Google Merchant Center · Status at source date: Newsletter archive
Google's AI shopping insights report begins rolling out across five markets
Google's AI shopping insights report: the Merchant Centre reporting suite previewed at GML: is now rolling out, flagged by Arpan Banerjee. The report shows a brand's share of voice on AI surfaces against similar brands across AI Mode, AI Overviews, and Gemini, a shopping funnel breakdown spanning discovery, evaluation, and purchase, product term insights revealing which terms shoppers use in AI conversations and the brand's share of voice for each, and an attribute completeness score that pinpoints which products are missing the specs AI surfaces look for.
What changed
Rollout covers the US, Canada, Australia, India, and New Zealand in the coming months.
Why it matters for advertisers
For you, this means retailers in the rollout markets gain a direct read on AI-surface visibility and the product-data gaps holding it back. Worth using the attribute completeness score to prioritise feed enrichment, since it shows exactly which products lack the specs AI surfaces need to feature them.
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Original newsletter text and archive evidence
Google's AI shopping insights report begins rolling out across five markets
Google's AI shopping insights report: the Merchant Centre reporting suite previewed at GML: is now rolling out, flagged by Arpan Banerjee. The report shows a brand's share of voice on AI surfaces against similar brands across AI Mode, AI Overviews, and Gemini, a shopping funnel breakdown spanning discovery, evaluation, and purchase, product term insights revealing which terms shoppers use in AI conversations and the brand's share of voice for each, and an attribute completeness score that pinpoints which products are missing the specs AI surfaces look for. Rollout covers the US, Canada, Australia, India, and New Zealand in the coming months.
For you, this means retailers in the rollout markets gain a direct read on AI-surface visibility and the product-data gaps holding it back. Worth using the attribute completeness score to prioritise feed enrichment, since it shows exactly which products lack the specs AI surfaces need to feature them.
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