Feature tracking guidance for PMs

Description

This merge request adds a new section to the handbook titled "Guidance for Instrumenting Feature Tracking." It provides a comprehensive guide for Product Managers on how to implement and track metrics for their features. The new content includes quick links to relevant resources, information about self-service feature tracking dashboards, and a step-by-step process for instrumenting feature tracking. It also covers special considerations for AI Gateway features and lists key contacts and resources. This addition aims to streamline the process of feature tracking and ensure consistent data collection across GitLab's product teams.

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Commits

• Feature tracking guidance

---

content/handbook/enterprise-data/programs/data-for-product-managers/index.md

@@ -137,13 +137,26 @@ If your analytics needs for your new or recently modified feature are met by the
 
 ### Special Considerations for AI Gateway Features
 
-For features routed through the AI Gateway:
-
-- New distinct features should be represented as a [unit primitive](https://gitlab.com/gitlab-org/cloud-connector/gitlab-cloud-connector/-/tree/main/config/unit_primitives). This will enable AI features to be tracked automatically via a new AI Gateway events tracking system. AI Gateway events using the unit primitive framework cannot be blocked by users and are tracked at the event grain for all deployment types.
-- For reporting requiring more granularity than a 'request' of the AI Gateway, utilize [Internal Events Tracking](https://docs.gitlab.com/ee/development/internal_analytics/internal_event_instrumentation/quick_start.html).
-- Internal events can be connected to unit primitive events seen in the AI Gateway using a `correlation_id` for behavior funnel use cases (for GitLab.com only).
-- [AI Gateway Reporting](https://10az.online.tableau.com/t/gitlab/views/AIGatewayReporting/Overview) will automatically display new unit primitive requests.
-- [AI Gateway instrumentation](https://docs.gitlab.com/ee/development/internal_analytics/internal_event_instrumentation/quick_start.html#internal-events-on-other-systems)
+When instrumenting features routed through the AI Gateway, follow these guidelines:
+
+1. Represent new features routed through the AI Gateway as unit primitives
+   - New distinct features should be represented as a [unit primitive](https://gitlab.com/gitlab-org/cloud-connector/gitlab-cloud-connector/-/tree/main/config/unit_primitives)
+   - To add a new unit primitive, reach out to ~"group::cloud connector"
+
+1. Set up tracking for the new unit primitive
+   - Contact ~"group::analytics instrumentation" with the necessary fields to be tracked
+   - For more information on AI Gateway instrumentation, see the [documentation](https://docs.gitlab.com/ee/development/internal_analytics/internal_event_instrumentation/quick_start.html#internal-events-on-other-systems)
+   - Once instrumented, AI Gateway events using the unit primitive framework:
+     - Cannot be blocked by users
+     - Are tracked at the event grain for all deployment types
+
+1. For more granular reporting
+   - If you need more detail than a 'request' of the AI Gateway at the broad feature grain, use [Internal Events Tracking](https://docs.gitlab.com/ee/development/internal_analytics/internal_event_instrumentation/quick_start.html)
+   - Internal events can be connected to unit primitive events using a `correlation_id` for behavior funnel or more granular reporting use cases (GitLab.com only)
+
+1. Viewing AI Gateway data
+   - [AI Gateway Reporting](https://10az.online.tableau.com/t/gitlab/views/AIGatewayReporting/Overview) automatically displays new unit primitive requests once they have been instrumented by ~"group::analytics instrumentation"
+   - Additional analytics can be requested by creating a [Product Data Insights (PDI) Issue](https://gitlab.com/gitlab-data/product-analytics/-/issues/new)
 
 ### Key Contacts and Resources