Google Now Shows If Your Products Appear in AI Search — And India Made the List

Google will now tell you if AI search shows your products

For a year, the honest answer to "do my products appear inside AI Overviews or AI Mode?" was a shrug. You could search a few queries yourself, eyeball the results, and guess. There was no dashboard, no share number, nothing you could track over time.

That changed. Google's Merchant Center now includes AI Performance Insights, a report that shows how your brand performs for shopping-intent queries inside AI Mode and AI Overviews. Google published the feature through Merchant Center Help around 27 May 2026 and has been rolling it out since. The detail that should make Indian D2C teams sit up: it's live in just 5 countries at launch — the US, Canada, Australia, New Zealand, and India.

India rarely makes the first wave of anything Google ships. This time it did. So before your competitors notice, it's worth understanding exactly what this report tells you and what to do about it.

What AI Performance Insights reports

The report is built around a few metrics that, together, answer "am I visible, and to whom?"

Share of voice compares your impressions to the total across your competitor set for related shopping queries. It's the headline number — your slice of the AI shopping conversation.

Competitors' average share gives you a benchmark, so your share of voice has context instead of hanging in the air.

Frequency shows how popular specific search types, terms, intents, and attributes are — essentially what people are actually asking AI when they shop in your category.

Products showing counts how many of your products appear for the top terms and intents. This is the one that stings or reassures: it tells you whether your catalogue is present or invisible.

Two boundaries matter. First, it covers organic visibility only — paid ads are excluded, so this is a pure discovery and feed-quality signal, not an ads dashboard. Second, at launch it works for English-language queries. For a lot of Indian D2C brands whose buyers search in English, that's fine; if your demand is heavily regional-language, the report won't see it yet.

The uncomfortable backdrop: AI search shows fewer products

Here's the context that makes this report more than a vanity metric. AI shopping surfaces are far narrower than traditional Shopping.

A data study by Productrise reported that if AI Mode became the default, the vast majority of Google Shopping product visibility would vanish — their analysis pointed to roughly 95% fewer products being surfaced than in standard search. Separate reporting, including coverage in Search Engine Journal, noted that AI Mode has shown the same products at meaningfully higher prices than the traditional carousel in some tests. Treat these as third-party findings rather than Google numbers, but the direction is consistent and worth planning around.

The implication is simple and a little brutal. Traditional Shopping is a wide shelf where almost every product gets some exposure. AI Mode behaves more like a shortlist — a handful of products that best match a conversational query get named, and the rest aren't mentioned at all. Being "on Google" no longer guarantees being in the answer.

That's exactly why a measurement tool matters now. You can't improve a shortlist you can't see.

Traditional Shopping SEO vs AI shopping visibility

The two games reward different things. Here's how they compare:

The brands treating these as the same channel are the ones who'll be surprised when their Shopping numbers hold but their AI visibility is near zero.

What to fix to earn a spot in AI answers

The report doesn't just grade you — it points at the work. A few priorities that consistently matter:

Complete every product attribute buyers search

AI Performance Insights flags attributes people frequently search that your feed is missing, effectively handing you a to-do list. Fill them. Material, fit, skin type, ingredients, use case, size — the specifics that a conversational query hinges on. A thin feed with a title and price is easy to skip.

Write for the question, not the keyword

AI shopping queries are full sentences with constraints. "Under ₹1000," "for sensitive skin," "for a 6-month-old." Your product descriptions and content should answer those constraints in plain language, because that's what the model matches against.

Make your best products unmistakably specific

Since AI Mode names a shortlist, generic positioning gets you nowhere. The product that clearly says who it's for and what problem it solves has a far better chance of being the one mentioned.

Keep price and availability accurate

With AI surfaces pulling live data, stale prices or out-of-stock items don't just look bad — they can quietly drop you from consideration.

This is feed and content work that compounds, and it's the sort of ongoing discipline that decides whether you're on the shortlist or invisible. If you want your catalogue and content built to earn AI shopping visibility rather than react to it, that's part of what our growth marketing team handles for D2C brands.

How to actually use the report if you're in India

Don't just glance at share of voice and move on. Work it in a loop.

Start by reading your products-showing count against your competitors' average share — that tells you if you're under-represented before you agonise over percentages. Then pull the top terms and intents the report surfaces; these are real category questions your buyers are asking AI, and they're gold for both your feed and your content roadmap. Fix the missing attributes it flags first, because those are the cheapest, highest-leverage changes. Then re-check in a few weeks, since this is a trend to move, not a one-time score.

Because India is in the launch group, you have a genuine head start — most of your local competitors haven't opened this report yet, if they know it exists.

The regional-language gap to plan around

One limitation deserves its own note, because it's specific to how India shops. At launch, the report reads English-language queries. Plenty of Indian D2C demand is English, so for many brands that's no obstacle. But a growing share of buyers search and speak to AI in Hindi, Tamil, Telugu, Marathi, and more, and that behaviour is exactly where AI assistants are expanding fastest.

For now, that means two things. First, the visibility you can measure is your English-query visibility, so don't read a strong share of voice as proof you're winning across all of India — it's proof you're winning in one slice of it. Second, the feed and content discipline that earns English AI visibility is the same discipline that will pay off when regional-language coverage arrives: complete attributes, specific descriptions, accurate data. You're not doing throwaway work by fixing your feed now; you're building the foundation for the queries the report can't see yet.

If regional-language demand is central to your brand, keep measuring it the old-fashioned way in parallel — run sample queries yourself in your buyers' languages and note whether you show up — until Google widens coverage. Keep a simple log of which regional queries you tested and whether your product appeared, so you have a rough baseline to compare against once the report expands. Treat the report as one lens, not the whole picture, and pair it with what your own eyes tell you across the languages your customers actually use.

Where this is heading

AI shopping is still a small slice of how India buys online, so nobody needs to panic or abandon what's working. Traditional Shopping and free listings will keep driving the bulk of your traffic for a while yet.

But the trajectory is clear enough to act on early. As more buyers ask AI to shop for them, the shortlist gets more valuable and the wide shelf gets less so. Google just handed you the instrument to see whether you're on that shortlist. Open it now, fix your feeds, and check back monthly, and you'll build a visibility lead that's hard to catch — quietly, while most of your category is still guessing.