If your ideal buyers now ask ChatGPT, Perplexity, or Google’s AI Overviews for advice, the question isn’t “How do we rank?”—it’s “How do we get cited?” This guide shows you how.

TL;DR: AI Search Optimization (AISO) is the discipline of making your content discoverable, trustworthy, and assistant-friendly so models choose and cite your pages in their answers. Use the Discovery → Citation → Measurement loop to build eligibility, win selection, and track coverage.

What is AISO?

AI Search Optimization (AISO) adapts classic SEO to AI answer experiences. Beyond crawlability and relevance, AISO emphasizes entity clarity, E-E-A-T surfaces, corroboration, and assistant-friendly structures (definitions, Q&A, frameworks) so systems like ChatGPT and Perplexity can confidently select and attribute your content.

At AISO Hub we operationalize this through four packages—AISO Audit, AISO Foundation, AISO Optimize, and AISO Monitor—to take you from baseline to sustained citations.

Why AISO matters now

  • Answers happen in-chat: Assistants compress the click. If you’re not cited, you’re invisible at the exact moment of decision.
  • Citations transfer trust: Users want to see who the model trusts. Being the named source builds brand salience—and qualified clicks when people want to dig deeper.
  • Entity-first web: Models build answers around entities and consensus. The clearer your entity signals and corroboration, the more cite-worthy you are.
  • Multilingual & local: Language and locale influence selection. Clear hreflang and genuine local cues (e.g., Lisbon for PT-PT) improve fit.

How AI assistants choose sources (in practice)

Selection differs by model, but common signals include:

  1. Discovery & access – Crawlable pages, helpful sitemaps, and an explicit allowance policy (e.g., llms.txt).
  2. Entity clarity – Clean Organization/Person/Service/Article schema, consistent naming, stable @id URLs, and strong About/Team/Contact pages.
  3. E-E-A-T surfaces – Real author bios, credentials, editorial standards, date transparency, and references.
  4. Answer usefulness – TL;DRs, Q&A blocks, step-by-steps, comparisons, and credible external citations.
  5. Consensus & corroboration – Your claims align with reputable sources; you link out where it helps verification.
  6. Freshness & coverage – Comprehensive, updated coverage of the task—not just a keyword match.
  7. Language/locale fit – Assistant answers in the user’s language; you offer the matching version with hreflang.

The AISO framework: Discovery → Citation → Measurement

Think of AISO as a continuous loop. You make your content discoverable and eligible, you earn the citation, then you measure and iterate.

1) Discovery & Eligibility: Be seen and understood

Goal: Ensure assistants can find, fetch, and trust your content.

Checklist:

  • Crawl access: Robots allow essential sections; XML sitemaps are clean; avoid parameter noise.
  • LLM allowances: Place a simple llms.txt at the root to clarify allowed use and point to canonical pages.
  • Entity & schema: Organization, WebSite, Service, Article, FAQPage schema with stable @id, inLanguage, and sameAs references.
  • Trust surfaces: Robust About, Team (with credentials), Contact, Privacy, and Terms.
  • Information architecture: Pillar → cluster → FAQ, mapped to real assistant prompts; no orphaned content.
  • Multilingual & local: Human-written EN/FR/PT-PT versions with hreflang and geo cues as relevant.
  • Performance & UX: Fast, accessible, distraction-free templates.

Quick win: If you need a reliable baseline across schema, IA, trust, and llms.txt, start with AISO Foundation after an AISO Audit.

2) Win the citation: Be the source assistants prefer

Goal: Structure and substantiate pages so the model chooses your URL.

On-page patterns that work:

  • Answer-first: Start with a concise TL;DR answering the core prompt.
  • Q&A scaffolding: Use H2s phrased as questions buyers actually ask.
  • Named frameworks: Offer memorable steps (like this Discovery → Citation → Measurement loop).
  • Comparisons & trade-offs: Explain when to choose A vs. B; assistants reward balanced guidance.
  • Corroboration: Cite reputable sources; link out where verification helps the model and reader.
  • Author & date transparency: Bio, credentials, and last-updated stamp.
  • Unique value: Templates, checklists, examples, and real process detail.

Site-wide plays:

  • Schema completeness at scale for Articles/FAQs/Services.
  • Internal-link sculpting so your canonical “best answer” is obvious.
  • Reputation & mentions via PR, partnerships, and authoritative citations.

Ready to grow coverage? Expand pillars, clusters, and FAQs with AISO Optimize.

3) Measurement: Track coverage, citations, and outcomes

Goal: See where you’re cited (or missing) and iterate.

What to measure:

  • Assistant citation coverage: % of tested prompts where your domain is cited (by model and locale).
  • Movement of key pages within AI answers vs. classic SERPs.
  • Leads & pipeline from assistant-influenced sessions (UTMs, form questions, last-touch notes).
  • Entity drift: Do assistants describe your brand and services accurately?

Tools & cadence:

  • Weekly snapshot of AI answers for priority prompts; monthly trendline. Pair with Search Console/Bing coverage. Managed programs like AISO Monitor automate tracking and roadmap refresh.

AISO in 30 days: a practical plan

Week 1 — Audit & baseline

  • Run an AISO Audit: entity gaps, schema coverage, crawl allowances, content/IA, and trust surfaces.
  • Define 15–25 buyer prompts across 2–3 buying tasks (EN/FR/PT-PT).

Week 2 — Foundation

  • Ship Organization/WebSite/Service/Article/FAQ schema and author bios.
  • Publish/upgrade About, Team, Contact; add editorial standards and update cadence.
  • Deploy llms.txt and clean sitemaps; fix the first pillar’s internal links.

Week 3 — Assistant-friendly content

  • Publish 1 pillar (1,800–2,500 words) + 3–5 clusters + 10–20 FAQs aligned to prompts.
  • Add TL;DRs, Q&A blocks, diagrams/tables, and external citations.

Week 4 — Corroboration & monitoring

  • Earn reputable mentions/links; add case snippets and examples.
  • Ship PT-PT/FR variants with hreflang.
  • Turn on monitoring, then iterate titles/intros/schema based on how assistants respond.

The assistant-friendly content checklist

  • Clear definition + TL;DR
  • H2 = questions users ask; short answer first, depth after
  • Named framework with 3–6 steps
  • Comparisons, pros/cons, and “it depends” logic
  • External citations and internal links to pillars/services
  • Author bio + last updated
  • Schema: Article + FAQPage (+ Service where relevant)
  • Localized variants with hreflang

Common pitfalls (and fixes)

  • Keyword-only thinking → Map prompts → pages by task and entity.
  • Thin trust surfaces → Strengthen About/Team/Contact and policies.
  • No corroboration → Add and maintain reputable citations.
  • Competing duplicates → Consolidate and canonize one best answer.
  • No measurement → Track AI answer coverage monthly; tune content accordingly.

How AISO Hub can help

  • AISO Audit: Baseline discovery/eligibility and a prioritized roadmap.
  • AISO Foundation: Essentials shipped—schema, entity pages, FAQ system, IA, llms.txt, and multilingual setup.
  • AISO Optimize: Ongoing pillars, clusters, FAQs, link earning, and internal-link sculpting.
  • AISO Monitor: Track which answers cite you, alert on changes, and iterate the roadmap.

Wrap-up

Assistants reward sites that are discoverable, unambiguous, and genuinely helpful. If you implement the Discovery → Citation → Measurement loop—and keep iterating—you’ll appear more often in AI answers with a visible citation.