Wayfair
shoppable genAI interior image generation
Wayfair launched Muse in February 2025 to replace Decorify, its interior image generation tool that had produced more than 175,000 designs, connecting each generated scene to a catalog of about 30 million SKUs.
Objective
Help the customer who does not know where to start move from a vague idea to a concrete scene, then to buyable products, in order to open up top-of-funnel discovery and feed conversion.
The deployment
Wayfair first launched Decorify in the summer of 2023, a tool where the customer uploaded a photo of their room, chose a style, and received an AI-generated image, with similar Wayfair products offered as shoppable links. Decorify produced more than 175,000 designs since its launch, but it often distorted the architecture of rooms and started over from scratch with each new image. On February 11, 2025, Wayfair replaced Decorify with Muse, a Pinterest-style inspiration engine: the customer types a query such as moody 1920s style living room, browses AI-generated interior images, and clicks to see the closest products in the catalog of 30 million SKUs. Muse deliberately no longer tries to pixel-match a real product, and instead presents items inspired by the generated scene.
Results Proof C
Official Wayfair release about Muse and major retail press (Retail Dive, Business of Home) naming the brand, with the figure of 175,000 designs for Decorify and the size of the catalog. No conversion or financial result published on the tool, which places it at C.
How it works
Documented architectureThe stack in detail
- llm Modeles de generation d'images Wayfair In-house genAI models that produce Muse's interior scenes (and before it Decorify's); the exact architecture is not published.
- outil Muse Inspiration engine launched February 11, 2025: style query, generated images, clickable inspired products.
- outil Decorify Previous tool (2023-2025): uploaded room photo, generated restyling, similar products; more than 175,000 designs produced before its replacement by Muse.
- infra Recherche visuelle et catalogue Wayfair Matching between the generated scene and the buyable SKUs from the catalog of about 30 million SKUs.
How it runs, concretely
For ops teams-
1Inspiration query customer
The customer describes a style or a room in natural language, or uploads a photo (Decorify).
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2Scene generation AI
The model generates an interior image matching the request.
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3Product matching AI
The system connects the scene to catalog SKUs presented as inspired by the image.
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4Move to purchase customer
The customer explores the proposed products, builds a collection, and adds to cart.
The relevance of the match between the generated image and the real catalog. If the mapping to the SKUs is weak, the customer sees a nice scene but products that are far off, and the move to purchase breaks.
How your customers perceive this type of use
Sourced studiesUn ecart net separe les annonceurs des consommateurs : 77% des annonceurs voient l'IA positivement contre 38% des consommateurs (Yahoo/Publicis, 2024). Les mesures implicites confirment le rejet declare : en EEG, les pubs generees par IA produisent une activation memorielle plus faible que les pubs traditionnelles et sont decrites comme agacantes, ennuyeuses et confuses (NIQ, 2024). La disclosure a un effet ambivalent : elle augmente fortement la confiance quand elle est remarquee (Yahoo/Publicis), mais 27% des jeunes consommateurs disent faire moins confiance a une entreprise dont la pub est creee par IA (IAB, 2024).
Acceptance conditions
- Une disclosure visible : quand la mention IA est remarquee, la confiance globale envers l'entreprise augmente de 96% (Yahoo/Publicis 2024)
- Une qualite visuelle suffisante : les visuels IA de basse qualite augmentent l'effort cognitif et distraient du message (NIQ 2024)
Red lines
- Le contenu IA non declare puis identifie : 72% des consommateurs disent que l'IA rend l'authenticite difficile a etablir (Yahoo/Publicis 2024) et les marques utilisant des pubs IA sont plus souvent jugees inauthentiques ou non ethiques par les consommateurs que par les dirigeants (IAB 2024)
- Les mannequins et personnes generes par IA : 46% des consommateurs n'en veulent pas dans la publicite, l'inquietude premiere etant les standards de beaute irrealistes (Attest 2025)
Sources: Yahoo / Publicis Media (terrain Ebco) 2024 · IAB (avec Attest) 2024 · NIQ (NielsenIQ) 2024 · Attest 2025
How to replicate
Inference, not sourcedData prerequisites
- Rich product catalog with visuals
- Reference set of styles and room ambiances
- Measurement loop from inspiration to purchase
Org prerequisites
- Transparency rule on generated images
- Legal basis and minimization for customer-uploaded photos
- Team able to maintain an image generation model
Possible stack
- Interior image generation model
- Visual search for catalog matching
- Shoppable moodboard exploration interface
The plan, step by step
- Step 1Frame the styles you sell and gather a reference image set per style.Deliverable: Style reference set with examples validated by merchandising.
- Step 2Plug in or fine-tune a room image generation model on these styles.Deliverable: Generator producing coherent scenes per style, evaluated internally.
- Step 3Build the scene-to-buyable-SKU matching (visual search).Deliverable: Product match rate measured on a sample of scenes.
- Step 4Assemble the shoppable exploration interface, with disclosure that the images are AI-generated.Deliverable: Accessible beta with an inspiration-to-product-page journey.
- Step 5Instrument the funnel and decide on scaling.Deliverable: Measured funnel: product click rate and conversion from inspiration.
First step: Train or plug in a room image generation model on the styles you sell, then connect each scene to buyable SKUs.
The same pattern, proven in other industries
Adobe
in-house genAI production of marketing content at scale
Atlassian
internal genAI agents for account targeting and marketing content production
BMW
advertising and experiential creation with generative AI
Sources
- S1 Wayfair Introduces New AI-Powered Tool 'Muse' to Inspire and Personalize the Home Shopping Experience Primary archive pending
- S2 Wayfair wants AI images to stoke IRL purchases Established press archive pending
- S3 Wayfair's new tool shows AI's strengths and limitations Secondary archive pending
An error, newer info, a source?
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