The issue arises when we move away from objective trivia and into subjective, localized buying intent, which is where the web monetizes itself.
If I ask an LLM 'who created Linux?', there is one right answer. But if I ask an LLM 'who are the best commercial roofers in Houston?', there isn't one right answer. There are dozens of highly qualified local businesses that do possess unique value, unique pricing, and unique availability.
When an LLM answers that roofing question, it typically cites 3 to 5 businesses. The other 40 legitimate roofing companies in the area are left out. My study isn't arguing that every single one of those 40 companies deserves to be in the answer; it's pointing out that those 40 companies currently have no idea they are being left out.
In the Google era, if you weren't on page 1, you could look at Search Console, see your ranking, check your backlinks, and understand why. In the AI Search era, businesses are being scraped to build these answers, but they have zero telemetry on whether they are actually making the cut. This index is just an attempt to provide that missing telemetry.
I don't see how mentioning the other 40 should follow from that fact. You get exactly what you're asking for - the best, according to agent's judgement. Judgement and processing of simple search results is exactly what you're using the intelligent agent for. Ask for a list of all commercial roofers in Houston and then you can expect a list.
It can be argued that models are clustering their replies around a few options when asked to choose from a list of equally valid ones (due to mode collapse, distribution biases, primacy/recency biases etc), but these options are not equally valid for the agent, it looks at their sites or possibly in some other places like review sites to rank them. Its ranking criteria might be not good at all, but that's another question.
Also, I would assume that really "GEO" is just like "SEO". If you rank on the '1st page' of results for whatever common searches, you are _very_ likely to rank the same way for LLM questions, because all the LLM is doing (nearly all of the time for 'best roofers in Houston') is doing a web search and summarising the first x results. So if you are on page 1 for that term, it's very likely IME that you will get mentioned on LLM answers for that.
You're effectively reminding us that brands don't get understand well how to influence ai seo
I would expect a judgement of a modern model to be superficial for this request, but still better than nothing. A deep research agent might be a lot better and much less susceptible to "optimization".
Also what is the incentive for me to rank on LLMs? People do not use it to click sources or even take action. Do you have any proof that being ranked as the best roofer in houston drives sales more than not being ranked as it? If not, why should i care as the roofer?
However, if you are looking for the best product/service/whatever, then yes it really does matter. I've bought _so_ many products because of LLM recommendations. For example, I wanted a new webcam, I asked the LLM to find me the best ones with a large sensor and Linux compatibility. It gave me a shortlist then I chose one and then I bought it.
This experience is far better than trailing through dozens of pages of (even pre LLM) SEO slop.I just tried the same on Google search and all the links recommended a camera with ~10% the sensor size that I bought.
I think your assessment of this result being as expected... but this is about the LLM equivalent of SEO becoming an area of interest
Not even Wikipedia.
Let’s say I ask “who created Linux?” Claude correctly tells me Linus Torvalds, and links to Wikipedia.
There are probably thousands, maybe hundreds of thousands of other sites that have that some piece of information. Are LLMs supposed to link to every site?
Most sites do not have unique information at all, and even sites that do rarely contain only unique information. Implying that most sites deserve links because they were crawled seems like a statistical fallacy. You could say the same thing about the percent of sites crawled by Google versus ever showing up on first page of results.