Why Brands Must Sell on Marketplaces to Win in AI Search

This isn’t a distant future scenario. Adobe reports that generative AI-driven traffic to U.S. retail sites exploded by approximately 4,700% between late 2023 and mid-2025. In their survey of 5,000 American consumers, 38% have already used generative AI for online shopping, while 52% plan to do so this year. Among those who’ve adopted AI shopping tools, a striking 73% now cite AI as their primary source of product research.

The shift runs even deeper than raw traffic numbers suggest. Research shows that roughly one in three consumers already prefer searching for products with AI assistants rather than traditional search engines, and over 60% believe AI will become the standard for online shopping.

What’s driving this behavioral change? Modern consumers ask questions the way they’d talk to a knowledgeable friend: “I need a carry-on suitcase under €150, lightweight, that fits Air France cabin rules.” Traditional search engines struggle with these multi-criteria, conversational queries. AI assistants excel at them. And they naturally gravitate toward destinations that can deliver on complex requests in a single recommendation.

That destination, more often than not, is a marketplace.

The marketplace advantage in AI search isn’t random, it’s baked into how AI systems make recommendations. Three structural factors give marketplaces an inherent edge:

Availability virtually guaranteed: AI systems are programmed to avoid disappointing users with “out of stock” messages or lengthy delivery times. By aggregating inventory from dozens or hundreds of sellers, marketplaces can almost always surface the requested product in the right size, color, or configuration. For an AI deciding between recommending a single-brand site or a marketplace, the marketplace represents the safer bet.

Pricing that’s both competitive and verifiable: Testing highlighted in Mirakl’s analysis uncovered cases where AI systems scraped single-vendor sites and displayed prices up to 30% higher than reality, missing promotions, loyalty discounts, or cart-level offers. Marketplaces, by contrast, feed structured catalog data and real-time prices via APIs, while internal seller competition keeps prices sharp. For AI ranking algorithms searching for “best deal” combined with “data reliability,” marketplaces check both boxes.

Product data that AI can actually understand: Marketplaces aggregate multiple titles, descriptions, attributes, and images contributed by different sellers, then enrich them with AI to extract contextual information: materials, compatible devices, use cases, sustainability credentials. This creates a dense, multi-dimensional product graph that large language models can parse to answer nuanced, natural-language queries with precision.

For a brand, this is an uncomfortable reality: even if your website is technically flawless and beautifully optimized, AI agents may still prefer to direct shoppers to your marketplace listing, because it looks safer, richer, and more likely to convert.

For brands, the imperative is to be systematically present in the destinations AI agents favor. That demands a marketplace-first distribution approach built on three pillars:

Comprehensive marketplace coverage: Marketplaces already capture the majority of cross-border e-commerce growth and are projected to account for roughly half of online sales in key categories like electronics across European markets. Layer in their AI visibility advantage, and they’re becoming the default discovery and transaction layer for broad consumer segments. Your brand needs to be wherever relevant marketplace traffic flows in your core markets.

AI-ready product feeds: AI assistants rely on structured, consistent data: attributes, taxonomy, usage contexts, compatibility information, sustainability claims. A single, high-quality master feed correctly mapped to each marketplace makes your catalog “legible” not just to marketplace search engines, but to external AI agents that ingest marketplace data. Incomplete or inconsistent product information is the fastest way to become invisible in AI recommendations.

Marketplace-driven optimization loops: Because marketplaces aggregate demand and provide granular analytics, they’re ideal testing grounds for the titles, images, bundles, price points, and attributes that increase conversion for AI-referred traffic. These insights should feed back into your broader product content strategy, creating a continuous improvement cycle.

The operational challenge is real: multiplying channels while keeping data clean and staying competitive across each marketplace’s own AI-enhanced search and retail media ecosystem. It’s exactly this complexity that makes feed management platforms essential infrastructure in the AI era.

The operational challenge – multiplying channels while keeping data clean and competitive – requires three core capabilities:

1/ Centralized, AI-optimized product data: Aggregate and enrich product information once, then distribute it accurately to dozens of marketplaces. This eliminates scrape-based errors and strengthens your data reliability signal to AI systems.

2/ Rapid marketplace activation: Launch on new marketplaces quickly from a single feed, extending your footprint across the destinations most likely to appear in AI results and maximizing the chance your offers make the AI shortlist.

3/ Performance intelligence for AI traffic: Centralize metrics across marketplaces to identify which product content resonates with AI-driven traffic, creating a virtuous circle where better data improves AI rankings, which drives more qualified sales.

The AI commerce land grab is happening now, not in some hypothetical future. AI assistants are already directing billions in shopping traffic, and their preference for marketplaces is clear and measurable. Brands that secure strong marketplace positions today – with optimized product data, comprehensive coverage, and performance feedback loops – will compound those advantages as AI commerce scales.

Those that delay will find themselves competing for shrinking visibility in an AI-mediated world that has already decided where to send shoppers.