Introduce CCA PR merge count, cycle time, and acceptance rate (Enterprise-level API only) (#59671)

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Sam Browning <106113886+sabrowning1@users.noreply.github.com>

Author: 3 people

content/copilot/concepts/agents/code-review.md

@@ -19,7 +19,7 @@ category:
 
 ## Introduction
 
-{% data variables.copilot.copilot_code-review_short %} reviews code written in any language, and provides feedback. It reviews your code from multiple angles to identify issues and suggest fixes. You can apply suggested changes with a couple of clicks. 
+{% data variables.copilot.copilot_code-review_short %} reviews code written in any language, and provides feedback. It reviews your code from multiple angles to identify issues and suggest fixes. You can apply suggested changes with a couple of clicks.
 
 This article provides an overview of {% data variables.copilot.copilot_code-review_short %}. To learn how to request a code review from {% data variables.product.prodname_copilot_short %}, see [AUTOTITLE](/copilot/how-tos/agents/copilot-code-review/using-copilot-code-review).
 
@@ -78,7 +78,7 @@ Some file types are excluded from {% data variables.copilot.copilot_code-review_
 * Log files
 * SVG files
 
-If you include these file types in a pull request, {% data variables.copilot.copilot_code-review_short %} will not review the file. 
+If you include these file types in a pull request, {% data variables.copilot.copilot_code-review_short %} will not review the file.
 
 For more information, see [AUTOTITLE](/copilot/reference/review-excluded-files).
 

content/copilot/concepts/agents/coding-agent/about-coding-agent.md

@@ -67,6 +67,18 @@ Having {% data variables.copilot.copilot_coding_agent %} as an additional coding
 
 You can create specialized {% data variables.copilot.custom_agents_short %} for different tasks. For example, you might create a {% data variables.copilot.copilot_custom_agent_short %} specialized for frontend development that focuses on React components and styling, a documentation agent that excels at writing and updating technical documentation, or a testing agent that specializes in generating comprehensive unit tests. Each {% data variables.copilot.copilot_custom_agent_short %} can be tailored with specific prompts and tools suited to its particular task.
 
+## Measuring pull request outcomes for {% data variables.copilot.copilot_coding_agent %}
+
+Enterprise administrators can use {% data variables.product.prodname_copilot_short %} usage metrics to analyze pull request outcomes for pull requests created by {% data variables.copilot.copilot_coding_agent %}.
+
+The enterprise-level {% data variables.product.prodname_copilot_short %} usage metrics API includes pull request lifecycle metrics such as:
+
+* The total number of pull requests created and merged
+* The number of pull requests created by {% data variables.copilot.copilot_coding_agent %} that have been merged
+* Median time to merge for merged pull requests, including pull requests created by {% data variables.copilot.copilot_coding_agent %}
+
+These metrics can help you track adoption of {% data variables.copilot.copilot_coding_agent %} and monitor changes in pull request throughput and time to merge over time. See [AUTOTITLE](/copilot/concepts/copilot-usage-metrics/copilot-metrics).
+
 ## Integrating {% data variables.copilot.copilot_coding_agent %} with third-party tools
 
 You can also invoke {% data variables.copilot.copilot_coding_agent %} from external tools, allowing you to assign tasks to {% data variables.product.prodname_copilot_short %}, provide context, and open pull requests without leaving your workflow. See [AUTOTITLE](/copilot/concepts/tools/about-copilot-integrations)

content/copilot/concepts/copilot-usage-metrics/copilot-metrics.md

@@ -1,7 +1,7 @@
 ---
 title: GitHub Copilot usage metrics
 shortTitle: Copilot usage metrics
-intro: '{% data variables.product.prodname_copilot %} usage metrics provide visibility into how {% data variables.product.prodname_copilot %} is adopted and used across your organization, including engagement, activity, and code generation trends.'
+intro: '{% data variables.product.prodname_copilot_short %} usage metrics provide visibility into how {% data variables.product.prodname_copilot_short %} is adopted and used across your organization, including engagement, activity, code generation, and pull request lifecycle trends.'
 versions:
   feature: copilot
 topics:
@@ -21,14 +21,14 @@ category:
   - Track Copilot usage
   - Learn about Copilot
   - Get started with metrics
-  - Manage Copilot for a team  
+  - Manage Copilot for a team
 ---
 
 {% data reusables.copilot.usage-metrics-preview %}
 
 ## About {% data variables.product.prodname_copilot_short %} usage metrics
 
-{% data variables.product.prodname_copilot_short %} usage metrics help key stakeholders and decision-makers understand how their teams are adopting and using {% data variables.product.prodname_copilot_short %}. By tracking usage patterns across the enterprise, you can measure engagement, identify opportunities to increase value, and make data-driven decisions about enablement and rollout.
+{% data variables.product.prodname_copilot_short %} usage metrics help key stakeholders and decision-makers understand how their teams are adopting and using {% data variables.product.prodname_copilot_short %}. By tracking usage patterns across the enterprise, you can measure engagement, identify opportunities to increase value, and assess how AI-assisted workflows influence pull request throughput and time to merge.
 
 Metrics are available through:
 
@@ -116,7 +116,7 @@ For example, all usage data for a Monday (which closes at midnight UTC) will be
 
 ## What does the data measure?
 
-{% data variables.product.prodname_copilot_short %} usage metrics can be grouped into four main categories: Adoption, Engagement, Acceptance Rate, and Lines of Code (LoC) metrics.
+{% data variables.product.prodname_copilot_short %} usage metrics can be grouped into a few main categories: Adoption, engagement, acceptance rate, Lines of Code (LoC), and pull request lifecycle metrics.
 
 **Adoption** measures how many licensed developers are actively using {% data variables.product.prodname_copilot_short %} within your enterprise. For example, daily active users (DAU) tells you how many unique users interacted with {% data variables.product.prodname_copilot_short %} on a given day. Ideally, you'll see a consistent upward trend in these metrics during rollout.
 
@@ -126,6 +126,8 @@ For example, all usage data for a Monday (which closes at midnight UTC) will be
 
 **Lines of Code (LoC) metrics** measure the number of lines {% data variables.product.prodname_copilot_short %} suggested, added, or deleted in the editor, providing a directional view of {% data variables.product.prodname_copilot_short %}’s tangible output. For example, "Lines added" shows how much code was actually accepted and inserted into the editor.
 
+**Pull request lifecycle metrics** measure how {% data variables.product.prodname_copilot_short %} activity relates to pull request outcomes and delivery flow. These metrics include pull request creation and merge counts, median time to merge, and review suggestion activity. By comparing overall pull request activity with pull requests created by {% data variables.product.prodname_copilot_short %}, you can evaluate how AI-assisted workflows influence throughput and cycle time across your enterprise.
+
 ## How can I use these metrics?
 
 These metrics can be used together to answer key questions about your teams' usage of {% data variables.product.prodname_copilot_short %}.
@@ -136,6 +138,7 @@ These metrics can be used together to answer key questions about your teams' usa
 | Which features deliver the most value? | Requests per chat mode, agent adoption |
 | Do developers trust {% data variables.product.prodname_copilot_short %}’s output? | Acceptance rate trends |
 | Are enablement efforts working? | Growth in adoption and engagement after training or communication campaigns |
+| Is {% data variables.product.prodname_copilot_short %} influencing delivery speed or PR throughput? | Pull request merge counts and median time to merge |
 
 Look for patterns across these signals rather than focusing on any single number. For example, a steady DAU paired with a rising acceptance rate indicates growing trust and value.
 

content/copilot/reference/copilot-usage-metrics/copilot-usage-metrics.md

@@ -97,11 +97,19 @@ These fields appear in the exported NDJSON reports and in the {% data variables.
 
 ### Pull request activity fields (API only)
 
-These fields capture daily pull request creation and review activity across the enterprise, including activity performed by {% data variables.product.prodname_copilot_short %}.
+These fields capture daily pull request creation, review, merge, and suggestion activity across the enterprise, including activity performed by {% data variables.product.prodname_copilot_short %}.
 
 | Field | Description |
 |:--|:--|
 | `pull_requests.total_created` | Total number of pull requests created across the enterprise on this specific day. <br/><br/>Creation is a one-time event. Each pull request is counted only on the day it is created. |
 | `pull_requests.total_reviewed` | Total number of pull requests reviewed across the enterprise on this specific day. <br/><br/>The same pull request may be counted on multiple days if it receives reviews on multiple days. Within a single day, each pull request is counted once, even if multiple review actions occur. |
+| `pull_requests.total_merged` | Total number of pull requests merged across the enterprise on this specific day. <br/><br/>Merging is a one-time event. Each pull request is counted only on the day it is merged. |
+| `pull_requests.median_minutes_to_merge` | Median time, in minutes, between pull request creation and merge for pull requests merged on this specific day. <br/><br/>Median is used to reduce the impact of outliers from unusually long-running pull requests. |
+| `pull_requests.total_suggestions` | Total number of pull request review suggestions generated on this specific day, regardless of author. |
+| `pull_requests.total_applied_suggestions` | Total number of pull request review suggestions that were applied on this specific day, regardless of author. |
 | `pull_requests.total_created_by_copilot` | Number of pull requests created by {% data variables.product.prodname_copilot_short %} across the enterprise on this specific day. |
 | `pull_requests.total_reviewed_by_copilot` | Number of pull requests reviewed by {% data variables.product.prodname_copilot_short %} across the enterprise on this specific day. <br/><br/>A pull request may be counted on multiple days if {% data variables.product.prodname_copilot_short %} reviews it on multiple days. |
+| `pull_requests.total_merged_created_by_copilot` | Number of pull requests created by {% data variables.product.prodname_copilot_short %} that were merged on this specific day. Each pull request is counted only on the day it is merged. |
+| `pull_requests.median_minutes_to_merge_copilot_authored` | Median time, in minutes, between pull request creation and merge for pull requests created by {% data variables.product.prodname_copilot_short %} and merged on this specific day. |
+| `pull_requests.total_copilot_suggestions` | Number of pull request review suggestions generated by {% data variables.product.prodname_copilot_short %} on this specific day. |
+| `pull_requests.total_copilot_applied_suggestions` | Number of pull request review suggestions generated by {% data variables.product.prodname_copilot_short %} that were applied on this specific day. |