iiRecord
Agentic AI Atlas · Marketing Mix Modeling Cycle
workflow:marketing-mix-modeling-cyclea5c.ai
II.
Workflow JSON

workflow:marketing-mix-modeling-cycle

Structured · live

Marketing Mix Modeling Cycle json

Inspect the normalized record payload exactly as the atlas UI reads it.

File · workflows/workflows/workflows-marketing-analytics.yamlCluster · workflows
Record JSON
{
  "id": "workflow:marketing-mix-modeling-cycle",
  "_kind": "Workflow",
  "_file": "workflows/workflows/workflows-marketing-analytics.yaml",
  "_cluster": "workflows",
  "attributes": {
    "displayName": "Marketing Mix Modeling Cycle",
    "workflowKind": "operational",
    "triggerType": "scheduled",
    "typicalCadence": "quarterly",
    "complexity": "cross-team",
    "description": "Executes marketing mix modeling analyses to quantify channel effectiveness\nat the aggregate level — preparing input data spanning media spend,\nimpressions, pricing, seasonality, and macroeconomic factors, running\nregression models to decompose revenue drivers, estimating saturation curves\nand adstock decay rates per channel, simulating budget reallocation scenarios\nto maximize predicted outcomes, validating model outputs against known\nbusiness events, and presenting recommendations to leadership for budget\nplanning. Produces MMM model outputs, scenario simulation reports, and\nchannel saturation analyses. Excludes real-time campaign optimization and\nattribution modeling.\n"
  },
  "outgoingEdges": [
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "role:data-scientist",
      "kind": "involves_role",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "role:business-analyst",
      "kind": "involves_role",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "role:planner",
      "kind": "involves_role",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "skill-area:data-analytics",
      "kind": "requires_skill_area",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "skill-area:market-research",
      "kind": "requires_skill_area",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "domain:marketing",
      "kind": "applies_to_domain",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "domain:digital-marketing",
      "kind": "applies_to_domain",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "responsibility:data-quality-monitoring",
      "kind": "triggers_responsibility",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "responsibility:cost-optimization",
      "kind": "triggers_responsibility",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "org-unit:analytics-team",
      "kind": "performed_by_org_unit",
      "attributes": {}
    },
    {
      "from": "workflow:marketing-mix-modeling-cycle",
      "to": "org-unit:marketing-team",
      "kind": "performed_by_org_unit",
      "attributes": {}
    }
  ],
  "incomingEdges": []
}