It’s one thing to set up Zendesk AI. It’s another to prove it’s actually working. Whether your goal is faster response times, fewer manual tickets, or better customer satisfaction, you need real numbers to back up the investment.
This chapter covers what to track, how to track it, and what a good ROI looks like when AI is doing its job or not.
Key metrics
Here are the core metrics that matter when measuring Zendesk AI performance:
- CSAT (Customer Satisfaction Score)
Are your customers actually happier? Watch for improvements here once AI starts resolving simpler issues faster. - FRT (First Response Time)
AI should bring this number down, especially for high-volume tickets like FAQs and status requests. - Resolution Time
Good AI speeds up overall resolution for simple tickets, freeing agents to focus on complex ones. - Ticket Deflection Rate
How many tickets never hit an agent because AI resolved them? This is where AI can drive serious ROI if your volume is high.
Chapter 6.1: How to build a baseline and measure progress
Building a baseline
Before you let AI loose, take a step back and measure what is going on right now. This is your baseline. Without it, you will not really know if things are improving.
Start by tracking:
- CSAT scores over the last 30 days
- Average first response and resolution times
- How many tickets your team handles manually vs through self-service
- What kind of tickets are taking up the most time
This snapshot will give you something real to compare to once AI is running.
Measuring progress
Check your numbers weekly at first, then monthly. Do not just look for small dips and call it a win. You want to see patterns:
- Is your deflection rate climbing steadily?
- Are agents actually spending less time on repetitive tickets?
- Are customers happier and reopening fewer tickets?
If you are not seeing these things, AI might be active but not actually helping. It might need fine-tuning or better content to work from.
