Stop thinking about keywords: how conversational search really works

Keywords are no longer the unit of search. The conversation is.

In this episode Simon Young of Question.Marketing explains how search has turned into a conversation. Google AI Mode, ChatGPT and Gemini take one long question, break it into many hidden searches, and write a single answer from what comes back. He covers what Google's People Also Ask box was telling us for a decade, two worked examples (a Doncaster accountant and a South Yorkshire recruitment agency), why a top 10 ranking is now closer to a raffle ticket, and a practical plan for this week.

Read the full article and transcript: https://question.marketing/library/stop-thinking-about-keywords-conversational-search-2026
Watch the video: https://www.youtube.com/watch?v=RgOnpI5vxHM

Chapters
00:00 Why stop thinking about keywords?
00:47 From typing keywords to asking questions
01:50 Why so many Google searches are brand new
03:01 What People Also Ask was telling us
04:41 Who writes the People Also Ask answers now?
07:27 Search is now a conversation
08:23 What is a fan-out query?
10:52 Fan-out examples: lawn care and headphones
11:57 Why your keyword tool misses the questions that matter
14:09 Why a top 10 ranking is now a raffle ticket
15:53 How fast is AI Mode growing?
18:10 Longer questions get the machine's answer
19:02 Ad money is following longer searches
20:05 UK searches are getting longer
20:47 How many follow-up questions do people ask?
22:36 Worked example: choosing a recruitment agency
25:44 Is this still just SEO?
28:18 Keywords are no longer the unit of search
28:35 What to do this week: start with questions
30:00 Use People Also Ask as a free map
30:45 One page per conversation
31:15 Say what only you know
32:23 Ask it the long way and check if AI names you
33:07 Sources and wrap-up

Notes on figures as spoken
01:25 Semrush's 23 words is for ChatGPT prompts without web search, against about 3 to 4 words for a Google search (2024 data).
03:41, 06:18 and 32:04 Google's 15% new-searches figure covers Google Search only, not AI platforms or the wider web.
10:57 Google's own lawn example lists herbicides, weeding without chemicals and weed prevention. Grass types and watering are my additions.
11:41 No study shows that queries with a date or statistics get cited more. That's my observation, not a published finding.
15:56 Google's billion is monthly active users of AI Mode, not searches.
27:31 AI referrals were about 1% of traffic on Conductor's 2025 US data and 0.14% on Semrush's 2026 data.

Key sources
Google 15% new searches (Search Engine Journal): https://www.searchenginejournal.com/google-revisits-15-unseen-queries-statistic-in-context-of-ai-search/543160/
People Also Ask answers now AI Overviews (Brafton, AlsoAsked data): https://www.brafton.com/blog/seo/google-ai-overviews-are-taking-over-people-also-ask-heres-what-marketers-should-know/
Query fan-out in Google AI Mode (Search Engine Journal): https://www.searchenginejournal.com/query-fan-out-technique-in-ai-mode-new-details-from-google/552532/
Gemini 3 fan-out research (Seer Interactive): https://www.seerinteractive.com/insights/gemini-3-query-fan-outs-research
AI Overview citations from top 10 pages (Ahrefs via Search Engine Journal): https://www.searchenginejournal.com/google-ai-overview-citations-from-top-ranking-pages-drop-sharply/568637/
Pew Research Center on AI summaries and clicks (The Decoder): https://the-decoder.com/pew-finds-that-only-1-percent-of-users-click-a-source-link-directly-from-googles-ai-overviews/
How AI Mode is changing search (Google): https://blog.google/products-and-platforms/products/search/ai-mode-us-insights/
Google's AI search guide and scaled content abuse (TechWyse): https://www.techwyse.com/news/ai-search/google-ai-search-guide-seo-geo-hacks
Semrush ChatGPT prompt length study: https://www.semrush.com/news/379285-new-semrush-study-reveals-chatgpt-search-trends-insights-from-80-million-clickstream-records/
Google Search Central guide to generative AI features: https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
AI referral traffic benchmarks (Conductor): https://www.conductor.com/academy/aeo-geo-benchmarks-report/
Traffic channel mix study (Semrush): https://www.semrush.com/blog/traffic-channel-mix-study/
Peec, what is a query fan-out: https://docs.peec.ai/research/what-is-a-query-fanout
RealityMine, UK search behaviour: https://www.realitymine.com/articles/ai-powered-search-how-google-search-behavior-is-shifting

Question.Marketing: https://question.marketing
Simon Young on LinkedIn: https://www.linkedin.com/in/aeo/

Transcript

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SPEAKER_00 0:01

Hey everybody, Simon here from Question Dot Marketing, and I want to talk to you today about try to stop thinking about keywords. Think more about how people are going to be speaking, how we're going to ask questions of LLMs and how search is evolving. In 2026, and this is the latter part, we're into Q4 of 2026. We're looking now at how queries fan out. And I want you to understand how people are now searching and use that in your marketing, which is going to be hugely important. Probably one of the most important changes in how search works is happening right now, and the opportunity is huge. So as we move forwards, we're going to go into a world where you know we used to type, for example, accountant, Doncaster. You would type in a phrase or a keyword, and we're now moving into a world where people are prompting. Obviously, we're we're asking questions of LLMs. And you might then, in that example, somebody might ask, which accountant near Doncaster is good for a small builder who's fallen behind on his VAT? Now, one of the findings from SEMrush was that uh queries are now have gone from maybe you know three or four words when we were working a keyword universe or a key phrase universe to now 23 words on average, where people are asking questions. So we now need to think how does this affect us? One thing that is really important to understand, and I don't think many people actually realize this before AI, way before AI, all the way through search, people have on average um been typing in things that aren't answered, things that are not answered, right? So 15% of the time, and this is according to Google, every single day, there are searches going into Google that have never been asked before, right? No keyword tool um can reference them or has use of them because they've never been typed in. This is how the human mind works, right? We need to understand that if somebody hasn't searched something yet, how can we optimize for it? And if you know, if you are an SEO listening to this or you're dealing with an SEO company who are still talking about keywords, trust me, they are getting it wrong. We need to move to a query-based, prompt-based, question-based um way of optimizing. So if we go back in time a little bit, um, let's look back to April 2015. Google started testing a system called People Also Ask. And hopefully we all understand how this works. When you search something, a little way down the page, you will see People Also Asked. Now, our business is question.marketing. The reason it's question marketing is because it is about the questions that people are asking. And I want you to seriously think about how you optimize for the questions. Now, based on the previous slide that I showed you, think about also the fact that 15% of the queries that are going into search and LLM have never ever been typed in before. So that might sound ridiculous, but you know, there's 15% of the world that are putting things in in a different way. So purely rephrasing things, wording them differently, asking different questions, and that is every single day. So think how that compounds, right? 2017. Um, each click then started to load a lot more questions, um, and the box never ends. If you've ever tried this, if you go to the People Also Ask section and just keep clicking and clicking and clicking it, open and close the questions and answer sections of Google, it produces hundreds and hundreds and hundreds of queries, and it's starting to then populate what people are asking around a subject and how a query is fanning out. So now we're at 2025. If we well look at mid-2025, only 12% of the people also asked answers are in AI overviews. So I think this is really um crucial because we're starting to see the shift, and this is where fundamentally traditional SEO is finished just because it's not about keywords anymore. And it is now about how we optimize content to answer many, many queries, and that's what I'm trying to or will hope to explain to you in some examples in this video as we go on. August 2026 jump forward 86% of those people also asked answers are now in AI overview. So we're now in a significant position where um answers really, really do matter. So it's not just about phrases, it's so obvious that people try and optimize for a phrase. You know, in our example earlier, find me an accountant near Doncaster, or who's the best accountant in Doncaster, or which Donka, which Doncaster accountant should I use, or is there an accountant in Doncaster that could help me with my VAT? You can now see that there could be thousands of iterations of that, even that just one basic phrase. And now once you start going into billions of different searches that are happening all the time, you can hopefully understand how uh we can talk about 15% of the searches that go into these AI platforms have never even been asked before. So, how does an AI deal with that? Think about it. Uh, now September 26, and things are moving really quickly. 97% of the sampled answers are AI written. So I think we can see that Google has started mapping this conversation years and years and years before anybody was even beginning to have a conversation with it. So they see the end game, you've got to work with how this is moving. The box that showcased your content is now written by Google's AI, right? So if we move from 12% of the people also asked answers being used about well, just over a year ago, um, 97% of that is getting used. So 19.2 million sampled English people also asked answers in the first week of September 2026 alone. So 90% of results pages with an AI overview also uh show people also are asked in an AI answer on top, right? Remember that. So follow-up questions. Um it's a conversation. Think of search as a conversation now, not as a keyword or a key phrase, right? We're not we're not trying to come top for a keyword or a key phrase, right? This is the whole of SEO ending right now just because it's nothing to do with keywords anymore, it's to do with conversation and it's to do with answers and questions, and how people uh discern what they're looking for. How do they move through that map of questions and answers that's already there? So it one question, and this is what I'm trying to get across to you guys, right? One question may fan out into many, many different answers, right? So, in the example, if somebody asks which accountant near Doncaster is good for a small builder who's fallen behind with his VAT, right? Only a very small search volume, right? So don't start looking at in the past, if somebody typed in accountant Doncaster and they just started clicking links, that's a very general search. If somebody ends up on a website, they might produce an inquiry, they might be a decent customer, they may or may not. But once somebody qualifies themselves, we have to understand that behind that are a whole bunch of queries that AI is using to map who to cite and recommend. So if somebody asks which accountant near Doncaster is good for a small builder who's fallen behind his VAT, that's probably not been typed in very much at all. It's 100% definitely not been optimized for because I can imagine there's not somebody who's produced a page that is specifically aimed at that phrase and for somebody who has fallen behind with their VAT. If somebody has, I'd be amazed and well done you if you did. But anyway, behind that, the AI will be searching accountants in Doncaster, accountant for construction trades, help with late VAT returns, HMRC penalty for a late VAT return, firm name and then reviews, and accountant fees, sole trader builder. So hopefully we can now see there are many questions being then queried by the LLM in the background. So if somebody's telling you they want to optimize you for just accountants in Doncaster, that's not gonna work, right? It's it will be general and it will not be specific to the person's need. So therefore, we're and it's not how people type it in, they won't converse with LLMs in that way, right? So hopefully you can now see that building up a set of questions and queries behind an actual query that somebody's typing in is what actually matters. So this will then produce a result of maybe one or two decent recommendations from an LLM. Other examples, um for example, if someone Google's own example was how to fix a lawn, right? And in that they named herbicides for lawn weeds, best grass types for your climate, how to prevent weeds, lawn watering schedule, right? So these are all things that matter to the first query. Um, another one from ChatGPT, and this was from Peaks Research. Somebody searches best headphones. We would look for, for example, the AI might be looking for the best wireless headphones, best noise cancelling for flights, best budget headphones, best headphones 2026. The last one is quite interesting because we are seeing that quite a lot of queries that include a date or statistics do get referenced quite often. So what you need to think about is how do I come into the main search based on all of the content that somebody might ask a question around? Most of the questions that decide the answer are not in your keyword tool. So somebody's optimizing you for best accountant in Doncaster, all those phrases you're definitely not optimizing for or even telling people, telling the LLM that you're optimizing for that. You don't have the content built behind it to do that. Um, and you're most certainly not measuring whether you come up for those foundational phrases and um keywords, right? The other things that matter to build the search query to give the answer. Um Google or Gemini, so Gemini will look for roughly 10 searches per prompt. Um, 95% of those probably had zero search volume. So that's really important. We're looking for the fact that you know these are phrases and keywords and things that are people asking. They're never they don't have volume in traditional search. Um between six and twelve words per chat GPT are hidden search, and 32.9%, 33% of chat GPT cited pages surfaced only via a hidden subquery. So meaning that when that subquery the content matched it and was cited, that then brought forward a page that could not possibly have necessarily been optimized to come up for a particular phrase or keyword. So it's the fan out that matters. You have to understand, and I don't think people I don't think very many SEO agencies understand what I'm talking about here, and maybe I'm educating some of them to understand to how to build content properly behind the scenes that matches the query. Okay, it's not it's not rocket science, this is this is a process that has to go through to understand how to build content in this new LLM search universe. Ranking in the top 10 uh now buys you effectively uh a raffle ticket, it doesn't get you into the answers. Um in mid-2025, if you look back, roughly 75% of pages would produce or would be cited in those uh AI overviews. Now in Feb 2026, and I'm recording this video in October 2026, if we look back to February, that had already reduced um roughly by half. So 38% of uh pages that were previously in the top 10 now being cited. So you you are not, or your content as it stands, if you have spent years, and you may well have spent years optimizing your content to appear for certain uh keywords or phrases, the foundation that that is built on is quicksand, right? It is disappearing. Um half of the overlap between AI citation and Google or traditional search uh positions has now disappeared in less than a year. And I think this is set to shift completely to the point where the only thing that matters is the questions, the answers, and the citation in the fan-out query. You've got to build the content around how you're stacking content to answer a question to be cited. Um this isn't a new thing, right? It's definitely not a new thing, right? We're there's a billion plus searches now in uh monthly in AI mode. Um, and that's only you know, really in Google, that's probably only a year after they've really moved into providing AI mode to people. Um AI mode queries have more than doubled every quarter, so it's exponential, it's just a speed thing. This is just growing so quickly. Um, this is the the searches that come out are three times the length of a traditional search on average. So people are beginning to talk to these LLMs. We are going to see a shift from typing in phrases and keywords to asking questions. We are going to ask questions and want to learn more, right? And one in six, this is crucial as well, one in six searches in the US now uh are voice or image search, right? So we're we're moving very, very quickly away from what you would call traditional search. I've heard people talking about you know the web disappearing, you know, moving to uh an AI LLM assistant universe. That is happening, right? I got called a crackpot, or what you know, was I on mushrooms about a month ago for saying, you know, there is a possibility that the traditional web or uh search disappears. I think I'm gonna be proven right. Um we are moving to a world where the web, yes, it exists, but it's more like a repository or a library, and it's not where we end up. Um you know, we don't end up on people's websites. We we aren't answer our queries within the LLM, we probably buy there, we book meetings there, we converse there, our AI assistants talk to each other, talk, book meetings, etc. etc. Why would you spend your time or moreover, waste your time searching through websites when you can get the answer given to you? The longer the question, now listen to this carefully, the longer the question, the more likely the machine answers it for you, right? So searches that triggered an AI summary by length. One to two words, only eight percent, and ten plus words, fifty-three percent, right? And this is only set to increase again. So eight percent versus fifteen percent, a click will click a normal result with an AI summary versus one without one, and one percent will click a source link inside the AI summary. So this is why we're starting to see people not click um through to sites, and this is again set to increase. Add money is already following these longer uh search queries, right? So share of Google ads impressions by query length. If we look at one to two words a year earlier, uh 42%, now 24%, and longer queries, three to four words a year earlier, 33%, and now in August 2026, 50 nearly 50%, 48%. So conversions from seven or more words has moved from one percent to four percent, and this is evidence from search engine land analysis of Google Ads data in August 2026, right, via Optimixed. This data shows that people are moving again. You you cannot be surprised about this that people are moving to asking questions and researching within their query. UK searches are getting longer, um, even for people who never used Chat GPT. So characters in the average UK Google search in a year has gone from 21 to 26. So not a huge shift, but you can see that it's moving. UK searches over 30 characters are up 24%, and Google searches per person in the UK versus May 2025 up 26%. So people aren't searching for different things, they're saying things differently, they're asking more questions, they want more depth in their search. So most people will still ask only once or twice, right? But buyers will keep diving in, right? So we are seeing a slight divergence between the seriousness of a query, if we put it that way. Um what we what we're seeing is a shift in, you know, you are getting your answers more quickly, so you only have to maybe ask once or twice. And I don't know that people are in the mood or they haven't necessarily learnt quite yet to dive deeper and deeper on more general topics. That's actually good because it's you know, you get the answer straight away, uh, you can take action on it, or if you're just browsing, you're not um you're not wasting any time, right? You you don't have to go and dive through four, five, six websites, you don't have to go and check reviews, you don't have to make your own mind up. The AI can do that for you, right? Um people are making sort of two or three queries per AI mode session versus five in traditional Google. So again, people are getting answers more quickly. 1.7 messages in the app. Average chat GPT conversation. So seeing that backs up our one or two um people ask metric. Um but we are seeing 94% down to 43% of prompts needing one round of hidden searches. So we are seeing the fact that there are many, many more hidden searches behind content that is getting served to you or served to the people that are potentially trying to find your business. So I've I built a little example. Now, if you're listening on my podcast, um I'll I'll try and explain clearly what's going on. So I've built a little example. So if a recruitment agency, so somebody's looking, a business is looking for a recruitment agency, and somebody's thinking about should we use an agency or shouldn't we? And the question they ask, should we use an agency or keep our keep trying ourselves? That could be a question, right? Um which agencies in South Yorkshire Yorkshire, I went a bit West Country then, which agencies in South Yorkshire specialise in engineering, right? Consistent name and specialisms win. What do they charge? Contin contingency fees or a retainer? Um what would win that? Publishing your fees, right? So you would have to have your fees published because if your competitors aren't, one of the subqueries would pick up your fees and you may then be referenced in the answer. How do I know they can find a maintenance engineer? So how does how do we know that that particular recruitment business can find me the person I'm looking for? And what will win that query? A named case study with times and dates on it. So if you can demonstrate that you can find maintenance engineers in a particular area, that's how the content would be picked up and you would then be referenced. So think below the query that's getting asked. What if the person leaves after a few weeks? Quite a quite um a regular question that would come up, you know, if you wanted to deal with a recruitment agency. Um, and what would win that? Publishing your rebate terms on your site. And which recruitment agency would you pick for us and why? And what wins it? Reviews that agree with your site. So external reviews on an external site would then pick you up. So what we can see is it's not about these top-level queries. You know, somebody can ask, should we use an agency or keep trying ourselves, looking looking for staff ourselves? Now, you know, if you if you want to win those queries, um that's quite difficult if you don't build the content below it. That's what I'm trying to get across here to you. Think below, think more deeply into what people are searching and how um you can satisfy the query, and it's not about optimizing for the phrase in the first place. Hopefully, I'm making myself clear. So, Google, you know, like to caveat this, Google says it is all just SEO at you as usual, right? Google says we're still in an SEO world, um, and we are to some extent, right? Because we haven't fully gone into um the universe where we are going to end up. So we are we are not fully into uh full AI mode where we end up talking to LLMs, talking to our AI assistants like MuseCharm, etc., and it gives us the answer and we have a proper conversation with it, right? But when we're having those conversations, think about the knowledge that it needs to have behind it. Uh, it's not about a web page that says this is the best recruitment company in Doncaster because somebody created a page saying they are the best recruitment company in Doncaster, it's about uh all of the fan-out queries that you you need to have below it, right? But Google would say a page per fan out variation is spam, and that is true. It's not we're not going back to the good old days where I go and build 50 different web pages just to cover all the individual scenarios, right? Um, Google would call that content abuse, and pages covering every sub question will get cited less, right? You need to cover a solid base and foundation and be cited externally as well. That's one of the obviously one of the most important things that are going to happen, right? Um, AI referrals are still only, and I say still only, around 1% of traffic for most sites. But again, we have said that a massive chunk of the web search that is happening still, even when answered by LLM or AI query, um that's just cutting the dead wood, the traffic that nobody wanted anyway. You know, it's traffic that's not going to convert. So all of that, if you get rid of, I don't know, 75% of the traffic just because it gets rid of all the people that would have landed on your site and never made an inquiry or you weren't a good fit or just bounced, if we get rid of all of that and then we say 1%, that's 1% of 25%, right? So we're now at four or four percent, right? It's only set to increase. So keywords, look, I can't stress it enough. Keywords are no longer the unit of search or value, right? The conversation is what you have to be optimizing for. So a little bit of exercise, something you can do this week that's going to make a difference for you as a business. Start with questions, right? Not keywords. I think I've been clear about that throughout this whole presentation. Record your sales calls, right? Route, write down everything that a customer says in their own words. I've been telling people to do this for years, right? And we're all, maybe we're all a little bit lazy, but um, I have, in a recent example, taken one of my clients. I've taken all of their phone calls for the last six months, downloaded them all, I took out everything that was less than five minutes long. The remaining calls, we transcribed them all, put them into Clawed, and some amazing insights came out of it, right? Not just things where we could learn from which salespeople were working, but all of the questions that people were asking, right? And that is hugely valuable. So then we can build content around that to answer those questions on topic, right, and not trying to be based on keywords or phrases, but based on actual things that your actual customers are saying, right? I can't stress it enough. Record your calls, start with the questions, right? It's not about the keywords anymore. Use the People Also Asked free map pack, right? So within that, you've got People Also Asked, use that as a template. So go in to Google and ask it the questions, look for the People Also Asked section, download every single one of those questions and then draw a line through the ones which aren't relevant to your business, and you'll be left with possibly hundreds that are relevant, right? And you can use that, go and answer those questions in your own words, record that, produce it into pieces of content, publish it, right, and share it, and then you've got a very good chance of covering off a lot of this ground that we've been talking about in this video. Stick to one page for a conversation, right? Put your answer first and then follow up each follow up under it in a heading that is another question. So structure your page correctly, but keep those questions on topic, stick to a theme, um, don't go wandering off into massive subqueries. Keep it succinct and accurate. Um, and accuracy is one of the huge things, right? And most importantly, say things that only you know, right? If you can get stuff, and I say to people, get it out of your head onto paper, right? That would be the old school way of doing it. Get it out of out of your head and onto paper. Well, now we're talking about digitising your knowledge and talk about your prices, your process, things people can do with your products that you know they they might find as an advantage or some way to use it that hadn't necessarily been published. Um put down your numbers and your experience and just give something to the knowledge base. And as we discovered earlier, maybe this was a light bulb moment for an awful lot of you. I can certainly say it was for me when I first found this out. 15% of things that are getting typed into the web on a daily basis have never been typed in before. So think about that for a minute. You can't optimise for all of that, but you can optimise for the subqueries that come below it. So ask it the long way, right? The way your best customer would ask the question. Some people of us, you know, we all can be very guilty of being too close to our own business and thinking like, well, not putting ourselves in the customer's shoes. So ask, ask the questions, go and ask Chat GPT and Gemini and Claude and Perplexity and ask them all the questions that you think that you should come up for and have a look, right? Do you come up? Are you sighted at all? And if not, work out why and who is coming up and why they're coming up ahead of you. Some of the sources that I quoted today are in the blog. I will publish them in my transcript, but I think I've really tried to get to the bottom of this and show you how you need to think more broadly beyond keywords and phrases. And I think that's the lesson for today. Just make sure you are understanding what those subqueries are below a particular one. And if you have to, go back into the video, look at the examples I've given, and hopefully that's useful. I'll see you in the next one. Cheers, guys.