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Microsoft Copilot

AI Assistant Entry Point Optimization

Microsoft Copilot product screenshot

+15%

Engagement Lift

+35%

TAM Expansion

490M MAU

Global Reach

The Problem

Microsoft Copilot needed to be more than an AI chatbot — it needed to meet users in context, surfacing relevant actions at the right moment within Windows. Early entry points weren't optimized for how users actually interacted with the assistant, leading to lower-than-expected engagement and discovery.

The Approach

Optimized Copilot's entry point to surface more contextually relevant actions based on user behavior and system state. Partnered cross-functionally with design, engineering, and data science to iterate on placement, triggers, and action recommendations. Led Copilot's global expansion, ensuring the experience met regulatory requirements (DMA/CTA) and localization standards across the EU and China.

The Outcome

Entry point optimization drove a 15% increase in user engagement — a meaningful lift at Windows scale. Global expansion extended Copilot's reach by 35% of TAM, bringing the AI assistant to approximately 490M monthly active users across regions. These improvements established Copilot as a central, indispensable part of the Windows experience.

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