AI Discovery Readiness

Case Study – Preparing A Curriculum Platform For Emerging AI Search And Answer Experiences

Overview

Amplify.com supported a complex portfolio of K–12 curriculum products but functioned primarily as a marketing destination rather than a structured discovery platform. I led a multi-year transformation to reposition the site as a sustainable growth engine by introducing publishing infrastructure, technical governance practices, discovery architecture, and lifecycle optimization workflows.

Within the first year:

Organic search became the #1 acquisition channel, increasing 99% YoY, followed by sustained ≥27% annual growth over the next three years.

The Opportunity

Amplify.com served a complex portfolio of curriculum experiences spanning literacy, math, and science programs. While strong investments had already been made in traditional SEO, the site required additional readiness across:

  • Structured Schema Interpretation
  • Accessibility-Aligned Media Signals
  • Semantic Relationships Between Content Surfaces
  • Scalable Metadata Governance
  • Image Interpretation Clarity
  • Video Indexing Improvements
  • Structured Discovery Across Webinar And Resource Libraries

I introduced a layered approach to improving how the platform could be understood by both search engines and emerging AI answer systems.

Strategy

I implemented AI discovery readiness across four platform layers.

Outcomes

Key Outcomes

  • +68% growth in Google AI Overview visibility
  • +25% increase in AI mentions across search environments
  • 1,386 new users from AI discovery sources

These initiatives strengthened the platform’s readiness across AI-mediated discovery environments including:

  • Improved structured interpretation across curriculum evaluation pathways
  • Expanded eligibility for enhanced SERP features and AI overview inclusion
  • Improved accessibility-aligned media interpretation signals
  • Improved video discoverability across webinar library surfaces
  • Strengthened semantic relationships between curriculum content experiences
  • Improved long-term discovery adaptability across evolving search environments

Transformation Timeline

Phase 1 —
Structured Content Interpretation Readiness

Improved how curriculum content could be interpreted across search and answer engines by introducing structured metadata improvements.

This included:

  • Schema alignment across key discovery surfaces
  • Video schema deployment within webinar experiences
  • Structured metadata improvements supporting curriculum evaluation content
  • Strengthening entity clarity across program relationships
  • Improving structured relationships between pillar and supporting content

Impact: Improved machine readability across high-value curriculum discovery pathways

Phase 2 —
Accessibility-Aligned Media Interpretation

Search engines increasingly rely on accessibility-aligned signals to interpret visual content.

I introduced governance practices supporting scalable image interpretation across the platform.

This included:

  • Evaluation and rollout of ai-assisted alt-text generation workflows
  • Governance patterns for maintaining descriptive media accessibility standards
  • Collaboration with design to introduce image specification guidelines
  • Improving alignment between accessibility readiness and discovery signals

Impact: Improved interpretability of visual curriculum content across both accessibility and AI indexing pathways

Phase 3 —
Semantic Discovery Surface Expansion

Improved interpretability of supporting discovery environments beyond program pages.

This included:

  • Webinar library search visibility improvements
  • Structured video metadata enhancements
  • Improvements to google business profile discovery alignment
  • Strengthening structured relationships between resource hubs and curriculum experiences

Impact: Expanded structured entry points into the curriculum ecosystem beyond primary navigation pathways

Phase 4 —
Lifecycle Optimization For AI-Era Discovery

Introduced workflows supporting continuous semantic improvement across discovery surfaces.

This included:

  • RankIQ-supported topic evaluation workflows
  • Structured refresh cycles for declining discovery surfaces
  • Strengthening metadata alignment across existing content
  • Supporting early visibility improvements within ai overview environments

Impact: Positioned the platform to remain adaptable as discovery environments continue shifting toward answer-driven search

Platform Enablement Systems Introduced

To support sustained readiness across teams, I implemented supporting infrastructure including:

  • Ai-assisted alt-text governance workflows
  • Rankiq lifecycle optimization workflows
  • Structured schema deployment across video content
  • Internal documentation supporting seo-aware publishing practices
  • Semantic interlinking reinforcement between curriculum experiences
  • Image specification standards supporting performance and interpretation

Impact: Improved consistency of machine-readable signals across the curriculum platform