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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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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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Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

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