Introduction
Mapp Fashion is a personalization solution built specifically for fashion retail. It helps shoppers discover relevant products, understand how items work together, and decide with confidence across a retailer's website and email.
In fashion, relevance depends on styling, context, and intent — not only on category or popularity. Mapp Fashion is built around this: it interprets each product the way shoppers evaluate fashion, and uses that understanding to generate recommendations and content.
Core concepts
All Mapp Fashion features build on a shared understanding of your catalog.
Enriched Product Attributes are the foundation. Standard catalog data is enriched into fashion-relevant context such as fit, occasion, styling role, and intended use. This shared attribute layer keeps every feature consistent.
Building on this foundation, Mapp Fashion provides:
Outfits: complete looks built around an item, showing how it can be worn.
Similar Items: relevant alternatives when a shopper's first choice is not the right one.
Recommendations: personalized product suggestions across pages such as the homepage, basket, and checkout.
Email recommendations: the same fashion logic extended into BAU, themed, and post-purchase emails.
Because these features share the same enriched understanding, recommendations become more relevant as shoppers interact: the more Mapp Fashion learns from browsing and purchases, the better it personalizes.
Where to go next
For scenarios and business value, see the Use Cases.
For technical setup and data integration, see the Integration Overview.