Glossary
Persona Vectors
Mathematical representations of customers as points in complex space, enabling computable similarity and distance.
Definition
Persona Vectors are mathematical representations of customers (or audiences, creators, segments) as points in high-dimensional vector space. Each dimension captures a behavioral, psychographic, or semantic attribute. Two persona vectors that are close in space are similar in behavior; distance indicates divergence. This enables computable operations: find audiences similar to your best converters, match creators to brand psychographics, cluster users into archetypal segments. Persona vectors replace demographic proxies-'Males 30-40'-with mathematical representations that predict action. The Customer Lifetime Value module enhances projections using persona-vector modeling. Creator matching uses persona vectors to assess audience-product fit. Persona vectors are the atomic unit of Sentient's audience intelligence.
Why It Matters
Persona vectors enable the shift from demographics to behavior. Sentient OS builds mathematical representations of people that predict conversion, resonance, and fit.
Related Pages
Related Terms
Vector Spaces
High-dimensional mathematical spaces where actors, products, campaigns become 'Persona Vectors.' Mathematics instead of databases.
Archetypal Clustering
Unsupervised learning to identify behavioral clusters like 'The Skeptical Innovators' rather than demographic groups.
Psychographic Profiling
Understanding attitudes, interests, personality traits. Sentient's Layer 4 creates mathematical psychographic models.
Customer Segmentation
Dividing audiences into groups. Sentient transcends demographics with behavioral archetypes.
Semantic Alignment
Multi-modal embedding similarity between content themes and product categories. Deep matching beyond keywords.
Explore the Full Platform
See how these concepts come to life inside Sentient OS.