LMO7 Blog

Amazon has quietly moved from being a search box with filters to something much closer to a personal shopper that knows you, understands products, and is increasingly willing to act on your behalf.

AI Overviews sit above the blue links and often satisfy the query. The job is to be accurately represented inside the summary and make the click you do get convert.

Rufus chooses products it can confidently recommend inside an answer. Proof and structured attributes matter more than loose keyword coverage.

Assistants compress decisions. If your attributes and proofs are explicit and consistent, you get included in the answer; if not, you are skipped.

Black Friday 2025 wasn’t just another record shopping weekend. It was the moment AI assistants - Rufus, Gemini, ChatGPT, Walmart’s Sparky - actually mediated global retail behaviour at scale. Traffic patterns shifted. Conversion curves bent. The majority of product discovery for many categories began inside AI systems rather than search bars. Brands that were prepared won big. Those that weren’t… didn’t appear at all.

If you’re a consumer product brand right now, you’re not just fighting for space on shelves and search results. You’re fighting for space inside AI assistants like ChatGPT, Gemini, Claude, Perplexity, Amazon Rufus and whatever lands next.

LMO7 exists for that world.

Why a single “SEO plan” no longer cuts it and how to win across Traditional, Retail, Social, and AI search.

A simple test every brand should run today.

Semantic collision is when models (and people) confuse two meanings of the same word or two near-identical entities.

AI search is reshaping how people discover brands. ChatGPT, Gemini, Claude, Perplexity, and Amazon’s Rufus now sit beside (or even ahead of) Google in the consumer journey. That means brands need a new kind of visibility strategy — one built for LLMs, structured answers, and machine-readable content.

Here’s a simple roadmap that any brand can start using today, as shared by Jonny Bentwood at Golin. Profound Zero Click Conference, Nov 2025.

TechCrunch covered Google’s latest AI shopping update: conversational shopping in Search, new shopping flows in Gemini, agentic checkout, and an AI that literally phones local stores to check stock for you.

With Sponsored Products prompts and Sponsored Brands prompts, Amazon has moved from “ads in Rufus” to ads made out of Rufus.

TL;DR. A9 helps you get found; Rufus helps you get recommended. Optimise for answer inclusion, not just rank. Focus on questions, outcomes, proofs, and cross-surface consistency.

AI at retail is a two-engine game: data to train on and compute to process it. Amazon has both at world scale, its retail graph (first-party + marketplace signals) and AWS (the world’s leading cloud). Add a native shopping model (Rufus) that already lives inside the store, and Amazon’s path to winning AI Search + Retail looks structurally advantaged.

ChatGPT has revolutionised online shopping habits completely. People used to search "best bed sheets" on Google and scroll through links or Shopping ads last year. Now they ask ChatGPT directly: "I sleep hot and have sensitive skin. Can you recommend some breathable bed sheets that won't irritate me?"

Fresh tracking shows Google still dominates referral traffic by a huge margin, but it’s edging down, while ChatGPT’s share (still tiny) keeps compounding. For CPG, that means you cannot ignore AI assistants: treat Answer Engine Optimisation like product work, not blog work.

Lexem.io is LMO7’s query-clustering engine. You start broad (category, geography, funnel stage), add your high-converting keywords, and the tool generates human-validated, AI-expanded prompt sets grouped by intent. You curate, save, visualise as clusters, and extend them into prompt paths that mirror how shoppers move from research → comparison → purchase. These sets then power our Share-of-Model tracking and your content, PDPs, FAQs, and retail media.

Amazon just put hard numbers behind AI shopping. In Q3, Andy Jassy said Rufus, the AI assistant inside Amazon’s store, has 250 million customers using it this year. Shoppers who use Rufus are 60% more likely to complete a purchase. Monthly users are up 140% year-on-year, interactions are up 210%, and Rufus is on track to drive more than $10B in incremental annualised sales.

Most product journeys now bounce across open search, a chat assistant to clarify, and a marketplace to check out. Recent studies show AI assistants are rapidly becoming one of the most influential shopping touch points (second only to search engines in some research), and they often hand off to retailer sites or marketplaces for the final purchase.

Short version: In Answer Engine Optimisation (AEO), guesses don’t move revenue—experiments do. A hundred “answers” you publish without a control tell you nothing. A hundred you publish with a proper control, repeated across cycles, tell you what actually causes lifts in Share of Model, traffic from AI, and sell-through.

Rufus is now widely available in the U.S., U.K., Canada, India, Japan and across major EU5 markets, with desktop + mobile app support in each of those regions (most moved from beta to general availability during 2025). Expect further rollouts to remaining Amazon marketplaces (e.g., Australia, Mexico, Brazil, Netherlands, Sweden, Poland, UAE, Saudi Arabia, Turkey, Singapore) as Amazon targets “at least 13” additional markets beyond the earliest launches.

Ahrefs’ latest analysis finds that AI Overviews appear on ~16% of US searches, that position #1 loses ~34.5% of clicks when an Overview shows, and that assistants can answer directly—often without linking. In short: classic SEO still matters, but you also need to earn a place inside AI answers.

Consumer brands don’t need another generic “full-service” shop; you need a crew that’s lived inside the Amazon flywheel, understands how CPG actually sells, and builds for AI surfaces first. LMO7 was designed that way from day one: operator-led, AI-native, and tuned for speed.

AI search compresses CPG choice into a 1–3 product shortlist, so small ranking gains now drive outsized repeat orders. LMO7 makes your PDPs and D2C pages machine-readable, aligns them to real buyer prompts, and runs weekly optimisation loops so you stay in the answer set.

According to a new case study from Seer Interactive, traffic referred from ChatGPT converted at 15.9%, compared with 1.76% from Google Organic.
That’s a 9× lift in conversion rate. Small volume, but huge intent.

It’s an early glimpse into how AI-driven discovery behaves differently from traditional search.

What it is, why it matters, and how to win the new shelf space

TL;DR: Amazon doesn’t need a deep pact with ChatGPT because it already owns the data, the compute, and the last mile. That means your AI shelf-space on Amazon will be decided increasingly inside Amazon, by Rufus. If you sell on Amazon (or drive demand to Amazon), your growth lever isn’t chasing external assistants, it’s making your PDPs the easiest thing for Rufus to recommend with confidence.

According to Similarweb’s 2025 eCommerce report, referrals from ChatGPT now convert at roughly double the rate of organic search — and Amazon consistently leads among retailers capturing that traffic.

Most consumer brands treated SEO as a setup task, not a growth driver but that’s changing fast. As discovery shifts into AI systems like ChatGPT, Perplexity, and Rufus, the same SEO fundamentals now determine whether your brand ranks in Google or appears in the top answers in chat.

Search is shifting from rule based to probabilistic. Google still retrieves; ChatGPT predicts. For brands, visibility now depends on influencing how AI thinks, not just how it searches.

What OpenAI’s Apps SDK Means for Brands, Discovery, and the Future of eCommerce

The brands that adapt now will own the agent-era shelf space. Everyone else risks becoming a nostalgic case study in “how e-commerce used to work."

Most of the noise around Generative Engine Optimisation (GEO) and visibility in Large Language Models (LLMs) has focused on “hacking” the models themselves nudging prompts, seeding Reddit threads, or gaming Q&A sites. But the truth is far more straightforward.

As AI-powered search and conversational tools like ChatGPT become more central to discovery, content visibility isn’t just about Google any more. One name that keeps cropping up in recent research is Bing. Not just as a secondary search engine, but as a primary lever for being cited in AI answers.

AI has become cheap, fast, and most importantly approachable. We’ve quietly crossed a threshold: intelligence is no longer scarce. What happens when billions of people suddenly gain access to powerful cognitive tools? The early signs are both exhilarating and unsettling.

For much of its early history, artificial intelligence carried three stubborn labels: expensive, energy-hungry, and complex to use. The most powerful models were locked behind paywalls, the environmental footprint raised eyebrows, and even experienced users struggled to make sense of model choices. That story is changing fast.

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.