Insights on AI-powered marketing, GEO optimization, and getting your brand recommended by AI assistants.
As AI systems learn to see, hear, and understand context the way humans do, e-commerce brands face a defining choice: optimize for the new discovery layer or become invisible to it. This guide breaks down what multimodal AI search is, why it's reshaping product discovery, and exactly what brands need to do to stay competitive.
Hexagon analyzed 50,000 AI shopping citations across ChatGPT, Claude, and Perplexity to uncover the six signals that determine which brands AI engines recommend—and which brands remain invisible. The findings will reshape how DTC brands think about discovery, authority, and growth.
Over 90% of e-commerce marketers can't define the AI search terms shaping their industry—here's the practical glossary your entire team needs to compete in 2025 and beyond.
58% of consumers now use AI-powered tools to research products before buying online. If your competitive strategy still relies on traditional SEO tools, you're measuring the wrong game—and losing revenue to competitors who aren't.
An estimated 85% of mid-market e-commerce brands are systematically invisible to AI assistants that now influence 58% of consumer purchase decisions. Here's the structural reason why—and a four-phase roadmap to close the gap before the competitive window closes.
AI shopping assistants are actively parsing, synthesizing, and ranking your customer reviews to power product recommendations. Here's what brands need to know—and do—to win in the $1.2 trillion AI commerce opportunity.
Fifty-eight percent of young U.S. consumers now use AI assistants to research products before buying—yet most e-commerce brands have zero control over how AI systems represent them. Learn how llms.txt closes that gap and why early implementation is a competitive advantage that's closing fast.
When customers ask AI assistants for product recommendations, the same handful of brands appear again and again—not by accident, but by design. Here's what's driving the most concentrated marketplace in e-commerce history, and the strategic playbook for emerging brands to compete before the window closes.
Most e-commerce brands are optimizing for a search paradigm that's already obsolete. Here's what multimodal AI search actually rewards—and how to build the content foundation that wins AI-driven discovery.
AI recommendation engines are projected to influence $1.2 trillion in e-commerce revenue by 2026. Here's what e-commerce marketers need to understand about AI search user intent—and how to structure content that earns recommendations at every stage of the customer journey.
In 2025, generative AI has become the dominant product discovery engine for consumers aged 18–45—yet just 2% of brands capture approximately 80% of all unprompted AI recommendations. This post breaks down why the citation economy works the way it does, which authority signals drive it, and what CMOs must do in the next 18 months before competitive positions lock in permanently.
In 2024, AI tools reshaped how consumers discover and buy products online—but the hidden engine powering those recommendations is one most brands are still overlooking: customer reviews. This guide decodes exactly how AI systems analyze, rank, and act on review data, and what e-commerce brands must do to win visibility in AI-mediated commerce.
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.