Google’s 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.
Keyword Fragmentation In AI Search
Liz Reid explained that users have always wanted to express longer natural language queries but were forced to narrow them down to keywords like “best restaurants in New York” 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.
For as long as I’ve been in SEO, and I’m 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’s always been the case.
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 “restaurants in New York.” 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’t rank.
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’re 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.
Liz Reid begins:
“We have seen with AI overviews meaningfully longer queries. We see more natural language queries, but it’s also not even something as basic as that.
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, “restaurants New York.”
And you’re 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’t afford to go to them.
Okay, but like, are you picking 10 random ones, etc.?
But like, part of why people would do that is they had a much more complex– I want a restaurant in this location for five people. It can’t be too pricey. I have a vegan member. I also have kids. That was the question they had in their mind.
And in the old world of keyword-ese, that information would be spread throughout the web. And so you wouldn’t feel confident you could just put in the question.
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?
They don’t 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.”
The big ideas to unpack there are:
- A typical complex question asked in AI Search may not be solved by one web page.
- 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.
- 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.
- And yet, perhaps the bigger takeaway is that it’s 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’s AI then picks from among the top three for each query and uses that to synthesize an answer.
So it’s 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.
Addressing Real Needs
Reid didn’t go into detail about this point but it’s 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’t searching with the same keyword phrases which means that Google can’t cache similar queries in the same way it can with organic search.
She explained:
“I think it means you have to do, it’s a harder job on quality, right?
You have to take this question, there’s 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’t just, you know, if everyone uses the same keyword and it’s 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.
But I think we just see that it’s very empowering people, right? That it takes some of the work out of searching.
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’s actually not that hard for me. … And so it’s been kind of exciting to just… make people’s lives easier by helping them address their real need.”
On the surface, the idea of addressing user’s real needs sounds like one of those unhelpful “be awesome” or “content is king” type slogans. But it’s 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’s filling some kind of need.
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’s 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, “what need is this page filling?” as well as by asking, “How is this not just different from some other page but different and better?”
Watch the Liz Reid interview here:
Google’s Liz Reid on Who Will Own Search in a World of AI
Featured Image by Shutterstock/TierneyMJ
