real-time CX Insights

The fact of the matter is that for even the best DevOps teams, flaws creep into production. While DevOps teams do their best to foresee and predict potential gaps, they need a little help. Automated testing early in the development cycle, and throughout the entire process, is a proven way to identify potential flaws and mitigate errors before it becomes a costly threat to customers' experience. This requires automation because the faster a data set can be analyzed, the more value it will deliver.

Automated CX testing solutions work by generating synthetic interactions — either a single or thousands — to test the customer journey from the outside-in, from the network through IVRs to digital apps and routing systems, all the way to agents at their desktops — engaging in systems just as a customer would. Testing elements such as connectivity, responsiveness, quality and functionality can help DevOps teams ensure quality is achieved throughout the entire CX development life cycle. You can then dictate what data should be collected, who will own and examine the data and why it matters in the business' unique context to ensure the information collected within the customer journey is useful and impactful for the organization.

Be a Champion for CX Success

While the virtues of improving CX through automated testing are well known, it is worth mentioning the importance of executives championing CX observability and making the investment to prioritize it. Considering the potential revenue lost annually due to poor CX, it is important for executives to champion CX improvement efforts. For CX digital transformation initiatives to succeed, they must be led by an executive leader who can assert the need to drive cultural change and strategic investments. Appointing an executive to this role will ensure that CX initiatives are not siloed from DevOps teams, but also from the rest of the enterprise, including sales, marketing, operations and more. The organization's digital transformation champion must have broad authority that covers budget, people and processes in order to be effective in their role.

Online and in-person CX will always play a key role in brand loyalty. In an increasingly digital age, the reliability of our brand's digital frameworks will play an undeniable role in achieving brand loyalty and reputation through positive customer experiences. With greater observability and automated testing capabilities, enterprises can be empowered to innovate faster and deliver higher-quality solutions that will improve customer interactions and solidify brand loyalty for years to come.

James Isaacs is President of Cyara

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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 ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...