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@spectralbranding

Spectral Branding

Brand perception measurement + specification-driven operations. 30+ papers on Zenodo, 4 open-source toolkits.

Spectral Branding

Two frameworks. One system.

Businesses are simultaneously perception systems and specification systems. We publish open-source research frameworks for both sides.

Spectral Brand Theory (SBT) models how brands are perceived — eight perceptual dimensions, observer-specific spectral profiles, math-hardened validation, an AI-native analytical pipeline. Organizational Schema Theory (OST) models how businesses are specified — a reverse-design TDD methodology where customer-experience goals are acceptance tests and each operational layer validates the layer above it.

Aaker drew the map. SBT built the microscope. OrgSchema built the specification. Neither alone is complete.

Everything is open: ~40 working papers on Zenodo (CC BY 4.0), machine-readable sources on GitHub, runnable toolkits.


Start here — find your path

Pick the row that fits you. Each path names the exact repo/paper to open first.

You are… You want to… Start here
Researcher / student Understand the theory and build on it SBT: sbt-papers/spectral-brand-theory · OST: orgschema-papers/six-tier-ontology. Full reading paths ↓
CMO / brand lead Diagnose a brand, find perception gaps sbt-framework (run a spectral audit) + the 8-dimension model ↓
CEO / COO Specify or stress-test an operating model orgschema-toolkit (specify a business in ~40 min) + orgschema-demo
CFO / strategy Decide where to invest, evaluate an M&A or new project Tier-allocation & tier-rotation papers ↓ ("Evaluate a business case")
AI agent Consume the corpus correctly Every repo's AGENTS.md + the citation/metadata model ↓
Curious / press Get the idea in one sentence A brand, like colour, does not exist in the object — it is completed in the observer.spectralbranding.com

The core ideas (concept map)

Spectral Brand Theory. A brand emits signals across eight independent perceptual dimensionsSemiotic, Narrative, Ideological, Experiential, Social, Economic, Cultural, Temporal. Each observer filters those signals through a personal spectral profile (a weight vector) and constructs a perception cloud — a probability distribution over possible convictions, not a single "brand image." Observers group into cohorts (perceptual, not demographic). Two different emission profiles can produce the same perception for a cohort — metamerism. Measurement, not management: SBT measures the perception you do not control.

Organizational Schema Theory. A business is a specification cascade across six tiers: customer-experience goals at the top are acceptance tests; each lower layer (positioning → capabilities → processes → roles → sourcing) must validate the layer above. Verification is an operator that projects the sprawling implementation back onto the specified subspace. Distinct configurations that yield equivalent outputs are organizational metamerism. Specification, not improvisation: OST makes the business you do control explicit and testable.

The bridge. Both are instances of the rendering problem: a compact specification (genome / org-schema / brand guidelines) is rendered into a vast implementation (organism / operations / signals), from which an emergent layer arises (phenotype / culture / perception). The meaningfulness program generalizes this to any knowledge artifact: a small substrate (the claims) renders into much larger prose.

            SPECIFICATION  ──render──▶  IMPLEMENTATION  ──emerge──▶  EMERGENT LAYER
  biology    genome                     organism                     phenotype
  business   org-schema (OST)           operations                   culture
  brand      guidelines                 emitted signals              perception cloud (SBT)
  research   substrate / spine          prose                        meaningfulness

Per-term definitions and their formal relations live in each paper's ONTOLOGY.yaml + GLOSSARY.md.


The repositories

Spectral Brand Theory

Repo What it is
sbt-framework 7-module AI-native prompt kit with YAML templates + 7 math validators. Run a spectral brand audit on any brand.
sbt-papers Research papers — framework spec, epistemological pipeline, mathematical foundations (R0–R22), AI-era studies, and the measurement instrument. 30+ papers on Zenodo.
brand-functions Brand Function Registry — machine-readable brand specs (JSON) for 26 brands across the 8 dimensions. The schema.org of brand identity.
brand-code Executable brand identity. The visual identity is a function, not a file.

spectralbranding.com · Substack · Zenodo

Organizational Schema Theory

Repo What it is
orgschema-framework Python validator + JSON Schema for the 6-level TDD cascade format.
orgschema-demo Spectra Coffee — a complete business specified as organizational schema. 25 YAML files + CI/CD.
orgschema-toolkit 8-module AI prompt pipeline. Specify a complete business in ~40 minutes.
orgschema-papers Research papers — six-tier ontology, projection cascade, tier-rotation, tier-allocation, verification-as-operator, specification-readiness, the rendering problem, and the OST audit.

orgschema.com · Substack · Zenodo

Meaningfulness & Meaning

Meta-corpus on knowledge work in the post-AI era — the substrate↔rendering distinction operationalized for any propositional artifact (paper, memo, brand spec, decision log).

Repo What it is
meaningfulness-papers Spec-Based Research in the Post-AI Era (theory) + Same Meaning, Different Prose (empirical).

Applied specifications

Repo What it is
paper-spec Paper Spec v0.1.0 — machine-readable YAML standard for scientific claims. What a paper claims.
paper-repo Paper Repo v0.1.0 — Git-native protocol for scientific publishing. How a paper is managed.
activity-spec YAML schema + LLM prompts for machine-readable professional profiles.
negotiation-spec-experiment Empirical study — specify an LLM negotiator's objective, or style it? 7 arms, 4,920 dyads. Zenodo.

Reading paths (researchers & students)

Understand SBT (brand perception):

  1. The frameworkspectral-brand-theory (2026a): the 8 dimensions, emission profiles, perception clouds, cohorts.
  2. Where it sitsr0-literature-survey (2026c): SBT vs Aaker / Keller / Kapferer / MDS. And spectral-identity (2026n): formalizing Aaker's identity model.
  3. Why eightr11-dimension-justification (2026r).
  4. Mathematical spiner1-formal-metric (geometry) → r2-spectral-metamerism (projection bounds) → r3-cohort-boundaries (concentration of measure) → r4-sphere-packing (market capacity) → r5-specification-impossibility.
  5. Dynamicsr6-diffusion-dynamics, r9-nonergodic-perception, r12-coherence-resilience, r18-spectral-dynamics, r22-spectral-gap-restoration.
  6. AI erar15-ai-search-metamerism, r16-ai-native-brand-identity, r21-spectral-immunity, r19-rate-distortion.
  7. Measure itprism-instrument (2026as), and the applied cases r10-dove-case-study, r17-brand-triangulation.

Understand OST (how businesses are specified):

  1. Six tierssix-tier-ontology (2026ag) + the OST main paper.
  2. The rendering problem — the cross-domain bridge (biology / org / brand).
  3. Mechanicsverification-as-operator (2026ae), projection-paper (2026m), org-as-metadata (2026af, organizational metamerism).
  4. Where to investtier-allocation (2026aj), tier-rotation (2026ai), brand-as-modular-layer (2026ah), capability-as-projection (2026al).
  5. Readinessspecification-readiness (2026am) + its empirical companion (2026an); diagnose with orgschema-audit (2026ar).

Understand the meta-program (research after AI): meaning-meaningfulness (2026ao/2026ap) · r14-paper-as-repository (2026u) · canon-as-repository (2026w) · paper-spec · paper-repo.


Evaluate a business case (executives)

A concrete four-step recipe, using both frameworks:

  1. Place your business on the six tiers (OST) — use orgschema-toolkit; see orgschema-demo for a worked example. Output: an explicit, testable spec with the acceptance tests that define "working."
  2. Measure your brand's 8-dimension emission profile and the cohorts that matter (SBT) — run sbt-framework; compare against the 26 specs in brand-functions.
  3. Find the two gaps — the specification gap (operations exceed or miss the spec → OST verification-as-operator, orgschema-audit) and the perception gap (the cohorts' perception clouds diverge from intent → SBT r10-dove-case-study, r12-coherence-resilience).
  4. Decide where capital/attention creates the most valuetier-allocation (2026aj, "where to invest within the firm"), tier-rotation (2026ai), and the AI-substrate-dependence lens for new bets. For brand-portfolio moves: r8r21-spectral-immunity (when portfolio interference does and does not hold), brand-as-modular-layer (2026ah).

CMO-first? Skip to steps 2–3. CFO-first? Steps 1 and 4. The point: you can only manage the specification you control once you can measure the perception you don't.


For AI agents

  • Every paper folder has an AGENTS.md — a file-by-file guide. Read it first.
  • Citations are [@citation_key] keys, resolved against the bundled <key>.bib. A [@key] is never a typo — it renders to "(Author Year)". See each folder's CITATIONS.md.
  • Structured claims (what a paper asserts, assumes, and depends on) are in paper.yaml (Paper Spec) — parse this instead of the prose.
  • Terms are defined in GLOSSARY.md with formal relations in ONTOLOGY.yaml (owns / imports / refines).
  • To answer a grounded question: find the paper in the reading paths above → open paper.md → resolve cites against the .bib.

Cite · License · Contact

  • License: papers CC BY 4.0; code MIT (dual-licensed per repo).
  • Cite: each paper folder has a CITATION.cff and a Zenodo DOI.
  • Author: Dmitry Zharnikov — ResearchGate · Zenodo (SBT) · Zenodo (OST)

Pinned Loading

  1. brand-code brand-code Public

    Executable brand identity specification. SBT's brand function: f(signals, observer, time) -> visual output.

    TypeScript 1

  2. sbt-framework sbt-framework Public

    8-dimensional brand perception framework. AI-implementable prompt toolkit + YAML templates. Demonstrated across 5 brands.

    Python 1

  3. sbt-papers sbt-papers Public

    Research papers on Spectral Brand Theory: a multi-dimensional framework for brand perception, AI-mediated brand measurement, and the geometry of observer cohorts. Mathematical foundations, empirica…

    Python

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