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Generative Engine Optimisation (GEO) is the extension of SEO with some key differences

We see a big shift from SEO to GEO for businesses which have an online presence. For decades now SEO has been the bedrock of visibility on the web. However, with LLM based answer engines we have entered a world where models like chatGPT, Gemini, Claude or perplexity synthesise information directly for the user. This big shift in the nature of how users get their information on the web has led to the emergence of the discipline of generative engine optimisation (GEO).

Itika Singhal
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SEO has always been about ranking on the search engine result pages (SERPs) and GEO is all about becoming a part of the generated answer with reference link within the answer engines. Lets look at the similarities and difference between the two disciplines -

1. Primary target interface

Search engine optimisation (SEO) is done for search engines like Google and Bing. Generative engine optimisation (GEO) is done for generative models and their answer engines like GPT-5 for ChatGPT, Opus 4.7 for Claude, Gemini 3.1 Pro for Gemini

2. Metrics for measuring success

There are so any parameters which can indicate the successful implementation of SEO or GEO discipline on your business. To name a few, CTRs (click through rate), SERP rankings, bounce rate would be the parameters for SEO. For GEO it would be inclusion in AI responses and citation frequency.

3. Output Goal

Search engine optimisation is done with the end goal of getting the business listed in search engine result pages for the queries user search. The end goal of generative engine optimisation is to be cited and referred in an answer generated in response to the user’s prompt query.

4. Code and content structure that matters

The technical content and code structure for both SEO and GEO have varied strategies. Some of the basic ones for SEO would be having keywords embedded through out your content, metadata about your content, H1-H6 defined to indicate the structure of your content, mentioning relevant tags.

Basic structure for GEO would be have natural language in your content, this would be more of conversational style in simple language which can easily be synthesised by answer engines, structuring data by defining the right schema, including relevant trust signals that would make the answer engines establish trust in your content.

5. Parameters that increase visibility

There are many parameters which are set for search and answer engines, which make your business visible to them. In SEO, some of the key visibility factors which also increased the chances of ranking were keyword matching, page rank, domain and page authority, quality backlinks and traffic to the pages. Technical factors like site speed, mobile friendliness and XML sitemaps also increased chances of ranking.

GEO is built on the principle of verifiability of the content and then synthesis of the same to form an answer. Verifiability is important because LLM answer engines are designed to reject anything that would lead to hallucinations and bias. LLM answer engines look for trust and authority indicators. They also look for facts and statistics. List and table formats increase visibility. LLM answer engines prefer to the point verifiable answers which are readable and citable.


6. The Big Shift From Keywords to Context

In search engine optimisation, keywords were the key. People would optimise for generic keywords, regional searches, long tail keywords etc. The idea was to get creative with the usage of keywords in order to get ranked in SERPs.

When in comes to GEO, keywords do not play such a big role and answer engines try to understand the context of your query and then synthesise answer by visiting a few top pages. The number of pages visited differ based on the model used for answer engines. When we say context it means that the answer engines try to get you what you have asked for instead of giving you links to pages and letting you to find the answers.

7. From Link Economy to Citation Economy

Traditional SEO focused on link economy i.e. trying to get your URL mentioned in SERPs. GEO focuses on citation economy i.e. get cited and referred in answers by LLM based answer engines.

In SEO, the end user would never get to read your content unless they clicked on a certain link. In GEO, you get the answer to what you are looking for first. Here it means a certain business may or may not get referred. If you do get cited in the answer, the user would then click on the link for verifiability.

Here we have discussed many similarities and differences between optimising for search engines and for generative answer engines. GEO does not replace SEO, it extends it with some modifications. Eventually, a citation in the generative answer would lead the user to your website where a certain intended conversion may happen. Hence, SEO is still quite relevant. GEO just makes sure that you are remembered and recommended.

Itika Singhal

Founder

Itika Singhal is an entrepreneur and a business leader with over 12 years of experience managing IT development, SaaS products, and end-to-end digital marketing solutions. Having successfully founded and led Cobaltqube Media Pvt. Ltd., she has a proven track record in B2B product management, digital transformation, and operations leadership. Itika possesses a strong command on emerging technologies like AI, Blockchain, XR. She also has deep hands-on SEO expertise, and is currently leading the charge into the future of search at ‘Discoverability Engine’. Her work now focuses on Discoverability and Generative Engine Optimization (GEO), ensuring brands remain retrievable and relevant in an AI-driven landscape. Her hands-on experience spans technology, finance, and compliance, delivering innovative results for everyone from startups to government institutions.

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Generative Engine Optimisation (GEO) is the extension of SEO with some key differences | Discoverability Engine