Gmail Segmentation, Validation, Targeted Interventions, and Experimentation

Context

You are evaluating how to segment Gmail users to drive targeted product improvements and messaging. Assume you have access to anonymized, aggregated event logs (sends, opens, device type), message metadata (category/tab, attachment size), and account-level flags (workspace vs consumer), with strict privacy constraints.

Tasks

1. Define actionable segmentation axes and concrete segment definitions (e.g., daily active senders, newsletter-heavy consumers, attachment-heavy users, mobile-only, power users, workplace vs personal domains, frequent spam reporters). For each axis, explain how the segment would be used.
2. Validate segment stability and separability over 8 weeks:
   • Propose metrics to assess week-over-week stability and drift.
   • Propose methods to assess separability between segments.
3. Choose three segments and design targeted interventions per segment (e.g., smart compose/autocomplete tuning, faster attachment upload, bulk unsubscribe UX). For each:
   • Define primary success metrics (and how to compute them), guardrails, and monitoring.
4. Outline an experiment/test design to measure lift versus the global average:
   • Randomization, duration, power, heterogeneity of treatment effects.
   • Handling small segments using k-anonymity thresholds and differential privacy noise to mitigate privacy/fairness risks.
5. Describe how segments inform lifecycle messaging (onboarding, activation, reactivation) and product roadmap prioritization.