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September 27, 2026

90 Day Generative Engine Optimization Plan for Marketers & SEOs

Google aligned 90 day GEO plan for marketers and SEOs, with entity audits, modular answer content, and citation tracking to prove AI visibility.

90 Day Generative Engine Optimization Plan for Marketers & SEOs

Modular content blocks arranged for AI retrieval

Generative engine optimization means structuring, attributing, and technically preparing content so AI systems like ChatGPT, Perplexity and Google’s AI Overviews can retrieve it and cite it as a trusted source. The priority for marketers right now is simple: clarify entity ownership across your web presence and publish content in modular, answer-ready blocks. Everything else, including measurement and tooling, builds on that foundation.

TL;DR:

  • Indexability and crawlability are essential for content to be retrieved and cited by AI systems, serving as the entry point for effective GEO strategies.
  • Clear entity signals, such as consistent naming and structured data, outperform keyword density in influencing AI citation accuracy.
  • Structuring content into modular, answer-ready blocks increases the likelihood of being retrieved correctly by retrieval-augmented generation systems.
  • Building GEO requires integrating it with existing SEO, PR, and branding efforts, not treating it as a separate, standalone project.
  • Measuring GEO success involves tracking citation frequency, cited URL performance, and prompt clusters, alongside traditional traffic and click metrics.
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Table of Contents

What is generative engine optimization, and where does AEO fit?

Generative engine optimization (GEO) is the practice of shaping content and technical signals so large language models select it when assembling AI-generated answers. Some practitioners call the same discipline answer engine optimization (AEO); the terms overlap so heavily that treating them as separate disciplines mostly creates confusion rather than clarity.

The mechanics matter more than the label. Most generative search tools use retrieval-augmented generation (RAG), pulling from multiple indexed sources at the moment a query is asked rather than relying purely on training data baked into the model. Google documents this process, including query fan-out, where a single search prompt spawns several related queries behind the scenes. A page only gets pulled into that process if it is indexed, crawlable, and clearly attributable to a real entity.

That is where the myths creep in. Tactics like publishing an llms.txt file or forcing content into rigid chunk sizes get circulated as GEO hacks, but Google has explicitly said conventional SEO fundamentals still govern eligibility for its AI features.

Three things actually move the needle:

  • Indexability and crawlability remain the entry ticket. No index, no citation.
  • Clear entity signals (who wrote this, who published it, what expertise backs it) outweigh keyword density.
  • Structure beats volume. Short, self-contained claims retrieve better than sprawling narrative pages.

Semrush frames GEO as an extension of SEO, not a replacement, and that framing holds up against everything else in the research.

Why does GEO matter now for visibility?

AI-first research behaviour is no longer a niche pattern among early adopters. MarGen’s 2026 UK market analysis tracks rising use of AI search platforms and predicts that AI Overview citations will become a standard reporting KPI alongside traditional organic rankings within the next reporting cycles.

The zero-click reality: when a user gets a complete answer inside an AI Overview or chatbot response, they often never click through to a website at all. Influence still happens. The brand gets named, quoted, or recommended, but the traffic never lands in your analytics.

That gap between influence and visits is why citation tracking has to sit alongside click metrics, not replace them. Regulators are already watching how these features present results: the Competition and Markets Authority’s Fair Ranking CR covers how organic results are ranked and presented within search generative AI features, a signal that transparency and provenance will only become more scrutinised. Model hallucination on business queries has reportedly declined but remains material, which means the source you attribute your claims to still carries real weight in whether an AI system trusts and repeats them.

Core GEO strategies: content, entities and technical readiness

Three workstreams do most of the work in a functioning GEO programme, and none of them require rebuilding your entire content library from scratch.

1. Design content as modular, answer-ready blocks. Break long-form pages into self-contained units: a question, a direct answer in the first sentence, then supporting evidence with a named source. A retrieval system can lift a well-formed Q&A pair intact; it struggles to extract a clean answer buried in paragraph four of a 2,000-word narrative piece.

2. Treat entity clarity as non-negotiable. This means consistent naming of your company, consistent author bylines with real credentials, and structured markup that ties people to their expertise. If your “About” page calls the founder something different from what your press releases and LinkedIn use, you are giving AI systems conflicting signals about who you actually are. The University of Leicester’s approach to GEO leans hard on this point: clarity and provenance outperform sheer content volume when a model decides what to cite.

3. Get the technical basics genuinely right. Crawlability, working canonical tags, and pragmatic structured data (FAQ schema, Organization schema, Person schema where relevant) give retrieval systems clean signals to work from. You do not need exotic markup. You need the fundamentals applied consistently across every page that matters.

4. Put editorial governance behind all of it. Templates for how answer blocks get written, clear ownership of who updates entity information when it changes, and a change control process that stops five different teams publishing five different bios for the same spokesperson.

Pro Tip: Audit your own brand name across your last twenty published pages. If you find three spellings, two job titles for the same person, or an old company address still live somewhere, fix that before touching a single piece of new content. Entity confusion is the single most common reason well written content gets ignored by retrieval systems.

Core GEO strategies: content, entities and technical readiness — overview diagram

How do you measure GEO performance?

Traditional analytics were built for clicks, not citations, so measuring GEO means adding a layer most dashboards do not track by default.

  • Citation frequency: how often your brand, pages, or named experts get mentioned inside AI-generated answers, tracked separately from page views.
  • Cited URL mapping: which specific pages get pulled into answers, so you know which content format and structure is winning.
  • Prompt cluster analysis: grouping the queries that trigger citations reveals which topics you own in the eyes of AI systems and which ones a rival is winning instead.
  • Referral conversion: tracking what happens when a visitor does click through from an AI answer, since that traffic tends to arrive further along the decision path than typical organic clicks.

Zero-click volume rising in your search console data is not automatically bad news if citation frequency is rising alongside it. Read the two together, not in isolation. A page losing clicks while gaining citations is often doing exactly what a well-optimised page in an AI-first world is supposed to do.

Which tools and official guides should you consult first?

Start with primary sources rather than secondhand summaries, because the guidance keeps shifting and paraphrased advice ages fast.

  • Google Search Central’s guide to optimizing for generative AI features is the closest thing to an authoritative rulebook, directly from the company running the largest AI-integrated search product.
  • Semrush’s practical GEO guide translates that guidance into workable tactics and covers tools for monitoring how often your content surfaces in AI-generated answers.
  • MarGen’s UK state-of-market report gives useful strategic context on adoption trends and where the market is heading over the next reporting cycles.
  • The CMA’s Fair Ranking CR decision is worth reading if you want to understand the regulatory direction shaping how AI features present ranked content in the UK.

Treat vendor blog posts as useful interpretation, never as a substitute for what Google itself publishes.

Your first 90 days of a GEO programme

Building GEO into a marketing operation does not require a full quarter of planning before anything ships. It requires sequencing.

  1. Weeks 1 to 2: Audit indexability and entities. Map every authoritative asset you own, including any existing knowledge panel, and flag inconsistent naming or missing structured data.
  2. Weeks 3 to 4: Prioritise query clusters. Pick the ten to fifteen questions your buyers actually ask, and rank them by commercial value, not by search volume alone.
  3. Weeks 5 to 8: Build modular answer blocks. Rewrite or create content around those clusters using the question first, direct answer first format, with named provenance on every claim.
  4. Weeks 9 to 10: Apply technical fixes. Crawlability, canonical tags, and minimum viable structured data go live across the prioritised pages.
  5. Weeks 11 to 13: Configure measurement. Set citation tracking, agree baseline KPIs with stakeholders, and lock in a reporting cadence so week one’s numbers mean something by week thirteen.

Pro Tip: Run the entity audit before you write a single new answer block. Publishing beautifully structured content under a confused or fragmented entity identity wastes the effort. Fix who you are online before you fix what you say.

How Radkaadvertising approaches GEO for clients

Radkaadvertising builds generative engine optimization into the same digital marketing and AI-driven SEO work that already spans brand strategy, content creation, and PR and press distribution. That combination matters because entity clarity, one of the strongest levers in GEO, depends on consistent branding, consistent public mentions, and a coherent digital footprint across every channel, not just a website.

Work in this space typically spans:

  • E-commerce and product brands needing modular product content that AI shopping assistants can retrieve cleanly.
  • Startups and SMEs building a first authoritative online presence where entity confusion has not yet had time to set in.
  • Established brands consolidating fragmented messaging across UK and Eastern European markets into one consistent identity.

Bart, the author of this piece, brings a practitioner’s view shaped by direct agency experience across brand and digital campaigns; specific case studies and measured GEO outcomes will be added here as they complete.

GEO is an integrated layer, not a bolt-on project

Treating GEO as a standalone task, separate from SEO, PR and brand work, is the most common mistake I see. Entity clarity depends on PR-driven mentions; content structure depends on the same editorial discipline good SEO already demands. Give it a dedicated owner, budget three to six months before expecting citation gains, and put citation frequency next to your traffic dashboard, not in a separate deck nobody opens.

— Bart

Speed up your GEO results with expert help

Building entity clarity and modular, answer-ready content across an entire site takes real editorial discipline, and most in-house teams are already stretched thin running everyday marketing. Radkaadvertising’s AI Growth Package is built for exactly this gap: an audit that maps your current entity signals and indexability gaps, prioritisation of the query clusters worth targeting first, hands-on delivery of modular answer content, and measurement that tracks AI citation frequency alongside traditional traffic. A typical engagement moves through those four stages in sequence, so you are not guessing at what to fix first. If your brand also needs the wider groundwork that AI systems reward, consistent public mentions and press coverage that reinforce who you are, the PR and press distribution service builds exactly that kind of provenance. Visit the full services overview to see where GEO fits alongside your existing marketing plan, and get in touch to scope an audit.

Sources

FAQ

Is generative engine optimization a real practice?

Yes. It describes the concrete work of making content retrievable and citable by AI systems using RAG, and Google’s own guidance confirms that indexability, crawlability and clear content signals genuinely affect eligibility for AI-generated features.

How do I start learning SEO and GEO as a beginner?

Start with Google Search Central’s documentation, since it covers both traditional ranking factors and the newer generative AI requirements in one place. Once the fundamentals click, layer in entity clarity and modular content structure, the two areas that separate basic SEO from effective GEO.

Is GEO replacing SEO entirely?

No. Semrush and Google both frame GEO as an extension of SEO, built on the same crawlability and indexing requirements rather than a separate rulebook. Sites with strong SEO foundations tend to adapt to GEO faster than sites starting from scratch.

No. Search engines still need to crawl, index and rank pages before any AI feature can cite them, so the underlying SEO discipline remains the entry requirement for GEO. What is changing is the reporting layer on top of it, where citation frequency now sits alongside clicks and rankings as a measure of success.

Pricing for the AI Growth Package is available on request through Radkaadvertising’s AI Growth page. Related services with published rates, such as AI-driven digital marketing and content creation, are listed on the main services page.

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