TL;DR
AI search engines (Google’s AI Overviews, Perplexity, and others) summarise answers and link to sources. To be the source they cite, prioritise helpful, people-first content, explicit facts, structured data, and authority signals. Google’s documentation explains helpful content and AI features; Perplexity explains how “Deep Research” runs multi-query investigations before answering. Treat each assistant as a discerning researcher: give it the facts, the proof, and the structure. (Google Support; Google Search Central; Perplexity Deep Research).
The landscape: “answer engines” and what they reward
Google AI Overviews (AIO) appear on queries where an AI snapshot helps users get to the gist, including links to learn more (Google Support; AI features). Google emphasises helpful, reliable, people-first content and clean technical signals (Helpful content; Structured data intro).
Perplexity brands itself an “answer engine” and documents a “Deep Research” mode that spends minutes running multiple searches, reading sources, and synthesising a longer report (Perplexity; Deep Research). It cites sources prominently throughout.
Across engines, the pattern is clear: systems reward pages that are (1) useful to humans, (2) unambiguous to machines, and (3) credible enough to cite.
A cross-engine optimisation framework (7 pillars)
1) Intent coverage: organise around real questions
Catalogue the compound, decision-stage questions your audience asks: comparisons, plans, constraints, troubleshooting. AI Overviews are designed for these “complex questions” (Google Blog). Perplexity’s Deep Research explicitly investigates such questions across the web before answering (Deep Research). Build one definitive page per priority question.
2) Answer-first page design
Start with a distilled answer (claim), then evidence, steps, and alternatives. This mirrors how answer engines present a snapshot plus links. Use descriptive headings and include trade-offs, assumptions, and edge cases. Helpful-content guidance encourages depth, clarity, and genuine value (Helpful content).
3) Verifiable facts and citations
State measurements, thresholds, compatibility, version support, and procedures. Reference canonical documentation or standards where relevant. When assistants audit your page for citations, they need explicit, checkable statements.
4) Structured data and entity clarity
Add JSON-LD to define your organisation, products, and page types. Google explains that it uses structured data to understand content and the world (people, companies), and lists supported features in the Search Gallery (Structured data intro; Search Gallery). Follow Google’s structured-data policies for eligibility and hygiene (Policies).
5) E-E-A-T signals
Demonstrate first-hand experience and trustworthy authorship; provide contact details, ownership, and policy pages. E-E-A-T informs Google’s quality perspective, though not a single “ranking signal” (E-E-A-T explainer). Depth, transparency, and maintenance logs bolster credibility across engines.
6) Technical health and crawlability
Keep robots, sitemaps, canonical tags, and internal links clean; fix broken pages; ensure performance basics. Google’s SEO Starter materials remain the baseline for crawl, index, and understanding (Search documentation hub).
7) Monitoring and iteration
Spot-check target questions across devices and profiles; track whether your pages are cited in AIO and Perplexity summaries; fix gaps in facts or clarity. Because features evolve, continuous review protects your visibility (AI features; Deep Research).
Building “citable” pages: a blueprint
Page anatomy:
- Title that mirrors the core question (“How to choose X for Y when Z applies”).
- Executive answer (3–5 sentences) with the claim and the context in which it holds.
- Diagnostic or selection steps with thresholds (e.g., “If dataset > N, use …”).
- Comparison table of options with criteria columns (“works offline,” “supports SSO,” “latency < X ms”).
- Constraints and exceptions clearly marked (“Not for regulated workloads requiring …”).
- References to primary docs (standards, APIs, regulations).
- Authorship and update stamp (“Updated 2025-10-26. Reviewed by …”).
Why engines like it: It’s easy to quote and link. The AI can lift a step, reference your thresholds, and attribute the claim. Google’s AI features page emphasises that AIOs are a jumping-off point to explore links; your job is earning that link by being the most useful explainer (AI features).
Per engine: nuances that matter
Google (AI Overviews)
- Complex queries focus: Be the guide for nuanced decisions; don’t just restate basics (Google Blog).
- Helpful-content standard: Thin summaries are disadvantaged versus detailed, people-first answers with experience and transparency (Helpful content).
- Technical clarity: Structured data improves entity understanding and eligibility for rich, well-understood presentations elsewhere, and aids comprehension generally (Structured data intro; Policies).
Perplexity
- Citations by design: Answers include sources inline; Deep Research compounds this by reading across many pages before synthesising (Perplexity; Deep Research).
- Be quotable: Short, declarative claims with proof links are more likely to be pulled verbatim, with attribution.
- Evergreen + up-to-date: Maintenance logs and explicit versioning help Perplexity prefer your page for accuracy.
Execution plan (30–60 days)
Week 1–2 — Research & planning
- Interview sales/support to extract the top 25 decision questions.
- For each, list the specific facts and thresholds needed to answer responsibly.
- Identify primary references you can cite.
Week 3–6 — Production & implementation
- Publish 10–15 answer-first pages with the blueprint above.
- Implement Organization, FAQ, and Product (where relevant) structured data and validate against Google’s guidelines (Search Gallery; Policies).
- Add author bios and update stamps.
- Review robots/sitemaps and fix internal linking issues (Search docs hub: SEO Starter).
Week 7–8 — Monitoring & iteration
- Spot-check target queries; log whether your pages are cited in AIO and Perplexity.
- Where you’re not cited, compare against cited sources: what facts or formats are you missing?
- Expand coverage and tighten facts (more thresholds, more procedures, more primary citations).
Related articles:
Frequently Asked Questions
Do I need separate pages for each assistant (Google vs Perplexity)?
No. Build people-first pages with explicit facts and references. The same clarity helps each engine for different reasons (AIO snapshots + links; Perplexity citations). Use structured data per Google’s guidance to improve understanding (Structured data intro).
Is structured data mandatory to be cited?
It’s not mandatory, but it reduces ambiguity and supports many downstream features. Google explicitly states it uses structured data to understand content and entities (Structured data intro).
How fast can this work?
Timelines vary by crawl, competition, and update cycles. What you control is the density of verifiable, citable facts and your site’s technical clarity, both emphasised in Google’s documentation (Helpful content; Search docs hub).
Do I still need classic SEO?
Yes. Crawlability, indexing, and site quality remain prerequisites and are covered in Google’s Search documentation (Search docs hub). AEO complements SEO by packaging facts and credibility for assistants.
The Bottom Line
Optimising for AI search means writing for a sceptical research assistant: answer the exact question, show your work, and make your claims machine-readable. Follow Google’s people-first and structured-data guidance; embrace Perplexity’s citation culture. Iterate where you’re not yet the best source.
Want help turning your top 25 questions into citable pages? Talk to Rankmeon.
References (Harvard style)
- Google (2025a) Find information in faster & easier ways with AI Overviews in Google Search. Available at: https://support.google.com/websearch/answer/14901683
- Google (2025b) AI features in Google Search and your website. Available at: https://developers.google.com/search/docs/appearance/ai-features
- Google (2025c) Creating helpful, reliable, people-first content. Available at: https://developers.google.com/search/docs/fundamentals/creating-helpful-content
- Google (2025d) Introduction to structured data. Available at: https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data
- Google (2024) Generative AI in Search: Let Google do the searching for you. Available at: https://blog.google/products/search/generative-ai-google-search-may-2024/
- Perplexity (2025) Introducing Perplexity Deep Research. Available at: https://www.perplexity.ai/hub/blog/introducing-perplexity-deep-research
- Perplexity (n.d.) Perplexity. Available at: https://www.perplexity.ai/