Grounding Queries Are Reshaping Local Search Intent

Proximity used to be straightforward: rank in the local pack, show up on Maps, win the walk-in. Then AI Overviews arrived, and suddenly the question isn’t just where you rank — it’s whether the machine even considers you worth citing.

Moz’s Dr. Peter J. Meyers has done something genuinely useful here: he pulled real data on how Google Gemini uses grounding queries — the behind-the-scenes searches Gemini fires off to verify facts before generating an answer. The finding that should reorient your local SEO strategy: these aren’t the same queries your customers type. They’re precise, often technical, and almost always aimed at sourcing a citable fact rather than discovering a brand.

What Grounding Queries Actually Are (And Why Local Teams Should Care)

When someone asks Gemini “What’s the best dim sum spot near Orchard Road open on a Sunday morning?”, Gemini doesn’t just pattern-match from training data. It fires a grounding query — something closer to “dim sum restaurants Orchard Road Singapore Sunday hours” — and retrieves live results to anchor its response.

Meyers’ data shows these grounding queries skew toward specificity and recency. Zero-volume keywords that SEOs have historically ignored are, paradoxically, exactly the kind of precise signals Gemini trusts. For local businesses, this means that a well-structured Google Business Profile with accurate, detailed attributes — specific cuisine type, verified hours for each day, service options like dine-in versus takeaway — is now doing double duty: serving human searchers and feeding the machine’s verification layer.

The practical implication: stop optimising only for what people type. Start optimising for what an AI would need to confirm you’re the right answer.

The GEO Layer That Most Local Strategies Are Missing

Generative Engine Optimisation (GEO) for local isn’t a rebrand of what you’re already doing — it requires a structural shift in how you publish content. Semrush’s AI Brand Visibility Report framework makes this concrete: the brands that earn AI citations consistently have one thing in common — they’ve published specific, attributable facts that a grounding query can surface and verify.

For a local restaurant in Ho Chi Minh City, that might mean a dedicated page stating: “We source 100% of our pho broth bones from a single farm in Đà Lạt, slow-cooked for 14 hours.” That’s citable. “We serve authentic Vietnamese cuisine with fresh ingredients” is not.

The Semrush framework pairs AI share of voice and citation frequency against GA4 conversion data — which is the right instinct. Without connecting AI visibility to business outcomes, you’re measuring vanity. For Southeast Asian brands navigating Shopee Food, GrabFood, and Google simultaneously, building this attribution layer is genuinely complex, but skipping it means you’re flying blind on where AI-referred traffic actually converts.

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Mobile-First Signals and the Thumbnail Lesson from YouTube

This might seem like a detour, but stay with me. YouTube’s Todd Beaupré reported that the desktop homepage redesign — showing fewer videos but with larger thumbnails — actually drove more long-form engagement. The mechanism: bigger visual context helped users make faster, more confident viewing decisions.

The local SEO parallel is direct. On mobile — where the majority of local searches in Southeast Asia originate — your Google Business Profile photo quality and primary image framing function exactly like a thumbnail. A cramped, low-resolution storefront photo shown in a small map card is the equivalent of YouTube’s old compressed grid. Users scroll past.

Google’s local pack on mobile now surfaces profile photos more prominently than it did 18 months ago. Brands like Greyhound Café in Bangkok and Boost Juice across Malaysia have invested in consistent, high-resolution imagery across their GBP listings — not coincidentally, their local pack click-through rates reflect it. The lesson: visual hierarchy isn’t just a design concern. It’s a local search conversion lever that most teams treat as an afterthought.

For multi-location brands, this scales through a simple image governance protocol: one approved hero image per location type (dine-in, kiosk, drive-through), updated quarterly, sized to Google’s recommended 720×540 minimum for map card display.

Building a Search Visibility Stack That Covers All Three Layers

The brands that will own local and hyperlocal search in 2027 aren’t choosing between traditional SEO, AEO, and GEO — they’re running all three in parallel with distinct KPIs for each.

Traditional local SEO: GBP completeness score, local pack ranking position, review velocity. These still matter enormously for direct human intent.

AEO (Answer Engine Optimisation): Structured FAQ content, schema markup for business attributes, and voice-search-ready sentence construction. In multilingual markets like the Philippines or Malaysia, this means publishing FAQs in both English and the primary local language — Tagalog and Filipino, Bahasa Malaysia — because Gemini’s grounding queries will reflect the language of the original user query.

GEO: Citation frequency in AI-generated answers, sentiment polarity of those citations (Semrush’s report template tracks this), and the specific facts being sourced. Audit your AI citations monthly: if Gemini is citing your hours as 10am–9pm when you now close at 8pm, you have a grounding query accuracy problem that no amount of ranking work will fix.

The stack isn’t complicated. The discipline to maintain all three simultaneously is.

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Key Takeaways

• Publish specific, attributable facts on location pages — vague brand claims don’t survive Gemini’s grounding query verification layer.
• Treat your Google Business Profile imagery as a conversion asset, not an admin task — mobile-first visual hierarchy directly impacts local pack click-through.
• Build a monthly AI citation audit into your local SEO reporting to catch grounding query inaccuracies before they compound.

The interesting strategic question for Southeast Asian brands isn’t whether AI search will reshape local intent — it already has. The question is whether your content infrastructure is built to be cited, or just to be crawled. Those are no longer the same thing. How much of your current local content would survive a grounding query?

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At grzzly, we work with regional brands across Southeast Asia on exactly this — building local and hyperlocal search strategies that hold up across traditional rankings, AI citations, and the platforms your customers actually use. If your local visibility stack needs a clear-eyed audit, we’re happy to dig in. Let’s talk