Google Merchant Center AI Performance Insights Expand in 2026: Key Changes for E-Commerce

What Is Google Merchant Center, and Why Does It Matter in 2026?

Google Merchant Center is the platform retailers use to upload product data and make it eligible for Google Shopping ads, free listings, and—increasingly—AI-powered search experiences like AI Overviews and AI Mode. As Google accelerates its shift from the classic "10 blue links" to a generative answer-first interface, Merchant Center has become the control panel for e-commerce visibility in the AI era.

Three developments in the second half of 2026 underscore this transformation:

• Google expanded its AI performance insights reports to merchants in Australia, Canada, India, and New Zealand, adding to the existing U.S. availability.
• A new study by Productrise found that products shown in Google AI Mode were on average 21.6% more expensive than the same products in traditional search—and only 1.28% of products overlapped between the two surfaces.
• Google rolled out a performance reporting overhaul on August 24, 2026, changing how merchants measure organic traffic, YouTube affiliate results, and Google Ads performance.

Each change has implications for how merchants allocate budget, optimize product feeds, and interpret their data. This article breaks down what happened, what the numbers mean, and how to adapt.

Key Update: AI Performance Insights Expand to Four New Markets

On September 3, 2026, Google expanded its Merchant Center AI performance insights reports to merchants in Australia, Canada, India, and New Zealand. The feature had previously been available only in the United States, which served as a testbed after Google began integrating conversational shopping queries from AI Mode and AI Overviews into merchant analytics.

The AI performance insights reports show how brands perform for conversational queries with shopping intent—think queries like "best running shoes for flat feet" or "affordable gaming laptop under $1,000." According to seroundtable.com, these reports provide specific data on product visibility within AI-generated answers, helping merchants understand which products surface in AI Mode and AI Overviews, which queries trigger those appearances, and how click-through rates compare to traditional search.

For merchants outside the U.S., this expansion means they can now benchmark their AI-driven performance without relying on third-party tools. The rollout also signals Google's broader strategy: bringing AI-native shopping analytics to every major e-commerce market before the end of 2026.

Study Reveals AI Mode Products Are 21.6% More Expensive—What That Means

A study published on September 5, 2026, by Productrise, an e-commerce analytics firm, examined product pricing and visibility across Google's traditional search results and its newer AI Mode. The results were striking:

• Products displayed in Google AI Mode were, on average, 21.6% more expensive than the same products shown in the traditional Google Shopping carousel for identical queries.
• Only 1.28% of products that appeared in the traditional product carousel also appeared in AI Mode for the same query.

Metric	Traditional Google Search (Shopping Carousel)	Google AI Mode
Average product price	Lower (baseline)	21.6% higher
Product overlap (same query)	—	1.28%
Visibility source	Structured product feed + bid	AI-generated answer + conversational context

The data, reported by realinternetsales.com, suggests that Google's AI Models are surfacing a dramatically different set of products than the traditional shopping carousel—and those products tend to be higher-priced. The study controlled for query type, product category, and device, making the disparity hard to dismiss as random variation.

What this means for merchants:

• Optimizing for AI Mode is a separate challenge. Even if a retailer dominates the traditional shopping carousel, they have no guarantee of visibility in AI Mode. The algorithmic criteria—reviews, brand authority, price competitiveness, and possibly conversational relevance—appear to differ sharply.
• Higher-priced products may get an edge. If Google's AI tends to recommend premium products (perhaps because they have better review signals or longer descriptions), merchants with mid-range goods may need to adjust their content strategy.
• Track both surfaces independently. Merchants cannot rely on traditional search ranking data to predict AI Mode performance. The AI Performance Insights reports in Merchant Center are now the best native tool for that purpose.

Performance Reporting Overhaul: What Changed on August 24, 2026

Starting August 24, 2026, Google began rolling out updates to Merchant Center performance reports to align reporting definitions with other Google platforms like Google Ads and YouTube. support.google.com details three major changes:

1. Separation of YouTube affiliate results from organic traffic. Previously, clicks and impressions from YouTube affiliate links were grouped under "organic" traffic. Now merchants can distinguish between standard organic shopping traffic and traffic originating from YouTube shopping content. This is critical because YouTube affiliate performance often follows different seasonal patterns and conversion rates.

2. Expanded product-level reporting for Google Ads. Merchants can now see product-level metrics for Shopping ads at a granularity that was previously only available at the campaign or ad-group level. This includes impression share, click-through rate, and cost-per-click broken out by individual SKU.

3. Updated attribution definitions for conversions. The new reports apply consistent attribution windows across Merchant Center, Google Ads, and YouTube, reducing discrepancies when comparing performance across channels.

Change	Previous Behavior	New Behavior
YouTube affiliate traffic	Grouped with organic	Separate row in performance reports
Product-level ad metrics	Campaign-level only	Per-SKU impression share, CTR, CPC
Attribution windows	Inconsistent across platforms	Unified windows (e.g., 30-day click)

For merchants who rely on YouTube influencers or run heavy Shopping ad campaigns, these changes mean performance analysis will be more accurate—but also require re-baselining historical trends. Google warns that historical data may be adjusted retroactively, so merchants should export current data before the transition completes.

How AI Overviews Are Quietly Reshaping E-Commerce SEO

According to Semrush data from August 2026, cited by onlinestorenews.com, clicks on informational e-commerce queries have dropped by an average of 34% year-over-year in categories where Google's AI Overviews are present. At the same time, paid placements in Google Shopping's carousel are showing improved performance.

The trend is clear: generative AI answers are absorbing queries that used to send users to product category pages or buyer's guide blog posts. When a user asks "What are the best wireless headphones for running?" Google's AI Overview may directly answer with a curated list, and the user never clicks through to any merchant site. However, if the merchant is featured in the Overview via Shopping listings or a paid ad, the product can still get exposure.

Implications for e-commerce teams:

• Organic content strategy must adapt. Traditional SEO for blog posts like "best running headphones" may decline as AI Overviews replace those pages as the primary answer vehicle. Content teams should focus on structured data, product schema, and review signals that feed AI instead of purely keyword-stuffed articles.
• Paid Shopping campaigns become more important. With organic clicks dropping, merchants who maintain strong Shopping campaigns may actually benefit from higher visibility in the AI-generated carousel.
• Merchant Center data is the new SEO dashboard. The metrics that matter most now—product impression in AI Overviews, click-through rate from AI Mode, and YouTube affiliate performance—all reside in Merchant Center's updated reports.

The Bigger Picture: Merchant Center as the Nerve Center of AI Commerce

Google's investments in Merchant Center reflect a broader strategic pivot. The platform is no longer just a feed submission tool—it's becoming the analytics hub for an AI-first shopping ecosystem. Features like Product Studio, launched in 2023, allow merchants to generate custom product images using generative AI directly within Merchant Center. Combined with the AI performance insights reports and the revamped performance dashboard, Google is building a self-service infrastructure that lets retailers optimize for AI-driven discovery without needing a team of data scientists.

However, the transition is not frictionless. Some merchants have long criticized Merchant Center's complexity and error handling. In a 2025 blog post titled "Google Merchant Center Is a Whiny Pain in the Arse", a developer cataloged frustrations with feed validation errors, inconsistent warnings, and slow support. The reporting updates and AI insights may help, but they also add new layers of complexity—especially for small-to-medium retailers who lack dedicated Merchant Center specialists.

What Merchants Should Do This Week

Given these changes, here are actionable steps:

1. Enable AI performance insights (if you're in one of the newly supported countries) and begin tracking which products surface in AI Mode and AI Overviews.
2. Re-baseline your performance data after the August 24 reporting update. Export historical data now to avoid losing context when Google retroactively adjusts definitions.
3. Audit your product feed for AI Mode criteria. Since AI Mode seems to favor higher-priced products and different ranking signals, experiment with optimizing product titles, descriptions, and review snippets accordingly.
4. Shift budget toward paid Shopping ads if organic traffic from informational queries has declined. The Semrush data suggests paid placements still perform well even as organic clicks vanish.
5. Monitor the overlap (or lack thereof) between your traditional Shopping placements and AI Mode appearances. Use the Productrise finding of 1.28% overlap as a benchmark—if your own data shows a similar gap, it confirms you need separate strategies for each surface.

Conclusion

Google Merchant Center in 2026 is not the same platform it was a year ago. The expansion of AI performance insights, the stark pricing disparity in AI Mode, and the performance reporting overhaul all point to one conclusion: e-commerce visibility is no longer a matter of feed optimization alone. It requires understanding how Google's generative AI selects, ranks, and presents products—and using Merchant Center's new tools to track that process. Merchants who adapt early will capture the traffic that AI is reshaping; those who wait may find their products invisible in the search engines of tomorrow.