For online businesses and publications, Search Engine Optimization (SEO) has been vital for finding an audience across the vast and ever-growing internet. It can be relatively inexpensive and level the playing field for smaller businesses targeting niche topics and user intents.
Since the advent of generative AI, users have had a workable alternative to search engines, and prominent engines like Google have integrated AI into search results. The result is Generative Engine Optimization (GEO). Here are the main differences between them.
GEO cites your content
Even before GEO, marketers have been using AI to streamline and automate some of the simpler, time-consuming aspects of the job. For example, some popular marketing automation solutions automate busywork and free marketers up to offer personalized interactions, targeted by using AI to detect user behavior and preferences. Those predictive insights only got more powerful with generative AI, allowing even small marketers to cater to growing audience needs.
When it comes to the search results page, generative AI has automated users’ browsing experience. Instead of clicking around to find information, AI gathers it and then presents it in its own way. However, to give credit or further reading, all leading AI models include links to where they’ve sourced facts, claims, and other info.
So, if SEO is all about getting on the search results page, GEO is about getting your link as a source in an AI-generated answer. With Google’s Gemini AI breakdown sitting in position zero, SEO and GEO have started to work hand-in-hand. Savvy marketers try to make AI-friendly content that will get scraped and presented at the very top of a question search, before the first result.
GEO demands different content
Writing for SEO is an evolving practice that changes with every Google update, especially as they move away from rigid and exploitable keywords and toward targeting search intent. Put simply, those who target human intuitions will get rewarded over those who cynically pursue keywords with low-quality content.
GEO changes this dynamic since the human user is now accessing content through an AI filter. Like how SEO experts make their pages easy to index, GEO writers need to present answers with enough clarity that GEO sees them first when asking the internet a question, then delivers the answer (and a citation) back to the human user. This means clear, confident, structured content that’s easy to parse and summarize.
Naturally, the content still needs to be readable and enjoyable for people. Balancing writing for humans and Google’s bots isn’t a new idea in SEO, but GEO blurs the line between content-based SEO and technical backend SEO. GEO content needs to stand out technically without coming off as robotic or inauthentic to the reader.
GEO answers questions
In most cases, a productive GEO citation happens because the user has asked their AI a direct question or typed one into the Google search bar to summon a Gemini intervention. Being predictive machines, LLMs can and will predict what the user wants to hear, including conversational pleasantries, but it’s the questions that send citations to engaged, interested users.
SEO targets that and more, including matter-of-fact short-tail keywords. Longer-tail, question-based keywords provide rich niches for SEO experts too, but now GEO can take long, conversational input without getting confused or losing context. Then it can find direct answers or brand names online and deliver them to the user in an equally conversational tone.
With GEO on the rise, there’s no doubt we’ll see refinements of its search abilities in the future. In the meantime, it’s a forward-facing alternative or supplement to typical SEO, especially if targeting digitally native, tech-savvy audiences who have adopted AI.
This content is provided for informational purposes only and is not a substitute for professional advice. AFP editorial staff were not involved in the creation of this content.
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