Gartner: Majority of Technology Purchases Come with High Degree of Regret

As technology continues to become more critical to the business, technology customers have access to more options and information than ever before leading to more instances of buyer remorse.

56% of organizations said they had a high degree of purchase regret over their largest tech-related purchase in the last two years, according to a new survey by Gartner, Inc.

"The high regret feelings are at their peak for tech buyers that have not started implementation, indicating significant frustration with the buying experience," said Hank Barnes, distinguished VP analyst at Gartner. "In the past, it was relatively easy for product leaders to predict who buyers were, but no longer. Buying team dynamics are changing and customers can find buying to be a real challenge."

Barnes identified key changes in tech buying behavior: "There can be significant downside to regret associated with enterprise technology decisions. The survey found that the organizations that indicated they had high regret for their purchase took, on average, 7 to 10 months longer to complete that purchase. Slow purchase decisions can lead to frustrated teams, wasted time and resources and even, potentially, slower growth for the company."

According to the survey, 67% of people involved in technology-buying decisions are not in IT which means that anyone could be a tech buyer for their organization. In this environment, a new technology adoption chasm is emerging. This new chasm divides organizations that are confident adopters and buyers of technology from the vast majority that are not. High-tech providers need new approaches to identify and engage these different types of B2B customers and predict which type of customer they are dealing with to improve the odds of winning good business.

"To shift strategies, we need to think about psychographics beyond the motivations for buying to also include how decisions are approached and which groups are driving the strategy," said Barnes. "Gartner has developed a psychographic model called Enterprise Technology Adoption Profiles (ETAs) that revealed seven specific customer segments. Using ETAs is one element that can help high tech providers move from a product/market fit strategy towards a product/customer fit strategy."

Enterprise Technology Adoption Profiles (ETAs) are a proprietary model developed by Gartner that assesses the psychographics that drive how and when organizations make technology decisions.

Additionally, high tech providers should create a model to help identify "best fit" situations and "should avoid" situations. "Best fit" situations should be captured in an ideal customer profile — an enterprise persona — which focuses on the characteristics of the organizations being targeted, not the individuals within those organizations. It can include a variety of factors including the technologies they use, their business situation, the resources available to them and psychographic ETAs.

"There will be a big grey area in between that you have to be thoughtful in evaluating whether to commit to pursuing the opportunity. This is all about improving your odds and allocating resources and investments effectively," said Barnes.

Having a keen understanding of the ideal customers will help high tech providers shape their strategies. With this insight, Gartner recommends that high tech providers do three things:

1. Focus the bulk of investments and effort toward supporting the "best fit" situations with the right offering, the right messaging, and the right type of content and engagement activities.

2. Train customer-facing teams on how to recognize the customer characteristics that indicate a "best fit."

3. Train customer-facing teams on how to adjust their approach when encountering prospects that fall into the grey area between "best fit" and "should avoid."

Methodology: In November and December 2021, Gartner surveyed 1,120 respondents in North America, Western Europe and Asia/Pacific to understand how organizations approach large-scale buying efforts for enterprise technology. Respondents were required to be at a manager level or higher, aware of large-scale buying efforts for technology occurring during the past two years, and directly involved in the evaluation or selection of products or services for technology projects.

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Gartner: Majority of Technology Purchases Come with High Degree of Regret

As technology continues to become more critical to the business, technology customers have access to more options and information than ever before leading to more instances of buyer remorse.

56% of organizations said they had a high degree of purchase regret over their largest tech-related purchase in the last two years, according to a new survey by Gartner, Inc.

"The high regret feelings are at their peak for tech buyers that have not started implementation, indicating significant frustration with the buying experience," said Hank Barnes, distinguished VP analyst at Gartner. "In the past, it was relatively easy for product leaders to predict who buyers were, but no longer. Buying team dynamics are changing and customers can find buying to be a real challenge."

Barnes identified key changes in tech buying behavior: "There can be significant downside to regret associated with enterprise technology decisions. The survey found that the organizations that indicated they had high regret for their purchase took, on average, 7 to 10 months longer to complete that purchase. Slow purchase decisions can lead to frustrated teams, wasted time and resources and even, potentially, slower growth for the company."

According to the survey, 67% of people involved in technology-buying decisions are not in IT which means that anyone could be a tech buyer for their organization. In this environment, a new technology adoption chasm is emerging. This new chasm divides organizations that are confident adopters and buyers of technology from the vast majority that are not. High-tech providers need new approaches to identify and engage these different types of B2B customers and predict which type of customer they are dealing with to improve the odds of winning good business.

"To shift strategies, we need to think about psychographics beyond the motivations for buying to also include how decisions are approached and which groups are driving the strategy," said Barnes. "Gartner has developed a psychographic model called Enterprise Technology Adoption Profiles (ETAs) that revealed seven specific customer segments. Using ETAs is one element that can help high tech providers move from a product/market fit strategy towards a product/customer fit strategy."

Enterprise Technology Adoption Profiles (ETAs) are a proprietary model developed by Gartner that assesses the psychographics that drive how and when organizations make technology decisions.

Additionally, high tech providers should create a model to help identify "best fit" situations and "should avoid" situations. "Best fit" situations should be captured in an ideal customer profile — an enterprise persona — which focuses on the characteristics of the organizations being targeted, not the individuals within those organizations. It can include a variety of factors including the technologies they use, their business situation, the resources available to them and psychographic ETAs.

"There will be a big grey area in between that you have to be thoughtful in evaluating whether to commit to pursuing the opportunity. This is all about improving your odds and allocating resources and investments effectively," said Barnes.

Having a keen understanding of the ideal customers will help high tech providers shape their strategies. With this insight, Gartner recommends that high tech providers do three things:

1. Focus the bulk of investments and effort toward supporting the "best fit" situations with the right offering, the right messaging, and the right type of content and engagement activities.

2. Train customer-facing teams on how to recognize the customer characteristics that indicate a "best fit."

3. Train customer-facing teams on how to adjust their approach when encountering prospects that fall into the grey area between "best fit" and "should avoid."

Methodology: In November and December 2021, Gartner surveyed 1,120 respondents in North America, Western Europe and Asia/Pacific to understand how organizations approach large-scale buying efforts for enterprise technology. Respondents were required to be at a manager level or higher, aware of large-scale buying efforts for technology occurring during the past two years, and directly involved in the evaluation or selection of products or services for technology projects.

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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 ...

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

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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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 ...

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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 ...

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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 ...

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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.