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@tjrobertson52 TikTok profile avatar

@tjrobertson52

2025-12-06

10% of search goes to ChatGPT - here's what that actually means for your business and why the old SEO playbook is dead ๐Ÿ“Š #SEO #ChatGPT #BusinessTips #AISearch

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ChatGPT now accounts for 10% of search online, at least according to the head of ChatGPT. Let's talk about where that number comes from and what business owners should be doing to get found online right now. That number was part of a LinkedIn post discussing how well ChatGPT is doing right now.

Several people in the comments asked where that number came from and they did not get a response. I think it's pretty clear where the number comes from though. It comes from opening eyes initiative to promote themselves as the leader.

And at least right now, they really are the leading AI assistant. Even though it looks like Google currently has the smartest model, as many people have pointed it out in my comment section, a lot of people don't need the smartest model. They just want the best product.

And ChatGPT has always been focused on product while Google's always been more focused on research. So while I do think Google is currently winning and will continue winning for the foreseeable future, ChatGPT is not going away anytime soon. And while it is fun to follow these stories and micro trends, it's easy to miss the forest for the trees.

So what is the forest? Well, if you're a business owner, it's important that you're paying attention to the larger trend right now. Regardless of how much market share each model has, one thing is very clear, the way people find information and businesses online is changing fundamentally.

More and more of that discovery is happening within large language models. So while specific details are unclear, we now know enough about the future to shift our strategy. So how exactly should this shift towards large language models affect your strategy?

We're moving from a winner takes all economy to a situation where there can be many winners. In traditional search, the average business is fighting over a few very competitive, very common search terms. If someone is going to Google search to look for a dentist, as a dentist, you need to be in the top three positions.

Otherwise you're gonna get little to none of that search traffic. Large language models change things in two fundamental ways. If that same person goes to ChatGPT looking for a dentist, they're unlikely to type in something simple like dentist near me.

More often, they're gonna have a full conversation with ChatGPT. And it's the same thing with Google's AI mode. ChatGPT or Gemini will then run not one but a series of searches in their own search engine.

However, these searches are gonna be way more specific than dentists near me. It's gonna take all that context it has from your conversation as well as previous conversations and run a series of specific searches. Searches like best dentists for kids or dentists that take my insurance for dentists with availability on the weekends.

And unlike humans, these large language models aren't just gonna look at the top three results, they're gonna look through multiple pages of results. And so while the old strategy was to have one really strong page that needed to rank in the top three positions, we're moving into a world where quantity matters more than quality. And don't get me wrong, quality still matters.

You need to protect your brand, but it no longer makes sense to put all your eggs in one basket. Nowadays, the best strategy is to create as much content as possible, get as many people talking about your brand online as possible. As I've said before, the noisiest brands are going to be the winners.

Source Intelligence

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LLM discovery can turn one buyer conversation into multiple specific searches based on the user's context.

3 related signals ยท AI discovery / search behavior / AI visibility / SERP depth / Brand mentions / AI visibility

  • Map likely conversational buyer scenarios and create content for specific needs, constraints, and modifiers, not only broad head terms.
  • For priority prompts, test whether target LLMs cite sources beyond top results before scaling broader content coverage.
  • Build authentic public brand evidence across owned and earned surfaces; risk/avoid fake reviews, spam comments, or low-quality mass posting.

Questions this source answers

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What is this source mainly about?

LLM discovery can turn one buyer conversation into multiple specific searches based on the user's context.

What should an operator take from it?

Map likely conversational buyer scenarios and create content for specific needs, constraints, and modifiers, not only broad head terms.

Which topics does it connect to?

This source is connected to AI discovery / search behavior, AI visibility / SERP depth, Brand mentions / AI visibility.

What public evidence supports the record?

rds large language models affect your strategy? We're moving from a winner takes all economy to a situation where there can be many winners. In traditional search, the average business is fighting over a few very competitive, very common search terms...