GitHub engagement dropped 20% in two weeks among security teams. Diagnose the issue

Problem Statement Description

Product context: Microsoft is a productivity, software, AI, gaming, and cloud company; its products include Windows, Microsoft 365, Teams, LinkedIn, Xbox, Azure, Dynamics, and Copilot.

GitHub has seen a 20% drop in engagement over the last two weeks among security teams. This is an RCA interview focused on diagnosing what may have changed, whether the decline reflects a real user behavior shift, and how to prioritize investigation across product, data, customer, and market signals.

Assume the affected users are security practitioners and security engineering teams using GitHub for workflows such as code scanning, secret scanning, dependency review, vulnerability alerts, security policy enforcement, pull request review, and coordination with development teams. Engagement may include actions such as logging in, viewing security alerts, triaging vulnerabilities, reviewing pull requests, configuring policies, or interacting with GitHub Advanced Security features.

Your task is not to propose a new product strategy, but to structure a clear investigation: validate the anomaly, isolate where it is happening, form plausible hypotheses, identify the evidence needed, and determine appropriate mitigation and prevention steps. The diagnosis should account for GitHub’s enterprise context, where trust, compliance, reliability, integrations, and developer workflow continuity are critical.

The experience should consider:

- How to define “engagement” precisely, including numerator, denominator, time window, and whether the metric is user-, team-, organization-, repository-, or feature-level.

- How to verify whether the 20% drop is real versus caused by logging, tracking, identity, permission, billing, or data pipeline changes.

- Segmentation by enterprise vs. smaller teams, plan type, geography, industry, repository type, organization size, and GitHub security feature usage.

- Workflow-specific cuts across code scanning, secret scanning, Dependabot, vulnerability alerts, security overview, pull request security checks, and third-party security integrations.

- Product or platform changes in the last two weeks, including UI changes, notification behavior, API changes, policy defaults, access controls, performance, outages, or latency.

- External factors such as compliance cycles, customer security incidents, competing tools, enterprise procurement changes, holidays, or changes in developer activity.

- Evidence sources including product analytics, incident reports, customer support tickets, enterprise account feedback, admin audit logs, feature telemetry, and qualitative customer interviews.

- Mitigation, communication, and prevention steps if the issue is confirmed, including how to monitor recovery and avoid recurrence.

The goal is to demonstrate a structured RCA approach that narrows a broad engagement decline into testable hypotheses, identifies the highest-leverage data to inspect first, and balances rapid customer impact mitigation with disciplined root-cause validation.