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Proof: controlled tests and case studies
Proof means measured lift against a control: matched-spend A/B tests and holdouts that separate what a change to product data caused from what would have happened anyway.
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Case studies
Fast-growing performance apparel brandRevenue +7.3%
How a fast-growing performance apparel brand turned product data into a 7.3% revenue lift on Google Shopping
Global prestige beauty companyROAS +28%
How a global prestige beauty company turned product content into cross-channel performance and AI-recommendation visibility
Global home furnishings retailerRevenue +5.7%
How a global home furnishings retailer grew Google Shopping revenue 5.7%, while clicks went down
A.L.C.Net sales +129%
How A.L.C. boosted full-catalog product discovery on Google
thredUPSell-through +15%
thredUP increases sell-through by 15% with enriched product data
Global luxury retailerRelevant results up to 30x
A global luxury retailer increases relevant results for descriptive searches by up to 30x
Large multi-brand retailer$22M projected revenue
A large multi-brand retailer boosts product discovery, projecting a $22M revenue increase
Large multi-brand retailerRPV +0.65% · $20-30M
Lily AI recommendations increase RPV by 0.65%, driving $20-30M in incremental demand
Multi-brand apparel & accessories retailerUp to $48M projected revenue
Lily AI demand forecasting drives 7-8 digit revenue lift with accuracy at scale
Luxury home brandROAS boost in 2 weeks
How a luxury home brand boosted sales from Shopify site search and Google search
TapestryDouble-digit search lifts
Tapestry boosts traffic and sales from Google Search with Lily AI
Rue Gilt GroupeVideo
From experimentation to full AI vibes at Rue Gilt Groupe
MerrellVideo
From SEM to GEO: how Merrell connects with Gen Z and millennials
Bloomingdale'sVideo
How Bloomingdale's makes site search convert with enriched product data
TapestryWebinar
“AI is here, now what?” with Tapestry and Lily AI
J.CrewVideo