GEO vs SEO: differences, similarities, and how they work together

What is the difference between GEO and SEO?

As mentioned, the short answer is that SEO (search engine optimization) is meant to give you a better position in the results list on Google or Bing, while GEO (Generative Engine Optimization) is meant to get you a mention in search engines' AI-generated answers.

SEO revolves around your position in the search results and how it develops over time. As a company, you want your link to rank highly when someone searches, and for that person to click through to your page. GEO instead focuses on getting your brand mentioned (the company name is included) or cited (the company is referenced with a link) in AI-generated answers. There, the customer gets the answer directly in the interface, and your content is the source the answer is built on. A deeper look at the concept is available in our guide on what GEO is.

Take a customer looking for an ERP system. In Google's search box, the customer types "ERP system small business" and is met with ten links to compare. In ChatGPT, the same person types "which ERP system suits a company with 20 employees in the construction industry" and gets a reasoned answer naming four or five specific vendors.

What determines which providers show up in an AI answer?

Which providers get mentioned in an AI answer depends on where the AI tool gets its information from: what it has already learned (training data), or a search it performs right when the question is asked (real-time retrieval).

In the first case, how well-known and talked-about the brand already is matters, and that takes time to build. It can't be changed overnight. In the second case, a new article or updated page can actually be picked up the same day.

Most AI answers are a mix of both. That's exactly why regular SEO visibility still matters for GEO. If you don't show up in search results, the chance is lower that an AI model will even find you when looking for sources to cite.

Why GEO is harder to measure than SEO

Traditional SEO builds on relatively structured user behavior. Users type a keyword or a short search phrase and get a results page with links. A given search phrase therefore becomes a clear measurement point where we can track search volume, ranking, and clicks over time.

In an AI-driven search engine, the behavior looks different. The search often develops into a conversation where the user starts broad and then adds requirements, follow-up questions, and new criteria. This means the final answer can be the result of a long conversation rather than a single question.

For anyone trying to measure visibility, large parts of this user journey become a "black box." We can measure individual prompts, but we can't know which questions, follow-ups, and paths actually led to the user's final answer.

AI tools can also use previous conversations and other available context to tailor their answers. Traditional search engines personalize results too, but the amount of context that can influence an AI answer is far greater.

On top of this, generating AI answers involves a degree of controlled randomness. As the model builds an answer, the next word or word fragment is chosen based on a probability distribution, which means the exact same question won't always produce the exact same answer. A user who gets an AI recommendation of five companies might, a minute later, get a partly or entirely different set of companies if the same question is asked again. That's why tracking GEO visibility tends to be far more volatile than tracking traditional SEO.

The upshot is that AI visibility is considerably harder to measure than traditional SEO. Some parts simply can't be measured, while others require us to work with entirely different conditions than we're used to from traditional search.

How to measure visibility in AI answers

There are several ways to measure AI visibility. Google Search Console and Bing Webmaster Tools now include some data on how your website performs in AI-driven search experiences. You can also measure traffic coming from services like ChatGPT, Perplexity, Copilot, and Gemini via GA4, and track how different AI bots visit and fetch content from your site.

All of these measurement points give valuable signals, but each shows a different part of the picture and has its limitations. Traffic data, for example, only captures the AI answers that actually lead to a click, and also misses Google AI Mode and AI Overviews. Search Console currently shows no click data. Bot traffic shows that a page has been accessed, but says nothing about whether the content is then used or shown in a generated answer.

The most central method for actually measuring GEO visibility is therefore prompt and answer tracking. A prompt is the question or instruction a user writes to an AI service. By repeatedly asking a selection of relevant prompts, you can track how the answers change over time. Unlike traditional ranking measurement, which focuses on positions in search results, this measures mentions and citations in AI answers above all. A mention means your company is named in the generated answer. A citation means the AI answer also links to a page on your website as a source.

Since AI answers tend to vary, it's mainly the development over time and at the segment level that's important to follow. By grouping prompts by, for example, topic, service, or audience, you can see which areas you have strong or weak visibility in. The measurement can also show which competitors most often appear in the answers, which of your content gets cited, and which pages AI services prefer as sources.

An important overall metric is AI Share of Voice, which shows how much of the visibility within a defined set of prompts your brand accounts for compared to competitors. Tracked over time, these metrics give a far better picture of progress than the result of a single measurement, and can be used to identify strengths, gaps, and priorities in your GEO strategy.

How SEO and GEO work together

As mentioned, SEO and GEO rest on the same groundwork. That means a well-structured text that clearly answers a question works well both for search results and in an AI answer, provided the page is indexable and the publisher has built credibility over time. Fast loading, a clean page structure, and thoughtful internal linking pay off in both channels.

Still, the link between high rankings and citations in AI answers has weakened recently. In March 2026, Ahrefs reviewed 863,000 keywords and four million sources in AI Overviews and found that 38 percent of cited pages also ranked among Google's top ten organic results. A year earlier, in July 2025, that share was 76 percent.

A strong ranking doesn't automatically mean high visibility in AI search. The reason lies in how a generative search engine assembles its answers.

If a question is a bit more complex, the AI engine can split it into several smaller sub-questions, known as query fan-out, and search each part separately. The question "which ERP system suits a company with 20 employees in the construction industry?" could, for example, be split into parallel searches like "best ERP system for construction companies," "ERP system with project accounting," and "price ERP system small business."

Pages are then retrieved from the search indexes and sources the engine has access to. The generative answer is built from whatever best answers each sub-question.

That means you're not competing for one position, but to be the best answer to several sub-questions at once. The groundwork is the same, but the ambition needs to widen. You should therefore cover the questions surrounding your main question, and make each answer easy to lift out of context.

Because the two disciplines overlap so much, at BBO we work on SEO and GEO within the same plan, with shared keyword research and content production. Running them as two separate projects really just leads to duplicated work.

When should you prioritize SEO vs. GEO?

There are really three questions you need to ask yourself when deciding where to focus. The first is how much traffic each channel actually delivers. AI services still send through a small share of visitors; Ahrefs' review of 81,947 websites in June 2025 found that AI referrals made up 0.25 percent of an average website's total traffic, roughly one visit in four hundred. Most visitors still come from organic search, so when it comes to clicks, SEO remains your biggest opportunity.

The second question is what a visit is worth once it arrives. Someone who clicks through from an AI answer has already received a recommendation and enters the buying journey further along. In a study of 312 B2B companies between January 2025 and January 2026, AI-referred traffic converted at 14.2 percent, compared with 2.8 percent for organic traffic from Google. A visit from an AI answer is therefore worth several times more than an organic one.

The third question concerns which direction the trends are moving. According to Semrush, around 93 percent of searches in Google's AI Mode end without a click, a pattern that follows wherever AI answers appear. At the same time, AI-referred traffic is growing quickly from its low base; a review by Previsible and Search Engine Land in August 2025 found a 527 percent increase compared with the year before. Traditional search therefore yields fewer clicks per search, while AI traffic grows larger every quarter.

Three steps to get started with GEO

1. 1

   Keep your SEO work as the foundation. It still drives the most visits, and the groundwork you put into technology, structure, and credibility pays off in AI answers as well.

2. 2

   Run a GEO/AI audit to identify technical barriers and understand how you and your competitors show up in generative search.

3. 3

   Invest based on those insights, for example by fixing technical barriers and creating more and better content that strengthens visibility in both traditional and AI-driven search. Budget should also increase to track AI visibility for your site and your competitors.

Priorities also look different depending on what you sell. A complex B2B offering, where the customer asks exploratory questions and compares for a long time, shows up early in AI answers. E-commerce with short purchase decisions still draws most of its volume from classic search and Google's shopping surfaces.

How do SEO, GEO, and AEO relate?

SEO is the work of being visible in traditional searches on Google and Bing. GEO and AEO are instead about AI and answer engines, meaning becoming the answer an engine chooses to show, and the two terms are usually used synonymously. AEO stands for Answer Engine Optimization and points to roughly the same thing as GEO. For your work, a single shared plan covering both regular search and AI answers is more than enough.

Start where you already have momentum

GEO is easiest to introduce in the middle of a functioning SEO effort. The content exists, the technology is in place, and what remains is to phrase clearer questions and answers in text, measure mentions, and build authority in the places models draw from. At BBO, we bring GEO and SEO together in a shared plan, often combined with copy, tracking, and paid advertising. If you'd like that setup, we're happy to help, with the goal of making you more visible online no matter where the customer asks their question.

FAQ about GEO vs SEO