One topic that’s come up frequently in SEO circles is the difference between creating content for information retrieval and creating content that earns citations from large language models (LLMs) such as Claude, ChatGPT, and Google AI Overviews.
As AI search evolves, that distinction is reshaping content strategy. Content that delivers the best user experience and meets people where they are is more likely to earn citations and be recognized as a trusted source.
More importantly, we need to think beyond our own websites and consider third-party platforms as well. As algorithmic marketers, our goal is to keep our brand and messaging consistent so machines clearly understand what we do, who we serve, and when to surface our company and information.
The change from SEO to experience-based GEO
For LLMs in particular, it’s important to stop thinking about interactive search as SEO. Instead, focus on the users you want to attract through citations, or those for whom you want information about your brand to surface.
Some SEO fundamentals apply, but LLMs and AI Overviews are looking to provide customized experiences based on users’ preferences. Your content marketing, both on your website and externally, should keep this in mind rather than focusing on creating content for citations and retrieval.
I’ll start with an example of this customization to show the difference between SEO and generative engine optimization (GEO) or AI Overview approaches, then jump into actionable items you can take.
Your customers search everywhere. Make sure your brand shows up.
The SEO toolkit you know, plus the AI visibility data you need.
Start Free Trial
Get started with
LLMs know consumers better than you think
On a team call this week, I pointed out that the client’s CEO and I are very similar. We’re both around the same age, in the same geographic region, have executive job titles, are very similar demographically, and both like to drink red wine.
However, if we both asked an LLM to make recommendations for a new wine to try, and both said we were looking for a wine with dark fruit notes that was dry and had a big, bold mouth splash, it’s almost certain that we wouldn’t get the same recommendation, even if we were using the same LLM. Why? Because he likes Italian wines, and I prefer Napa Valley wineries.
Google, functioning as a search engine, may know what a big red wine is, but LLM systems know more about our buyer personas because of how we engage with them. They remember who we are, while Google does not. From LLMs, I’ll likely get a recommendation for a Cabernet from California, while he may get an Amarone from Italy.
The LLM and Google AI Overview may both source products to recommend from retailers like Total Wine & More or Binny’s, and use publications like Food & Wine, Wine Spectator, and Vivino for…
Source link
Disclaimer
We strive to uphold the highest ethical standards in all of our reporting and coverage. We blogs.grocliq.com want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.
Website Upgradation is going on for any glitch kindly connect at [email protected]
