One-Touch Resolution Metric

And How to measure it in the Age of AI

For years, "One-Touch Resolution" has been a key metric for support managers, and for good reason. The idea is simple: a customer has a problem, they contact you, and a single agent reply solves it. Done. Fast and Efficient.

It's long been considered a sign of support efficiency and of a well-trained team with the right resources.

But in the new AI era, the role of this metric is changing. In fact, if you are implementing AI and automation correctly, your human agent "one-touch" rate should be going down.

Why "One-Touch" Metric Was So Important

In a traditional support model, managers love a high one-touch rate because it's a powerful indicator of efficiency. It means:

• Low Customer Effort: The customer's problem was solved in a single, frictionless interaction.

• Clean Processes: Your team has the right macros, Knowledge Base, and tools to solve problems on the first try.

• High Customer Satisfaction: Customer love when they get a quick resolution.

After being a key indicator of an efficient support operation, the introduction of AI automated resolutions is now fundamentally changing what this metric means.

Why One-Touch Rate Should Decrease with AI?

The most important question to ask is: what are most "one-touch" tickets?

Think about them:

• "How do I reset my password?"

• "What is your return policy?"

• "Where is my order?"

These are simple, repetitive, low-complexity questions. And in 2026, these are exactly the tickets that a well-implemented AI bot should handle.

This is the critical shift:

1. Your AI bot should be deflecting a very high percentage of these simple, repetitive "one-touch" issues before they ever reach a human.

2. This means the only tickets that get through to your agents are the complex, high-friction problems that require human empathy and advanced problem-solving.

3. By definition, these complex issues are almost never one-touch tickets. They require investigation, follow-up, and multiple replies.

Therefore, a decreasing one-touch rate for your human team is a sign of success after implementing AI. It's a key indicator that your AI strategy is working.

Your bots are handling the simple, high-volume work, freeing your expensive, skilled agents to focus on the high-value, complex problems.

Your new goal isn't a high agent one-touch rate; it's a high bot resolution rate.

What to Measure Now

One-Touch Resolution isn't a "bad" metric, but its meaning has evolved.

Stop chasing a high agent one-touch rate as your primary goal. Instead, start measuring:

1. Bot Resolution Rate: How many of those simple, repetitive "one-touch" issues is your AI successfully deflecting? This is your new primary efficiency metric.

2. Agent-Handled Ticket Complexity: This measures if the tickets reaching your human agents are the right ones (i.e., complex, multi-step problems).

3. Agent One-Touch Tickets: You should still track your agents' one-touch resolutions, but for a new reason. Every one-touch ticket probably represents a missing use case the bot could handle. Treat this report as an improvement queue for your AI, highlighting the simple issues that should be added to its automated workflows.

The main takeaway: Your goal is to have your AI handle the "one-touch" problems so your human experts can focus on the complex issues that truly require their skill.

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About the Author:

Moshe Anisman is a CX consultant and Zendesk expert who helps support teams build efficient, scalable, and data-driven operations. When he's not optimizing client workflows, he builds apps for the Zendesk Marketplace, including the Advanced User Merge app to automatically detect duplicates and easily merge them with one click.