Generative Engine Optimization (GEO): Get your content chosen by AI
By
Product Marketing
August 16, 2025
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23 minute read
For the better part of two decades, B2B marketing has been anchored by a singular truth: if you want to be found, you must master Search Engine Optimization (SEO). We built careers on understanding the intricate dance of keywords and backlinks required to please Google’s algorithms.
But the ground, once firm, is now in a state of seismic flux. The familiar landscape of search results is being rewritten in real-time by artificial intelligence, demanding a fundamental evolution in our thinking.
The age of simply “searching” is giving way to an era of “synthesis.” Generative AI has transformed search engines into answer engines. This shift requires us to move beyond SEO into two new, critical disciplines: Generative Engine Optimization (GEO) and the broader LLM Engine Optimization (LEO).
This is not a theoretical, future-state discussion; it’s the new operational reality for B2B technology brands.
Generative Engine Optimization (GEO) is the practice of optimizing your digital content so that AI models can understand, cite, and summarize it in response to user prompts. GEO ensures your content feeds AI-generated responses in tools like SGE, Perplexity, and ChatGPT.
If SEO gets you indexed, GEO gets you included in the AI-generated answer.
Think of it like this:
Traditional SEO was about getting your website to the top of a list of links, hoping someone would click on yours.
GEO is about making your website’s information so clear and trustworthy that when someone asks an AI (like Google’s AI Overviews or ChatGPT) a question, the AI uses your information to create the answer and ideally mentions you as the source.
What is LLM Engine Optimization (LEO)?
LLM Engine Optimization (LEO) is the holistic discipline of making your brand’s knowledge and data optimized for discovery and accurate representation across the entire ecosystem of Large Language Models (LLMs).
This includes search engines, but also extends to LEO, ensuring that the public librarian, the private corporate librarian (such as an AI inside a large company), and the specialist researcher (like an AI tool for finance or technology) all have the same, correct information about you.
LEO ensures your brand’s voice is consistent and authoritative, wherever an AI-powered conversation occurs, enterprise chatbots, AI-powered APIs, and proprietary AI research tools.
Think of it as the next step up from GEO:
GEO is focused on public librarians (similar to Google Search or Bing). You want them to give the public the right facts about you.
Overall understanding:
SEO: Get found by search engines – Human-first
GEO: Get cited by generative AI – Machine-first
LEO: Be understood by all AI systems – Model-first
Why organic discovery is changing, and what it means for visibility
To grasp the urgency of this shift, we must first understand the mechanics of the disruption. This isn’t a simple algorithm update; it’s a complete change in the user experience, driven by Large Language Models (LLMs).
The evolution from search engine to answer engine is driven by a desire to provide more direct, efficient user experiences.
At the forefront is Google’s Search Generative Experience (SGE). When a user enters a complex query typical of B2B research, SGE generates a comprehensive, narrative “AI Snapshot” at the very top of the page.
The prime real estate you once fought for with SEO is now occupied by an AI. Early data on SGE’s impact shows that for some queries, organic clicks can drop by 34.5% as users get their answers without needing to scroll (eMarketer).
This matters because B2B buyers are actively seeking more efficient ways to get answers. A staggering 77% of B2B buyers reported that their latest purchase was very complex or difficult, a clear sign that buyers are seeking more efficient ways to get answers (Gartner, “Smarter GTM for a Smarter B2B Buyer”).
Generative AI provides that efficiency.
It can synthesize product reviews, technical documentation, and pricing pages into a single paragraph. If your content is unstructured, locked in PDFs, or full of ambiguous marketing jargon, the AI will ignore it in favor of a competitor’s clearer, more structured content.
SEO alone does not account for this deep level of machine comprehension.
Similarities and Differences of GEO and SEO
GEO is an evolution of SEO, not a replacement. The two are intrinsically linked but have distinct objectives and tactics.
Similarities
Foundation in Quality Content: Both disciplines depend on high-quality, relevant, and well-researched content that addresses a user’s intent.
Importance of E-E-A-T: Google’s principle of Experience, Expertise, Authoritativeness, and Trustworthiness is paramount for both. An AI model is explicitly trained to look for these signals to verify information.
Technical Health: A technically sound website (fast load times, mobile-friendliness, secure protocols) is crucial for both crawlers and AI models to access your content efficiently.
Understanding User Intent: At their core, both SEO and GEO are about deeply understanding the questions your audience is asking and providing the best possible answer.
Differences: GEO vs SEO
Primary Goal
SEO: To achieve the highest possible ranking on the Search Engine Results Page (SERP).
GEO: To be accurately included and cited in the AI-generated answer (synthesis and inclusion).
Focus
SEO: A focus on matching and ranking for specific keywords.
GEO: A focus on demonstrating deep knowledge about specific entities and concepts and their relationships.
Audience
SEO: A “Human-First” approach where content is written for a human and optimized for a crawler.
GEO: A “Machine-First” approach where content is structured for an AI, which then synthesizes it for a human.
Key Tactic
SEO: Acquiring backlinks from other sites as a primary signal of authority.
GEO: Using Structured Data (Schema) to provide explicit, machine-readable context as the primary signal of clarity.
Success Metric
SEO: Click-Through Rate (CTR)—the percentage of users who click your link.
GEO: Share of Synthesis—the frequency and accuracy of your inclusion in AI-generated answers.
Why GEO matters for B2B marketers
B2B Buyers Now Use AI as a Trusted Research Assistant
Before ever speaking to a sales team, potential customers use AI tools like Gemini, Grok, and Google’s AI Overviews to make important business decisions. They rely on these tools to:
Research products and vendors.
Compare different solutions and features.
Create a shortlist of companies to contact.
This new reality means buyers expect instant, summarized answers backed by expert-level information.
If your brand doesn’t appear in these AI-generated results, you are invisible during the earliest, most critical stages of their buying journey.
GEO ensures your brand shows up in these answers.
The impact of this shift is amplified in the B2B technology sector for several key reasons:
Complex Buying Decisions: B2B tech purchases involve high stakes, multiple stakeholders, and extensive research. Buyers ask complex, multi-part questions—the exact kind of queries that trigger AI-generated snapshots.
Information Density: Your buyers are technical and demand deep, credible information. GEO allows you to structure that dense information (e.g., spec sheets, integration guides, security protocols) so an AI can accurately represent it.
The Rise of AI in the Workplace: Your target audience is already using AI. A 2024 report revealed that 72% of executives are using generative AI for their work, indicating that your prospects are already comfortable turning to AI for research and answers (Deloitte, “The State of Generative AI in the Enterprise”). Your marketing must meet them on this new ground.
Evolving Search Landscape: As AI-powered search technologies like ChatGPT, Gemini, and Google’s AI Overviews become more prevalent, GEO is crucial for maintaining visibility and competitiveness.
The Benefits of GEO
Increased Visibility in AI Snapshots: The primary benefit is earning a place in the valuable, top-of-page AI-generated answers.
Enhanced Brand Authority: Being cited as a source by an AI positions your brand as a trusted authority in your field.
Improved Lead Quality: By providing clear, accurate information upfront, you pre-qualify prospects.
Those who do click through are often better informed and have higher intent.
Future-Proofs Your Content: Building structured, entity-focused content today makes your digital assets resilient and valuable for future AI developments.
Competitive Differentiation: While your competitors are still focused solely on traditional rankings, GEO offers a significant first-mover advantage.
Better Data for Product Development: Analyzing the questions users ask AI can provide invaluable insights into customer needs and pain points.
Consistent Cross-Platform Messaging (LEO): A GEO/LEO approach ensures your company’s information is presented consistently, whether it appears in Google SGE, a Microsoft Teams Copilot, or a custom internal chatbot.
Direct Engagement: GEO ensures that your brand is featured in AI-generated results when users search for relevant information, potentially leading to direct engagement with potential customers.
Brand Consistency: GEO helps maintain brand consistency and messaging across different AI platforms, ensuring that AI-generated responses accurately reflect your brand’s identity.
How AI ‘Reads’ Your Content—What It Notices, What It Ignores
Generative AI doesn’t read like humans—it parses content using large language models (LLMs) to identify entities and understand their relationships. Unlike traditional search engines that crawl pages for keywords and backlinks, AI focuses on meaning and structure.
For example, if your product is QuantumLeap CRM, the AI extracts:
Entity: QuantumLeap CRM
Attributes: SaaS platform, tiered pricing
Relationships: Integrates with Microsoft Outlook, competes with Salesforce
Clear definitions, natural language: When you explicitly define a term—”A Zero-Trust Network Architecture (ZTNA) is…”—the AI recognizes this as a high-value piece of information.
Data and Attributions: It actively looks for data points and the sources that back them up to verify claims. Pay attention to verified sources with outbound links, add author and publish date metadata.
Contextual Links: It analyzes both internal and external links to understand how a piece of content fits into the broader knowledge landscape.
AI Ignores:
Keyword Stuffing: Overloading content with keywords, an old SEO tactic, is a negative signal indicating low-quality, unhelpful content.
Ambiguous Language: Vague marketing claims like “world-class” or “revolutionary” are meaningless to an AI and are discarded. So is fluff or jargon-heavy content
Images Without Alt Text: An AI cannot see an image; it relies on descriptive alt text to understand its content and context.
Unstructured Data: Information buried in a complex infographic or a poorly formatted PDF is often invisible.
Broken Links and Outdated Data: Links that no longer work or data that is outdated diminish the credibility of your content and signal to AI that your material may not be trustworthy or current.
Integrating GEO with SEO (Strategies)
A winning strategy does not choose between SEO and GEO; it integrates them.
Conduct Keyword Research, Then Map to Entities: Continue your traditional keyword research to understand user demand. Then, take the extra step of identifying the core entities (products, people, concepts) within those keywords and build your content strategy around them.
Elevate On-Page SEO with Structured Data: After optimizing your title tags, meta descriptions, and body copy for SEO, implement robust TechArticle, FAQPage, and SoftwareApplication Schema to make that same content perfectly legible to an AI.
Use Link Building for Authority Signals: Continue building high-quality backlinks. For GEO, the context of those links is even more critical. A link from a highly authoritative, topically relevant source serves as a powerful E-E-A-T signal that AI models will recognize.
Amplify Pillar Pages with GEO Tactics: Your SEO-driven pillar pages and topic clusters are the perfect foundation for GEO. Enhance them by adding structured FAQ sections, clear definitions of terms, and citing verifiable data to make them prime sources for AI synthesis.
How to write new machine-discoverable content for GEO?
Transitioning to a GEO-centric strategy requires a deliberate, multi-faceted approach. We have structured this into five core pillars that provide a roadmap for B2B technology brands to build a competitive advantage.
Pillar 1: Foundational Authority & E-E-A-T on Steroids
Google’s concept of E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) has always been important for SEO, but for GEO, it is the absolute bedrock. Generative AI models are prone to “hallucinations,” or making up information. To combat this, their algorithms are being aggressively trained to identify and prioritize content from sources that demonstrate unimpeachable credibility.
Your organization’s overall digital presence must scream trustworthiness.
Demonstrate First-Hand Experience: Go beyond generic statements. Showcase a real-world application. For a cybersecurity firm, this means publishing detailed case studies of incident response engagements or articles authored by engineers who have deployed the solutions they write about.
Showcase Your Experts: The expertise of your people is your greatest GEO asset. Author bios should not be an afterthought; they should be detailed pages linking to their professional profiles (e.g., LinkedIn), academic publications, or conference speaking engagements. Use the Person Schema to mark up your authors, connecting them explicitly to your Organization.
Establish Verifiable Authority: Authority is about your recognized position in the industry. This includes mentions in reputable trade publications, reviews on platforms like Gartner Peer Insights, and partnerships with other established technology leaders. These third-party signals serve as powerful validation for an AI model.
Build Unquestionable Trust: Trust is built on transparency. Your website needs easily accessible “About Us” and “Contact” pages. Publish your original research and data, and make your methodologies clear. If you make a claim, back it up with a link to the source, whether it’s your data or a respected third-party report.
For an AI to use your content, it must first understand it with zero ambiguity. This is where technical precision becomes a competitive differentiator. Your content must be structured not just for human eyes, but for machine consumption.
The most powerful tool in your arsenal is Schema markup.
This is a vocabulary of structured data that you add to your website’s code to tell engines exactly what your content is, not just what it says.
Go Beyond Basic Schema: Every B2B tech marketer should be using Article, Breadcrumb, and Organization schema. To lead with GEO, you need to implement more specific types:
TechArticle: This schema is more specific than Article and can be used to denote technical content, signaling its nature to the engine.
SoftwareApplication: For your product pages, this is non-negotiable. Use it to detail your application category (designApplication, securityApplication), features (featureList), and compatibility (operatingSystem). This allows an AI to perform accurate comparisons.
HowTo & FAQPage: Structure your tutorials and frequently asked questions with this schema. It directly maps to the conversational nature of generative search, making it incredibly easy for an AI to pull your step-by-step instructions or answers into a snapshot.
Here is an example of how you might nest schemas to build a rich context.
An article is written by an expert who works for your company:
The above code block explicitly tells an AI: “This technical article was written by a named expert, whose credentials you can verify, and published by this specific organization.”
This is the language of trust for a machine.
Pillar 3: Shifting from Keywords to an Entity-Centric Content Strategy
AI models think in terms of entities and concepts, not just strings of keywords.
An entity is a single, well-defined thing, like a company (“Microsoft”), a software category (“Customer Relationship Management”), a technology (“Kubernetes”), or a person (“Satya Nadella”). Your content needs to demonstrate a deep understanding of the key entities in your domain and the relationships between them.
Define and Map Your Knowledge Graph: Start by identifying the core entities that define your market. What are the key products, technologies, problems, and competitors? Your goal is to build a content ecosystem that comprehensively covers these entities, establishing your site as a “knowledge hub.”
Build Topic Clusters Around Entities: Structure your content with central pillar pages for broad entities (e.g., “Data Observability”) and a web of “cluster” content that dives deep into related sub-entities (“Data Lineage,” “Schema Drift,” “Anomaly Detection in Time-Series Data”). This internal linking structure signals a comprehensive understanding of the topic to AI models.
Practice Disambiguation: Be relentlessly clear. When you mention a term with multiple meanings, provide the context to disambiguate it. For example, when writing about “python” in a data science context, make it clear you are referring to the programming language, not the reptile. This precision is vital for correct machine interpretation.
Start with the Entity, Not the Keyword: Before drafting a single word, define the central entity your content is about. This could be a product, a problem, a technology, or a concept. Your goal is to create a clear, structured resource that maps directly to what a B2B buyer—and by extension, an AI engine—wants to understand.
Write for Questions, Not Keywords: Identify the top 5–10 questions your audience is likely to ask about that entity. These should reflect real buyer intent, such as “How does this technology integrate with existing systems?” or “What are the security risks of this solution?” Use these questions as your subheadings to align your content with the natural language patterns of generative search.
Structure Like a Machine Thinks: Use logical heading hierarchies (H1, H2, H3) to break down content. Prioritize skimmability—short paragraphs, bullet lists, and clear formatting help both humans and machines parse your message quickly.
Use Precise, Accessible Language: Avoid marketing fluff and vague superlatives. Define technical terms explicitly and clearly. If you must use industry jargon, explain it in plain terms. Clarity isn’t just a readability benefit—it’s a trust signal for generative engines.
Pillar 4: Mastering Conversational Relevance and Prompt Optimization
The final pillar is about aligning your content with the new user behavior: conversation.
B2B buyers are asking AI detailed, multi-part questions. Your content needs to contain the answers in a format that is easy for the AI to parse and present.
Think in Questions and Answers: Structure key sections of your content to directly answer the natural language questions your buyers are asking. Turn your headings into questions. Use FAQ sections—marked up with FAQPage schema—to address common objections, feature comparisons, and implementation queries.
Optimize for “Prompts,” Not Just Keywords: Use tools like AlsoAsked and AnswerThePublic, but view the results through the lens of a user prompting an AI. A keyword might be “cloud cost management,” but a prompt would be “what are the best strategies for reducing AWS spend without impacting performance?”
Your content should be optimized to directly address the latter. This is the essence of achieving Prompt-Market Fit.
Embrace Comparative and Explanatory Content: A significant portion of B2B research involves comparison. Create content that directly compares solutions, explains complex technical concepts in simple terms, and defines industry jargon. This is high-value fuel for generative engines looking to provide comprehensive answers.
Interlink for Context: Create meaningful connections between pages. Link to other relevant internal content to help AI engines understand your domain expertise and the broader context of your knowledge.
Pillar 5: Balance Machine Logic with Human Warmth
Finally, remember the human reader.
While your structure should support machine comprehension, your tone and narrative should still feel natural, engaging, and trustworthy.
GEO-optimized content doesn’t have to sound robotic—it just has to be clear.
How to Audit and Upgrade Existing Content for GEO
Your existing content library is a valuable asset. A systematic audit can elevate your most important pieces to be GEO-ready.
Prioritize by Performance and Relevance: Start with your highest-traffic, most strategic content.
Perform a Clarity Check: Is the core entity of the page immediately obvious? Rewrite for precision and remove ambiguous marketing jargon.
Conduct a Structure Audit: Use Google’s Rich Results Test to analyze your current Schema markup and identify opportunities to add more specific types (e.g., adding FAQPage schema to a Q&A section).
Execute a Trust Audit: Are all claims backed up by a citation? Is the data current? Add or enhance author bios to signal expertise.
Identify Synthesis Gaps: Read your article and ask, “What question might a user ask next?” If your content doesn’t answer it, the AI will look elsewhere. Fill these gaps to make your content more comprehensive. Use tools like Schema.org, ChatGPT, or Perplexity to test how your content appears in AI tools.
Measuring Success in the Era of GEO
As our tactics evolve, so must our metrics. Relying solely on organic traffic and SERP ranking will give you an incomplete picture of your performance in an AI-driven world.
B2B marketers must begin tracking a new set of KPIs:
Brand & Source Mentions in AI Snapshots: Are you being cited as a source in SGE and other answer engines? Tools are emerging to track this, but for now, it requires manual, qualitative analysis of your most important SERPs.
Accuracy of AI-Generated Summaries: When an AI does cite or summarize your content, is the information correct and favorable?
Incorrect summaries could indicate that your content lacks the clarity and structure needed for machine interpretation.
Share of Voice within Answer Engines: Instead of just share of voice in traditional search, analyze how frequently your brand appears as a trusted source for the key concepts and questions in your industry.
Traffic from “Cited Sources”: Monitor your analytics for referral traffic from generative AI platforms as they improve their source attribution.
Checklist: Signs of GEO-Optimized Content You Can Apply Right Now
The main topic (entity) is clearly stated in the H1 title and introduction.
Subheadings (H2, H3) are phrased as the questions a B2B buyer would ask.
Key technical terms and concepts are explicitly defined in the text.
All data points or statistics are hyperlinked to their original, credible source.
The page uses specific Schema markup (e.g., FAQPage, TechArticle) that you can verify with Google’s Rich Results Test.
Author information is visible and links to an expert bio, signaling E-E-A-T.
The content directly compares features, solutions, or concepts where applicable.
Acronyms are spelled out upon first use (e.g., “Customer Relationship Management (CRM)”).
What GEO Means for Paid Search
The changes in organic discovery are shifting paid media strategies, too. As AI snapshots occupy the top of the SERP, the placement and performance of traditional search ads will change.
Strategies must adapt:
Ads within AI Snapshots: Google is already experimenting with placing ads directly within the AI-generated answers. This creates a new, highly valuable ad placement that will require different bidding strategies and ad copy.
From Keywords to Concepts: Targeting will likely move beyond simple keywords to target broader concepts or user intents that are likely to generate an AI snapshot.
Performance Max (PMax) and AI: Google’s PMax campaigns are already heavily AI-driven. Success in a GEO world will mean providing these campaigns with high-quality assets (text, images, audience signals) that the AI can use to effectively place ads across Google’s entire inventory, including in generative results
Branded Search Is the New Battleground: Most users validate AI recommendations with branded searches. Protect and optimize branded keywords.
Prompt-Based Advertising Is Emerging: Platforms like Perplexity AI and OpenAI are experimenting with sponsored prompts, where advertisers appear in response to specific user queries. This trend points toward a future where prompts—not just keywords—become the primary unit of ad targeting. Marketers should start preparing for this shift by developing prompt-aligned content and messaging frameworks.
New Metrics to Track: In the GEO era, performance measurement must expand beyond traditional CTRs. Key emerging metrics include:
Brand lift from AI mentions
Increased branded search volume following AI exposure
Inclusion in AI Overviews, snapshots, and answer engines
Tips to Future-Proof Your B2B Content for Long-Term Visibility
Own Your Niche: Focus on becoming the undisputed, authoritative source for a specific, well-defined niche. It is better to be the #1 citable source for “AI-driven network monitoring for fintech” than the #100 source for “IT solutions.”
Create Original Data: Commission surveys, conduct research, and analyze your proprietary data. Original research is one of the most valuable assets for GEO, as it is, by definition, a primary source.
Build a Multimedia Asset Library: Develop high-quality images, videos, and diagrams with clean, descriptive metadata (alt text, titles, descriptions). AI is becoming increasingly multimodal, and structured media is essential.
Embrace Continuous Learning: The pace of change is accelerating. Dedicate resources to staying informed on the evolution of generative AI and be prepared to experiment and adapt your strategy quarterly, not yearly.
Key Takeaways
Search isn’t going away. But how people and machines interact with your content is evolving fast.
Marketers who embrace GEO will:
Gain more organic reach through AI tools
Build stronger brand visibility
Prepare for new paid formats and evolving user journeys
Start now. Audit your content. Build for discovery. And become a trusted voice, by machines and humans alike.
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