Quantum Metric Research Finds Shoppers Are Tuning Out Peak Sales as AI Decides Where and When They Buy

New 2026 Peak Benchmark finds AI agent sessions grew 25x in under a year, and more than 1 in 4 AI-related sessions now come from AI assistants that browse alongside shoppers.

MONUMENT, Colo. – Nov. 05, 2026 – Quantum Metric, the experience context platform for enterprise AI, today released its 2026 Peak Benchmark, revealing growing peak fatigue as consumers tune out sale days now that AI makes it easier to decide when and where to buy. Findings show many consumers are paying less attention to major peak moments like holiday travel sales (48%), phone launches (55%) and even early October sales (34%), as 2 in 3 have turned to AI to shop, book or select services in the past six months.

While Cyber 5 (Thanksgiving through Cyber Monday) is still expected to draw more traffic, with 28% of consumers paying more attention to Cyber 5 this year, more of that shopping is shifting to AI. AI agent sessions on brand sites, where AI browses and buys on a shopper's behalf, have grown 25x in under a year, and AI assistants like Meta's Muse now drive more than 1 in 4 AI-related sessions.

"Peak used to mean planning for a few big days. Now customers pick the moments that matter, and more often an AI agent or assistant is shopping with them," said Mario Ciabarra, founder and CEO of Quantum Metric. "Traditional analytics often can't tell those visitors apart, so a blocked agent looks like any other drop-off. Brands need to see what every visitor did, what got in their way and what it cost the business. That's experience context, and it's how teams will know what to prioritize through this peak."

What do the findings show about peak behavior this year?

The 2026 Peak Benchmark dug into findings across three forms of AI-influenced traffic. AI-referred traffic comes from shoppers who reach a brand site by clicking a link from an AI tool. AI-assisted sessions start with an AI assistant browsing part of a site for a shopper, who then takes over, often to add payment or account details. Agent traffic comes from AI browsing a brand site on its own on a shopper's behalf.

• Consumers are making fewer visits before they buy. The share of consumers who book flights, hotels or event tickets in a single visit rose to 40% from 33% in 2025, and the share who buy holiday gifts in a single visit rose to 33% from 27%. Even with October retail sessions up 31% year over year, retail shoppers spent 18% less engaged time per session.
• Agents get stuck far more often than human shoppers. Retail agents abandon 48 carts for every completed purchase, compared with about three for all retail traffic, and if an agent can't complete a purchase, fewer than half of consumers would finish it themselves on the same site.
• AI-assisted shoppers are among the most engaged visitors. Sessions where a person browses with an AI assistant last about 19 minutes, compared with 7 minutes for typical human traffic, and in retail they convert about 30x higher than agent sessions.
• The costliest friction often goes unseen. 92% of consumers hit at least one issue during peak periods, and 62% lost at least one purchase to it. During retail's highest-traffic weeks of the past year, server errors held steady while frustration rates rose 25%.
• Interest in Cyber 5 is rising, and so is AI shopping. 28% of consumers are paying more attention to Cyber 5 this year, rising to nearly 40% of Gen Z and Millennials. Early-October AI-referred retail traffic is already 3.1x higher than the same week last year, and 1 in 5 consumers have let, or would let, AI complete a holiday gift purchase.

What should digital teams do to prepare for peak?

Peak success now depends on understanding every visitor, including the AI agents and assistants that traditional analytics often can't detect. Agents don't always identify themselves, and AI-assisted sessions, like those from Meta's Muse, behave more like a brand's most engaged customers than like bots. When teams can't tell these visitors apart, they can't see where agents get blocked or which AI-assisted shoppers are ready to buy.

Quantum Metric's Agent Probability Score, introduced in September, estimates the likelihood that a session is driven by an AI agent based on its behavior, rather than relying on rare instances where the agent self-identifies. With Quantum Metric's experience context, teams can see where agents stall or abandon, measure agent activity separately from human behavior and prioritize fixes by business impact before the busiest weeks of the year. Over time, that context can help teams evolve from applying fixes themselves when experiences break, to self-improving experiences powered by AI.

What is the report's methodology?

Findings from the 2026 Peak Benchmark are based on a survey of 1,500 consumers across the US and UK, combined with aggregated, anonymized behavioral data from the Quantum Metric platform.

The full 2026 Peak Benchmark is available at: quantummetric.com/resources/2026-peak-benchmark

About Quantum Metric

Quantum Metric gives enterprises complete experience context. The company captures every customer interaction across web and mobile, providing the most complete digital experience data available. Felix Agentic, Quantum Metric's agentic analytics platform, monitors customer experiences continuously, explains why customer behavior changes, and quantifies the impact on the business so teams know what to fix first. Teams can ask Felix questions in natural language, and the same data can be connected to the AI agents and tools enterprises already use. Global enterprises rely on Quantum Metric, which supports billions of digital interactions each month and reflects insights from roughly half of the world's internet users. For more information, visit www.quantummetric.com.