This is placeholder for the case study of Amazon 25-26 Trade upMessaging Systems for Amazon Everyday Essentials messaging.
WHAT I DID
• Established AI Copy Governance: Acted as the lead marketing creative for the Progressive Discovery initiative, designing the foundational language systems and UX guardrails for AI-generated copy across major surfaces like Subscribe & Save and Buy Again.
• Scaled Automated Messaging: Developed a repeatable framework to ensure LLM-created content remained clear and contextually appropriate across 30+ live experimentation frameworks and hundreds of unique product types.
• Created the "Motivation Matrix": Engineered a strategic language framework that transitioned recommendation copy from static product features to dynamic customer mindset modeling.
• Optimized for Intent: Organized recommendation behaviors into thematic categories tied to shopping psychology, allowing the AI to prioritize user motivation over simple attribute matching.
• Prioritized Cognitive Ease: Championed the use of simplified, everyday language to reduce friction and better align with natural decision-making patterns, enhancing overall readability and customer trust.
• Streamlined Global Experimentation: Transformed fragmented copy creation into a scalable, documented system that supported rapid-fire testing while maintaining a consistent brand voice.g.
