The .onto Format

// ═══════════════════════════════════════════════════════
// domain: consumer_goods_intelligence.onto
// version: 2.4.1
// ═══════════════════════════════════════════════════════

// ── Base Entities ────────────────────────────────────────

entity Brand {
  name: String @required
  parent_company: Company @relation
  market_share: Float @confidence
  segments: [ConsumerSegment] @relation
  products: [Product] @relation
}

entity Product {
  name: String @required
  brand: Brand @relation
  category: Enum["beverage", "snack", "dairy", "frozen"]
  sku: String @unique
  price_point: Currency
  distribution: [Retailer] @relation
  launch_date: Date
  status: Enum["active", "discontinued", "planned"]
}

// ── Inheritance ──────────────────────────────────────────

entity CompetitorProduct extends Product {
  competitor: Company @relation
  threat_level: Enum["low", "medium", "high", "critical"]
  overlap_segments: [ConsumerSegment] @relation
  price_delta: Float @derived  // vs our equivalent SKU
  source: Provenance @tracked
}

entity ConsumerSegment {
  name: String @required
  demographics: Map<String, String>
  size_estimate: Integer @confidence
  growth_rate: Float @confidence
  preferences: [String]
}

// ── Provenance Tracking ─────────────────────────────────

source NielsenIQ {
  type: "syndicated_data"
  reliability: 0.92
  refresh: weekly
  fields: [market_share, distribution, price_point]
}

source InternalSales {
  type: "first_party"
  reliability: 0.99
  refresh: daily
  fields: [revenue, volume, returns]
}

source SocialListening {
  type: "unstructured"
  reliability: 0.68
  refresh: hourly
  fields: [sentiment, trends, mentions]
}

// ── Inference Rules ─────────────────────────────────────

rule competitive_threat_detection {
  match product: CompetitorProduct
  where product.status == "active"
    and product.overlap_segments.any(
      s => s.growth_rate > 0.05
    )
    and product.price_delta < -0.10
  then {
    flag: "competitive_threat",
    severity: "high",
    confidence: 0.84,
    action: recommend("pricing_review", {
      product: product.name,
      segments: product.overlap_segments,
      suggested_response: "price_match_or_differentiate"
    })
  }
}

rule market_gap_opportunity {
  match segment: ConsumerSegment
  where segment.growth_rate > 0.08
    and segment.size_estimate > 500000
    and not exists(
      p: Product where p.brand.parent_company == self
        and p.segments.contains(segment)
    )
  then {
    flag: "market_gap",
    severity: "medium",
    confidence: min(
      segment.size_estimate.confidence,
      segment.growth_rate.confidence
    ),
    action: alert("product_development", {
      segment: segment.name,
      estimated_tam: segment.size_estimate * avg_revenue_per_consumer,
      competitors_present: count(
        cp: CompetitorProduct
        where cp.overlap_segments.contains(segment)
      )
    })
  }
}

rule distribution_erosion {
  match product: Product
  where product.status == "active"
    and product.distribution.count() < 
        product.distribution.count(lookback: 90d) * 0.85
  then {
    flag: "distribution_erosion",
    severity: "critical",
    confidence: 0.91,
    action: alert("sales_ops", {
      product: product.name,
      lost_retailers: product.distribution.diff(lookback: 90d),
      revenue_at_risk: estimate_revenue_impact(product)
    })
  }
}