Your complete Zendesk Explore tutorial for 2025

If you work in customer support, you live and breathe data. Ticket volume, agent performance, customer satisfaction, these aren't just buzzwords, they're the pulse of your entire operation. Zendesk Explore is supposed to be the tool that helps you make sense of it all. And it can be, but let's be real: sometimes firing it up feels like you're about to take a statistics final you didn't study for.

This guide is here to fix that. We'll walk you through a practical Zendesk Explore tutorial to build your first reports and dashboards from scratch. We’ll also cover the very real limitations you'll bump into when trying to measure modern, AI-driven support and show you a smarter, more intuitive alternative.

What is Zendesk Explore?

Think of Zendesk Explore as the command center for all your support data. It pulls information from every customer interaction (tickets, calls, chats) and gives you the tools to build reports and dashboards. To get anywhere, you just need to get your head around three main building blocks:

• Datasets: These are basically pre-sorted buckets of data. Think of them as starting points, like "Support - Tickets" or "Support - Updates History". Picking the right one is your first, and honestly, sometimes the trickiest, step.

• Metrics: This is the "what" you want to measure. It's almost always a number, like the "COUNT(Tickets)" or the average number of "Agent replies".

• Attributes: This is the "how" you want to slice up your data. For example, you might want to look at your ticket count (the metric) and break it down by "Assignee name" (an attribute) or "Ticket created - Date" (another attribute).

Nailing this combination is the secret to building a report that actually tells you something useful. It just takes a clear idea of what you want to find out and a little patience to find where Zendesk keeps that info.

A Zendesk Explore tutorial: Building your first ticket volume report

Alright, let's build something. A great first report is to see how many tickets are assigned to each agent. It's super useful for balancing workloads and seeing who might be getting swamped.

Step 1: Choosing the right dataset

First, we have to tell Explore which bucket of data to use. For pretty much any report about tickets, the "Support - Tickets" dataset is your best bet. It has all the basic info you'll need.

Step 2: Adding metrics and attributes

Now for the fun part, building the actual query.

1. Head to the Metrics panel and click Add. Search for and select "Tickets". Explore is smart enough to know you probably want to count them, so it will automatically apply "COUNT(Tickets)".

2. Next, in the Columns panel, click Add. This is how you'll break the data down. Find and select "Ticket created - Date" to see the ticket numbers over a period of time.

3. Let's add one more layer. In the Rows panel, click Add and select "Assignee name". This will show you which agent is handling which tickets.

You've just asked Explore to "Show me the count of tickets, broken down by the date they were created and by the agent assigned to them."

Step 3: Customizing and visualizing your report

A giant table of numbers is a start, but a chart is way easier to understand at a glance.

• On the right side of the screen, find the Chart configuration menu (it looks like a paintbrush). Click it and pick a different chart type, like a bar chart or a line graph, to see what looks best.

• To keep things snappy, you should filter your data. Click Add in the Filters panel at the top and select "Ticket created - Date". From here, you can choose a specific range, like "Last 30 days," so you're not trying to load your entire company history at once.

Step 4: Adding your report to a dashboard

Once your report looks good, click Save. Now you can pop it onto a dashboard with your other key reports. Just go to your dashboard, click Add > Add report, and pick the one you just made. You can move it around and resize it until you have the perfect custom view for your team.

3 essential reports to build in Zendesk Explore

Now that you've got the hang of it, here are three other reports you should definitely build in Zendesk Explore to get a better handle on your support operations.

Tracking agent performance and workload

It's not just about how many tickets an agent takes, but how efficiently they handle them.

• Metrics to use: "Solved tickets", "First reply time (hrs)", "Full resolution time (hrs)".

• Attributes to use: "Assignee name", "Ticket channel".

• Why it matters: This helps you spot your top performers (who can maybe mentor others) and identify agents who are struggling or just plain overloaded. It's key to balancing the workload fairly.

Monitoring customer satisfaction (CSAT)

Knowing how your customers actually feel after an interaction is gold.

• Metrics to use: "% Satisfaction Score", "Good satisfaction ratings", "Bad satisfaction ratings".

• Attributes to use: "Ticket tags", "Ticket channel", "Agent name".

• Why it matters: This report can show you if certain types of issues or specific channels are leading to unhappy customers. It gives you a clear target for where to improve your training or processes.

Measuring AI and automation impact

If you're using Zendesk's built-in AI, you can create reports to track things like "Automated resolutions" to see how many tickets the bot is deflecting. But that brings up a couple of big questions: What happens when your knowledge isn't just in Zendesk? And how do you get insights that help you improve your automation, instead of just a summary of what already happened? This is where you start to feel the edges of what Explore can do.

Where Zendesk Explore falls short

Look, for basic reports, Explore gets the job done. But if you're a modern team trying to use AI and manage knowledge that's scattered everywhere, you're going to hit a wall. Fast.

Steep learning curve and complexity

As one frustrated user put it in a Zendesk forum, it can feel like you need to be a data scientist to get anything useful. The whole process of picking the right dataset, metric, and attribute can be rigid and confusing. Getting the report you actually need often feels like a whole lot of trial and error.

In contrast, platforms like eesel AI are built to be used by anyone on the team. You connect your helpdesk, and you get useful AI analytics right away, no data science degree required.

Siloed data

The reality is, your company's "brain" isn't just in Zendesk articles. It's in that super-helpful Google Doc the engineering team wrote, the answers in that one Slack channel, and that massive Confluence space. Zendesk Explore is completely blind to all of it. This means your reports are only telling part of the story. An AI-powered platform should learn from everything, which is exactly what eesel AI does. It instantly connects these scattered sources, giving your AI agents and your analytics the full picture.

This infographic from the Zendesk Explore tutorial alternative, eesel AI, shows how it connects scattered knowledge sources.

Reactive reporting vs. proactive insights

Zendesk Explore is fantastic at showing you what already happened. It’s a rearview mirror. But it's not going to tell you why your AI agent fumbled a question or what knowledge base article you desperately need to write next.

This is where the reporting in eesel AI really makes a difference. It gives you insights you can actually use by flagging knowledge gaps when the AI can't find an answer. If customers keep asking a question that stumps your bot, it shows up in your analytics. It's basically a to-do list for improving your documentation and boosting your automation rate.

This screenshot shows how eesel AI provides proactive insights by flagging knowledge gaps, a key limitation discussed in this Zendesk Explore tutorial.

Zendesk pricing for reporting and AI

Getting access to the more powerful reporting and AI features in Zendesk doesn't come free. While you get some basic reporting on the lower-tier plans, the good stuff, like fully custom reports and real-time dashboards, is saved for the more expensive plans.

Pricing sourced from Zendesk's pricing page as of late 2024.

A better alternative: Confident, actionable AI reporting with eesel AI

Instead of building reports and just hoping your AI is working, you need a tool that lets you test things out with confidence. This is where eesel AI’s simulation mode makes a huge difference. It lets you test your AI agent on thousands of historical Zendesk tickets in a safe environment, all before a single customer ever talks to it. You get a clear forecast of your resolution rate and potential cost savings, taking the guesswork out of launching AI.

The eesel AI simulation mode, an alternative to the methods in this Zendesk Explore tutorial, lets you test AI performance on historical tickets.

On top of that, eesel AI's analytics are built for taking action. The dashboard doesn't just show you pretty numbers; it points out your biggest automation opportunities and shows you exactly where the gaps are in your knowledge base. It gives you a clear path to keep getting better.

Move beyond basic reporting

So, there you have it. This Zendesk Explore tutorial should give you the confidence to start building some genuinely useful reports. It’s a solid native tool for looking back at what's happened in your support world.

But for today's support teams, just looking back isn't enough. To scale effectively with AI, you need a platform that’s easy to use, connects all your company knowledge, gives you proactive insights, and lets you deploy new tools without crossing your fingers. You need analytics that don't just report on the past but help you build a much more efficient future.

Ready to see what truly actionable AI analytics look like? Discover how eesel AI can transform your Zendesk reporting and automation in minutes.