Cosmo's Backend Data Model: The 18 Structured Fields That Rufus Actually Reads скачать в хорошем качестве

Cosmo's Backend Data Model: The 18 Structured Fields That Rufus Actually Reads

Everyone talks about optimizing titles and bullet points for Rufus. But when Cosmo indexes your flat file, it's reading 18 specific structured fields in your back-end data before it even looks at your customer-facing content. What structured fields does Cosmo prioritize when indexing products for Rufus? Cosmo processes 18 back-end structured fields—including item type keyword, target audience, material type, special features, item form, and 13 others—before reading your title or bullets. These fields create embedding vectors that map your product to semantic categories in Amazon's knowledge graph. When Rufus receives a natural language query, it searches against these structured attributes, not keyword-matched titles. That's why 60-70% of seller catalogs with incomplete back-end data don't appear in Rufus recommendations despite having "optimized" front-end content. KEY INSIGHTS: • Cosmo creates embedding vectors from 18 structured fields to build semantic product representations before processing unstructured title/bullet text • Rufus matches search intent to attributes (target audience + special features), not keywords to keywords like A9's traditional search • Back-end attribute templates vary by category but prioritize the same 18 core fields across all 350+ million products in Amazon's catalog • Empty or generic back-end fields (like target audience = "general") exclude your ASIN from demographic-filtered Rufus queries even if your title mentions the demographic 50 times Why this matters: If you're a 7-8 figure seller still optimizing like it's 2019—keyword-stuffing titles and assuming that's what Rufus reads—you're invisible to AI search queries. This episode breaks down the actual platform architecture so catalog managers and brand owners understand what Amazon's systems prioritize. TIMESTAMPS: 0:00 - Introduction: What Rufus actually reads first 0:45 - The 18 structured fields in Cosmo's data model 2:30 - How embedding vectors map products to semantic categories 4:15 - Search intent mapping: Why A9 and Rufus work differently 6:00 - Why keyword-stuffed titles dilute semantic clarity 7:45 - The 3 backend fields to audit immediately ABOUT AMAZON RUFUS: Breaking down how Amazon's AI systems actually work for sellers who've outgrown surface-level advice. Platform mechanics, technical architecture, and what really drives visibility. Subscribe for regular episodes on Rufus, Cosmo, and Amazon's backend systems. Get your tailored Amazon Rufus AI Audit today www.atomicamz.com Find out if Rufus is discovering your brand on Amazon This episode is brought to you by Atomic AMZ. We help brands get discovered, rank and scale on Amazon (plus for sellers who've outgrown generic Amazon agencies). Learn more: www.atomicamz.com #amazonrufus #amazonsellers #amazonfba #amazonseo #amazonai