Search engine optimisation is always a hot topic in web design and digital marketing but its successor is just around the corner; generative engine optimisation (GEO). According to a very recent study, generative engine optimisation methods boosted a website's visibility from 12% to 63%; evidently showing that optimising websites for AI tools has a major benefit on the overall success of a website.
GEO is an incredibly new but the long-term theory is that with time generative AI experiences will take over from search engines, meaning a new optimisation method is on the horizon.
What is Generative Engine Optimisation (GEO)?
In short, GEO is optimising content for AI powered searches and experiences, such as Google Gemini and ChatGPT. Basically it's following certain methods to increase the chance of your content being pulled by an AI through refinement and GEO tactics.
Common SEO tactics such as keyword optimisation, backlinking, and content optimisation are still fundamental to GEO however, they now don't exist in a search engine vacuum. By harnessing the power of algorithms you can optimise your content to be seen as better and more relevant than your competitors, but how?
GEO Methods and Tactics
Many SEO strategies were tested to see which, if any, were beneficial for optimising for generative searches. The following were found to be the most effective GEO methods meanwhile having very little impact on the actual content of the website, but with an impact of 30-40% increase on visibility.
Cite Sources
Citation was the most effective strategy in relation to factual queries. This works to build authority and trustworthiness, which is a big tick in SEO and GEO.
Quotation Addition
Quoting authoritative sources helps encourage AI to push your content to users.
Statistics Addition
Quantitate data was shown to be much more powerful than qualitative for GEO, adding either your own statistics or citing stats from other studies or website can have a big benefit.
Benefits of GEO
The biggest advantage of GEO, like with many AI and future tech tools, it adapts to trends and user needs quicker and easier than any human ever could in real-time. It allows marketers to increase their content creation without much more effort.
It almost automates the task of content generation by tailoring an answer to each individual users, using your exisiting content. This saves times for marketers, allowing them to focus their efforts elsewhere.
Furthermore, GEO offers space for personalisation that SEO simply can't. When users are constantly having your content tailored to them they are more likely to have a memorable digital experience. This highly targeted content hasn't really been available outside of paid ads such as Google Ads, Meta, LinkedIn and more. Now content can be automatically personalised without the marketer having to lift a finger.
Disadvantages of GEO
A shortfall of GEO is its lack of measurability. SEO visibility can be easier measured through search engine results page rankings, you can see improvements and changes easily to summarise whether your SEO tactics are working in your favour or not.
This is not the case for generative engine optimisation. The study that coined the term GEO, a collaboration between Princeton University, Georgia Tech, The Allen Institute for AI and IIT Delhi, noted that unlike SERPs AI search tools combine information in a single answer. So, instead of basing visibility off of one simple metric, impressions, instead a combination would be required. This combo of metrics included:
- Word count; how many words of your content were included or cited to you
- Influence of the citation on the single response; is your content the main citation?
- Relevance of the cited material to the user query
- Probability of the user clicking though via your citation
- As well as many other metrics.
The study refers to this as 'subjective impression' and G-Eval is used to measure each of these metrics. Clearly this is a lot more complicated than SEO, where you can view your SERP ranking and make a conclusion on website visibility.
A further disadvantage to GEO methods is the same as many AI tools, the output quality will always depend on the quality of the input as well as the underlying technology. Meaning that GEO could become costly for companies attempting it as they'll require robust technologies for testing and measuring.
Is Generative Engine Optimisation the Future of Digital Marketing?
If generative search engines and AI is the future, surely GEO must be the next big thing. Not necessarily. This is still an incredibly new term and, while incredibly interesting, is very difficult for the average market to implement currently. While offering a new opportunity for businesses online to increase their visibility, there's still no saying that generative search engines will favour larger, more-established websites - leaving smaller businesses behind.
On the other hand, it's still exciting to see how the digital world is evolving and it is likely that some day soon we will all be optimising for AI when measuring and reporting become easier. Embracing change is important for staying ahead, so watch this space.
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