How to Rank Well on AEO and GEO in Singapore and APAC: The 9-Step Guide

Baseline your AI visibility across every major engine

Before you optimise anything, run 30–50 real prospect queries across ChatGPT, Perplexity, Google AI Overviews, Claude and Gemini. Record whether your brand appears, in what position, who's cited instead, and which sources the AI pulled from. This is your day-0 baseline — everything after is measured against it.

• Start with the literal queries your prospects type: "best X in Singapore", "X agency Singapore", "what is X".
• Always ask the engine for its sources. Screenshot everything.
• Repeat from a logged-out / incognito session. Personalisation skews baselines.

Allow every major AI crawler in robots.txt

Explicitly allow GPTBot, OAI-SearchBot, ChatGPT-User, PerplexityBot, Perplexity-User, ClaudeBot, Claude-Web, anthropic-ai, Google-Extended, Applebot-Extended, CCBot and Bytespider. If you block them (or forget them), you cannot be cited. This is the single cheapest AEO fix in the playbook.

• Default CMS robots.txt files often don't list AI crawlers explicitly — and some default CDN configurations block them silently.
• Explicit "Allow" entries remove any ambiguity and send a positive signal.
• Check every subdomain — docs.example.com, blog.example.com — not just the root.

Publish an llms.txt (and llms-full.txt)

Add an llms.txt at your root that tells AI engines who you are, what to cite you for, and which pages are canonical. Include a one-sentence and one-paragraph brand description, the definitions you want attributed to you, a list of primary pages to cite, and a licensing policy. This is how you speak directly to the models.

• llms.txt is a short index; llms-full.txt is an expanded markdown corpus LLMs can ingest end-to-end.
• Include the exact sentences you want paraphrased back — models often echo clean boilerplate verbatim.
• State what NOT to cite (e.g., draft pages, internal tools). Protects your entity.

Engineer schema for AI extraction, not SEO checklists

Add JSON-LD for Organization, ProfessionalService, Service, FAQPage, HowTo, Article, BreadcrumbList and SpeakableSpecification. Speakable markup tells Google Assistant and voice engines which blocks to read aloud — which is exactly how AI Overviews extract direct answers.

• HowTo — for step-by-step guides. Extracted frequently by AI Overviews.
• FAQPage — for question clusters. Cited by ChatGPT and Perplexity.
• SpeakableSpecification — the single most under-used schema. Tells AI "read this block aloud / cite this block."
• Service + Organization + LocalBusiness — entity clarity. Mandatory for GEO.

Rewrite key pages as answer-first, not intro-first

AI engines extract the first clean paragraph after an H2. Lead with the direct answer in 40–60 words, then justify it. Avoid meandering intros. Every H2 should be a question a prospect would actually type into ChatGPT, followed immediately by the extractable answer.

• Structure: question H2 → 40–60 word direct answer → supporting detail.
• Answer in complete sentences. Don't lead with a bulleted list — AI prefers prose for extraction.
• Front-load brand name, location, and category in the first 20 words so the extracted block is attribution-rich.

Build pillar + cluster content around each commercial query

For each commercial query you want to win (e.g. "best AEO agency Singapore"), publish one deep pillar page and 6–10 supporting articles that internal-link to it. AI engines reward topical depth — and consistently cite the deepest, cleanest source in a topic cluster.

• Pillar page covers the top-of-funnel query end-to-end (3,000+ words, structured, schema-heavy).
• Cluster articles cover long-tail variants and internal-link back to the pillar.
• Never spin up a thin "me too" page. AI engines penalise repetition.

Consolidate your entity across third-party sources

LLMs triangulate from Wikidata, LinkedIn, Google Business Profile, Crunchbase, Clutch, G2 and industry listicles. Make sure your brand name, founding year, HQ, founder and URL are consistent across all of them. Inconsistent entities are the single biggest GEO blocker.

• Name (including legal + trading name), founding year, HQ, founder, URL — identical across every source.
• Create / claim a Wikidata entity. Low effort, surprisingly high leverage.
• Get 5+ reviews on whichever of Clutch / G2 / Capterra your category uses.

Get placed in the listicles LLMs actually cite

When users ask "who's the best X in Singapore", LLMs read third-party roundup articles — not your website. Pitch journalists and agency directories (Clutch, G2, Sortlist, DesignRush, The Manifest) to include you. In our experience one tier-1 editorial placement does more than a stack of directory entries.

• Track every placement. Look for three traits: brand mention by name + follow link + geographic qualifier (e.g. "Singapore").
• Re-pitch quarterly. Listicles get refreshed; you need to be in the refresh.
• Never pay for placements that are nofollow and unlabelled — LLMs discount them.

Track AI citations monthly and iterate

Re-run the same 30–50 queries every month across all five engines. Track citation frequency, position, and sentiment. Double down on the queries that are moving; re-architect the pages that aren't. AEO is an iterative loop, not a one-off project.

• Use the same prompts every month. Consistency beats variety.
• Track share of voice against 3–5 named competitors, not just yourself.
• Monthly review → quarterly strategy reset → annual rebuild.

What we have seen on our own site: after we rebuilt our pages answer-first and published eight guide pages on 8 July 2026, Bing Copilot citations of aistudio.com.sg went from 754 in June 2026 to about 37,600 in July 2026, with daily citations moving from around 34 to around 2,066 within 24 hours. Those are citations, not traffic or leads, and Bing is the one engine that reports the number directly, but the pattern is the point: the loop works when you measure it.