Overview:


Microsoft's Commercial Marketplace generates customer data that could help predict purchases and identify churn risks. But this information was spread across separate platforms. Sales teams couldn't quickly access customer engagement history before meetings. Marketing teams struggled to identify which prospects were actively evaluating products. When executives needed customer insights, analysts had to pull information from various sources, creating delays in decision-making.

The Problem I solved:


• Fragmented Data Access Microsoft had useful customer data browsing patterns, usage metrics, engagement signals, but teams had to search through multiple systems to find relevant information for their specific needs.

• Limited Sales Context Account managers prepared for meetings without easy access to recent customer activity or product interest patterns that could inform their conversations.

• Broad Marketing Approaches Campaign teams created general promotions because they couldn't efficiently identify which prospects had shown interest in specific product categories.

• Slow Executive Reporting When leadership requested customer insights, the manual data compilation process delayed strategic planning and response times.

My Role:
As Lead Product Designer, I designed an analytics platform serving 200+ Microsoft employees. I conducted user research, architected the experience, and collaborated with data scientists to transform complex datasets into intuitive visualizations and actionable insights.

My Solution:
I designed an analytics platform that consolidated customer engagement data, purchase history, and usage patterns into one interface. The system provided role-specific insights for sales, marketing, and executive teams. I transformed complex datasets into clear visualizations and actionable reports, with predictive analytics to identify future opportunities and risks.

Key Design Principles I Applied:

• Context-Aware Intelligence: Show different information based on user needs, detailed engagement history for sales prep, campaign metrics for marketing, strategic summaries for executives.

• Predictive Early Warning System: Surface alerts about customers showing churn warning signs and prospects demonstrating strong buying signals before competitors notice.

• Self-Service Data Access: Enable business teams to explore customer insights independently without waiting for analyst support.

• Cross-Team Alignment: Ensure all teams see consistent customer metrics and status updates so they can coordinate effectively.

Impact:

• 200+ Microsoft employees adopted the new analytics platform

• Increased platform usage as teams found the interface more intuitive

• Reduced time spent on manual reporting by consolidating data sources into automated views

• Improved marketing campaign targeting through better visibility into customer behavior patterns

• Time savings for analyst teams who could focus on analysis instead of data compilation

• Measurable reduction in customer churn through early intervention system that flagged at-risk accounts