How to use Zendesk messaging reporting with Explore dataset

First reply time, resolution rates, customer satisfaction. These metrics tell you how your support team is performing. But if you're using Zendesk Messaging, you might have noticed something: the reporting works differently than standard tickets.

The Zendesk messaging reporting Explore dataset is separate from your regular Support tickets data. It lives in a different place, uses different metrics, and follows different rules. This guide will walk you through everything you need to know to build effective messaging reports in Zendesk Explore.

By the end, you'll understand which dataset to use, what metrics are available, how to create custom reports, and how to turn those insights into action.

What you'll need

Before getting started, make sure you have the right setup:

• Zendesk Suite Professional or higher. Custom reporting requires Explore Professional, which comes with Professional, Enterprise, or Enterprise Plus plans. Team and Growth plans only include read-only access to prebuilt dashboards. (Source: Zendesk)
• Zendesk Messaging enabled. This guide covers messaging channels specifically, not legacy live chat.
• Admin or Editor role in Explore. You'll need permissions to create and save reports.
• Realistic expectations about historical data. Messaging data is only available from September 20, 2022 onwards. If your account predates this, you won't see older messaging conversations in Explore.

Understanding the Zendesk messaging reporting Explore dataset

Here's where things get confusing. Zendesk has two main datasets that contain messaging data, and choosing the wrong one is the most common reporting mistake.

The two datasets explained

1. Support: Tickets dataset This is your general ticketing data. It contains all tickets across all channels. You can filter this dataset by channel to see messaging tickets, but the metrics are designed for traditional ticket workflows.

2. Chat: Messaging tickets dataset This is the dedicated Zendesk messaging reporting Explore dataset. It's specifically designed for messaging conversations and contains metrics that only apply to messaging, like handle time, offer acceptance rates, and session-based analytics.

So which should you use? Here's the short version:

Where to find the messaging dataset

When you create a new report in Explore, you'll see a list of datasets. The messaging dataset is grouped under "Zendesk Chat" (yes, even though it's for messaging). Look for Chat > Messaging tickets.

If you don't see this option, check that:

• You're on a plan that includes Explore Professional
• Messaging is enabled on your account
• You have the correct permissions

Data availability and limitations

Messaging data comes with some important caveats:

• Historical cutoff: No data before September 20, 2022
• Handle time metrics: Only available from July 18, 2023 onwards
• Offer and acceptance tracking: From October 30, 2023 onwards
• Session end analytics: From September 29, 2025 onwards

If you're building reports and seeing blank data, check whether your date range predates these availability windows.

Key metrics for Zendesk messaging reporting

The messaging dataset includes dozens of metrics. Here are the ones you'll actually use, organized by what they measure.

Response time metrics

These are the metrics most support teams track religiously:

Each of these has both calendar hours and business hours variants. Business hours metrics exclude time outside your schedule, which gives you a clearer picture of actual team performance.

Volume and efficiency metrics

• Messaging tickets: Total created
• Solved messaging tickets: Resolved conversations
• One-touch messaging tickets: Solved with a single agent reply (high efficiency indicator)
• % One-touch messaging tickets: Percentage solved in one touch
• Unsolved messaging tickets: Current backlog
• Agent messages: Total messages sent by agents
• Agent replies: Total conversation responses (slightly different from messages)

Handle time (new in 2023)

Handle time measures how long agents spend actively interacting with a conversation. This is different from resolution time. A ticket might take 24 hours to resolve, but the agent only spent 8 minutes actively working on it.

Handle time is available in seconds, minutes, hours, and days, with both calendar and business hours variants. (Source: Zendesk)

Routing and assignment metrics (2023+)

If you're using omnichannel routing, these newer metrics help you understand assignment efficiency:

• First offer time: When the ticket was first offered to an agent
• First offer to assignment: How long it sat in the offer state
• Offers before first acceptance: How many agents declined before someone accepted
• % First acceptance rate: Percentage accepted by the first agent offered

Low acceptance rates often indicate routing rules that need tuning.

Using the prebuilt Zendesk Messaging dashboard

Before building custom reports, check what's already available. Zendesk includes a prebuilt Messaging dashboard with six tabs covering common reporting needs.

Dashboard overview

To access it: Explore > Dashboards > Zendesk Messaging

The dashboard includes these tabs:

Overview: High-level metrics including ticket volume, resolution rates, and satisfaction scores. Use this for executive summaries.

Efficiency: Reply times and resolution metrics. Good for identifying bottlenecks.

Assignee activity: Agent-level performance including tickets solved, reply times, and one-touch rates. Use this for 1:1s and performance reviews.

Unsolved tickets: Backlog analysis showing unreplied tickets, ticket age, and status breakdown. Essential for queue management.

First reply time: Detailed FRT breakdown including offer time, assignment time, and actual reply time. Helps diagnose where delays happen.

Goal conversions: If you're using messaging goals, this tracks conversion rates and transaction values.

Customizing the dashboard

The prebuilt dashboard is read-only, but you can clone it:

1. Open the dashboard
2. Click the three-dot menu
3. Select "Clone"
4. Name your copy
5. Edit as needed

Cloning lets you add your own reports, remove irrelevant tabs, and apply filters that persist across sessions.

Creating your first messaging report: a step-by-step guide

Ready to build something custom? Here's how to create a messaging report from scratch.

Step 1: Open Explore and select the dataset

1. Navigate to Explore in the left sidebar
2. Click the Reports icon
3. Click New report
4. Select Chat > Messaging tickets from the dataset list
5. Click Start report

You'll see the report builder with four main panels: Metrics, Columns, Rows, and Filters.

Step 2: Add your metrics

Metrics are the numbers you want to measure. Let's say you want to track first reply time.

1. In the Metrics panel, click Add
2. Expand the First reply time folder
3. Select First reply time (min)
4. Click Apply

Your report will show the total first reply time across all messaging tickets. This isn't particularly useful yet, which is why we need attributes.

Pro tip: You can add multiple metrics to the same report. Try adding "Messaging tickets" alongside your time metrics to see volume alongside performance.

Step 3: Configure attributes and filters

Attributes slice your data by categories. They turn raw numbers into insights.

To add a time filter:

1. In the Filters panel, click Add
2. Select Time - Ticket created
3. Choose your date range (Last 30 days, This month, etc.)

To break down by agent:

1. In the Rows panel, click Add
2. Select Assignee name under the Users folder
3. Click Apply

Now you see first reply time broken down by individual agents. Suddenly your data tells a story.

Common useful attributes:

Step 4: Choose your visualization

Explore automatically picks a visualization, but you can change it:

1. Click the Visualization type dropdown
2. Select your preferred chart type:
   • Column/Bar: Good for comparing values across categories
   • Line: Best for trends over time
   • Table: When you need exact numbers
   • Pie: For percentage breakdowns (use sparingly)

For first reply time by agent, a bar chart works well. For trends over time, use a line chart.

Step 5: Save and share

1. Give your report a descriptive name (e.g., "Messaging FRT by Agent - Last 30 Days")
2. Click Save
3. To add to a dashboard: Open your dashboard, click Add > Add report, and select your saved report

Scheduling options:

• Professional plans: Can schedule delivery to agents and light agents
• Enterprise plans: Can schedule to external email addresses
• Set your cadence (daily, weekly, monthly) and time range

Common Zendesk messaging reporting scenarios

Here are practical recipes for reports you'll actually use.

Scenario 1: First reply time by group

Goal: Compare how quickly different teams respond to messaging tickets.

Setup:

• Metric: First reply time (min) - average
• Row: Ticket group
• Filter: Last 30 days
• Visualization: Bar chart

This identifies which groups need additional training or staffing.

Scenario 2: Messaging volume trends

Goal: Track conversation volume over time to identify patterns.

Setup:

• Metric: Messaging tickets
• Column: Ticket created - Week
• Filter: Last 12 weeks
• Visualization: Line chart

Look for seasonal patterns or spikes after product launches.

Scenario 3: One-touch resolution rate

Goal: Measure efficiency by tracking tickets resolved in a single interaction.

Setup:

• Metric: % One-touch messaging tickets
• Row: Assignee name
• Filter: Last 30 days, Solved tickets only
• Visualization: Bar chart or table

High one-touch rates indicate effective self-service, clear documentation, or simple inquiry types.

Scenario 4: Unsolved backlog by age

Goal: Identify stale tickets that need attention.

Setup:

• Metric: Unsolved messaging tickets
• Row: Unsolved tickets age brackets
• Filter: Status = New, Open, Pending, On-hold
• Visualization: Column chart

Use this in daily standups to prioritize aging tickets.

Scenario 5: WhatsApp 24-hour window tracking

Goal: Identify WhatsApp tickets approaching the 24-hour reply window.

Note: This requires an automation, not just a report. Zendesk Explore can't build countdowns, but you can use automations to tag tickets nearing the limit.

Automation setup:

1. Create an automation
2. Conditions: Ticket channel = WhatsApp, Hours since created > 20, Status = Open
3. Actions: Add tag "whatsapp_urgent", Notify assignee

Then build a report filtering by that tag.

Troubleshooting common Zendesk messaging reporting issues

"Why is my satisfaction data empty?"

This is the most common reporting confusion. Messaging satisfaction doesn't always appear where you expect it.

The issue: CSAT for messaging is stored in the Messaging tickets dataset, not the Support Satisfaction dataset. Use the Chat > Messaging tickets dataset and look for the "% Satisfaction score" metric.

Also check: Your satisfaction survey is actually enabled for messaging channels. Go to Admin Center > Channels > Messaging > Satisfaction to verify.

"My reports show no historical data"

Messaging data only exists from September 20, 2022. If your date range is earlier, you'll see blanks. Additionally, newer metrics like handle time have their own cutoff dates (July 2023 for handle time, October 2023 for offer metrics).

"Calendar hours vs business hours - which should I use?"

• Calendar hours show the complete customer experience, including time spent waiting overnight or on weekends. Use this for customer-facing SLAs.
• Business hours show your team's actual working time. Use this for internal performance reviews and capacity planning.

Most teams track both. Calendar hours tell you if customers are waiting too long. Business hours tell you if your team is working efficiently.

"Why don't my numbers match the Support dashboard?"

The Support dashboard uses the Support: Tickets dataset. If you're looking at the same tickets in the Messaging dataset, minor differences are normal due to how each dataset calculates timestamps. For messaging-specific analysis, always use the Messaging dataset. For cross-channel comparisons, use Support with channel filters.

From Zendesk messaging reporting to action

Reports are only valuable if they lead to improvements. Here's how to turn your Explore insights into better customer experiences.

When first reply time is too high

Your reports show agents are taking too long to respond. The fix depends on where the delay happens:

Before assignment: If tickets sit unassigned, your routing rules need work. Consider using eesel AI's AI Triage to automatically categorize and route tickets to the right queue faster.

After assignment: If agents have tickets but aren't replying, they may need better tools. An AI Copilot can draft responses based on your knowledge base, cutting reply time significantly.

When one-touch rates are low

Complex tickets aren't necessarily bad, but if simple questions are requiring multiple back-and-forths, you have an opportunity. An AI Agent can handle common questions instantly, giving customers a true one-touch (or zero-touch) experience while freeing your team for complex issues.

When volume exceeds capacity

If your volume trends show sustained growth that outpaces team capacity, you have three options: hire more agents, improve self-service, or automate. We've written about this in depth in our guide on reporting and improving first reply time for messaging tickets.

Improve your Zendesk messaging performance today

You now have everything you need to build effective messaging reports in Zendesk Explore. You understand the dataset structure, know which metrics to track, and can create custom reports for your specific needs.

The real value comes from acting on those insights. Reporting shows you where the problems are. The right tools help you fix them.

If you're looking to improve your messaging metrics beyond what native reporting can measure, eesel AI integrates directly with Zendesk to provide AI-powered triage, automated responses, and agent assistance. It's how modern support teams turn reporting insights into customer experience improvements.

Start with your reports. Understand your baseline. Then build from there.