LMO7 Blog

When marketers think about optimisation, titles and meta descriptions usually get all the attention. But there’s another element, often overlooked, that plays a major role in both SEO and AI-driven visibility: the slug.

Crafting content that wins citations in AI-powered search isn’t just about keywords anymore. The new battleground is matching both intent and signal strength through title, slug, and language precision

What really moves the needle in AI-driven search visibility?

When the web became searchable, Google transformed information into a utility. Fast, frictionless, universal. Today, something similar is happening with artificial intelligence. Worldwide Intelligence is the idea that AI is no longer a niche tool for experts or a costly luxury for enterprises. Instead, it is becoming as accessible and indispensable as a search bar. GPT-5 sits at the heart of this shift, pushing AI toward mass adoption in ways earlier generations only hinted at.

For years, site owners have optimised for two audiences: humans and search engine crawlers. But now a third audience is here. AI crawlers powering systems like ChatGPT, Claude, and Perplexity.

The challenge? AI crawlers interact with websites differently. They don’t execute JavaScript, they prefer compressed and concise information, and they demand speed. The solution lies in a niche but powerful discipline: Edge SEO.

Google’s Gemini app has just received a juicy new upgrade: Gemini 2.5 Flash Image, nicknamed “Nano Banana.” This update brings powerful, intuitive editing tools that unlock creative possibilities, all through natural language prompts.

Resoneo Study: “How People Really Interact with ChatGPT – Analysis of 87,725 Public Conversations.” This remarkable dataset is made possible by users who shared their ChatGPT dialogs publicly via the platform’s sharing feature, providing a rare, behind-the-scenes glimpse into real conversational behaviours.

You should think about AI search visibility the same way high-growth companies look at marketing channels: as a portfolio of experiments.

ChatGPT, Perplexity, Gemini, Claude.
They’re starting to recommend products and link to sites. The problem?
Google Analytics doesn’t show “AI search” traffic out of the box.

Once you’ve got your LLM tracking data in hand, the question is simple: now what? If you stop at “we measured it,” you’re leaving influence and traffic on the table. Here’s how to turn raw tracking data into brand visibility in ChatGPT, Perplexity, Gemini, and other AI search tools.

OpenAI has just rolled out GPT-5, and while most of the headlines are about its speed and smarts, there’s a change under the hood that’s a big deal for anyone in marketing, especially if you care about product discovery and brand visibility.

At LMO7, we spend a lot of time helping brands improve their visibility inside platforms like ChatGPT and Perplexity. But one of the most important and overlooked questions is this:

Where do these platforms actually send people once your brand gets mentioned?

In the world of search and eCommerce, we’ve been trained to believe that higher visibility is always better. More impressions. More clicks. More conversions. But what if there are cases where you actually want your product to rank lower?

We're sharing a powerful and surprisingly simple new tactic that any brand can use: Prompt-to-Rank.

So how does Rufus actually “understand” shopper queries and respond with helpful, relevant answers? The answer lies in semantic similarity models. Algorithms designed to match what a user means with the most relevant product or answer available.

AI-powered shopping is rewriting the rules of product discovery. Whether it’s Amazon’s COSMO, ChatGPT’s shopping recommendations, or other large language models (LLMs), the way your product detail page (PDP) is read, understood, and ranked is now based on meaning, not just keywords.

The goal: Make your listing so clear, relevant, and compelling that AI knows exactly when to recommend you.

Amazon’s research paper, “A Shopping Agent for Addressing Subjective Product Needs”, unveils how its conversational assistant Rufus leverages GenAI to help customers find products that align with feelings, contexts, and personal scenarios, not just specs and keywords. We provide and overview of the paper and why it matters for brands.

Voice search is no longer a novelty. It is becoming the default. With over 1 billion voice searches made every month and over 50% of U.S. adults using voice search daily, the way we interact with the web is shifting fast. But this change isn’t stopping at “Hey Siri, what’s the weather?” It’s heading straight into the world of eCommerce and not in isolation.

Amazon search is no longer just about matching keywords. It’s becoming more semantic, contextual, and intent-driven—and two of the most important systems shaping this shift are A9/A10 and COSMO. But what exactly are they? How do they interact? And what should brands optimise for?

COSMO (Common Sense Knowledge Generation and Serving System) is an industry‑scale system created at Amazon to automatically build common sense knowledge graphs that capture what shoppers really intend, not just what they type or click.

Most brands obsess over the written word when it comes to AI visibility. Product titles, bullet points, backend keywords, FAQs. But here's the overlooked truth: AI doesn't just index text. It scans your images too. And just like your copy, your visuals need to be optimised for machines as well as humans.

As LLM-powered chatbots (ChatGPT, Perplexity, and Copilot) reshape how audiences discover information, understanding what content they cite and why becomes crucial.

Growth Memo analysed 1,600+ URLs and 7,000+ citations. The findings? Classic SEO (backlinks, rankings) barely matters for LLM visibility. Instead, success comes down to: Depth & Comprehensiveness, Readability and Brand Recognition.

Amazon’s AI revolution is in full swing. With Rufus delivering conversational recommendations and COSMO powering intelligent search intent, alongside the evolving A10 system, sellers must adapt strategies to remain competitive.

Amazon has launched a feature that could change the future of online shopping. The new “Buy for Me” service, now rolling out in the US, acts as an AI shopping agent, not just helping you find products, but purchasing them from other retailers’ websites without you ever leaving the Amazon app.

Learn how to get ChatGPT to recommend your brand

The upcoming release of OpenAI’s GPT‑5, expected this summer 2025, promises a revolutionary shift in how people discover brands online. With its advanced capabilities in language understanding, reasoning, and multimodal input, GPT‑5 isn't just another upgrade, it's a potential game changer for eCommerce brands.

As AI reshapes how we search, businesses are adapting fast. Here is a compilation of key remarks from US public firms, highlighting how they’re navigating this seismic shift, from classic SEO to AI and “generative search.”

One of the biggest shifts happening under the hood of platforms like ChatGPT, Perplexity, Google, and even Amazon’s Rufus is synthetic query generation. It’s a powerful concept with real implications for brands who want to be discoverable in the new era of AI-driven search.

Ahrefs’ study of 75,000 brands analysed through its Brand Radar tool shows that off‑site brand presence trumps traditional SEO when it comes to being cited in Google’s AI Overviews.

In a recent episode of The Joe Rogan Experience, Replit CEO Amjad Masad laid out what might be the most important entrepreneurial shift of the decade: AI is becoming a cofounder. Not metaphorically—literally. With tools like Replit’s Agent v2, you can now describe an app in plain English and have it built, deployed, and iterated without writing a line of code.

Kevin Indig analysed 7,000+ AI-driven citations in ChatGPT, Perplexity, Gemini, and more to identify what makes content stand out in generative search results. His findings, published in Growth Memo, challenge traditional SEO wisdom and offer a fresh playbook for content strategy (growth-memo.com).

In the age of AI-powered chatbots and LLMs like ChatGPT, Perplexity, Gemini, and Microsoft Copilot, Answer Engine Optimisation (AEO) is rapidly emerging as a new discipline, evolving from traditional SEO strategies. Rather than targeting single keywords, AEO focuses on optimising entire clusters of commonly asked questions, delivering specific, authoritative answers that can be cited by AI chat interfaces.

If a challenger brand asked us how to transform their visibility in LLMs, then this is what we would do.

Traditional e‑commerce giants like Amazon, Walmart and Best Buy are no longer safe in their silos. As LLM‑powered shopping experiences like OpenAI, Gemini, Perplexity, and Grok grow, shoppers are skipping homepages and landing directly in AI chat interfaces.

As LLMs begin to shape brand visibility across search, chat, and commerce, understanding how you’re seen and whether you’re being seen at all is no longer optional. It’s essential.

In the world of AI search, the tidy buckets we once used to define user intent are breaking down. Welcome to the era of intent collapse and with it, a new challenge for brands trying to stay visible and relevant.

There’s a hidden layer behind Google’s new AI Overviews, and it’s quietly reshaping how organic results are generated and how brands need to think about visibility.

New data from a dataset of tens of millions of real ChatGPT prompts reveals something fundamental: we’ve entered the generative era of search. And it’s already rewriting the rules for content, commerce, and brand discovery.

If you want your brand’s content to be understood not just by users, but by search engines and large language models, then Schema.org should be in your toolkit. At LMO7, we specialise in helping challenger brands win visibility in AI-first interfaces. This post explains what Schema.org is, why it matters, and how to get started.

AI agents are starting to change how we shop, from discovery to delivery. But how far along are we, really? Drawing on Scot Wingo’s framework from Retailgentic, here’s a simplified take: three key stages in the rise of agentic commerce.

How voice-activated shopping is changing consumer behavior and what brands need to do to capitalize on this trend.

A comprehensive analysis of the leading agencies helping brands optimise for AI visibility and LLM performance, with special focus on Amazon optimisation capabilities.

Master the technical implementation of schema markup and structured data to enhance AI understanding of your Amazon product listings.

Leverage artificial intelligence to maximize your Amazon advertising ROI with data-driven bidding strategies.

A short guide to ensuring your brand appears accurately in ChatGPT, Claude, and other AI model responses.

How artificial intelligence is reshaping Amazon search algorithms and what brands need to know to stay competitive in 2024 and beyond.

Learn how to establish your brand as an authoritative entity in knowledge graphs and AI systems through strategic digital presence optimization.

Learn how to structure product Q&A sections to maximise visibility and accuracy in Amazon's Rufus AI shopping assistant responses.

Discover how to measure and enhance your brand's visibility in AI shopping assistants with LMO7's comprehensive LLM Visibility Index framework.

Learn how semantic competitive analysis provides deeper insights than traditional methods in the age of AI-driven commerce. LMO7 explores AI-focused competitor research.

Prepare your brand for success in the AI-driven commerce landscape. LMO7 presents a comprehensive strategic framework for UK businesses entering the AI commerce era.

Learn how to create a cohesive content ecosystem connecting Amazon listings with your website for maximum AI visibility. LMO7 explores building semantic bridges.

Optimise product Q&A content for both AI understanding and customer conversion. LMO7 explores strategies for creating authentic responses that trigger Rufus recommendations.

Great for merchants, marketers, or anyone curious about how to get their products noticed via ChatGPT’s new product-discovery features.