Emily Meadows

I design the content architecture that powers high-velocity digital experiences. Bridging the gap between storytelling, cognitive psychology, and scalable technical systems design.

Core Competencies:

Strategy:

Governance, Content audits, RACI Modeling, Stakeholder Alignment

Design:

Information Architecture (IA), Taxonomy, User Journey Mapping, User Flows

Systems:

Developer Handoff, Modular Content Modeling, CMS Strategy (Sanity / Contentful)

Featured Work:

Project 1: Systems Architecture & Content Operations

Scalable Content Infrastructure for Global EdTech

The Impact: Architected a relational content model that transformed static SME expertise into a responsive web experience. I designed logic-driven content states that adapt in real-time to user progress, reducing production friction by 30% and ensuring 100% accuracy across thousands of unique user pathways.

Key Deliverables:

SME-to-Product Translation, Relational Content Models, Conditional Logic Documentation

Project 2: Governance & Strategy

Operationalizing a Global Web Ecosystem (200+ Assets)

The Impact: Established the governance frameworks and SOPs for a high-volume ecosystem at Time4Learning. I executed a comprehensive audit of 200+ assets, aligning legacy content with new brand standards and architecting scalable production pipelines that accelerated time-to-market by 20%.

Key Deliverables:

Scalable Content Pipelines (End-to-End Lifecycle), Content Governance Framework (RACI), Metadata & Audit Strategy

Project 3: Research & Taxonomy

Psychology-Informed IA & Search-First Systems

A set of detailed user personas created for a Master’s thesis project, FoodCreations.com. The mockup displays diverse user profiles with specific goals, pain points, and mental models. Each persona is mapped to a search-first information architecture, illustrating how the digital system accommodates different cognitive approaches to food and recipe discovery.

The Impact: Leveraging cognitive psychology principles, I conducted primary research to design a navigation logic that prioritizes findability. This research serves as a blueprint for building intuitive SaaS platforms that adapt to user mental models rather than forcing traditional B2B hierarchies.

Key Deliverables:

Cognitive Load Analysis, Search-First Taxonomy, Mental Model Mapping