Retail Tech Insights: Specials Magazine

Tilia Wong is VP of Digital Strategy and Analytics for Macy’s Digital, leading digital operations and analytics to drive data-informed growth and enhance the customer experience. Before joining Macy’s, she spent several years at Amazon, where she gained valuable P&L experience running multiple retail functions spanning operations, merchandising and technology, while championing data-driven growth. Her career began in construction after earning a civil engineering degree, where she developed strong leadership skills. She later moved into consulting at McKinsey & Co focusing on analytics for the semiconductor industry in areas such as R&D, manufacturing and product strategy. Across her journey, she has championed the use of data to drive efficiency, innovation, and strategic decision-making in complex environments. This feature explores Wong’s approach to building analytic and operational systems that deliver measurable impact and shares practical insights on how strategic thinking and cross-functional collaboration drive lasting business success. Building Systems of Insight across Industries In my current role, I ensure that Macy’s Digital teams have the analytic and operational frameworks necessary to optimize performance and customer experience, focusing on the core drivers of digital success: traffic, conversion and average order value. Transitioning across industries, from construction to consulting to e-commerce, I have leveraged my experience to establish clear baselines for operational efficiency and data-driven strategy. In every role, my priority has been strengthening analytics capabilities to ensure all decisions are driven by actionable insights and measurable outcomes.

tracked hands, motion, and behavior, hoping to infer whether an item was scanned, missed, or intentionally skipped. It was an imperfect solution to a structural problem. Behavior is ambiguous. Products are not. UltronAI was built on a different premise: stop interpreting actions and start identifying products. That shift, while subtle on the surface, changes everything. Instead of asking what a shopper might have done, UltronAI identifies exactly what product is present the moment it appears. Every item is visually recognized in real time, removing guesswork from checkout, shelf monitoring, and general retail operations. The product becomes the source of truth, not a behavioral assumption layered on top of it. This approach defines a new category in retail AI: product identification at scale. UltronAI operates the world’s first retail-specific foundational model designed from the ground up for product recognition. The platform supports more than 250,000 SKUs and is engineered to handle real-world retail conditions like changing packaging, varied lighting, partial occlusion, rotation, and cluttered environments. Unlike traditional computer vision systems, UltronAI is purpose-built for the complexity of modern retail..