April 2026 Google Ads Update – Product Feeds Power AI Shopping

Granular analysis and first look

Better AI Shopping Starts With Better Product Data

Google’s April 8, 2026, retail update delivers a straightforward message: advanced AI cannot compensate for incomplete product information. Retailers using Google Shopping management services should treat Merchant Center feed quality as a core part of campaign strategy—not a routine technical task.

In the latest episode of Google’s Ads Decoded podcast, Ads Product Liaison Ginny Marvin spoke with retail product leaders Firas Yaghi and Nadja Bissinger about how businesses can adapt to AI-driven shopping. Their central recommendation was to get the fundamentals right before pursuing more advanced advertising capabilities.

Merchant Center Feeds Support Google’s AI Experiences

Google uses retailer-provided product data to understand what an item is, who it may be relevant to and where it can appear. That data increasingly supports experiences beyond traditional Shopping ads, including:

• Conversational shopping in AI Mode
• Virtual product try-ons
• Shoppable connected TV ads
• AI-powered product recommendations
• Product discovery across Google surfaces

A missing or inaccurate attribute can limit more than ad quality. It can make a product less likely to appear when a shopper describes a specific need conversationally.

For example, a query may include details about material, fit, compatibility, color or intended use. Google needs sufficiently detailed product data to determine whether an item satisfies those requirements.

Why Feed Quality Matters More in AI Mode

Traditional product searches often resemble catalog language, such as “women’s black running shoes.” AI-assisted searches can be much more specific:

“I need lightweight black running shoes for wide feet that can handle wet pavement.”

A basic title and generic description may not provide enough context for Google to identify a relevant product. Complete attributes, descriptive titles and accurate landing-page information give its systems more signals to work with.

Google has also introduced additional Merchant Center attributes intended to help products appear in conversational commerce experiences. These can include information such as common product questions, compatible accessories and potential substitutes.

Clean Up Merchant Center Before Scaling Campaigns

Retailers should first resolve errors that prevent products from being eligible to serve. After addressing disapprovals, they can focus on improving the quality and depth of eligible listings.

Prioritize Required Product Information

Review essential attributes such as:

• Product titles and descriptions
• Price and availability
• Product identifiers
• Brand information
• Images
• Condition
• Shipping details
• Landing-page URLs

Feed information should match the product page. Conflicting prices, availability or variants can create disapprovals and poor customer experiences.

Add Useful Optional Attributes

Optional does not mean unimportant. Depending on the product category, details such as size, color, material, pattern, gender and age group can help Google understand relevance more precisely.

Product titles should be descriptive without becoming unreadable or overloaded with repeated keywords. The most meaningful attributes should generally appear early.

Keep Data Current

Inventory and pricing changes should reach Merchant Center quickly. A sophisticated AI shopping experience loses value when it recommends an unavailable product or displays outdated information.

Retailers should monitor automated updates, scheduled feed processing and direct integrations to ensure that changes are reflected consistently.

Product Imagery Is Part of the Feed Strategy

Virtual try-on and visual product discovery require more than text-based attributes. High-quality images help Google represent products accurately and give shoppers greater confidence before purchasing.

Retailers should provide clear images that:

• Show the full product.
• Match the listed variation.
• Avoid distracting promotional overlays.
• Use sufficient resolution.
• Include additional angles when appropriate.
• Accurately represent color and appearance.

Google continues to expand AI-powered creative and product visualization tools, but the quality of the original product assets still affects the output.

Shoppable CTV Connects Video and Product Data

Merchant Center data also supports shopping experiences on YouTube. Shoppable CTV in Demand Gen allows viewers to browse products associated with an ad while watching YouTube on a television.

Google reported that Demand Gen campaigns including TV screens produced an average of 7% additional conversions at the same return on investment in an internal 2025 experiment. Advertisers should treat that result as directional and evaluate performance using their own campaign data.

For retailers, this means video and feed strategies can no longer operate independently. The advertisement may generate interest, but accurate product information is needed to turn that interest into product exploration and sales.

What Retail Advertisers Should Do Next

Retailers do not need to adopt every new AI feature immediately. They should first improve the inputs that will support those features.

A practical audit should include:

1. Resolve Merchant Center errors and disapprovals.
2. Compare feed data with website information.
3. Expand thin titles and descriptions.
4. Complete relevant category-specific attributes.
5. Review product images and variant accuracy.
6. Confirm that inventory updates process reliably.
7. Segment performance by product, category and feed status.
8. Monitor how products appear across new Google experiences.

Feed optimization should also be connected to business results. A listing can be technically eligible while still attracting low-value traffic or producing weak margins.

Key Takeaways

• AI Mode, virtual try-on and shoppable CTV rely on Merchant Center product data.
• Incomplete feeds can reduce product visibility across emerging shopping experiences.
• Conversational searches require richer context than many traditional keyword searches.
• Optional product attributes can become valuable relevance signals.
• Accurate inventory, pricing and imagery remain essential.
• Retailers should improve feed fundamentals before relying on additional automation.

Google’s latest retail update is less about a single feature and more about the infrastructure behind its AI shopping ecosystem. As consumer searches become more conversational and commerce moves across Search, video and AI agents, product data becomes a primary source of advertising relevance.

Retailers that maintain accurate, detailed and timely Merchant Center feeds will be better positioned to participate in these experiences. Those that neglect the fundamentals may find that their products remain difficult to discover—regardless of how advanced Google’s AI