We surveyed 1,001 consumers about their frustrations, their patience thresholds, and their expectations for automated support. What we found was a population exhausted by broken automation and ready to act on its frustration.
Finding 01 — The comprehension gap
“Talking to a bot that doesn’t understand me” ranked as consumers’ single most frustrating support experience, and their tolerance threshold to help bots understand is low.
86.7%
60.1%
Finding 03 — The VOICE PREMIUM
When it comes to seeking support, 38.9% of consumers reach for the phone first, nearly triple the share that go to a website or FAQ. Even when choosing between automated options, voice automation is preferred over human support.
The channel customers trust most is also the one that fails them most consistently.
Just 7% of consumers say IVR consistently resolves their issues. Only 24.6% are remotely satisfied with it.
9.5%
Social media
9.6%
Ask ChatGPT/ Claude etc.
10.3%
13.8%
Website / FAQ
38.9%
Call
18%
Chat / AI assistant
Finding 04 — The EMOTIONAL SUPPORT TAX
55.4%
admitted to crying, yelling at loved ones, or breaking a device after a frustrating support interaction
Yes, one bad customer experience would push me to find alternative options
Yes, it generally impacts how loyal I am
Yes, one bad customer experience would push me to find alternative options
No, I am generally forgiving when something goes wrong
Yes, a good customer experience is necessary in my eyes
Finding 05 — The AI hesitation
Broken automation creates lasting distrust. Only 7.8% of respondents are extremely confident that automated systems can accurately understand and resolve their requests. 30.4% have no trust in AI’s ability to handle complex service interactions at all.
This skepticism has become the default: When automation fails and transfers to a human, 85.4% of consumers say they are forgiving to the rep because they had expected the automation to fail from the start.
84.9%
of respondents said they’d keep using automation if it consistently solved their problems.
75.2%
would even prefer automation if it could anticipate their needs and act proactively.
Finding 06 — The AGENTIC EXPECTATION
Despite the hesitation around AI, most respondents are not closed to the technology. They’re just waiting for consistent evidence that it works, and they expect that to be soon. 69.6% believe future AI systems will handle complex service requests better than humans. 43% expect AI to manage full service journeys end-to-end within one to three years. But the bar for reliable AI is non-negotiable: 66.6% say they won’t trade accuracy for speed.

Looking forward
Consumer expectations for automated customer experience have never been higher. Knowing the technology available, consumers want real-time, reliable, secure service, and they’re willing to switch brands to get it. The Consumer Patience Index paints a picture that CX leaders can’t afford to look away from. The cost of bad customer service, measured not only in churn, but also stalled revenue, is high. The good news is, brands don’t have to guess what a good customer experience looks like. This survey outlines exactly what brands need to deliver in order to earn customer loyalty. With the right AI in place, all of these expectations can be met.
But time is of the essence. With the volume of vendors available across industries today, customers don’t need brands. One bad experience, and they’ll just move on to the next. The companies that act quickly to meet consumer expectations will be the ones who successfully transform their support channels from being sources of churn to engines for revenue.
Are you ready to set the new standard for high-quality customer experience in your industry?
Methodology
This survey was commissioned by Parloa and conducted by independent research firm Propeller Insights in Spring 2026. Sample: 1,001 US consumers over the age of 18 who had interacted with a company’s customer service department in the prior 12 months. Data collected via online survey instrument. Results reported as percentages of respondents; data was not weighted.













