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DX More Important Than Ever to Consumers

Study of consumers reveals that brand loyalty takes a backseat to simple, efficient digital experiences — and shows that a great DX has a direct impact on revenue and retention

When it comes to digital transactions, Americans are loyal to the experience, not necessarily the brand, according to a survey of more than 7,000 consumers from across the US, Europe, and Asia Pacific commissioned by FullStory.

This research reveals that 40% of US consumers say they don't care where they buy from "as long as it works," making a great digital experience more important than ever for brands to remain competitive in uncertain economic times.

58% of Americans will pay a premium for a guaranteed flawless digital experience

The research also shows that even in a price-sensitive environment, the customer experience can have a direct impact on revenue: nearly six out of 10 of Americans (58%) will pay a premium for a guaranteed flawless digital experience. The demand is not exclusive to the US, with 59% of consumers worldwide stating the same.

The research also indicates that consumers' difficulty and stress on sites and apps pose a significant revenue risk for brands. More than half of respondents (53%) are unlikely to return to a business that provides a poor digital experience, and only 5% say they are "very likely" to give a brand a second chance after a bad online experience.

"Companies across sectors are looking for strategies to stand out and retain customers in the face of economic slowdown," said Scott Voigt, CEO of FullStory. "Providing an exceptional digital experience is one of the best ways to win customers, who are clearly open to switching brands and won't tolerate digital friction. Digital experience data and insights equip brands to create perfect digital experiences, making it easier for consumers to get things done online and helping businesses increase revenue and retention."

Keep It Simple

The data shows that the #1 factor to ensure a great digital experience in 2023 is the ability to "quickly accomplish what I came to do" — a priority for 81% of US consumers and 76% of consumers worldwide.


Unfortunately, many sectors are still failing to hit these fundamentals when it comes to the experiences they provide on sites and apps:

■ Healthcare — Only 31% describe the digital experience as "simple," with 27% saying the experience is "stressful" or "difficult."

■ Grocery — Only 33% describe the digital experience as "simple," with 16% saying the experience is "stressful" or "difficult."

■ Finance — Only 37% describe the digital experience as "simple," with 19% saying the experience is "stressful" or "difficult."

■ Retail — Online shopping sites fared the best, with nearly half of US consumers (46%) describing the digital experience as "simple," and 17% saying the experience is "stressful" or "difficult."

Focus on Digital Fundamentals

The study also shows that brands are failing to pay attention to the digital details that matter most to experience-obsessed consumers — and hurting their business as a result.

■ The majority of US consumers (53%) have struggled or been frustrated with a site or app in the past six months, and 64% say they're likely to leave without completing a transaction as a result.

■ 71% of Americans report that they have repeatedly clicked or tapped in frustration on a site or app.

■ The most common frustrations highlighted by US consumers include slow loading times (65%), page loading errors (62%), and dead links (45%).

■ Despite these issues, more than half (51%) will not report issues when they occur, meaning brands are often unaware of digital errors that are costing them revenue.

Global Consumers Reflect Same Attitudes

Comparable to US consumers, more than a third of Brits (38%) also say they "don’t care" where they buy from "as long as it works." Similarly, 46% in Australia and 48% of those in Germany say the same.

Methodology: FullStory's research was conducted by 3Gem, an independent research agency. It incorporates data from 7,000 consumers across the UK, US, Germany, The Netherlands, Australia, Singapore, and Indonesia. Research was conducted between December 2022 and January 2023.

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

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 ...

DX More Important Than Ever to Consumers

Study of consumers reveals that brand loyalty takes a backseat to simple, efficient digital experiences — and shows that a great DX has a direct impact on revenue and retention

When it comes to digital transactions, Americans are loyal to the experience, not necessarily the brand, according to a survey of more than 7,000 consumers from across the US, Europe, and Asia Pacific commissioned by FullStory.

This research reveals that 40% of US consumers say they don't care where they buy from "as long as it works," making a great digital experience more important than ever for brands to remain competitive in uncertain economic times.

58% of Americans will pay a premium for a guaranteed flawless digital experience

The research also shows that even in a price-sensitive environment, the customer experience can have a direct impact on revenue: nearly six out of 10 of Americans (58%) will pay a premium for a guaranteed flawless digital experience. The demand is not exclusive to the US, with 59% of consumers worldwide stating the same.

The research also indicates that consumers' difficulty and stress on sites and apps pose a significant revenue risk for brands. More than half of respondents (53%) are unlikely to return to a business that provides a poor digital experience, and only 5% say they are "very likely" to give a brand a second chance after a bad online experience.

"Companies across sectors are looking for strategies to stand out and retain customers in the face of economic slowdown," said Scott Voigt, CEO of FullStory. "Providing an exceptional digital experience is one of the best ways to win customers, who are clearly open to switching brands and won't tolerate digital friction. Digital experience data and insights equip brands to create perfect digital experiences, making it easier for consumers to get things done online and helping businesses increase revenue and retention."

Keep It Simple

The data shows that the #1 factor to ensure a great digital experience in 2023 is the ability to "quickly accomplish what I came to do" — a priority for 81% of US consumers and 76% of consumers worldwide.


Unfortunately, many sectors are still failing to hit these fundamentals when it comes to the experiences they provide on sites and apps:

■ Healthcare — Only 31% describe the digital experience as "simple," with 27% saying the experience is "stressful" or "difficult."

■ Grocery — Only 33% describe the digital experience as "simple," with 16% saying the experience is "stressful" or "difficult."

■ Finance — Only 37% describe the digital experience as "simple," with 19% saying the experience is "stressful" or "difficult."

■ Retail — Online shopping sites fared the best, with nearly half of US consumers (46%) describing the digital experience as "simple," and 17% saying the experience is "stressful" or "difficult."

Focus on Digital Fundamentals

The study also shows that brands are failing to pay attention to the digital details that matter most to experience-obsessed consumers — and hurting their business as a result.

■ The majority of US consumers (53%) have struggled or been frustrated with a site or app in the past six months, and 64% say they're likely to leave without completing a transaction as a result.

■ 71% of Americans report that they have repeatedly clicked or tapped in frustration on a site or app.

■ The most common frustrations highlighted by US consumers include slow loading times (65%), page loading errors (62%), and dead links (45%).

■ Despite these issues, more than half (51%) will not report issues when they occur, meaning brands are often unaware of digital errors that are costing them revenue.

Global Consumers Reflect Same Attitudes

Comparable to US consumers, more than a third of Brits (38%) also say they "don’t care" where they buy from "as long as it works." Similarly, 46% in Australia and 48% of those in Germany say the same.

Methodology: FullStory's research was conducted by 3Gem, an independent research agency. It incorporates data from 7,000 consumers across the UK, US, Germany, The Netherlands, Australia, Singapore, and Indonesia. Research was conducted between December 2022 and January 2023.

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

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 ...