Lead-to-Ideal-Customer Fit Score

{
  "model": "jev-latest",
  "state": {
    "ideal_customer_profile": "{{ideal-customer-profile}}",
    "lead": {
      "company_description": "{{company-description}}",
      "contact_title": "{{contact-title}}",
      "inbound_message": "{{inbound-message}}"
    }
  },
  "questions": {
    "company_fit": {
      "type": "score",
      "instructions": "How well does the company match the ideal customer profile in the state?",
      "criteria": [
        "Clearly outside the profile",
        "Partial match on industry or size only",
        "Matches industry and size, unclear on need",
        "Matches on industry, size and stated need"
      ]
    },
    "decision_power": {
      "type": "choice",
      "instructions": "What role does the contact play in a purchase decision, judged from their title?",
      "criteria": {
        "decision_maker": "Owns the budget or signs the contract",
        "influencer": "Evaluates or recommends but does not sign",
        "user": "Would use the product day to day",
        "unclear": "Title gives no signal"
      }
    },
    "buying_intent": {
      "type": "score",
      "instructions": "How close is this lead to buying, judged from the inbound message?",
      "criteria": [
        "Curious, gathering information",
        "Comparing options, no timeline",
        "Named a problem and a rough timeline",
        "Asked for pricing, a demo, or a contract"
      ]
    },
    "competitor_mentioned": {
      "type": "noul",
      "instructions": "The message names a competing product they use or are evaluating"
    }
  }
}

Score in code: fit = 0.5 times company_fit divided by 3, plus 0.3 times buying_intent divided by 3, plus 0.2 if decision_power.choice is decision_maker or 0.1 if influencer. Route above 0.7 to a rep the same day, 0.4 to 0.7 to a nurture sequence, and below 0.4 to the newsletter. Add a tag when competitor_mentioned is above 0.7 so the rep opens with a comparison instead of a pitch.