Marketing Domain Ontology

FLOW ALGEBRA
TITLE: Marketing Domain Ontology
VERSION: 1.0
SOURCE: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/business-domains/marketing-domain-ontology.html
STATUS: Domain-derived draft; source page content not independently verified.
AUTHORS: Mark Higgins — Sky (Recursive AI)

FLOW "MarketingDomainOntology" v1.0

DOMAIN:
  id: marketing_domain_ontology
  parent: business_domain_ontology
  scope: Marketing strategy, research, segmentation, positioning, communications, channels, customer relationships and performance measurement.

TYPES:
  Organisation: entity
  Brand: entity
  Product: entity
  Service: entity
  Market: entity
  MarketSegment: entity
  Audience: entity
  Customer: entity
  Prospect: entity
  Persona: model
  CustomerNeed: concept
  ValueProposition: concept
  MarketingStrategy: plan
  Campaign: activity
  MarketingChannel: channel
  ContentAsset: artifact
  Message: artifact
  Touchpoint: event
  Conversion: event
  Transaction: event
  Metric: measurement
  Observation: evidence
  Consent: permission
  Budget: quantity
  TimePeriod: interval

RELATIONSHIPS:
  Organisation -> owns -> Brand
  Organisation -> offers -> Product | Service
  Brand -> serves -> Market
  Market -> contains -> MarketSegment
  MarketSegment -> groups -> Audience
  Audience -> includes -> Customer | Prospect
  Persona -> models -> Audience
  Customer -> expresses -> CustomerNeed
  ValueProposition -> addresses -> CustomerNeed
  MarketingStrategy -> targets -> MarketSegment
  MarketingStrategy -> positions -> Brand | Product | Service
  Campaign -> implements -> MarketingStrategy
  Campaign -> uses -> MarketingChannel
  Campaign -> distributes -> ContentAsset
  ContentAsset -> conveys -> Message
  MarketingChannel -> enables -> Touchpoint
  Touchpoint -> may_precede -> Conversion
  Conversion -> may_lead_to -> Transaction
  Metric -> measures -> Campaign | Channel | Conversion
  Observation -> supports -> Metric
  Consent -> governs -> permitted_processing

RULES:
  R1: IF Campaign implements MarketingStrategy AND MarketingStrategy targets MarketSegment THEN Campaign targets MarketSegment.
  R2: IF ContentAsset conveys Message AND Campaign distributes ContentAsset THEN Campaign communicates Message.
  R3: IF Metric measures Campaign AND Observation supports Metric THEN Observation is evidence_for CampaignPerformance.
  R4: IF Conversion follows Touchpoint THEN mark association; DO NOT infer causation without valid attribution evidence.
  R5: IF Audience membership is inferred THEN record methodology, time period and uncertainty.
  R6: IF personal data is used THEN verify lawful basis, consent where applicable, purpose limitation and retention constraints.

METRICS:
  reach: unique_exposed_entities (definition and deduplication method required)
  impressions: exposure_events
  click_through_rate: clicks / impressions (when impressions > 0)
  conversion_rate: conversions / eligible_denominator (explicit denominator required)
  customer_acquisition_cost: attributable_acquisition_cost / acquired_customers (when acquired_customers > 0)
  return_on_ad_spend: attributable_revenue / advertising_spend (when advertising_spend > 0)
  retention_rate: retained_cohort_members / eligible_starting_cohort (when denominator > 0)

CONFIDENCE:
  range: [0,1]
  rule: Attach confidence to claims, observations and inferred links; distinguish statistical confidence from subjective confidence.
  unknown: null

SEMANTIC_EQUIVALENCE:
  exact: Only when definition, context, unit and measurement method match.
  related:
    - lead ~ prospect (context-dependent; not universally identical)
    - reach ~ impressions (related, not equivalent)
    - conversion ~ sale (sale is one possible conversion)
    - brand_awareness ~ brand_recognition (related, not equivalent)

PROVENANCE:
  required: [source, author_or_system, observed_at, method, version]
  distinction: Separate observed facts, estimated values, hypotheses and derived inferences.

FLOW_HASH:
  algorithm: SHA-256
  input: Canonical UTF-8 serialization of ontology definitions, relationships, rules and version.
  value: COMPUTE_ON_PUBLICATION

UPDATE_MODEL:
  strategy: versioned_incremental
  triggers: [new_evidence, changed_definition, corrected_data, revised_method, source_update]
  preserve: [prior_version, provenance, change_log]
  validation: [type_integrity, relationship_consistency, metric_denominators, privacy_constraints]

AI_CONSUMPTION:
  representation: typed_semantic_graph
  retrieval_keys: [entity_id, concept, relationship, source, version]
  outputs: [entity_resolution, semantic_search, explainable_inference, campaign_analysis]
  safeguards: [no_unsupported_causation, no_fabricated_metrics, privacy_by_design, uncertainty_disclosure]

END FLOW