Sales Strategy
Why Strong Product Data Will Define Retail Advertising Performance in the AI Era April 20, 2026 (0 comments)
Mountain View, CA--Retail advertising is shifting toward AI-driven experiences, but performance still depends on execution fundamentals. In an episode of Ads Decoded by Google, the discussion centers on how retailers can adapt by improving data quality, campaign strategy, and measurement.
[Image via iStock.com/Bangon Pitipong]
As the episode highlights, product data has moved beyond supporting shopping ads. It now powers a wide range of experiences, including conversational shopping, virtual try-ons, and shoppable video formats. This makes the product feed a core infrastructure layer rather than a basic catalog.
Product Data as the Foundation
The episode talks about how incomplete or low-quality product feeds limit visibility across platforms. Retailers are advised to focus on both quantity and quality—adding detailed attributes, high-resolution images, accurate descriptions, and differentiators such as pricing or shipping benefits.
Product data is also used across multiple surfaces, including Search, YouTube, and AI-driven interfaces. Richer data improves discoverability and enables more effective ad formats, including shoppable video and connected TV experiences.
Rethinking Campaign Strategy and Targeting
The episode also outlines a shift in how campaigns should be structured. Instead of treating formats like Performance Max, Demand Gen, and Shopping as competing tools, they should be used together to align with business goals.
A key change is the move from rigid targeting to signal-based optimization. Lookalike audiences, for example, are now treated as signals rather than fixed targets, allowing AI systems to identify potential customers more flexibly. As the episode notes, this requires stronger inputs from advertisers, especially first-party data and accurate conversion tracking.
Preparing for AI-Driven Commerce
The discussion points to a broader transition toward more automated and “agentic” commerce experiences. To prepare, retailers need to improve product feeds, strengthen data infrastructure, and ensure tracking covers both online and offline activity.
The episode also highlights the importance of connecting ad performance to in-store sales, given that a large share of retail transactions still happens offline. Measurement tools, product-level reporting, and omnichannel bidding are positioned as key enablers.
The direction is clear: retailers that invest in structured, high-quality data and integrate it across campaigns and channels will be better positioned to perform as advertising becomes more AI-driven.
Watch the episode below.