Hello and welcome back. It’s Paul here from Neural Adx. I’m now going to take you through explaining how to apply fluency to your website content in regards to Generative Engine Optimisation. So, I’m now going to take you to my website page, which is www.neuraladx.com where I have my guide on, how to do generative engine optimisation. I cover the seven core factors and in them, one of them is being the topic of this video, fluency. So I’m just going to run through that with you, so you can generally absorb in your mind exactly what fluency in the context of generative engine optimisation means, okay, because I think this will be really helpful for people because quite a lot, almost everyone I speak to doesn’t exactly know what it is, so I know this will be helpful. So if we look at fluency in the GEO context by definition. GEO fluency refers to how smoothly, clearly and naturally your content reads. Fluent content is easy to understand, free of awkward phrasing and flows logically from point to point. And of course, this matters because all generative engines such as ChatGPT, Perplexity, Claude and Google AI mode etc prioritise content that is readable, coherent and engaging. So, it’s very sort of common sense in that it’s prioritising content that is going to be easy for a user to comprehend. Simple as that, now, in order to achieve the fluency, you need to write with clarity and simplicity. So, we’ve got example here. First of all, you want to use short, direct sentences. So, if you’re writing about a particular topic, that might be multiple chunky paragraphs, you want to deduce that into a maximum of maximum paragraph size of three sentences. That’s just the preference of the generative engines and, again, it makes a lot of sense in terms of, from a psychological point of view, it doesn’t overwhelm the user. So that’s the theory. Okay an example of this, as we’ve got here, is from a not-so fluent bit of intel. It would say that implementation of generative engine optimisation strategies can, if necessary, if executed properly, result in a significant increase in the visibility of your content. Okay? Sounds quite intelligent, but where it’s deduced into being fluent is as follows. Generative engine optimisation can make your content more visible when done well. Now, I know it almost sounds like, sounds like you’re dumbing it down. Well it’s not sounds like it kind of is, isn’t it really? But you’re getting to the essence of it. it’s effortless to comprehend, ergo fluent for the majority of us. Taking into the consensus everybody that could potentially read this from all different environments. And origins. So that’s why it has that theoretical foundation as a core. The next point to consider is avoiding jargon. Unless your audience is highly technical. So, an example of this is, synergistic paradigms with working together effectively. So, again, as you can see here, and it is just stepping down the complexity of terminology to make it fully, you know, instantly understandable to the masses, okay- So moving further along, we then have to consider the aspect of fluency being ensuring that there’s a logical flow and coherence. So you’ve got sort of three strategic options of implementation here. You can go for option one, which is cause and effect evidence. So this is a classic structure that AI systems like to latch onto. An example of this is. Generative engines prioritise sources that can verify quickly. When a page uses clear citations and structured headings, its claims become easier to validate. This is why recent studies in AI retrieval evaluation show higher citation rates for pages with transparent provenance, and then it’s got the citation in it. So if you can see the construction of this small paragraph is in alignment with cause, effect, and evidence. So, the cause being generative engines prioritise sources they can verify quickly. When a page uses clear citations and structured headings, it’s its claims become easier to validate. This is why recent studies in AI retrieval valuation show higher citation rates for pages with transparent provenance. So if you can see you can kind of have a separation of the three. So the cause is generative engines prioritise sources they can verify quickly. So the effect, when a page uses clear citations and structured headings, it’s claimed to become easier to validate. Then the evidence, this is why recent studies in AI retrieval evaluation show higher citation rates for pages with transparent provenance, and then it’s got the citation in there. So, as you can see, here, you’re establishing the cause, you’re naming the effect, then you’re grounding it with a citation at the end. AI can follow the pattern. We then have option two, which is the strategy of problem, mechanism and solution. Okay.  AI engines love predictable rhetorical structure. So an example of this would be "many websites fail to appear in AI answers because their information architecture is fragmented". Okay, so we’ve covered the part one, the problem, then we’re moving into the mechanism. "A generative model can’t scan Meaningfully, if the content jumps between topics" and then the solution is about to come in, "a properly structured geo-article uses topic clustering, definition, evidence, application and examples to form the coherent map the model can traverse, increasing the odds of it being retrieved. So, as you can see, we’re measuring the way this sequence mirrors how AI models break down text internally in their processing.  Then we have option three that you can utilise, if it’s easier for you perhaps, which is concept sample and application. So, this is coherence on training data steroids. AI engines have seen this structure millions of times. So, yeah, it’s a favourite of AI engines we could say. So we start off with the concept. So in this example, "source diversity refers to the range of external authority cited on a page". There’s your concept. Now we’re moving into the example. "For instance, combining data. So from the Office of National Statistics, Ofcom and Stanford offers geographical and disciplinary spread." That’s the example. Now we move into application. "Generative engines treat this as a signal of breadth, increasing the likelihood of selection in multi-step reasoning chains."  So concept, then example, then application. Now, I know if you’re watching this video, a lot of that can sound a bit, sort of complex shall we say. But, the best thing to do would just be to select one of those options and manually apply it. And once you’ve done it two or three times, very, very quickly, the mind updates and gets used to it and it becomes quite effortless in doing your writing. The resources for this are on my website, which is www.neuraladx.com. And I have a hub page there explaining the seven core factors of generative engine Optimisation, how to do it, plus other information on how to optimise your website for different AI platforms like chatGPT,  Grok 4 and Google AI mode. And I’m going to be adding more as I continually learn more techniques, see they work, and then I’ll update it on the website. Okay. All right. Well, I hope that has been helpful for you. And as always, I look forward to seeing you in the next one. Goodbye.