Google's deep link best practices, AI SEO assistants, and local search signals are reshaping how brands get found. Here's what actually matters in 2026.
Google served up a quiet but consequential update last week: formal best practices for “Read more” deep links in Search. If you missed it, you’re not alone — but local and hyperlocal teams probably shouldn’t.
Why Google’s Deep Link Guidelines Matter for Local Search
Search Engine Journal’s Matt Southern reported that Google has now outlined specific conditions that increase the likelihood of “Read more” deep links appearing in results. The mechanic is straightforward: Google surfaces these links when it can confidently associate a snippet of content with a specific, crawlable destination inside your site. For national brands, this is a content architecture conversation. For local businesses and multi-location brands, it’s something more pointed.
Think about a Grab-registered restaurant group with 12 outlets across Bangkok and Kuala Lumpur. Each location page is effectively a mini landing page fighting for neighbourhood-level intent. If your location pages are thin — address, hours, a phone number — Google has nothing deep to link to. The deep link update is, indirectly, an argument for richer hyperlocal content: neighbourhood guides, location-specific FAQs, locally relevant offers. Proximity is a signal, but content depth is what makes that signal stick.
The practical implication: audit your location pages against Google’s new guidance. Each page needs a clear, crawlable structure with substantive content blocks — not just schema markup, but actual readable content that gives Google something to excerpt.
The 43-Point Checklist Nobody Has Time For (And What to Do Instead)
Semrush published a 43-tip SEO checklist this week, pitched at optimising for both Google and AI-driven results simultaneously. It’s genuinely comprehensive. It’s also, for most marketing teams managing multiple markets across Southeast Asia, completely unworkable as a linear to-do list.
The more useful read is what the checklist reveals about the current state of SEO priority: technical hygiene, E-E-A-T signals, and structured data are now table stakes, not differentiators. What’s climbing the priority stack is content that answers specific, intent-driven queries — particularly the kind of conversational queries that AI Overviews and Answer Engine Optimisation (AEO) are trained to surface.
For teams operating in multilingual markets — say, a retail brand with Bahasa Indonesia, Thai, and English content — the checklist surfaces a real tension: hreflang implementation, localised keyword research, and culturally appropriate content are all on the list, but they interact in ways that a flat checklist can’t capture. The strategic move is to treat the checklist as a diagnostic tool, not a sequential workflow. Run it quarterly to identify where you’ve drifted, then prioritise fixes by revenue impact rather than checklist order.
AI SEO Assistants: Useful Tool or Expensive Autocomplete?
WebFX’s piece on AI SEO assistants, published via SEO.com, makes the case that these tools are shifting from novelty to infrastructure. The core argument: AI assistants can compress the time between audit and action — identifying technical gaps, generating content briefs, and tracking ranking changes faster than manual workflows allow.
That’s true, with caveats. The tools are only as good as the strategic context you feed them. An AI assistant flagging thin content on your Shopee store pages is useful; an AI assistant that doesn’t know your category is seasonally driven in Q4 and recommends evergreen content at the wrong moment is just fast noise.
For Southeast Asian teams, there’s a more specific consideration: most AI SEO tools are trained predominantly on English-language data and US/EU search patterns. Their recommendations for Bahasa Melayu content optimisation, LINE-driven discovery in Thailand, or TikTok Shop search behaviour in the Philippines require a human layer of regional interpretation. The tool handles volume and velocity; the strategist handles cultural and platform context. Neither works well without the other.
Budget reality: mid-tier AI SEO assistants run USD 100–500/month depending on seat count and crawl volume. The ROI case is clearest for teams managing 50+ pages or multiple-location digital footprints — exactly the profile of most growth-stage Southeast Asian brands.
Proximity Is a Strategy, Not an Accident
Pull these three threads together and a single operational principle emerges: search in 2026 rewards specificity. Deep links reward specific, structured content. AI-ready SEO rewards specific, intent-matched answers. Local search rewards specific, proximity-anchored signals.
The brands winning hyperlocal in Southeast Asia right now — whether that’s a homegrown F&B chain dominating “near me” queries in Petaling Jaya or a logistics provider owning last-mile search terms in Metro Manila — aren’t doing so by accident. They’re running tighter content architectures, updating Google Business Profiles with granular service attributes, and using AI tools to audit at a pace that manual teams can’t match.
The question worth sitting with: if your competitors start using AI assistants to close their technical SEO gaps in the next six months, what’s the content and proximity depth that keeps you differentiated when the hygiene factors are equal?
grzzly works with growth teams across Southeast Asia on exactly this intersection — local search infrastructure, content architecture for AI-driven results, and the regional nuance that generic tools miss. If your multi-location or hyperlocal search presence needs a sharper strategy, we should compare notes. Let’s talk
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Dusty GrizzlyDeep in the weeds of Google Business Profiles, local pack mechanics, and neighbourhood-level search intent. Believes proximity is a strategy, not a coincidence.