Methodology · Model
Resonance Twin Model
Classical personas are stories without data. The Resonance Twin Model turns each persona into a quantified model that can be measured, compared and anchored in the Knowledge Graph.
What is broken about the classical persona concept
A photo, a first name, hobbies — and then an empty block titled 'goals and pain points'. Personas like this do not help, because they are neither measurable nor actionable. AI systems cannot reference them, audits cannot verify them, pipelines cannot optimize against them.
Two radar systems per persona
Each Resonance Twin has two radar visualizations: a values compass with 12 axes (status, security, sustainability, experience-seeking and so on) and a GEO profile with 6 axes (search behavior, AI affinity, decision speed, evidence requirement, price sensitivity, recommendation readiness).
Personas that AI systems can understand
Because each Resonance Twin is structured data, it can be fed into the Knowledge Graph. AI answer engines recognize the persona, map research prompts to it and can recommend the matching content modules.
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