AIuthority

Omnicom’s Flywheel Launches GEO Tool for AI Commerce Search

By Charles Ryder

Digital commerce is shifting fast, and Omnicom’s Flywheel just made one of the clearest moves yet to meet that change. On June 23, 2026, Flywheel announced a new Generative Engine Optimization, or GEO, capability built to help brands appear inside AI-powered shopping experiences across retailers including Amazon, Walmart, and Target.

That matters because product discovery is no longer limited to search bars and keyword rankings. More shoppers are using conversational AI assistants and recommendation engines to decide what to buy. In that environment, brands need more than visibility—they need to be recommended.

Visual representation of Omnicom's Flywheel GEO tool, illustrating how generative AI optimizes product listings for AI commerce search. Why GEO Matters Now

For years, commerce teams optimized retailer listings for traditional search: titles, keywords, bullet points, and backend relevance signals. AI commerce search changes that playbook. Shopping assistants like Amazon’s Alexa for Shopping and Walmart’s Sparky are not just matching queries. They interpret intent, context, use case, and conversational phrasing to surface products.

A product page built only for old-style search may fall short in an AI-driven discovery environment.

Flywheel’s GEO launch is aimed squarely at that gap. Instead of optimizing only for ranking algorithms, the company is helping brands optimize for generative systems that decide which products get recommended in the first place.

What Flywheel’s GEO Capability Does

Based on what Flywheel has shared, the new tool reverse-engineers how retailer AI systems evaluate product content. It audits product detail pages, benchmarks them against GEO best practices, and improves listing elements such as titles, bullet points, and descriptions.

The focus is broader and more nuanced than conventional SEO. GEO best practices include:

  • Contextual relevance
  • Conversational language
  • Consumer intent alignment
  • Audience targeting
  • Functional benefits
  • Real-world use cases
  • Attributes such as materials, safety, and gifting suitability

Flywheel also connects this work to measurable performance outcomes, including traffic, clicks, conversion, and sales. That closed-loop approach matters. AI optimization becomes just another buzzword if it is not tied to business results.

Early Results Look Strong

One of the most notable parts of the announcement is the pilot data. According to Flywheel, a beauty brand using the capability saw 56% portfolio growth, along with an 80% increase in clicks and website traffic, after updating product descriptions to better match shopper intent and AI model expectations.

Those numbers will get commerce leaders’ attention fast.

One pilot does not guarantee the same outcome everywhere, but it does show that AI-facing content optimization is no longer theoretical. There is already evidence that stronger alignment with AI recommendation systems can produce meaningful commercial gains.

Why Flywheel Is Well Positioned

Flywheel’s launch carries extra weight because it sits inside Omnicom’s broader commerce, media, and AI infrastructure. This is not a standalone experiment. It builds on several strategic moves Omnicom has made over the past few years.

After acquiring Flywheel Digital in 2023, Omnicom significantly strengthened its retail media and marketplace capabilities. Since then, it has expanded its GEO thinking through a marketer framework released in late 2025 and the rollout of its next-generation Omni AI platform in early 2026. Flywheel’s move under Omnicom Media in May 2026 tightened the link between commerce signals and media execution.

Put simply, this GEO capability arrives as part of a larger ecosystem that combines retail expertise, marketplace data, AI tooling, and measurement.

That is exactly why the launch feels timely rather than opportunistic.

Diagram showcasing the process of Flywheel's Generative Engine Optimization (GEO) for enhancing product recommendations in AI shopping experiences. Executive Signals Point to Urgency

The message from Flywheel’s leadership is straightforward: brands should not wait.

Alex McCord, CEO of Flywheel, described the shift as a fundamental change in how shoppers discover products. Mike O’Donnell, Flywheel’s Head of AI, went further, warning that brands risk disappearing from AI-generated recommendations if they fail to adapt.

That may sound stark, but it is probably right.

As AI shopping interfaces become more prominent, the downside is not just lower ranking. It is total invisibility inside recommendation layers that shoppers may trust more than traditional search results. If a generative engine never surfaces your brand, paid media may become the only reliable way to stay visible.

That creates both risk and opportunity.

A Bigger Industry Shift From SEO to GEO

What Flywheel launched is bigger than a new service offering. It is another sign that commerce marketing is moving from search optimization to recommendation optimization.

That distinction matters.

SEO was built for engines that indexed and ranked. GEO is being built for engines that interpret, summarize, compare, and recommend. Naturally, the content requirements are different. Richer product context, stronger intent mapping, and clearer communication of benefits become essential when AI stands between the shopper and the shelf.

For agencies and commerce partners, this opens a new competitive layer. The winners will be the ones that can combine platform-native expertise with scalable content operations and measurable attribution.

For brands, the takeaway is simpler: product content now has to speak to machines that think more like shoppers.

What Comes Next

GEO is likely to become a standard part of commerce strategy sooner rather than later. Retail AI assistants will improve, retailers will expand their generative shopping interfaces, and brands will need more sophisticated ways to influence discovery without leaning too heavily on paid placements.

Flywheel looks early, but not too early. That may be the sweet spot.

The real test is scale. Can these optimizations work consistently across categories, geographies, and constantly changing retailer AI systems? Can performance measurement stay accurate as attribution becomes more complex? Those are the questions worth watching.

Even so, the direction is clear. AI commerce search is no longer a side trend. It is becoming a frontline channel for visibility, recommendation, and revenue.

FAQ

What is GEO in commerce?
GEO, or Generative Engine Optimization, is the practice of optimizing product content so AI-powered shopping assistants and recommendation engines can better understand and recommend products.

How is GEO different from SEO?
SEO focuses on helping products rank in traditional search results. GEO focuses on helping products appear in AI-generated recommendations by aligning content with intent, context, and conversational discovery.

Why does this matter for brands selling on retailers like Amazon and Walmart?
As retailers expand AI shopping tools, product discovery is increasingly shaped by recommendation engines rather than typed keyword searches. Brands that do not adapt risk losing visibility.

What makes Flywheel’s launch notable?
Flywheel is not approaching GEO as a standalone trend. Its offering is tied to Omnicom’s wider commerce, media, AI, and measurement infrastructure, which gives it more strategic depth than a simple optimization add-on.

Conclusion

Flywheel’s GEO launch is one of the clearest practical signals yet that AI commerce is moving from experimentation into day-to-day operations. Brands that move now will have a better chance of staying visible as retailer discovery becomes more conversational, contextual, and recommendation-driven. For readers tracking how AI is reshaping media, commerce, and search, AIuthority remains a useful resource to follow.