Insights on AI-powered marketing, GEO optimization, and getting your brand recommended by AI assistants.
When a consumer asks ChatGPT to recommend the best sustainable running shoe brand, does your company even exist in the answer? For the vast majority of e-commerce brands launched in the past two years, the answer is a silent, invisible no—and the clock to change that is already ticking.
Hexagon's analysis of 50,000 AI-generated shopping recommendations across ChatGPT, Perplexity, and Claude reveals that the brands winning in AI-powered discovery aren't the ones with the biggest SEO budgets—they're the ones who understood the rules changed first.
AI search is projected to influence $54 billion in U.S. e-commerce revenue in 2026—but only four platforms are generating meaningful sales. Here's the data-driven framework brands need to stop spreading resources thin and start capturing disproportionate AI recommendation share before the first-mover window closes.
An estimated 82% of e-commerce brands are completely invisible to AI assistants like ChatGPT, Perplexity, and Gemini—not because of product quality, but because of a structural training data crisis that's about to get worse. Here's what's causing it, who's most at risk, and exactly how to fix it before the 2026 training cycle locks you out permanently.
Your brand ranks on Google, drives traffic, and converts customers—yet AI assistants act like you don't exist. This isn't a visibility problem. It's a structural training data problem, and understanding it is now a commercial imperative.
AI-powered product discovery now influences over $1 trillion in annual e-commerce revenue—yet 85% of brands receive zero mentions when consumers ask AI assistants for recommendations. This isn't a product quality problem. It's a training data architecture problem, and understanding it is the first step to solving it.
In 2024, AI engines quietly rewrote the rules of brand discovery. Hexagon's analysis of 100,000 citation instances reveals the exact trust signals separating the 7% of brands capturing 64% of all AI recommendations—and the actionable framework to join them.
For the first time, a systematic analysis of 100,000 AI citations across ChatGPT, Perplexity, Claude, and Google AI Overviews reveals the authority signals that determine which e-commerce brands AI recommends—and which it ignores.
A structural economic phenomenon is quietly reshaping how consumers discover products. AI recommendation concentration has reached a Gini coefficient of 0.82—more unequal than U.S. household income—and the brands that act now will build moats that compound for years. Here's what every CMO needs to understand before the window closes.
Your e-commerce brand is invisible to AI—and the clock is ticking. This guide breaks down exactly why 85% of post-2020 DTC brands have zero representation in major AI language models, and delivers the specific six-month playbook to fix it before the next training run locks in the competitive landscape for years.
Hexagon analyzed 100,000 citations across ChatGPT, Perplexity, and Claude to uncover the measurable signals driving brand authority in generative search—and found a 38% optimization gap that most brands haven't even identified yet.
A six-month analysis of 50,000 AI shopping recommendations across ChatGPT, Perplexity, and Claude reveals that brand visibility in generative AI is determined by seven measurable, replicable signals—not ad spend or company size. Here's what separates the brands winning AI recommendations from the 92% that remain invisible.
Hexagon helps brands optimize for AI search engines and get recommended by ChatGPT, Perplexity, Claude, and Gemini. Our blog covers Generative Engine Optimization (GEO), AI marketing strategies, and how to improve your brand's visibility in AI-powered search results.