How to Do GEO: A Step-by-Step Workflow
The Short Answer: How to Do GEO in Six Steps
- The Short Answer: How to Do GEO in Six Steps
- Step 1: Audit Your Current AI Visibility
- Step 2: Research the Prompts Your Audience Actually Uses
- Step 3: Structure Your Content for Extraction
- Step 4: Strengthen Your Entity and Topical Authority
- Step 5: Add Schema Markup and Structured Data
- Step 6: Earn Citations and Brand Mentions
- Step 7: Measure, Iterate, and Stay Current
Generative Engine Optimization (GEO) is the practice of structuring your content so AI search engines — ChatGPT, Google AI Overviews, Perplexity, Gemini — surface your brand as a cited source or direct answer. The core workflow: audit your current AI visibility, research the exact prompts your audience types into AI tools, structure content for easy extraction, strengthen your entity and topical authority, add schema markup, and earn the citations and brand mentions that signal trust to large language models.
Step 1: Audit Your Current AI Visibility
Before you can improve your GEO standing, you need a baseline. Most practitioners skip this step and fly blind. Don’t.
What to Do
- Open ChatGPT, Perplexity, and Google AI Overviews. Search for the ten to fifteen questions your target audience asks most often.
- Note whether your brand, domain, or content appears in the generated response — either as a cited source, a named recommendation, or embedded in the answer itself.
- Record which competitors are being cited. This tells you whose topical authority the model trusts in your space.
Why It Matters
AI models synthesize answers from sources they consider authoritative, trustworthy, and clearly structured. If you are not showing up at all, you have a gap in either topical coverage, entity recognition, or structured-data signals. The audit tells you which gap to close first.
Practical Tip
Create a simple spreadsheet: Column A is the prompt, Column B is whether your brand appears, Column C lists the sources that did appear. Revisit this audit monthly. Changes in AI responses often happen before changes in traditional rankings.
Step 2: Research the Prompts Your Audience Actually Uses
Traditional keyword research maps queries people type into Google. GEO research maps the conversational prompts people type into AI assistants. These are longer, more specific, and phrased as questions or tasks — not keywords.
What to Do
- Pull your existing Google Search Console queries and identify any that are phrased as full questions. These are high-confidence signals of AI-style intent.
- Use tools like Perplexity itself, Reddit threads, and forum discussions in your niche to surface the exact language real users employ.
- Group prompts by topic cluster. Each cluster becomes a content priority.
Why It Matters
An AI model answering “what is the best way to fix a crawl budget issue for an e-commerce site with 50,000 SKUs” needs a source that answers that specific question — not a generic crawl-budget overview. The more precisely your content matches the actual prompt, the higher the likelihood of extraction and citation.
Practical Tip
Ask ChatGPT: “What are the twenty most common questions people ask about [your topic] when using AI assistants?” The output is an immediate GEO research shortcut, and it surfaces phrasing patterns your audience uses in the very environment you are optimizing for.
Step 3: Structure Your Content for Extraction
AI models do not read pages the way humans do. They extract discrete, useful passages. Your job is to make extraction effortless.
What to Do
- Lead with the direct answer. Put the core answer in the first paragraph of every section, before supporting detail. This mirrors how AI Overviews pull snippets — they take the clearest, most self-contained statement of fact or process first.
- Use numbered steps for processes. AI models are trained to recognize and reproduce step-by-step instructions. If your workflow can be numbered, number it.
- Write short, self-contained paragraphs. Each paragraph should make one complete point. Avoid running multiple ideas together. A paragraph that stands alone is a paragraph that can be extracted and cited.
- Use descriptive H2 and H3 headings. The heading “Step 3: Structure Your Content for Extraction” tells a language model exactly what the section covers. Vague headings like “Our Approach” do not.
Why It Matters
Generative models favor content that is easy to parse, clearly attributed to a point, and free of ambiguity. Dense walls of text, heavy jargon without definition, and buried answers all reduce extractability. Clarity is a ranking signal in GEO.
Step 4: Strengthen Your Entity and Topical Authority
Large language models build an internal model of the world through entities — people, places, organizations, concepts — and the relationships between them. If your brand, your authors, and your topical footprint are weak as entities, AI systems default to citing whoever has the stronger signal.
What to Do
- Build out your Knowledge Panel signals. Ensure your organization and key authors have well-structured About pages, consistent NAP data, and are referenced across authoritative third-party sources (LinkedIn, industry directories, press mentions).
- Create named author profiles. Each piece of content should have a byline that links to a detailed author bio page. That page should list credentials, experience, publications, and external links that confirm expertise. This is the E-E-A-T signal AI models are trained to recognize.
- Cover your topic cluster comprehensively. A site that has fifteen high-quality articles on crawl budget signals far more topical authority than a site with one. Depth beats breadth. Pick your core clusters and own them completely before expanding.
Why It Matters
When a model is asked about crawl budget, it cites sources it has learned to associate with crawl budget expertise. That association is built through the volume, quality, and interconnection of content on that topic — plus off-site references that confirm the association. Entity strength is the long game of GEO.
Step 5: Add Schema Markup and Structured Data
Schema markup is machine-readable metadata that tells search engines and AI systems exactly what your content is, who wrote it, and what it covers. It is one of the most direct GEO levers you can pull.
What to Do
- Add Article schema to every blog post and guide. Include author, datePublished, dateModified, headline, and description at minimum.
- Add FAQPage schema to any page with a Q&A section. This directly feeds AI Overview extraction.
- Add HowTo schema to step-by-step workflow content like this article. Each step maps to a HowToStep object.
- Add Organization schema to your homepage and About page. Include sameAs links to your social profiles, Wikipedia entry (if applicable), and major directory listings.
Why It Matters
Schema does not guarantee citation, but it removes ambiguity. When an AI system can read structured metadata that says “this is a how-to guide, authored by Terry Samuels, a digital marketing expert with 30 years of experience,” it has a stronger basis for trust than an unstructured page with the same information buried in prose.
Step 6: Earn Citations and Brand Mentions
AI models are trained on the web. The more your brand and content appear as cited, referenced, or recommended across authoritative sources, the more likely a model is to treat you as a trusted answer source.
What to Do
- Pursue editorial mentions, not just links. A brand mention without a hyperlink still contributes to entity recognition. Podcast appearances, quoted expert commentary, industry roundups, and conference speaking credits all build the signal.
- Get listed in niche directories and resource pages. These carry topical relevance weight that broad directories do not. An SEO training site listed on a curated list of SEO education resources signals category authority.
- Publish original data or research. Studies, surveys, and benchmark reports earn organic citations because other publishers need a source to reference. One good original data piece can generate dozens of natural citations.
Why It Matters
The citation graph that trained the large language models underlying AI search is built primarily from the web as it existed before the model’s training cutoff. But AI systems also incorporate real-time retrieval in many implementations. Both layers reward well-cited, well-referenced brands.
Step 7: Measure, Iterate, and Stay Current
GEO is not a one-time project. AI search behavior evolves quickly, and the signals that matter today may shift as models update. Build a measurement habit.
What to Track
- AI citation frequency: How often does your brand appear in AI-generated answers for your target prompts? Track this manually or with emerging GEO monitoring tools.
- Zero-click referral traffic: Some AI citations drive direct traffic. Monitor referral sources in your analytics for Perplexity, ChatGPT, and similar platforms.
- Featured Snippet and AI Overview capture rate: Use Google Search Console to track queries where you appear in the “0” position or in AI Overviews. This is a strong proxy for GEO health.
Iteration Cadence
Run your AI visibility audit monthly. Refresh content quarterly to ensure accuracy and to incorporate new questions emerging in your niche. Every time a major AI platform updates its model or retrieval system, re-audit within thirty days.
Frequently Asked Questions
What is the difference between SEO and GEO?
Traditional SEO optimizes for position in a ranked list of blue links. GEO optimizes for inclusion in a generated answer — often at the expense of a click. Both matter. SEO drives the indexing and authority signals that GEO builds on. Think of GEO as the next layer up: once you rank, you optimize to be cited, quoted, or recommended by the AI summarizing the results page.
Does GEO replace traditional SEO?
No. AI Overviews and generative search tools still pull from indexed web content. Strong traditional SEO — technical health, quality backlinks, topical authority — remains the foundation. GEO adds a layer of structured, extractable, entity-rich content on top of that foundation. Sites with weak SEO fundamentals will not perform well in GEO regardless of how well they format their content.
How long does it take to see results from GEO?
It depends on your starting point. If your brand has strong topical authority and existing links, you may see citation improvements within four to eight weeks of restructuring content and adding schema. If you are starting from low authority, expect three to six months before meaningful AI citation frequency builds. Entity recognition, in particular, accrues slowly over time as references accumulate across the web.
Which AI platforms should I prioritize for GEO?
Focus first on Google AI Overviews — it reaches the largest existing search audience. Perplexity is the highest-intent AI search platform and worth tracking separately. ChatGPT's browsing mode matters for branded queries and is growing. Prioritize Google first, then Perplexity, then ChatGPT. All three share common optimization signals: clear structure, strong entity signals, and credible citations.
Terry has 30+ years in software and SEO. He’s the founder of Salterra Digital Services and SEO Spring Training, host of the Roundtable SEO Mastermind, and lead instructor at SEO University — teaching the exact tactics his team uses on client work.
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