Spectral Brand Theory: A Computational Framework for Multi-Dimensional Brand Perception

Brand measurement collapses multi-dimensional perception into single scores, destroying the information that explains why different observers form irreconcilable perceptions of the same brand. Prior dimensional approaches decompose brand meaning into attribute-level dimensions but treat those dimensions as properties of the brand rather than perceptual channels through which heterogeneous observers filter signals. This paper develops Spectral Brand Theory (SBT), arguing that brand perception is irreducibly observer-dependent. The framework decomposes brand signals across eight perceptual dimensions, defines observer cohorts through formal spectral profiles, and models perception as probabilistic cloud formation that collapses into conviction through evidence accumulation. Five formal propositions address observer heterogeneity, non-ergodic perception, structural absence, coherence types, and conviction asymmetry. An illustrative application to five brands articulates four candidate mechanisms: structural absence as brand strategy, a five-type coherence taxonomy, asymmetric conviction resilience, and independence of brand power from brand health. Cross-model replication suggests structural conclusions are framework-driven rather than model-specific. SBT contributes a computationally implementable, observer-centric architecture that extends customer-based brand equity theory. A companion proof-of-concept study replicating SBT’s cohort-divergence patterns across 17 LLM architectures confirms dimensional collapse as a systematic property of AI-mediated perception (Zharnikov, 2026); independent human-subject validation of the framework’s propositions is identified as the priority for future empirical work. Includes zharnikov-2026a-sbt.yaml (Paper Spec v0.1.0) – a machine-readable specification of the paper's claims, assumptions, and dependencies. The paper's full machine-first bundle (the SPINE claim/dependency graph and the ONTOLOGY term module) lives in the public repository; see https://github.com/spectralbranding/paper-spec for the standard. This PDF is generated programmatically from that machine-first source under a research-as-repository model.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-26
DOI
https://doi.org/10.5281/zenodo.20923330
Primary Topic
Consumer Behavior in Brand Consumption and Identification
Type
preprint
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preprint

Spectral Brand Theory: A Computational Framework for Multi-Dimensional Brand Perception

Zenodo (CERN European Organization for Nuclear Research)
Consumer Behavior in Brand Consumption and Identification
preprint

Spectral Brand Theory: A Computational Framework for Multi-Dimensional Brand Perception

preprint en

Abstract

Brand measurement collapses multi-dimensional perception into single scores, destroying the information that explains why different observers form irreconcilable perceptions of the same brand. Prior dimensional approaches decompose brand meaning into attribute-level dimensions but treat those dimensions as properties of the brand rather than perceptual channels through which heterogeneous observers filter signals. This paper develops Spectral Brand Theory (SBT), arguing that brand perception is irreducibly observer-dependent. The framework decomposes brand signals across eight perceptual dimensions, defines observer cohorts through formal spectral profiles, and models perception as probabilistic cloud formation that collapses into conviction through evidence accumulation. Five formal propositions address observer heterogeneity, non-ergodic perception, structural absence, coherence types, and conviction asymmetry. An illustrative application to five brands articulates four candidate mechanisms: structural absence as brand strategy, a five-type coherence taxonomy, asymmetric conviction resilience, and independence of brand power from brand health. Cross-model replication suggests structural conclusions are framework-driven rather than model-specific. SBT contributes a computationally implementable, observer-centric architecture that extends customer-based brand equity theory. A companion proof-of-concept study replicating SBT’s cohort-divergence patterns across 17 LLM architectures confirms dimensional collapse as a systematic property of AI-mediated perception (Zharnikov, 2026); independent human-subject validation of the framework’s propositions is identified as the priority for future empirical work. Includes zharnikov-2026a-sbt.yaml (Paper Spec v0.1.0) – a machine-readable specification of the paper's claims, assumptions, and dependencies. The paper's full machine-first bundle (the SPINE claim/dependency graph and the ONTOLOGY term module) lives in the public repository; see https://github.com/spectralbranding/paper-spec for the standard. This PDF is generated programmatically from that machine-first source under a research-as-repository model.

Zenodo (CERN European Organization for Nuclear Research)
Consumer Behavior in Brand Consumption and Identification
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