Industry · Apparel & fashion D2C
When AI agents shop for outfits, your brand should be in the answer.
Performance-wear, denim, intimates, footwear — agents now run the gift-recommendation and wardrobe-completion queries that used to be category-page browses. Tru Commerce gets you cited, then closes the transaction with sizing intact.
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Apparel AI shopping is dominated by intent-rich queries: "running shoes for flat feet," "work pants under $100," "wedding-guest dress under 5'4\"." Your SKU isn't a result unless your data is.
Where D2C brands lose AI presence
Three patterns we see in apparel & fashion d2c.
01
Sizing data isn't agent-readable
Your size charts are images. AI agents can't extract fit context, so they default to the brands whose sizing data is structured.
02
Variant complexity breaks agent checkout
Color × size × inseam × fit. When an agent commits to "the navy" but your SKU expects "navy / regular / 32W," the transaction fails silently.
03
Returns context never reaches the agent
AI agents recommend brands with friction-free returns. Your free-returns policy isn't in the citation graph unless you put it there in a way LLMs can extract.
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