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Gartner: 3 Customer Experience Myths

The performance gap between customer experience leaders and runners-up is widening, with those on top being disproportionately rewarded. Gartner, Inc. said organizations must ignore three myths in order to achieve a superior customer experience.

There are many factors that make customer experience leaders successful, and many are not in dispute.

“Organizations with superior customer experiences tend to appoint a leader, their executives are committed to the initiative and have a small dedicated team with 12 direct reports on average,” said Ed Thompson, VP and Distinguished Analyst at Gartner. “They also involve a broad range of departments from marketing and sales, to supply chain, IT, R&D and HR.”

“We also know that leaders in such position are patient, build trust and honor privacy with their customers,” Thompson continued. “They don’t invest and hope. They clearly focus on customer emotions and not just the numbers, and have a common sense of purpose. But that’s not enough to be the best in your industry.”

Above all, customer experience leaders need to beware of three common customer experience myths:

1. Delight the Customer

Gartner research shows that the return on investment (ROI) of meeting customer expectations, and making their interactions effortless, is high. But, as organizations invest to exceed expectations to delight the customer, and therefore drive up customer loyalty and advocacy, the chances of gaining a positive ROI are far lower.

As organizations invest to exceed expectations to delight the customer ... the chances of gaining a positive ROI are far lower

“It’s not that investing to delight the customer doesn’t work, but its likelihood of working is lower,” said Thompson. “Many organizations are inconsistent in the delivery of their customer experience strategy. While they are aiming to delight in one part of the organization, they still require effort from the customer in another part. We recommend that organizations don’t delight, but rather focus on being effortless.”

2. Focus on Innovation

With all the new possible technologies to use in the cause of a superior customer experience, many organizations strive to be unique before they have examined what is already working in their own industries, whether that be in their home country or in another country. Most innovation is just an imitation of an existing successful investment in a different geography or an adjacent industry.

“Too many companies are overlooking the benefits of imitation. You don’t need to come up with everything yourself. We recommend organizations don’t only focus on innovation, but rather consider the benefits of imitation,” said Thompson.

3. Correlate Data

The explosion of customer data that has become available at low cost over the last 20 years means many organizations are collecting it and sifting through it to seek correlations from which they can make investment decisions. Gartner research also shows that adding numerous channels and options to make things better for customers has the opposite effect — it makes the customer experience worse. Leading organizations are looking more closely at what causes customers to make choices, and focusing on what jobs the customer is trying to get done.

Adding numerous channels and options to make things better for customers has the opposite effect

“Organizations are better served by understanding what customers are trying to achieve rather than monitoring demographics or psychographic information,” said Thompson. He pointed out that Harvard Business School professor Clayton Christensen’s paper, tries to help people address their jobs to be done, sparking an interest by customer experience leaders in really understanding what the customer hopes to achieve.

“Rather than just looking at studying customer data, you need to examine the needs that arise during your customer’s lives. We recommend that you don’t correlate — but understand the jobs to be done,” added Thompson. “All three of these common myths are overrated. The most successful companies avoid overinvesting in these directions, and you do not want to do it either.”

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Gartner: 3 Customer Experience Myths

The performance gap between customer experience leaders and runners-up is widening, with those on top being disproportionately rewarded. Gartner, Inc. said organizations must ignore three myths in order to achieve a superior customer experience.

There are many factors that make customer experience leaders successful, and many are not in dispute.

“Organizations with superior customer experiences tend to appoint a leader, their executives are committed to the initiative and have a small dedicated team with 12 direct reports on average,” said Ed Thompson, VP and Distinguished Analyst at Gartner. “They also involve a broad range of departments from marketing and sales, to supply chain, IT, R&D and HR.”

“We also know that leaders in such position are patient, build trust and honor privacy with their customers,” Thompson continued. “They don’t invest and hope. They clearly focus on customer emotions and not just the numbers, and have a common sense of purpose. But that’s not enough to be the best in your industry.”

Above all, customer experience leaders need to beware of three common customer experience myths:

1. Delight the Customer

Gartner research shows that the return on investment (ROI) of meeting customer expectations, and making their interactions effortless, is high. But, as organizations invest to exceed expectations to delight the customer, and therefore drive up customer loyalty and advocacy, the chances of gaining a positive ROI are far lower.

As organizations invest to exceed expectations to delight the customer ... the chances of gaining a positive ROI are far lower

“It’s not that investing to delight the customer doesn’t work, but its likelihood of working is lower,” said Thompson. “Many organizations are inconsistent in the delivery of their customer experience strategy. While they are aiming to delight in one part of the organization, they still require effort from the customer in another part. We recommend that organizations don’t delight, but rather focus on being effortless.”

2. Focus on Innovation

With all the new possible technologies to use in the cause of a superior customer experience, many organizations strive to be unique before they have examined what is already working in their own industries, whether that be in their home country or in another country. Most innovation is just an imitation of an existing successful investment in a different geography or an adjacent industry.

“Too many companies are overlooking the benefits of imitation. You don’t need to come up with everything yourself. We recommend organizations don’t only focus on innovation, but rather consider the benefits of imitation,” said Thompson.

3. Correlate Data

The explosion of customer data that has become available at low cost over the last 20 years means many organizations are collecting it and sifting through it to seek correlations from which they can make investment decisions. Gartner research also shows that adding numerous channels and options to make things better for customers has the opposite effect — it makes the customer experience worse. Leading organizations are looking more closely at what causes customers to make choices, and focusing on what jobs the customer is trying to get done.

Adding numerous channels and options to make things better for customers has the opposite effect

“Organizations are better served by understanding what customers are trying to achieve rather than monitoring demographics or psychographic information,” said Thompson. He pointed out that Harvard Business School professor Clayton Christensen’s paper, tries to help people address their jobs to be done, sparking an interest by customer experience leaders in really understanding what the customer hopes to achieve.

“Rather than just looking at studying customer data, you need to examine the needs that arise during your customer’s lives. We recommend that you don’t correlate — but understand the jobs to be done,” added Thompson. “All three of these common myths are overrated. The most successful companies avoid overinvesting in these directions, and you do not want to do it either.”

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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 ...

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 ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...