- Welcome
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Getting started 2 min
- Main content
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Turn your metrics into measurable wins: Zendesk's approach to AI agent optimization 45 min
- Wrap up
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Course summary 4 min
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Share your feedback 5 min
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Congratulations 1 min
Turn your metrics into measurable wins: Zendesk's approach to AI agent optimization
Learn Zendesk's step-by-step method for optimizing your AI agent's performance through controlled testing and data-driven decisions.
Learn the data-driven method Zendesk uses to optimize Zea, its AI agent, and apply it to your own environment through hands-on, scenario-based decision-making. This interactive course walks you through two realistic test cycles—from spotting performance gaps in conversation logs to designing controlled tests, interpreting results, and confidently rolling out improvements. By the end, you will have a repeatable framework for turning assumptions into evidence and untapped potential into measurable gains.
Learning objectives
By the end of this course, you will be able to:
- Identify optimization opportunities — Analyze conversation logs and metrics to pinpoint areas where controlled testing can improve your AI agent's performance.
- Design and execute controlled tests — Create clear hypotheses, define success metrics and guardrails, set up traffic splits, and monitor results using a structured framework.
- Make data-driven decisions — Interpret test results, understand the root causes behind performance changes, and confidently roll out improvements based on validated findings.
Audience
This course is intended for all audiences.
Prerequisites
No prior knowledge is required.