The Zendesk AI Agent Performance Dashboard: A 2025 guide

Stevia Putri

Stanley Nicholas
Last edited October 15, 2025
Expert Verified

So you’ve launched an AI agent. That's a big step. But the real question is, is it actually helping? If you're not measuring its performance, you're basically flying blind. You have no idea if it's solving customer problems or just creating more headaches for your human agents. Are you saving money, or just paying for "solutions" that don't actually solve anything?
For teams using Zendesk, the tool for figuring this out is the Zendesk AI Agent Performance Dashboard. In this guide, we'll break down what it is, the metrics you absolutely need to watch, and some of its real-world limitations. We’ll also show you how a tool like eesel AI can give you a clearer, more powerful way to manage your support automation.
What is the Zendesk AI Agent Performance Dashboard?
Let's clear something up right away: the "dashboard" isn't actually a single dashboard. It's more like a few different reports and analytics tools scattered across Zendesk that you have to stitch together to see the whole picture.
Depending on your plan and the AI features you use, you'll find yourself jumping between a few different spots:
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The Insights Dashboard: This is your basic reporting tool for Zendesk’s core AI features. You’ll find it in the Admin Center, where it gives you a quick look at things like active users, transfers to human agents, and the number of automated resolutions. It’s a decent place to start, but you’ll probably outgrow it pretty quickly if you need to dig deeper.
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The Analytics Dashboard: If you're paying extra for the Advanced AI add-on, this is where you'll live. It gives you a more detailed look with tabs for overall performance, why customers are reaching out in the first place ("contact reasons"), and resolution data. You'll spend most of your time here trying to figure out what’s really going on.
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The Copilot Dashboard: This one is off on its own. It only focuses on how your human agents are using Zendesk’s AI-assist tools, like suggested replies and ticket summaries. It’s useful for tracking if your team is using the tools, but it doesn't really connect back to how your main AI agent is performing on its own.
You can probably see the problem already. To get a full understanding of how your AI agent is affecting your team’s workload, you have to bounce between at least two or three different interfaces. This disjointed setup makes it tough to get a single, clear view of your entire support operation.
Key metrics on the Zendesk AI Agent Performance Dashboard
No matter which dashboard you’re looking at, the KPIs are what count. These numbers are the story of whether your AI is a helpful teammate or just a frustrating bot. Here are the most important ones to keep an eye on.
Core performance metrics
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Automated Resolutions: This is the big one. It's the percentage of conversations your AI handles all by itself, from start to finish. A high number here is a good sign that your AI is deflecting tickets and giving you a return on your investment.
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Escalated Conversations: This is the other side of the coin. It tracks how many times the AI had to throw its hands up and pass a conversation to a human. A high escalation rate is a huge red flag. It could mean your AI doesn't have the knowledge it needs, or you're asking it to solve problems that are just too complicated for it.
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First Contact Resolution (FCR): We usually think of FCR as a metric for human agents, but your AI has a huge effect on it. If the AI agent nails a simple question on the first try, your FCR rate improves. If it gets confused and escalates a messy conversation to an agent, your FCR rate takes a hit.
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Customer Satisfaction (CSAT): Are people actually happy with the automated help they're getting? CSAT surveys tell you exactly that. A low score on automated chats is a clear signal that your AI is creating a bad experience, even if it’s technically "resolving" tickets.
Agent and AI interaction metrics
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Copilot Adoption: This metric, found in the Copilot dashboard, shows you how often your human agents are using AI-powered suggestions. If adoption is low, it might mean the suggestions aren't very good, or maybe your team just needs a bit more training to get the hang of it.
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Knowledge Source Usage: This report tells you which help center articles and internal docs your AI is leaning on to come up with answers. It's a great way to see what content is most valuable and to spot gaps where the AI is coming up empty.
Here’s a quick rundown of what to keep an eye on:
Metric | What It Measures | Why It Matters |
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Automated Resolutions | Percentage of issues solved entirely by the AI agent. | Directly shows ROI and deflection effectiveness. |
Escalation Rate | Percentage of AI conversations handed to a human agent. | Highlights knowledge gaps or overly ambitious automation. |
CSAT | Customer satisfaction with the AI interaction. | Tells you if the automated experience is actually good. |
Copilot Usage | How often human agents use AI-assist features. | Shows if AI tools are actually helping your agents. |
Knowledge Usage | Which documents the AI relies on for answers. | Helps you identify and improve your most critical content. |
How to use the Zendesk AI Agent Performance Dashboard to improve your support
Having data is one thing; doing something with it is another. Once you know your numbers, you can start making smart changes to your AI and your support workflows.
Here’s what a support manager can do with these dashboards:
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Pinpoint knowledge gaps: Check out the "Contact Reasons" report or look at conversations that weren't resolved. These are basically a to-do list of questions your AI can't answer. You can then go create the help center articles or internal guides to fill those gaps.
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Fine-tune AI agent responses: Don't just look at the escalation rate; read the transcripts of the conversations that got escalated. This helps you understand why the AI failed. Maybe it misunderstood the user, or maybe it just didn't have the right info. You can use what you learn to adjust the AI's prompts or connect it to better knowledge sources.
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Improve agent training: If the Copilot dashboard shows that some agents are ignoring the AI tools, you can offer them some one-on-one coaching. Sometimes, people just need a little nudge to see how much time a feature like suggested replies can save them.
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Refine your ticket routing: Look at how the AI is sorting and sending incoming tickets. If you see that billing questions are always ending up in the technical support queue, you can tweak your automation rules to fix it. Getting the ticket routing right from the start saves everyone a ton of time.
Zendesk AI pricing and its impact on performance analytics
It's important to talk about Zendesk's pricing because it can change how you use its AI. While some basic AI features are baked into the Zendesk Suite plans, the really useful stuff often costs extra.
The main Zendesk plans with AI are:
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Suite Team: Starts at $55 per agent/month (billed annually)
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Suite Professional: Starts at $115 per agent/month (billed annually)
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Suite Enterprise: Starts at $169 per agent/month (billed annually)
But tools like the Advanced AI agents and Copilot are usually sold as add-ons, which can run you an extra $50 per agent per month.
Here’s the real kicker, though: Zendesk charges you for each "automated resolution" (AR). It’s a pay-as-you-go model where every successful resolution can cost you between $1.50 and $2.00. This means your bill can swing wildly from one month to the next. If you get a surge in customer questions, your Zendesk bill surges right along with it, which makes budgeting a nightmare. This pricing can also make teams nervous about automating more, since a failed attempt could still cost money without delivering any value.
Limitations of the Zendesk AI Agent Performance Dashboard
While Zendesk gives you some decent tools, a lot of teams hit a wall when they try to get a truly clear, actionable picture of their AI's performance. The platform has some real drawbacks.
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Scattered reporting: Like we mentioned, the data is all over the place. You're constantly switching between the Insights dashboard, the Analytics dashboard, and the Copilot dashboard just to connect the dots. There's no single source of truth to see how your AI and human agents are working together.
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No real way to test things out: This is a big one. Zendesk doesn't give you a good way to test your AI on old tickets before you let it talk to your customers. You can't get an accurate forecast of its performance, what its resolution rate might be, or how much it will cost you. You’re kind of forced to just launch and hope for the best, which is a risky move.
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It’s a bit of a black box: The logic behind Zendesk's AI can feel mysterious. It's often hard to figure out why the AI made a certain decision or misread a ticket. And trying to customize reports in Zendesk Explore can be a real pain, feeling more like a job for a data analyst than a support manager.
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Reporting delays: The data in Zendesk’s dashboards isn’t always live. Some reports only refresh every hour or even once a day, meaning you’re always looking at slightly old information. For teams that need to jump on emerging issues quickly, this lag can be a real problem.
eesel AI: An alternative to the Zendesk AI Agent Performance Dashboard
The built-in Zendesk analytics get you started, but teams looking for more control, transparency, and simplicity often find them frustrating. This is where a platform like eesel AI offers a different approach.
eesel AI was built to solve the exact problems people face with native help desk AI. It plugs right into your existing Zendesk account in a few minutes, so you don't have to switch platforms or change how you work.
Here’s how it handles reporting differently:
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One dashboard for everything: Forget juggling multiple tabs. eesel AI gives you a single, straightforward analytics dashboard that puts everything in one place. It doesn't just show you what the AI did; it points out gaps in your knowledge base and spots trends, giving you a clear list of things to work on.
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Test without the risk: This is huge. eesel AI lets you safely test your entire AI setup on thousands of your own past tickets in a "simulation mode." You can see exactly how it would have answered, get accurate predictions on resolution rates, and calculate your potential cost savings before you ever turn it on for customers. It takes all the guesswork out of the equation.
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You're in control: With eesel AI, you're calling the shots. You get fine-grained control over which tickets get automated and a clear view into why the AI makes the decisions it does. No more black boxes.
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Simple, predictable pricing: The pricing is straightforward. Plans are based on the features you need, with no sneaky per-resolution fees. Your bill is the same every month, so you don't get punished for having a busy, successful month.
eesel AI's unified dashboard provides a clear overview of AI performance, a powerful alternative to the Zendesk AI Agent Performance Dashboard.
You can connect eesel AI to your Zendesk account with one click and start seeing the difference almost right away.
Final thoughts
For any modern support team, measuring AI performance isn't optional. The Zendesk AI Agent Performance Dashboard gives you a place to start, but its scattered reports, unpredictable pricing, and lack of a good testing environment can hold you back.
A platform like eesel AI offers a more unified, transparent, and effective way to not only track but also manage and improve your support automation. It provides the control and insights you need to build an AI experience that both your customers and your agents will actually like.
Ready for AI analytics that give you confidence and control? Sign up for eesel AI and see how it works with your Zendesk data today.
Frequently asked questions
The Zendesk AI Agent Performance Dashboard isn't a single entity but a collection of reports across Zendesk's Insights, Analytics, and Copilot dashboards. You need to combine data from these different areas to get a complete view of your AI agent's performance.
Key metrics include Automated Resolutions, Escalated Conversations, Customer Satisfaction (CSAT), and First Contact Resolution (FCR). Tracking these helps you understand your AI's effectiveness in solving customer issues and impacting overall support efficiency.
You can use reports like "Contact Reasons" and analyze escalated conversations to pinpoint areas where your AI agent lacks knowledge. This data helps you create new help center articles or update existing ones to improve the AI's ability to resolve future inquiries.
Unfortunately, the Zendesk AI Agent Performance Dashboard does not offer robust tools for testing AI performance on historical tickets before deployment. You are typically required to launch the AI live to customers to begin gathering performance data.
Common limitations include scattered reporting across multiple dashboards, a lack of pre-deployment testing capabilities, and a somewhat "black box" approach to AI logic. Additionally, reporting delays mean data isn't always real-time, which can hinder quick decision-making.
Zendesk charges for each 'automated resolution,' which can lead to unpredictable billing and potentially influence how you view your AI's success. This model makes it crucial to closely monitor resolution rates via the dashboard to ensure cost-effectiveness.
While some customization is possible using Zendesk Explore, it can be complex and often requires a deeper understanding of data analysis. Many users find it challenging to customize reports effectively to gain highly specific or granular insights.