Session: Designing Trust-First Personalization: Building Privacy-Embedded Analytics for Scalable Impact
In an era where consumer trust is paramount, personalization must be underpinned by privacy, accuracy, and governance. Drawing on enterprise-grade analytics transformations at Apple, Macy’s, and Albertsons, this session will show how to:
• Build first-party, privacy-resilient data systems that minimize tagging overhead while preserving data quality.
• Embed governance directly into analytics platforms, turning privacy from a blocker into a strategic advantage.
• Create cross-functional workflows between engineering, product, and marketing to enable impactful experimentation and personalization.
• Move from reactive reporting to proactive, trust-driven decision frameworks.
Attendees will leave with a clear action plan for implementing scalable, compliant personalization strategies that strengthen both customer experience and business outcomes.
Bio
Eshita Gupta is a seasoned analytics and data strategy product manager with over a decade of experience designing and scaling enterprise analytics infrastructures for Fortune 500 companies, including Apple, Macy’s, and Albertsons. In her current role at Apple, she leads the development of privacy-first, first-party data systems that deliver high-quality, governed datasets to power decision-making at scale. Her expertise spans data governance, cross-platform analytics integration, experimentation frameworks, and enabling organizations to move from reactive reporting to proactive insights.