track-usage-and-adoption.md

title	Tracking license activation and initial usage with Copilot usage metrics
shortTitle	Track usage and adoption
intro	Identify and act on {% data variables.product.prodname_copilot %} adoption signals and activation with usage metrics.
permissions	{% data reusables.copilot.usage-metrics-permissions %}
versions	feature copilot
contentType	tutorials
redirect_from	/copilot/tutorials/roll-out-at-scale/measure-adoption/analyze-usage-over-time /copilot/managing-copilot/managing-github-copilot-in-your-organization/reviewing-activity-related-to-github-copilot-in-your-organization/analyzing-usage-over-time-with-the-copilot-metrics-api /copilot/rolling-out-github-copilot-at-scale/analyzing-usage-over-time-with-the-copilot-metrics-api /copilot/rolling-out-github-copilot-at-scale/measuring-adoption/analyzing-usage-over-time-with-the-copilot-metrics-api /copilot/tutorials/rolling-out-github-copilot-at-scale/measuring-adoption/analyzing-usage-over-time-with-the-copilot-metrics-api /copilot/tutorials/rolling-out-github-copilot-at-scale/measuring-adoption/analyze-usage-over-time /copilot/tutorials/rolling-out-github-copilot-at-scale/measure-adoption/analyze-usage-over-time /copilot/tutorials/roll-out-at-scale/measure-adoption
allowTitleToDifferFromFilename	true
category	Copilot usage metrics Roll Copilot out at scale Track Copilot usage Measure success

After you assign {% data variables.product.prodname_copilot_short %} licenses across your enterprise, you can use the {% data variables.product.prodname_copilot_short %} usage metrics dashboard and APIs to verify that licenses are active and monitor early usage trends. This helps you evaluate whether your rollout is reaching the right people and take quick action if adoption is slower than expected.

To get a wider view of adoption, you can combine dashboard insights with qualitative feedback, for example, short pulse surveys or team check-ins.

Prerequisite

{% data reusables.copilot.copilot-metrics-dashboard-prereq %}

Step 1: Access the usage metrics dashboard

{% data reusables.copilot.access-copilot-metrics-dashboard %}

The dashboard displays aggregated telemetry from developer IDEs and updates daily, though data may be up to 3 days behind UTC.

Step 2: Track license activation

Use the "IDE active users" and "IDE daily active users" charts to confirm that developers are starting to use their assigned licenses.

Metric	What it tells you	How to act
IDE active users	How many licensed developers have used {% data variables.product.prodname_copilot_short %} at least once this calendar month.	Compare to your total assigned licenses. If the number is much lower, verify IDE configuration or communicate activation steps to your teams.
IDE daily active users	How many unique users are using {% data variables.product.prodname_copilot_short %} each day.	Look for an upward trend in the first two weeks after rollout. A flat line may signal that users need additional enablement or setup guidance.
IDE weekly active users	Rolling 7-day total of active users.	Use this to track consistency. Steady or increasing WAU indicates successful activation and recurring use.

{% data reusables.copilot.copilot-usage-metrics-sources %}

Step 3: Identify early adoption signals

Once licenses are active, focus on the metrics that indicate healthy early adoption.

Signal	Where to find it in the dashboard	What to look for
Consistent DAU growth	“IDE daily active users” graph	Steady increase in daily users over the first month.
Feature variety	“Requests per chat mode” graph	Developers trying multiple chat modes (Ask, Edit, Plan, Agent) suggests curiosity and engagement.
Initial agent usage	“Agent adoption” card	Even small agent adoption (5–10%) early on is a positive signal of experimentation.

Healthy early adoption usually looks like 60–80% of assigned users showing activity within the first month.

Step 4: Act on limited adoption signals

If your metrics show limited adoption, try one of the following strategies.

Symptom	Possible cause	What to do
Low total active users	Users haven’t activated licenses or configured {% data variables.product.prodname_copilot_short %} in their IDE.	Re-share onboarding materials or run a short “activation check” session.
Flat daily usage	Developers tried {% data variables.product.prodname_copilot_short %} once but aren’t returning.	Provide enablement resources like {% data variables.product.prodname_copilot_short %} prompts or internal success stories.
No agent usage	Teams may not know about the {% data variables.copilot.copilot_agent_short %}.	Share examples of advanced use cases to encourage exploration.

You can also use {% data variables.copilot.copilot_chat_short %} to help diagnose issues. For example:

What patterns might explain low adoption across some teams in the Copilot metrics export?

Step 5: Track activation programmatically

Now that you have a sense of what adoption data is available to you and what the data tells you about your rollout, consider using the API to continue monitoring adoption over time.

1. Use the Enterprise Usage endpoint to retrieve aggregated data for all organizations in your enterprise.
2. Filter the export by day or user_login to identify newly activated users.
3. Compare user_initiated_interaction_count and code_acceptance_activity_count to see whether users are actively engaging after license assignment.

Step 6: Export user-level data for deeper analysis

In some cases, you may need user-level activity data for deeper analysis or to integrate with internal BI tools. Exports are most useful when you want to analyze long-term trends or correlate adoption with other metrics (for example, productivity or enablement activities).

1. In the dashboard, click {% octicon "download" aria-hidden="true" aria-label="download" %} Export JSON in the top-right corner.

2. Download the NDJSON file and use {% data variables.copilot.copilot_chat_short %} to analyze the data. For example, ask:

    * Summarize which organizations show the largest increase in `loc_added_sum` this month.
    * Identify users with high `user_initiated_interaction_count` but low `code_acceptance_activity_count`.
   

Further reading

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