Generative Engine Optimization (GEO): The Future of AI in Search

Generative engine optimization (GEO) is quickly emerging as a leading strategy for businesses that want to rank within AI-driven search results. The shift from traditional SEO (search engine optimization), which optimizes onsite content for SERPs (search engine results pages), to AI in marketing using GEO, which optimizes content so it is cited as part of AI search results, is a growing trend among people who want direct answers to their search input without having to click through to different websites.

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What Is Generative Engine Optimization (GEO)?

GEO (generative engine optimization) is an evolving marketing strategy to optimize your onsite content, so generative AI models, such as Google AI, ChatGPT, and Perplexity, pull content from your site and include it in the AI-generated content provided by the AI model. AI models prioritize EEAT (experience, expertise, authoritativeness, trust), well-structured content, and user intent. 

For example, Google AI often places their AI-generated content at the very top of the page, above paid ads and SEO content. The objective of GEO strategies is to optimize the content on your website so that it can be scanned by LLMs (large language models), and listed as a credible source in AI-generated results.  

The Shift to Generative AI Search Engines

People are adapting to how they find answers to their search queries by relying more on AI in search. Instead of inputting a few keywords into the search, they are asking direct questions, such as, “Where can I find reliable used cars for sale near me?” 

The AI output is providing zero-click results, meaning users are not clicking through to websites to find the answers to their questions. To users, AI results provide a conversational feel without requiring users to skim through multiple search results to find the answers they seek. In order for businesses to be seen and encourage users to visit their websites, they need to be listed as one of the top sources in the AI-generated answers. 

How Generative AI Engines Work 

Generative AI works by generating responses by analyzing the user’s input, key terms, the context of the query, and intent. It then uses existing data from website pages, books, and other digital formats to provide an answer. 

Generative AI engines rely on an encoder-decoder framework, and a complex neural network architecture. The query is encoded into numerical vectors to find the required output. It then crawls through vector spaces looking for the relevant data. Once it does, it then decodes the results, converting it back into readable language. 

Foundational models, like ChatGPT, PaLM, and Gemini, were initially trained using large datasets from websites, text sources, books, and image sources, along with LLMs. Further training involved users inputting questions, allowing the AI engines to understand the context better, and generate appropriate responses. 

To generate responses, generative AI employs a complex process that involves advanced neural network transformer architectures and large datasets. AI uses tokenization to break down data obtained from LLMs, allowing it to consider the entire query and automatically assign weights to various words based on their relevance in the context of the query. 

Next, it gathers the relevant data and generates a response using the various knowledge and patterns it learned during training. The process also involves looking for and learning new content that fits with the initial query, and adding this to the appropriate data vectors.

Some of the more popular generative AI engines include:

• Bard: This is Google’s conversational AI, now known as Gemini. It is a chatbot designed to generate text, translate languages, and provide information in a conversational tone.  
• ChatGPT: ChatGPT is another conversational AI, developed by OpenAI, that generates answers to questions, creates text, and assists with tasks, such as summarization and coding. 
• DALL-E: DALL-E is an AI model, also developed by OpenAI, that generates images based on the user-inputed text.   

What Is the Difference Between SEO and GEO?

SEO and GEO have several similarities, including:

• Both are designed to help people find useful and helpful information.
• Both require high-quality content.
• Both use EEAT as part of the algorithms to find relevant search results.
• Both require the use of relevant keywords and search terms.

Some of the differences between SEO and GEO are:

• GEO performance is measured by the frequency of AI usage.
• SEO aims to improve ranking on SERPs in organic search results.
• GEO focuses on ensuring content is selected by generative AI engines for synthesized responses.
• SEO displays ranked organic links based on their relevance.
• GEO provides real-time responses with a list of relevant sources.
• SEO requires click-throughs to the website.
• GEO provides direct answers, resulting in zero-click throughs.
• SEO performance is measured based on site traffic and conversions.
• GEO performance is measured by the frequency of AI usage.

Benefits of Generative Engine Optimization (GEO)

Implementing GEO as part of your digital marketing strategy provides several benefits, including:

• Enhances user experiences: GEO responses are tailored to meet the specific preferences and needs of users, resulting in relevant and quality content for seamless interactions.
• Expands visibility and reach: Optimizing content for GEO enables you to expand your reach beyond search engines, and be featured in results on platforms, like ChatGPT and PaLM. 
• Expands brand visibility: GEO helps expand the awareness and visibility of your brand.
• Creates a competitive advantage: As people continue to increase their reliance on AI-powered search results, businesses can gain a competitive advantage by using GEO.
• Enhances trust and credibility: GEO sources content for their responses from trusted and credible sources. 
• Future-proofing content strategy: GEO helps complement your SEO strategies to ensure long-term relevance and visibility. 
• Help you better understand user intent: GEO can help you better understand user intent, so you can create content that fits their needs. 
• Improves voice search results: Since conversation AI relies on natural language, GEO can help improve the content on your pages to match a conversational tone, and show up in GEO responses and rank higher in SERPs. 
• Helps you to adapt beyond traditional ranking metrics: Traditional metrics focus on click-throughs and conversions, whereas GEO focuses on providing trustworthy, credible, and authoritative citations. As a result, you open the door to new key performance indicators (KPIs) from AI-generated content, including: user engagement, brand mentions, referral traffic, and citation rate. 

How To Optimize for GEO and SEO

Businesses need to balance their GEO and SEO strategies to maximize their visibility across both traditional and generative search engines. Both GEO and SEO services help support one another through the creation of high-quality content and ensure your business not only appears higher on SERPs, but is also cited in AI-generated answers. 

How To Optimize for Generative AI

Optimizing for generative AI requires that your content is readable by AI algorithms by doing the following:

• Content should be scannable: Use clear headings and subheadings throughout the content. Paragraphs should not exceed four lines, and incorporate numbered lists or bullet points wherever relevant. 
• Clear and concise content: The onsite content should be clear and concise by providing direct answers with key information at the top of the page.
• Utilize a table of contents when appropriate: Adding a table of contents improves optimization for AI.
• Include FAQ sections when appropriate: Add FAQ sections with direct questions and short, concise answers to appropriate pages. 
• Use descriptive headings and subheadings: Ensure your headings and subheadings are content-specific based on the content below them.  
• Focus on high-quality content: Just like SEO optimization, you need to ensure your content is well-researched, provides value, and is accurate and authoritative. It should not be spammy. 
• Use reliable citations and sources: AI favors links to reputable sources to support your content. 
• Write in a conversational tone: AI models look for content that has a conversational tone that fits with human language and speaking patterns. 
• Use long-tail keywords: Long-tail keywords can help answer more specific types of queries and questions asked by users. 
• Avoid keyword stuffing: Similar to SEO optimization, keyword stuffing should be avoided. 
• Ensure keywords flow naturally: Keywords should fit naturally within the content, just like they are for SEO optimization. 
• Optimize your onsite content for mobile-friendliness and speed: Al search algorithms will prioritize mobile-friendly and fast-loading pages. 
• Update content regularly: Another SEO optimization strategy that GEO also uses is looking for fresh content and regular page updates. 
• Include a schema markup for each page: Schema markups provide more context to AI search engines about your content. Additionally, verifying your schema includes speakable structured data. 

How To Optimize for Search Engines

Optimizing content for search engines focuses on creating high-quality, mobile-friendly user content, which requires the following: 

• Keyword research: You need to identify the relevant keywords users would search for that are related to your products or services. These keywords should be incorporated into your content and fit naturally. 
• Title tags and meta descriptions: Every page should have a clear and concise title tag and meta description that reflect the content on the page. 
• Authoritative backlinks: Your onsite content should have backlinks to authoritative websites. 
• Avoid keyword stuffing: Overusing keywords or stuffing them into content will result in lower SERP rankings. 
• Regularly update your content: Making regular updates to your content ensures that when search engine bots are scanning your content, your SERP rankings do not fall. 
• Internal linking: Use internal linking to relevant pages on your site to further build credibility. 
• Use headings and subheadings: The use of headings and subheadings makes it easier for search bots to crawl your pages. 
• Quick load times: Your pages should load quickly across multiple devices. 

How To Measure GEO and SEO Performance

To measure GEO and SEO performance, you need to use metrics specific to both GEO and traditional SEO. 

Some of the GEO metrics used include:

• Frequency of selection by generative engines.
• Engagement with AI-generated answers.
• Authority score in AI contexts.
• AI-driven referral traffic.
• Site engagement from AI platforms.
• Brand mentions in AI-generated answers.

Traditional SEO metrics used to measure performance are:

• Organic traffic: The amount of traffic visiting your site from search engines.
• Click-through rates (CTRs): How often users click on your website link in search results.
• Domain authority: How your website is viewed by search engines in their overall trustworthiness and authority.
• SERP rankings: Where your website shows up in search results.
• Conversion rate: How often organic traffic converts into a sale, phone call, or other desired action.
• Backlinks: The quality and number of websites linked to your website.

Tools for Performance Tracking

There are various tools available to monitor performance tracking. Google Analytics is one of the most popular SEO performance tracking tools used since it provides insight into several metrics, including organic search traffic, content performance, user behaviors, and audience demographics. 

Even though GEO monitoring is fairly new, there are several tools you can use for performance tracking, like:

• Rankscale.ai
• Brandrank.ai
• Otterly.ai
• Writesonic AI Traffic Analytics
• Peec.ai

These tools help with different metrics, such as the number of times your website was listed in the citations, AI search brand mentions, detailed AI crawler tracking, competitor benchmarking, and multi-platform performance tracking. 

It is important to use multiple tools for SEO and GEO performance tracking to get a clear picture of how well your brand is visible, and to identify areas that still need improvement. Additionally, you need to monitor user behavior changes due to generative AI adoption. 

Some effective ways to do this are:

• Define clear objectives and goals with relevant KPIs.
• Track interactions and feedback from users.
• Implement effective performance monitoring.
• Make continuous improvements.

Optimization Strategies for Popular Large Language Models (LLMs)

LLM optimization is adjusting your online content so that LLMs can more easily find it to analyze it, and add it to vector spaces used by generative AI. Your optimization goal is to have multiple models recognize your brand and content, allowing it to be included in their responses to user queries. 

Some strategies you should use for content optimization are:

• Use Google’s Knowledge Graph: You need to verify your business is included in the Knowledge Graph, as this is a knowledge base many LLMs and AI models use to generate results. 
• Continue to use SEO: Many aspects of SEO overlap with GEO, so it is vital to continue to use SEO best practices and strategies. 
• Use press releases when applicable: Press releases are another way to increase your visibility with LLMs. 
• Use entities: Make sure to use your business name, brand, locations, product lines, services, and people associated with your business where appropriate on your content pages. 
• Answers questions users ask AI: Ensure your content answers the questions people would ask about your business, brands, products, or services. For example, “What is generative engine optimization?” 
• Encourage user-generated reviews: LLMs also gather information from user-generated reviews to build authority and trust. 

Other specific optimization tips for LLMs, like GPT-4, PaLM, and Gemini, are:

• Craft prompts that align with LLM comprehensive patterns.
• Provide structured data inputs, such as tables, graphs, or bullet points, for better synthesis.
• Enhance factual accuracy and context relevance of your content to improve model-generated output.
• Leverage APIs, like OpenAI API, to test your content compatibility with LLMs.
• Integrate your proprietary data into LLMs using tools, like Elasticsearch Relevance Engine™ or similar frameworks.

Future Implications of GEO

GEO will be a significant component of digital marketing in the coming years. According to MarkNtel Advisors, the global generative AI market was valued around $28.9 billion in 2024, and is expected to grow to $142.7 billion by 2030, which is a 31.2% increase. What this means for you is that you need to start adapting your content for GEO now; otherwise, you will be playing “catch-up” later. 

Some indicators to support the increase in generative AI are:

• Users are now starting their searches on AI platforms for information, product research, and purchases.
• ChatGPT has over 180.5 million monthly active users, indicating a shift toward increased AI search.
• 79% of consumers are expected to use AI-enhanced search within the next year.

There will also be an increased reliance on GEO automation tools to determine how well your content is optimized for AI. This is not to say automation will replace human-generated content, as human-generated content will still be essential to ensure quality, authoritative, and trustworthy content. 

How Does Levy Online Approach Generative Engine Optimization? 

Adopting GEO strategies now helps future-proof your digital marketing efforts as the use of AI-driven search continues to increase. It can also help provide you with a competitive advantage, help you reach your target audience, increase your brand credibility and authority, and improve your location performance score in local GEO. 

At Levy Online, we approach generative engine optimization with results-driven approaches, with a foundation in traditional SEO principles. We take the time to understand your business, digital marketing goals, and target audience, creating a personalized strategy tailored to your needs. 

FAQ

Sources: 

Marketing Insights & Analysis: Global Generative AI Market (2025-2030). (2024).

Reid, E. (2025). AI in Search: Going Beyond Information to Intelligence.

Reid, E. (2024). Generative AI in Search: Let Google Do the Searching for You.