Skip to main content

Gartner: Customer Experience Pyramid Drives Loyalty and Satisfaction

New Research Shows Organizations How to Discover Innovative Customer Experiences that Build Stronger Relationships

According to Gartner, 81 percent of customer experience (CX) leaders report they will compete mostly or entirely on CX, but less than half have established the rationale for why CX drives business outcomes.

The goal of CX is to meet and exceed customer expectations, but while 48 percent say their CX efforts exceed management’s expectations, just 22 percent of customer experience leaders report their CX efforts exceed customers’ expectations.

To address this challenge, Gartner unveiled the CX Pyramid, a new methodology to test organizations’ customer journeys and forge more powerful experiences that deliver greater customer loyalty and brand advocacy.

"The fact that so many organizations understand the importance of CX to the brand, but are unable to deliver outcomes that meet or exceed customer expectations is indicative of the growing need for fresh approaches to delivering more positive outcomes for customers," said Augie Ray, Research Director at Gartner. "Leading brands in CX start with a strong foundation in customer satisfaction. Getting this right and understanding how to build upon it to drive positive financial and business outcomes is what sets the best brands apart from the rest."

The Gartner CX Pyramid is a framework to understand what separates the most powerful customer experiences from the rest. Each level, from bottom to top, defines an incrementally stronger way to forge relationships between an organization’s brand and their customers based on the way CX leaders listen for, understand, act on and solve customer needs.

The pyramid helps to identify the most powerful CX based on criteria including: (a) how the experiences are triggered, (b) the amount of effort required of the customer, (c) the completeness of the solution, and (d) the emotion and change in perception created by the experience. The CX pyramid goes beyond just solving today’s problems for today’s customers, by focusing on five key stages:

Stage 1: Communication Level – Furnish customers with the information they can use via the right channel at the right time.

Stage 2: Responsive Level – Solve the customer’s problem quickly and efficiently – meaning, balance both business and customer goals, measures and strategies.

Stage 3: Commitment Level – Listen for, understand and resolve customers’ unique needs.

Stage 4: Proactive Level – Provide experiences that resolve needs before customers ask.

Stage 5: Evolution Level – Make customers feel better, safer or more powerful.


Through these various levels, the CX pyramid should serve as a filter to review customer touchpoints and experiences throughout the entire buy, own and advocate journey.

CX leaders looking to drive more powerful, proactive and innovative solutions through the CX pyramid should follow three key steps:

■ Assess Your Capabilities – Ensure they're capuring a thorough understanding of customer wants, needs, and expectations, not just their perceptions of your existing initiative.

■ Tailor Your Customer Journey Maps – Push experiences in the top of the CX pyramid at key touchpoints and drive customers deeper into the buy, own and advocate journey.

■ Measure Your More Innovative CX Efforts Differently – CX leaders must make sure to measure their more innovative customer experiences against adoption, perception and financial objectives.

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Gartner: Customer Experience Pyramid Drives Loyalty and Satisfaction

New Research Shows Organizations How to Discover Innovative Customer Experiences that Build Stronger Relationships

According to Gartner, 81 percent of customer experience (CX) leaders report they will compete mostly or entirely on CX, but less than half have established the rationale for why CX drives business outcomes.

The goal of CX is to meet and exceed customer expectations, but while 48 percent say their CX efforts exceed management’s expectations, just 22 percent of customer experience leaders report their CX efforts exceed customers’ expectations.

To address this challenge, Gartner unveiled the CX Pyramid, a new methodology to test organizations’ customer journeys and forge more powerful experiences that deliver greater customer loyalty and brand advocacy.

"The fact that so many organizations understand the importance of CX to the brand, but are unable to deliver outcomes that meet or exceed customer expectations is indicative of the growing need for fresh approaches to delivering more positive outcomes for customers," said Augie Ray, Research Director at Gartner. "Leading brands in CX start with a strong foundation in customer satisfaction. Getting this right and understanding how to build upon it to drive positive financial and business outcomes is what sets the best brands apart from the rest."

The Gartner CX Pyramid is a framework to understand what separates the most powerful customer experiences from the rest. Each level, from bottom to top, defines an incrementally stronger way to forge relationships between an organization’s brand and their customers based on the way CX leaders listen for, understand, act on and solve customer needs.

The pyramid helps to identify the most powerful CX based on criteria including: (a) how the experiences are triggered, (b) the amount of effort required of the customer, (c) the completeness of the solution, and (d) the emotion and change in perception created by the experience. The CX pyramid goes beyond just solving today’s problems for today’s customers, by focusing on five key stages:

Stage 1: Communication Level – Furnish customers with the information they can use via the right channel at the right time.

Stage 2: Responsive Level – Solve the customer’s problem quickly and efficiently – meaning, balance both business and customer goals, measures and strategies.

Stage 3: Commitment Level – Listen for, understand and resolve customers’ unique needs.

Stage 4: Proactive Level – Provide experiences that resolve needs before customers ask.

Stage 5: Evolution Level – Make customers feel better, safer or more powerful.


Through these various levels, the CX pyramid should serve as a filter to review customer touchpoints and experiences throughout the entire buy, own and advocate journey.

CX leaders looking to drive more powerful, proactive and innovative solutions through the CX pyramid should follow three key steps:

■ Assess Your Capabilities – Ensure they're capuring a thorough understanding of customer wants, needs, and expectations, not just their perceptions of your existing initiative.

■ Tailor Your Customer Journey Maps – Push experiences in the top of the CX pyramid at key touchpoints and drive customers deeper into the buy, own and advocate journey.

■ Measure Your More Innovative CX Efforts Differently – CX leaders must make sure to measure their more innovative customer experiences against adoption, perception and financial objectives.

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...