The Challenge

A world-leading education foundation wanted to understand the real-world behavioral patterns behind the adoption of educational products — not just whether adoption happened, but why. They needed, first, to see how uptake is shaped by a mix of practical constraints, emotional resonance, and alignment with established learning philosophies; and, second, to track these dynamics in real time across audiences, products, and markets.

Our Approach

Using the Trace AI System, we built a living adoption platform — based on a model that continuously learns and updates as new signals emerge. By combining quantitative sources (market data, CRM, adoption rates) with qualitative data (social conversations, educator forums, informal feedback), we were able to connect adoption behaviors directly to learning frameworks.

Surfaced the narratives, motivations, and frictions most predictive of adoption or resistance
Mapped behaviors to specific learning philosophies, creating a shared interpretive language for understanding adoption patterns
Segmented audiences into behavioral archetypes, revealing the conditions that accelerate or slow uptake
Integrated and structured diverse data sources into a single, interactive knowledge base

The Outcome

Instead of a static report, the foundation has an interactive platform based on a living model of the global learning product landscape. The platform can:

Outcome

Track shifts in adoption patterns as soon as they emerge

Outcome

Benchmark products in the context of their pedagogical positioning

Outcome

Identify where strategic interventions will have the highest real-world impact