Michaels tested a Google Gemini-powered AI assistant on its site and reported a 2x conversion rate lift over traditional search results, according to Digiday. The craft retailer didn't release absolute conversion figures, but the doubling signals that conversational product discovery—properly executed—moves shoppers from browsing to buying faster than keyword matching alone.
The mechanism is straightforward: instead of typing "red paint" and scrolling through 400 SKUs, a shopper asks "what paint should I use for outdoor metal furniture?" The AI assistant narrows the catalog by use case, substrate, and durability, then surfaces three or four products with explanation. Michaels reported the assistant also increased average order value, though the company did not quantify the lift. The gain comes from the assistant recommending complementary items—brushes, primer, sealant—in context, rather than hoping the shopper notices a static "frequently bought together" module.
The underlying play works because physical products carry implicit questions that keyword search cannot answer. A shopper searching "acrylic paint" may need student-grade bulk or archival artist tubes; traditional search returns both and forces the shopper to filter manually. Conversational AI routes by intent in the first exchange, collapsing five clicks into one answer. For categories with high SKU counts and meaningful attribute differences—art supplies, hardware, pet products, supplements—the time saved directly correlates with completed purchases.
Smaller brands cannot deploy Google Gemini enterprise licensing, but they can replicate the conversion mechanism using accessible tools. Start with a product quiz or chatbot—Typeform, Landbot, or Octane AI all offer low-code interfaces—and script three to five questions that divide your catalog by the attributes that actually matter to your buyer. If you sell coffee, ask brew method first (espresso, pour-over, French press), then roast preference, then quantity. Each answer narrows the catalog. At the end, display two or three products with a one-sentence explanation tied to their answers: "This medium roast works in your Aeropress and ships in 12-oz bags."
Cost for a small brand: Typeform starts at $25/month for basic logic jumps; Octane AI runs $50/month with Shopify integration and conditional product recommendations. Build the quiz in an afternoon using your five most common customer questions from email or support tickets. Embed it on your homepage or run it as a pop-up for first-time visitors. Track conversion rate for quiz completions versus site average—if Michaels saw 2x, a small catalog with tighter attribute mapping can expect 1.5x to 2x as well, because the shopper never faces choice paralysis.
The broader pattern is that search works when the shopper knows exactly what they want; conversation works when they know the outcome but not the product. Physical goods live in the second bucket more often than digital. The brand that narrows the catalog for the customer, rather than asking the customer to narrow it themselves, wins the sale before the competitor's page even loads.
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AI assistants have quietly taken over the first step of buying — they answer from catalogs they can read and shortlist whoever can actually ship. Two questions now decide whether you exist to that buyer: can a machine read your catalog, and can you fulfill the order. Most brands fail one or both and never find out why the orders went elsewhere. The winners of this shift aren't the loudest. They're the most readable. Build for the machine that's about to do the shopping.
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