GEO vs. SEO: The truth behind modern search

What is GEO?

What do AEO, AISO, LLMO, GAIO, and GEO have in common? Besides that they are all another form of SEO, they essentially mean the same thing: they all refer to the process of optimizing content for AI-driven search. 

• Answer Engine Optimization (AEO)
• AI Search Optimization (AISO)
• Generative AI Optimization (GAIO)
• Generative Engine Optimization (GEO) 
• LLM Optimization (LLMO)

Recent Google Trend data (included below) illuminate that “GEO” is gaining ground as the preferred term, but all of these new digital marketing acronyms are being used somewhat interchangeably. GEO is the process of optimizing digital content to enhance its visibility in results generated by AI-driven search engines, such as Google’s AI Overviews and AI Mode, Gemini, ChatGPT, Perplexity, and Copilot.

AI optimization terms trends (Google Trends)

But what is the relationship between GEO and SEO? Let’s unpack it.

How does GEO differ from SEO?

Both GEO and SEO share the overarching goal of providing the most accurate and relevant result that aligns to the intent of a query. However, they diverge in their focus, mechanisms, and desired outcomes. 

• GEO’s primary goal is to be part of AI’s output, regardless of a click. This means ensuring content is understood, processed, and utilized by generative AI models (like LLMs) to be included in AI-generated content. The AI-generated content can come in the form of answers, summaries, conversational responses, and citations (links to web content) 
• SEO’s primary goal is to achieve high rankings in the organic search engine results pages (SERPs) of traditional search engines, like Google’s. The ultimate aim with SEO is to establish strong visibility with relevant content that aligns to user intent, driving clicks from these search listings to a website

What tactics differ between GEO and SEO?

Interestingly, the tactics used for effective GEO are not too dissimilar from SEO. SEO relies on creating high-quality, comprehensive, authoritative, and contextually rich content that directly answers potential user questions or provides detailed information on a topic, which is the exact same for GEO. Both GEO and SEO focus more on the semantic meaning and overall helpfulness of the content to accurately summarize (via AI) or reference (via search results).

Why might this be? The engines behind producing a Google traditional organic result or an AI Overview both use advanced algorithms and machine learning systems, like embeddings and vector similarity, to identify which content best matches the intent of the query. The information collected is then fed into a set of results for the SERP or for the data used when generating an AI response. In fact, depending on the study, at least seven of the top organic results are also cited by AI Overviews, which means these two disparate engines are identifying almost the same content, they’re just being used in different ways.

If brands are executing relevancy-driven content strategies through SEO, then it’s more than likely that many of the tactics are the same for GEO. However, there are some differences worth noting, specifically around page and copy structure, and how we optimize content. For example, GEO relies more on aligning the query to a passage (paragraph) within content. Consider this passage-level optimization for inclusion in an AI answer. This means a brand’s content needs to be:

1. More explicit at answering questions based on the query within paragraph (passage) form
2. Keyword selection needs to include more semantically related keywords naturally woven into copy. This copy should contain high semantic density specific for passage matching, and if warranted, should be communicated in formats such as FAQs, listicle blocks, short tables, and citations

While these are specific recommendations for GEO, they are the same recommendations we would suggest for SEO, further highlighting that following best practices for both GEO and SEO will help content have the best opportunity to be visible regardless of search method. 

While there are similarities in tactical work that can be completed for SEO and GEO, it’s important to note that even if your SEO performs well, it doesn’t mean your GEO will. Remember: GEO optimizes for AI models that generate direct answers. Content is often not optimized for informational question-based queries, meaning that content developed for SEO might need to be updated for GEO. In this new landscape, assume there are content gaps that will require attention. 

Where can marketers begin with executing GEO?

Assuming your brand’s SEO foundation is in order, we recommend marketers begin GEO execution by:

1. Identifying platforms to focus efforts: Research and understand the AI search landscape relevant to your vertical, including which platforms should be considered (such as Google’s AI Overviews, ChatGPT, Perplexity, Gemini, Copilot, etc.). CM recommends starting with AI Overviews as Google has the largest market share of users executing searches.
2. Collecting topics and phrases: Within your collected engine set, identify brand and nonbrand topics to focus on. Collect and search on topically related questions and search terms that your target audience would likely use when looking for information on the products and services you offer. Enter them into the selected platforms to determine if they are the phases worth targeting. 
3. Executing a performance and gap analysis: Analyze the AI-generated responses, observing how the AI models answer those queries. What information do they include? What sources do they cite (if any)? What is the format and tone of the answers? Are your competitors or other relevant entities being mentioned? Next, determine where your brand and nonbrand content is visible (or absent) in these AI responses. Identify the types of questions the AI handles well and where there might be opportunities to provide more comprehensive or specific information that the AI could utilize.
4. Optimizing or creating content: Based on gaps, focus on optimizing existing content or creating new content for topics within identified opportunities and gaps in previous steps. Prioritize content that directly addresses the topic and associated questions. Write or optimize content using common SEO tactics (utilizing specific and semantically related keywords). However, the structure of your content should be optimized for passage selection by the AI systems, meaning the content should directly answer and align to the intent or question of the query. One way to think about it is “one block = one intent = one retrievable unit.”
5. Measuring and repeating: Regularly measure performance and repeat previous steps with new topics.

Final notes for marketers

Generative AI search has been available to consumers for over two years, with the release of ChatGPT in November 2022 and Google’s AI Overview and Gemini in May 2023. Yet, many organizations and marketers still think this is something new and shiny.

As machine learning and generative AI advances, the algorithms of old will likely be replaced by these new systems. Steps toward this future are already in motion as the engine behind Google’s traditional search results identifies almost the same content as the AI Overview result. If Google simply swapped its AI algorithm with its standard algorithm, would anyone know the difference? You may not, but the performance of your content might change. For this reason alone, CM recommends coupling GEO efforts alongside your SEO efforts, even though the tactics executed will still be called SEO in the end.