How fast can we see results with GEO?

Timelines vary by crawl/index cycles and competition. Teams typically see early wins after deploying structured data and answer-ready content, especially in engines that cite sources by design.

Is there academic or industry backing for GEO?

Yes. GEO has been formalised in research and is supported by industry guidance emphasising E-E-A-T, structured data, and clear provenance for inclusion in AI answers.

What Is Generative Engine Optimisation (GEO)

What Is Generative Engine Optimisation (GEO)? An Executive Guide

A practical playbook to structure content, data and proof for inclusion in AI Overviews and answer engines.

Executive summary

Generative Engine Optimisation (GEO) is the practice of making your brand’s content, data and signals easy for answer engines to find, understand and cite—so your organisation is surfaced inside AI-generated summaries on Google (AI Overviews), Perplexity, Copilot, Gemini and similar tools. Unlike traditional SEO (which fights for rankings among “ten blue links”), GEO competes for inclusion and prominence inside machine-written answers that are increasingly the default way people search.

The shift is already here. Google began rolling out AI Overviews in May 2024 and expanded globally later that year, and answer engines such as Perplexity have normalised cited, real-time, summarised results. Leaders who adapt their strategy, content ops and structured data now will be disproportionately visible in this new landscape.

Why GEO matters now (and what’s changed)

1. Search experiences are becoming “answers-first.”

AI Overviews on Google and answer engines present a synthesised paragraph first, with sources cited inline; many queries never trigger a classic list of links. That means the unit of competition is no longer a page rank—it’s whether your brand is selected, trusted and quoted inside the AI’s answer.

2. Trust and quality signals still rule—just expressed differently.

Google’s quality frameworks (E-E-A-T: Experience, Expertise, Authoritativeness, Trust) continue to matter, and answer engines strongly prefer clear provenance, well-marked sources and consistent entity data. In other words: the clearer your evidence and structure, the more likely you’ll be cited.

3. Early evidence for GEO works.

Research introducing “Generative Engine Optimisation” shows content format, presentation, and signals can measurably increase the likelihood of being referenced by generative engines. Practically, that means the way you structure, attribute, and package knowledge can change inclusion odds.

4. The interface is still evolving.

Google continues to tune AI Overviews after widely reported oddities, and has experimented with more AI-forward modes. The direction of travel is unmistakable: more AI in search, tighter summaries, and higher bars for citation.

GEO vs. SEO: the quick contrast

Dimension	Traditional SEO	GEO (Answer-Engine Visibility)
Primary battleground	SERP rankings	Inclusion in AI summaries
Content goal	Relevance + backlinks	Citable facts, clarity, structure, provenance
Format emphasis	On-page optimisation	Schema/JSON-LD, citations, evidence blocks, explicit claims
Measurement	Rank, impressions, CTR	Citation presence, placement, co-mentions, assisted conversions
Technical	Crawlability, page speed	Entity consistency, structured data coverage, source hygiene

How answer engines decide what to cite

While each system is proprietary, repeated patterns emerge across engines:

1. Structured data and canonical entities.

Clear JSON-LD (schema.org) and consistent “Knowledge Graph” style facts improve machine understanding and reduce ambiguity—especially for people, organisations, products, locations and how-tos.

2. Source quality under E-E-A-T.

Demonstrable experience (first-party data, case studies), clear authorship, organisational authority, and rigorous referencing all increase perceived reliability.

3. Answerability.

Content that directly answers the query with explicit claims, definitions, steps and evidence (not just marketing copy) is easier for engines to quote. Practical guides with summaries and FAQs tend to be surfaced more often. Insights from Perplexity’s own guidance emphasise cited sources and well-structured explanations.

4. Recency and stability.

For time-sensitive topics, engines weigh freshness; for evergreen topics, they reward sources that are consistent and widely corroborated.

5. Presentation and formatting.

The GEO research indicates that plain-English headings, scannable sections, and calibrated style choices can meaningfully improve inclusion odds.

The GEO framework: Three layers of optimisation

1. Authority signals (prove you’re the source)

Authorship & credentials. Add author bios with relevant experience, qualifications, and links to academic/business profiles. Map authors as Person with affiliation, sameAs, and knowsAbout. Align with E-E-A-T expectations.
Evidence & citations. Use source-first writing: quote data, add references, link to methods. Make it easy for engines to verify claims.
First-party data. Publish proprietary stats, benchmark studies, and case results—with methods. Engines favour unique, citable assets.
Reputation graph. Ensure consistent organisation details across your website, LinkedIn, Companies House profiles, and key directories; link them with sameAs and Organization schema.

2. Structured clarity (make it machine-readable)

JSON-LD coverage. Mark up Organization, WebSite, WebPage, and the content type (HowTo, FAQPage, Article, Guide). Use about, mentions, and citation to point to entities and sources.
Canonical entities. Reference Wikidata/ISBN/DOI/official homepages via identifier/sameAs to remove ambiguity.
Table stakes technicals. Fast pages, clean URLs, and crawlable architecture still matter (they’re prerequisites to being found and indexed).

3. Answer design (package insights for quotation)

Definition blocks. Provide a crisp “What is X?” paragraph per key concept (like the one at the top of this guide).
Procedural sections. Use step-by-step frameworks and checklists (How-Tos) that answer engines can lift.
Mini-summaries. Start sections with a 1–2 sentence “TL;DR” and end with key takeaways.
Comparisons & tables. Help engines synthesise by presenting contrasts and pros/cons explicitly.

An executive GEO playbook (90-day plan: 3 Phases)

Phase 1: Discover (Weeks 1–3)

1. Audit your “entity footprint”.

Is your brand clearly defined as an Organization with consistent name, logo, founding date, and leadership?
Are key people (Person) and products/services (Product, Service) disambiguated with sameAs?
Is there a single, canonical “About” hub that other pages link back to?

2.Map answer intent to content.

Identify your top 20 buyer and thought-leadership questions. For each, note: definition, decision criteria, step-by-step, cost/ROI, risks, and alternatives. Prioritise those with commercial intent and strategic positioning value.

3. Benchmark answer presence.

Search your priority questions across Google (with and without AI Overviews) and Perplexity. Log whether your brand is cited, which competitors are, and what source features appear (FAQ, stats, case studies, schemas).

Phase 2: Build (Weeks 4–8)

1. Create “answerable” pillar content.

For each priority topic, produce a single, authoritative guide that contains:
A plain-language definition;
A decision framework;
A cost/ROI model;
A comparison table;
A short FAQ;
References.
Mark up with Article + Guide, add FAQPage (for the FAQ), and ensure citation links are clean.

2. Publish evidence assets.

Commission a small cohort survey, publish methodology, release a one-page “Key Findings” with charts; or open-source a dataset. These make you the origin of useful facts.

3. Strengthen author and org entities.

Build complete author pages with credentials, conference talks, and academic/business references. Link out to authoritative profiles; bring those links back to your site for a closed loop.

Phase 3: Amplify (Weeks 9–12)

1. Citable summaries.

Create short “stat cards”, quotable definitions, and reference pages that answer engines can safely lift.

2. Distribution to answer-friendly surfaces.

Publish exec summaries on LinkedIn Articles and developer docs where relevant, preserving canonical links and citations.

3. Feedback loop.

Track appearance in AI Overviews and Perplexity citations monthly; refine content and schema based on what wins citations and what doesn’t

Practical GEO tactics you can deploy this quarter

Definition modules: Add a consistent “In one sentence” definition component at the top of every concept page.
Evidence boxes: Introduce callouts with source, date, and a link to methods; use citation in JSON-LD.
People & org pages: Build a robust /about/people/ hub; interlink to articles by that author and mark each author’s specialties with knowsAbout.
FAQ clusters: Add 4–6 precise Q&As per page (avoid fluff), then mark up as FAQPage.
How-to and checklist patterns: Use numbered steps and clearly labelled materials/requirements; mark up as HowTo when appropriate.
Comparative tables: Make explicit, source-backed comparisons—engines love structured contrasts they can cite.
Citation hygiene: Prefer primary sources (official docs, standards, peer-review); avoid circular citations.

What not to do

Don’t chase tricks. Temporary “hacks” (e.g., stuffing invisible prompts) risk AI-search de-trusting your domain.
Don’t publish unsubstantiated claims. AI systems increasingly down-rank sources that propagate low-quality or misleading info; Google has tightened AI Overviews triggers after publicised issues.
Don’t neglect traditional SEO foundations. Crawlability, performance, mobile UX and internal linking still underpin discoverability.

Governance: policies and safeguards for enterprise GEO

Source standards. Create a content policy that mandates primary references for claims, dates on all stats, and a named owner for each page.
Fact-checking workflow. Require a subject-matter “reviewed by” with a timestamp.
Schema linting. Add schema validation to your CI/CD pipeline; fail builds when critical entities are missing or malformed.
AI use policy. If AI assists drafting, disclose it where appropriate and ensure human verification, especially for YMYL topics. Google’s rater frameworks continue to value real-world experience and verifiable expertise.
Risk register. Track reputational risks (e.g., being cited incorrectly) and implement takedown/contact protocols.

Measurement: KPIs for GEO

Beyond classic SEO metrics, track:

Citation Presence Rate (CPR): % of priority queries where your brand is cited in AI summaries (Google AI Overviews, Perplexity, Copilot).
Answer Share of Voice (ASOV): Weighted share of citations vs. competitors across your topic set.
Prominence Score: Position of your cited link within the AI summary (e.g., first three sources vs. footnotes).
Co-mention Graph Growth: Number and quality of authoritative sites that co-occur with your brand in citations.
Assisted Conversions: Conversions following sessions that included answer-engine interactions (where attributable).

GEO for different use cases

B2B services

Publish decision frameworks, implementation checklists, and ROI calculators with explicit assumptions.
Case studies should detail context, approach, outcomes, metrics, and caveats, not just testimonials.
Map offerings to Service schema; add AreaServed and clear category values.

SaaS & product companies

Maintain canonical feature definitions, API references and versioned release notes; mark up with SoftwareApplication where relevant.
Provide comparative explainers (“When to use X vs. Y”) with neutral tone and transparent sourcing.

Regulated sectors (YMYL)

Elevate experience signals: author credentials, affiliations, conflict-of-interest statements and method sections. Rater guidelines emphasise E-E-A-T more strongly here.

FAQ: Executives often ask…

1. Is GEO just “SEO with AI prompts”?

No. GEO overlaps with SEO foundations but targets citation within answers, not only rankings. It emphasises structured data, provenance, and answer-ready packaging.

2. Will GEO help with classic SEO rankings?

Often yes—because you’ll improve clarity, structure and trust. But treat classic SEO gains as a by-product of making your content citable to machines.

3. What about misinformation and AI hallucinations?

It’s precisely why rigorous sourcing and governance matter. Google has adjusted AI Overviews after widely reported issues; being a high-quality, well-cited source reduces the risk of misquotation and increases beneficial citations over time.

4. How fast can we see results?

Timelines vary by crawl/index cycles and competitive intensity. Many teams see early wins once structured data and answer-ready content go live—especially on engines like Perplexity that cite sources by design.

5. Is there academic backing for GEO?

Yes. The original GEO paper formalised methods for improving visibility in generative engines and demonstrated measurable effects on inclusion.

References & further reading

GEO: Generative Engine Optimisation (research paper). Introduces a black-box optimisation framework and shows presentation/style can increase visibility in generative answers. arXiv
Google: AI Overviews announcement (May 2024). Background and rollout details. blog.google
AI Overviews expansion. Background on international availability across 2024. Wikipedia
Google Search Quality Rater Guidelines (E-E-A-T). Foundations of quality signals that map well to GEO. Google+1
Google Developers: Structured Data (JSON-LD / schema.org). Implementation guidance for machine-readable content. Google for Developers
Schema.org “Guide” type. Useful for marking up executive guides like this pillar. schema.org
Perplexity: What it is and how it cites. Useful for understanding answer-engine behaviour and optimisation levers. Perplexity AI+1
Industry perspective: GEO vs SEO paradigm commentary. Andreessen Horowitz

How Brand Strategy AI can help

We partner with leadership teams to operationalise GEO—from entity audits and structured data roll-outs to evidence-led content programs and measurement. Our approach blends brand strategy (positioning, messaging, proof) with technical implementation (schema, governance, analytics) so you’re discoverable where decisions now start: inside the answer.