Introduction to Generative Engine Optimization
The game has changed, and quite recently, too. Generative engine optimization (GEO), AI Overviews (AIOs), or just an extension of SEO (now being dubbed on LinkedIn as Search Everywhere Optimization) – which acronym is correct? I’d argue it’s GEO, as you’ll see why. We’ve all seen various frightening data on how click-through rates have now dropped off the cliff with Google AIOs, how LLMs like ChatGPT are eroding Google’s share of search – basically “SEO is dead” – so I won’t repeat them here.
First Principles to Get Your Content Recommended by AI
What I will cover are first principles to get your content (along with your company) recommended by AI and LLMs alike. Everything I disclose here is based on real-world experiences of AI search successes achieved with clients. Using an example I can talk about, I’ll go with Boundless as seen below.
Tell The World Something New
Imagine the dread a PR agency might feel if it signed up a new business client only to find they haven’t got anything newsworthy to promote to the media – a tough sell. Traditional SEO content is a bit like that. We’ve all seen and done the rather tired ultimate content guide to [insert your target topic] playbooks, which attempt to turn your website into the Wikipedia (a key data source for ChatGPT, it seems) of whatever industry you happen to be in. The fundamental problem with that type of SEO content is that it has no information gain. When trillions of webpages all follow the same “best practice” playbook, they’re not telling the world anything genuinely new.
SEO May Not Be Dead, But Keywords Definitely Are
Keywords don’t tell you who’s actually searching. They just tell you what terms trigger ads in Google. Your content could be appealing to students, retirees, or anyone. That’s not targeting; that’s one size fits all. And in the AI age, one size definitely doesn’t fit all. So, kiss goodbye to content guides written in one form of English, which win traffic across all English-speaking regions. AI has created more jobs for marketers, so to win the same traffic as before, you’ll need to create the same content as before for those English-speaking regions.
AI Inputs, Not AI Outputs
I’m seeing some discussions (recommendations even) that creating data-driven or research-based content works for getting AI recommendations. Given the dearth of true data-driven content that AI craves, enjoy it while it lasts, as that will only work in the short term. AI has raised the content bar, meaning people are specific in their search patterns, such is their confidence in the technology. Therefore, content marketers will rise to the challenge to produce more targeted, substantial content. To create content that AI prefers, you need to be using the same data sources that feed AI engines.
SEO Basics Still Matter
GEO and SEO are not the same. The reverse engineering of search engine results pages to direct content strategy and formulation was effective because rank position is a regression problem. In AI, there is no rank; there are only winners and losers. However, there are some heavy overlaps that won’t go away and are even more critical than ever. Unlike SEO, where more word count was generally more, AI faces the additional constraints of rising energy costs and shortages of computer chips. That means content needs to be even more efficient than it is for search engines for AI to break down and parse meaning before it can determine its value.
Human, Not AI-Written
AI engines don’t cite boring rehashes. They’re too busy doing that job for us and instead cite sources for their rehash instead. Now, I have heard arguments say that if the quality of the content (let’s assume it even includes information gain) is on point, then AI shouldn’t care whether it was written by AI or a human. I’d argue otherwise. Because the last thing any LLM creator wants is their LLM to be retrained on content generated by AI.
Conclusion
Getting your content and your company recommended by AI means it needs to tell the world something new. Make sure it offers information gain based on substantive, non-LLM-derived research (enough to make it worthy of LLM model inclusion), nailing the SEO basics, and keeping it human-written. The question now becomes, “What can you do to produce high-effort content good enough for AI without costing the earth?” The future is a new targeted substantial value. By following these principles, you can increase your chances of getting your content recommended by AI and staying ahead in the game.