{"id":7721,"date":"2026-05-08T10:48:06","date_gmt":"2026-05-08T02:48:06","guid":{"rendered":"http:\/\/longzhuplatform.com\/?p=7721"},"modified":"2026-05-08T10:48:06","modified_gmt":"2026-05-08T02:48:06","slug":"google-on-keyword-fragmentation-and-user-needs-in-ai-search-via-sejournal-martinibuster-2","status":"publish","type":"post","link":"http:\/\/longzhuplatform.com\/?p=7721","title":{"rendered":"Google On Keyword Fragmentation And User Needs In AI Search via @sejournal, @martinibuster"},"content":{"rendered":"

<\/p>

Google\u2019s Liz Reid explained on the Bloomberg Odd Lots podcast how AI Mode and AI Overviews are enabling detailed, need-based query patterns that create new challenges for Google. This points to a consequential change in search behavior that directly impacts how to approach SEO.<\/p>

Keyword Fragmentation In AI Search<\/h2>

Liz Reid explained that users have always wanted to express longer natural language queries but were forced to narrow them down to keywords like \u201cbest restaurants in New York\u201d even though what they really wanted may have been more specific like a restaurant with vegan options and an opening for a party of five.<\/p>

For as long as I\u2019ve been in SEO, and I\u2019m near 30 years in the business, keyword research has been the foundation of digital marketing. You pick the keywords you want to rank for then create the content in a way that is optimized for that keyword. The problem with optimizing for a short keyword phrase is that there are hidden meanings within that keyword and that\u2019s always been the case.<\/p>

The way Google used the issue of latent meanings within keywords is to use things like clicks to better understand what users meant when they typed ambiguous keyword phrases like \u201crestaurants in New York.\u201d Some SEOs believe that the clicks were used for ranking websites but another use for clicks is understanding what people mean when they type ambiguous phrases. What Google has done for quite awhile now is to rank the most popular meaning of the keyword phrase first and no matter how many links a page received, if the content aligned with a less popular meaning the page wouldn\u2019t rank.<\/p>

Liz Reid said that people who use AI-based search are using longer queries that articulate what the problem or information need is, making it easier for Google fetch the information they\u2019re looking for. That change gets to the heart of the problem with organic search that AI search is solving and the implications for SEO are profound.<\/p>

Liz Reid begins:<\/em><\/p>

\u201cWe have seen with AI overviews meaningfully longer queries. We see more natural language queries, but it\u2019s also not even something as basic as that.<\/p>

It can also be like you were searching for restaurants. We used to laugh about the like before I worked on search, I worked on maps and local, some of the intersection with search, and people would just be like, \u201crestaurants New York.\u201d<\/p>

And you\u2019re like, what do you want me to do with that query? Like, okay, the best restaurants in New York are going to take three months and 99.9% of the population can\u2019t afford to go to them.<\/p>

Okay, but like, are you picking 10 random ones, etc.?<\/p>

But like, part of why people would do that is they had a much more complex\u2013 I want a restaurant in this location for five people. It can\u2019t be too pricey. I have a vegan member. I also have kids. That was the question they had in their mind.<\/p>

And in the old world of keyword-ese, that information would be spread throughout the web. And so you wouldn\u2019t feel confident you could just put in the question.<\/p>

And now with AI Overviews and AI Mode, you can start to actually, and you see people do this, they tell you the real problem, right?<\/p>

They don\u2019t take their need and translate it to what the computer understands. They try to give the computer their actual need and expect us to do the translation.\u201d<\/p> <\/blockquote>

The big ideas to unpack there are:<\/strong><\/h3>
  • A typical complex question asked in AI Search may not be solved by one web page.<\/li>
  • Complex questions may be one-off and rarely, if ever, repeated, which in many cases may lower the value of optimizing for those phrases, because the time used for crafting them could be more profitably spent doing something else.<\/li>
  • Given that a site will likely share the AI Overviews (AIO) space with another site it increases the need to optimize other factors such as brand icons that stand out in a positive way, use of images that are relevant, and even the use of videos to claim as much AIO space as possible.<\/li>
  • And yet, perhaps the bigger takeaway is that it\u2019s not all longtail because Google breaks down the longtail phrases into smaller highly specific keyword phrases that reflect a portion of the information need, query fan-out, and fires those off to classic search. Google\u2019s AI then picks from among the top three for each query and uses that to synthesize an answer.<\/li> <\/ul>

    So it\u2019s not really that SEOs should optimize for long-tail queries because query fan-out uses Classic Search, bringing it all back to the specific queries that web pages are relevant and optimized for.<\/p>

    Addressing Real Needs<\/h2>

    Reid didn\u2019t go into detail about this point but it\u2019s interesting anyway because she said that the process of breaking a complex natural language query into smaller queries becomes a quality issue. One of the problems with AI Search is that people aren\u2019t searching with the same keyword phrases which means that Google can\u2019t cache similar queries in the same way it can with organic search.<\/p>

    She explained:<\/em><\/p>

    \u201cI think it means you have to do, it\u2019s a harder job on quality, right?<\/p>

    You have to take this question, there\u2019s many parts, and you have to figure out how you break it apart. And you have to do work to think about things like latency, because you can\u2019t just, you know, if everyone uses the same keyword and it\u2019s not personalized, then you can cache it all. If all of a sudden the queries get much more diverse, you know, it has consequences there.<\/p>

    But I think we just see that it\u2019s very empowering people, right? That it takes some of the work out of searching.<\/p>

    A few years ago, they said, What more can you do with Google search? But if you actually ask them, Okay, when was the last time you spent 20 minutes searching when you would have preferred to spend 2? It\u2019s actually not that hard for me. \u2026 And so it\u2019s been kind of exciting to just\u2026 make people\u2019s lives easier by helping them address their real need.\u201d<\/p> <\/blockquote>

    On the surface, the idea of addressing user\u2019s real needs sounds like one of those unhelpful \u201cbe awesome\u201d or \u201ccontent is king\u201d type slogans. But it\u2019s actually a way that every SEO should be auditing web pages. Rather than limiting their scope to keywords, headings, technical issues, take a look at how it\u2019s filling some kind of need.<\/p>

    Someone today asked me to look at their website that was having trouble getting indexed. They suspected that it might be a technical issue. My response is that yeah, everyone hopes it\u2019s a technical issue but in many cases, especially for this one I was looking at, the problem becomes apparent when looked at through the lens of asking, \u201cwhat need is this page filling<\/em>?\u201d as well as by asking, \u201cHow is this not just different from some other page but different and better?<\/em>\u201d<\/p>

    Watch the Liz Reid interview here:<\/em><\/p>

    Google\u2019s Liz Reid on Who Will Own Search in a World of AI<\/h2>