Measuring the ROI of Copilot with analytics




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Copilot






Copilot brings AI to your service workflows, helping agents respond faster and
assisting customers sooner. To understand Copilot’s value, you need reliable, actionable
data. Before getting started, establish a clear baseline; knowing where you started
makes it easier to measure improvements and prove ROI over time.
Zendesk analytics help you monitor how Copilot tools impact ticket handling,
agent performance, and customer satisfaction. This article walks through best practices
on where to find prebuilt dashboards, which metrics to monitor, and how to customize and
share your reporting.
This article contains the following topics:

Using prebuilt dashboards to measure performance
Building custom reports with key Copilot metrics
Sharing results with stakeholders
Helpful resources



Using prebuilt dashboards to measure performance

The following prebuilt dashboards can help you to monitor and measure your Copilot
performance:

Zendesk Copilot: Agent productivity dashboard
Intelligent triage dashboard



Zendesk Copilot: Agent productivity dashboard

The Zendesk Copilot: Agent productivity dashboard is your command
center for monitoring how agents interact with Copilot AI in Zendesk. The dashboard
is organized into two tabs: AI suggestions and AI agent tools. It offers a clear
view of adoption and engagement across key AI tools, helping you track usage,
optimize workflows, and drive productivity.
Here's an overview of the two tabs:


AI suggestions: Measures engagement and performance of
Copilot features like similar tickets, merging suggestions, suggested macros, suggested replies and quick answers.

AI agent tools: Captures how agents use writing tools such
as expand, make formal, make friendly and ticket summary (we plan to expand
this tab to include enhanced writing tools like
simplify, custom prompt, and rewrite in your tone, as well as new
dimensional filters, such as channel, ticket ID and others). This tab
mirrors the current Generative AI Agent Tools dashboard. Because it
includes the same insights, we will deprecate the existing Generative AI
Agent Tools dashboard in Q3 2025 as part of the Dashboard Builder transition
process.


Key things to look for:

Compare tickets solved with AI to those without and measure
high-level agent adoption. Then look at specific agents’ AI usage and
cross-reference with their overall performance.
Spot agents with high AI suggestion acceptance rates. Use this
data to recognize and reward early adopters, or involve them in peer-to-peer
enablement and best practice sharing.
Analyze how features like suggested replies, merging suggestions,
and ticket summaries are being used. If adoption is low, investigate why,
then update training or processes. If adoption is high, scale those
behaviors across your team to improve resolution speed and consistency.
Track how AI tools are impacting key metrics like agent
productivity, resolution time, and customer satisfaction. By correlating AI
adoption with improved support outcomes, you can clearly demonstrate the
value of your AI investment to leadership.
Use the Zendesk Copilot: Agent productivity dashboard to compare
wait times for tickets with and without generative AI. For deeper insight
into agent handling time, we recommend the Time Tracking app from the Zendesk
Marketplace. This app helps you measure how long agents spend on each
ticket. To get meaningful results, make sure you're comparing similar ticket
types. For example, simple tickets or those automatically solved are
typically faster to resolve and may not require AI assistance, which can
skew the data if not properly segmented.




Intelligent triage dashboard

The Intelligent triage dashboard provides
valuable insights into your tickets, which you can use to improve your workflow
and determine how effective your service is. You can view the most common ticket
intents, check sentiment trends, and review how well triage is distributing
work. The intelligent triage dashboard has four tabs with detailed views of
intent, language, and sentiment.
Key things to look for:

Identify the top intents of incoming requests and monitor KPIs
across AI insights, allowing teams to make key optimization decisions.
Review one touch tickets by top intents and use those insights to
automate processes.
Reduce escalations by identifying low-sentiment intents. Use
customer sentiment reporting to spot common topics with negative sentiment,
then build or refine escalation workflows to proactively address them before
they escalate.
Optimize resource allocation across teams by reviewing ticket
distribution across different languages.
Look for intents or languages where resolution takes longer or
requires multiple replies. These patterns can point to training or workflow
improvement opportunities.





Building custom reports with key Copilot metrics

If you want more control over what you track, Zendesk analytics lets you
build custom reports using relevant Support and Copilot data. Here are some of the
common metrics customers tend to measure before and after they implement copilot:










Metric
What is it
Why it matters
Best practices / Actions


First response time
Time between ticket creation and the first agent
response.
Shows how quickly your team is responding to incoming
customer requests.
Compare difference between first response time of
tickets using Copilot to those that didn’t.


CSAT
Customer satisfaction rating after a ticket is
resolved.
Helps you understand how Copilot tools are impacting
customer experience.
Segment by AI-assisted vs non-AI tickets to assess
where satisfaction improves or drops. Use this to refine AI
deployment.


Average resolution time
Time from ticket creation to final resolution.
Tracks efficiency across the ticket lifecycle.
Compare AI vs non-AI tickets to see where Copilot
reduces resolution time. Review by intent to optimize
processes.


Automated resolution rate
Percentage of tickets resolved without a human
agent.
Measures how much value AI is delivering
independently.
Monitor trends over time. Look for intents with high
automation potential to expand coverage.


First contact resolution rate
Tickets resolved with a single agent reply.
Indicates the effectiveness of Copilot-generated
responses.
Filter by AI usage to identify which intents and agents
benefit most. Use insights to improve content or training.


NPS
Measures customer loyalty over time.
Gives a big-picture view of how AI influences long-term
satisfaction.
Compare before and after Copilot implementation to
track overall sentiment shift. Look for patterns in score
changes.







Sharing results with stakeholders

After creating dashboards and reports, consider sharing them with key
stakeholders to keep teams aligned and show the impact of Copilot over time. You can
schedule dashboards
to be sent out on a one time or regular cadence. This is useful for sharing updates
monthly, quarterly, or after deploying Copilot at your organization. Dashboards can
also be exported to share in presentations or
leadership updates.



Helpful resources

Review the following articles to learn more about measuring the impact of
Copilot with analytics:

Reporting on the auto assist feature of agent
copilot
Zendesk AI insights & reporting
Zendesk analytics recipes
reference
Working with prebuilt dashboards
Explore recipe: Intelligent triage
predictions and confidence
Explore recipe: Intelligent triage changes to
intent
Explore recipe: Comparing intelligent triage
intent predictions with a custom About field
Explore recipe: Breakdown of CSAT by customer
sentiment




