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5 Takeaways from the Observability Forecast for Retail and eCommerce

Nic Benders
New Relic

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability.

As economic pressures intensify and customer expectations rise, the retail industry is undergoing a reset. To protect margins and deliver seamless omnichannel experiences, retailers must improve the efficiency and reliability of their IT and digital operations while also managing against complexity created by AI. Drawing on insights from 147 retail and eCommerce leaders, this report reveals how retailers use observability and key benefits.

Here are five key takeaways from the report:

1. AI shapes observability priorities

The data shows that 50% of leaders identified AI as the primary driver of deploying observability platforms in the retail and eCommerce industries. As retailers adopt AI to better connect with shoppers and personalize their experiences, the complexity of their digital estate increases by introducing new models, data pipelines, and dependencies that must be monitored alongside existing applications.

Beyond AI, retailers also cite governance, risk, compliance, cost management, and customer experience management as key drivers of observability adoption, reflecting the need for end-to-end visibility across increasingly interconnected systems.

2. Outages are a costly business risk

Outages are not just IT incidents; they are a business risk that can damage a brand. The report found that 31% of retail organizations report experiencing high-impact outages weekly. Retailers remain quicker than most industries at detecting outages, with a median time to detection of 30 minutes, yet the damage can still be devastating. The financial impact of outages is profound, with respondents citing a median cost of a critical business outage at $1 million per hour.  

Downtime, however, is only one part of the equation. Nearly 60% of respondents recognized that their engineering teams were losing innovation opportunities due to outages and incident response. Reducing incident frequency and downtime allows teams to redirect efforts toward innovation and business growth.

3. Digital experience monitoring is mission-critical

Monitoring offers insights into the digital customer experience and any issues that could impact it. To support seamless, omnichannel journeys, retail organizations are deploying a range of monitoring capabilities that keep customers engaged across every touchpoint. Specifically, they have prioritized database monitoring (67%), network monitoring (66%), alerts (65%), and dashboards (63%). Security also ranks highly, with 61% indicating they have deployed a security monitoring platform.

That focus on deeper visibility now extends to AI-driven systems, with AI monitoring adoption rising from 35% in 2024 to 55% in 2025.

4. Tool consolidation gains momentum

Retail organizations continue to consolidate observability tools to improve visibility across the software stack, prevent incidents, and increase operational efficiency. In 2025, the number of tools retail organizations used dropped from 5.9 just three years ago to 3.9. At the same time, complexity remains a persistent challenge, with 37% of respondents citing complex tool stacks as their primary obstacle to achieving full-stack observability. Having too many tools and the tools being too expensive fall closely behind as the next cited obstacles. This shift reflects a broader push to reduce tool sprawl as retailers manage increasingly distributed, omnichannel environments with fewer resources and tighter margins.

5. Observability makes life better (and provides business value)

For IT decision makers, observability delivers value beyond incident response. 41% of respondents said the technology helps satisfy key performance indicators (KPIs) while 36% said it drives business strategy. In-the-trenches practitioners said it increased productivity, enabling them to find and resolve issues faster (55%). It also reduced the guesswork associated with complex tech stacks (31%).

44% of respondents also noted observability increases operational efficiency, while another 43% reported improvements in system uptime and reliability.

Notably, observability is also delivering clear financial returns. Nearly half (46%) of retailers report an ROI of 2x or higher from their observability spend, reinforcing its role as a core business investment.

Retailers cannot afford business downtime or abandoned shopping carts due to poor customer experiences. As retailers navigate tighter margins, rising customer expectations, and increasingly complex digital environments, observability is proving essential for delivering resilience, efficiency, and business value.

Nic Benders is Chief Technical Strategist at New Relic

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5 Takeaways from the Observability Forecast for Retail and eCommerce

Nic Benders
New Relic

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability.

As economic pressures intensify and customer expectations rise, the retail industry is undergoing a reset. To protect margins and deliver seamless omnichannel experiences, retailers must improve the efficiency and reliability of their IT and digital operations while also managing against complexity created by AI. Drawing on insights from 147 retail and eCommerce leaders, this report reveals how retailers use observability and key benefits.

Here are five key takeaways from the report:

1. AI shapes observability priorities

The data shows that 50% of leaders identified AI as the primary driver of deploying observability platforms in the retail and eCommerce industries. As retailers adopt AI to better connect with shoppers and personalize their experiences, the complexity of their digital estate increases by introducing new models, data pipelines, and dependencies that must be monitored alongside existing applications.

Beyond AI, retailers also cite governance, risk, compliance, cost management, and customer experience management as key drivers of observability adoption, reflecting the need for end-to-end visibility across increasingly interconnected systems.

2. Outages are a costly business risk

Outages are not just IT incidents; they are a business risk that can damage a brand. The report found that 31% of retail organizations report experiencing high-impact outages weekly. Retailers remain quicker than most industries at detecting outages, with a median time to detection of 30 minutes, yet the damage can still be devastating. The financial impact of outages is profound, with respondents citing a median cost of a critical business outage at $1 million per hour.  

Downtime, however, is only one part of the equation. Nearly 60% of respondents recognized that their engineering teams were losing innovation opportunities due to outages and incident response. Reducing incident frequency and downtime allows teams to redirect efforts toward innovation and business growth.

3. Digital experience monitoring is mission-critical

Monitoring offers insights into the digital customer experience and any issues that could impact it. To support seamless, omnichannel journeys, retail organizations are deploying a range of monitoring capabilities that keep customers engaged across every touchpoint. Specifically, they have prioritized database monitoring (67%), network monitoring (66%), alerts (65%), and dashboards (63%). Security also ranks highly, with 61% indicating they have deployed a security monitoring platform.

That focus on deeper visibility now extends to AI-driven systems, with AI monitoring adoption rising from 35% in 2024 to 55% in 2025.

4. Tool consolidation gains momentum

Retail organizations continue to consolidate observability tools to improve visibility across the software stack, prevent incidents, and increase operational efficiency. In 2025, the number of tools retail organizations used dropped from 5.9 just three years ago to 3.9. At the same time, complexity remains a persistent challenge, with 37% of respondents citing complex tool stacks as their primary obstacle to achieving full-stack observability. Having too many tools and the tools being too expensive fall closely behind as the next cited obstacles. This shift reflects a broader push to reduce tool sprawl as retailers manage increasingly distributed, omnichannel environments with fewer resources and tighter margins.

5. Observability makes life better (and provides business value)

For IT decision makers, observability delivers value beyond incident response. 41% of respondents said the technology helps satisfy key performance indicators (KPIs) while 36% said it drives business strategy. In-the-trenches practitioners said it increased productivity, enabling them to find and resolve issues faster (55%). It also reduced the guesswork associated with complex tech stacks (31%).

44% of respondents also noted observability increases operational efficiency, while another 43% reported improvements in system uptime and reliability.

Notably, observability is also delivering clear financial returns. Nearly half (46%) of retailers report an ROI of 2x or higher from their observability spend, reinforcing its role as a core business investment.

Retailers cannot afford business downtime or abandoned shopping carts due to poor customer experiences. As retailers navigate tighter margins, rising customer expectations, and increasingly complex digital environments, observability is proving essential for delivering resilience, efficiency, and business value.

Nic Benders is Chief Technical Strategist at New Relic

The Latest

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...