The Search is Over: Flywheel's GEO Targets AI-Driven Commerce

CANNES, France – June 23, 2026

In the world of e-commerce, visibility is currency. For years, the undisputed king of visibility has been Search Engine Optimization (SEO), a complex art and science dedicated to climbing the ranks of search results. But as generative AI begins to weave itself into the fabric of online shopping, a new contender for the throne has emerged. Today, Flywheel, the commerce and technology arm of media giant Omnicom, announced a new capability that signals a fundamental shift in how brands must compete online: Generative Engine Optimization (GEO).

Launched from the epicenter of creative marketing at Cannes, Flywheel's GEO capability is designed to help brands earn recommendations within the AI-powered conversational experiences now being deployed by retail titans like Amazon, Walmart, and Target. It’s a move that acknowledges a stark new reality: the future of product discovery may not be a list of blue links, but a conversational recommendation from an AI assistant.

"As product discovery rapidly shifts toward AI-driven shopping experiences, brands need to rethink how they appear in these environments," said Alex McCord, CEO of Flywheel. "Flywheel sits at the intersection of retail expertise, commerce data, AI enablement, and scaled execution, which uniquely positions us to help brands optimize for how AI-powered commerce ecosystems actually work."

From Search Engine to Recommendation Engine

The pivot from SEO to GEO represents more than just a new acronym; it’s a paradigm shift in strategy. Traditional SEO focuses on optimizing product detail pages (PDPs) with specific keywords to match user search queries. Success is measured in rankings, clicks, and traffic. GEO, however, plays a different game. Its goal is not just to be found, but to be chosen—by an AI.

As shoppers increasingly ask conversational questions like, "What's a good gift for a coffee lover under $50?" or "Find me a waterproof, breathable running jacket for mild weather," AI systems must synthesize information from countless products to provide a single, curated answer. They evaluate products on criteria far more nuanced than keyword density. These new algorithms prioritize contextual relevance, conversational language, and a deep understanding of consumer intent.

This evolution presents a clear and present danger for brands still clinging to old SEO playbooks. Existing tools and manual audits often fall short in this new environment, unable to measure or improve performance within generative AI. The risk is not just a lower ranking, but total invisibility.

"The GEO conversation is evolving quickly, but brands cannot afford to wait," warned Mike O'Donnell, Head of AI at Flywheel. "Without action, products risk disappearing from AI-generated recommendations, reducing organic traffic and increasing dependence on paid media to maintain visibility."

Reverse-Engineering the AI Black Box

Flywheel's answer to this challenge is a solution built on a simple but powerful premise: reverse-engineering the AI. The company's GEO capability is an integrated workflow that combines AI-powered auditing, content optimization, and performance measurement to decode what makes a product appealing to a recommendation engine.

The process begins by evaluating a brand's product content across retailers and benchmarking it against GEO best practices derived from analyzing AI behavior. The system identifies gaps in content that go beyond simple keywords, looking for missing signals that are critical for contextual understanding. This includes information like gifting context, age appropriateness, material composition, and safety information—details that help an AI confidently recommend a product for a specific use case.

Once gaps are identified, the system optimizes product titles, bullet points, and descriptions. It enriches them with conversational language, highlights functional benefits, and tailors the content to specific audiences and uses. The goal is to create product listings that speak the language of the AI, providing the rich, structured data it needs to make an informed recommendation.

"What makes this capability different is its focus on platform-native AI optimization," said O'Donnell. "We are connecting content, AI discovery, and business outcomes in one integrated solution that combines audit, activation, and measurement."

Early results suggest the approach has significant merit. In a pilot program for a beauty brand, Flywheel reported that its GEO-driven refinements drove 56% portfolio growth and an 80% increase in clicks and website traffic. By aligning product descriptions with consumer intent and the logic of AI models, the brand didn't just improve its visibility; it drove tangible business outcomes.

A New Arms Race in Digital Commerce

Flywheel’s announcement is a major development in what is becoming a new arms race for digital shelf space. The industry is buzzing with similar concepts, from Answer Engine Optimization (AEO) to Large Language Model Optimization (LLMO), all pointing to the same conclusion: optimizing for AI is the next frontier. Brands that adapt will gain a significant competitive advantage, while laggards will be left fighting for relevance in a shrinking pool of organic search traffic.

This technological shift is happening in lockstep with changes in consumer behavior. Shoppers are rapidly adopting generative AI tools for everything from meal planning to vacation booking, and their expectations for personalized, efficient e-commerce experiences are rising. Retailers are racing to meet this demand, pouring investment into proprietary AI assistants and agentic commerce capabilities designed to streamline the path from discovery to purchase.

The implications are profound. The digital shelf is no longer a static grid of products but a dynamic, conversational space. For brands, this means that product content is no longer just marketing copy; it is a critical dataset for training the AIs that will soon mediate a vast portion of online commerce. Winning in this environment requires a deep, technical understanding of how these systems work and a strategic commitment to feeding them the right information.

The Omnicom AI Play

This launch is not an isolated move but a calculated piece of a much larger strategy for parent company Omnicom. The global advertising and media holding company acquired Flywheel in early 2024 for a reported $835 million, a clear bet on the convergence of media, data, and commerce. Flywheel's GEO capability is a key deliverable on that investment, positioning Omnicom as a leader in the next generation of commerce marketing.

The solution is the latest addition to a global portfolio of GEO services at Omnicom that already spans media and public relations. It's designed to integrate with Omni, the company's proprietary data and intelligence platform, which powers its various media and creative agencies. By connecting Flywheel's granular product and transaction data with Omni's vast audience and behavioral data, Omnicom is building an end-to-end ecosystem for navigating the AI-driven world.

Megan Pagliuca, Chief Product Officer at Omnicom Media, framed the strategic value of the new offering. "By combining AI precision with deep retail and category expertise, Flywheel is helping brands adapt in real time to the changing dynamics of commerce and make smarter decisions that drive growth across retail channels."

This aggressive push into AI-powered commerce demonstrates Omnicom's ambition to provide its clients with the tools to compete not just in today's market, but in the one that is rapidly taking shape on the horizon.