Selling technology to wholesale distributors means qualifying on their ERP before you can demo, proving ROI on their own transactional data before they will commit, and catching acquisition-driven buying windows that open and close within 90 days. The qualification signals, trial outcomes, and market events that drive this pipeline usually live outside the CRM.

def score_erp_confidence(
    prospect_id: str, signals: dict
) -> dict:
    """Score ERP confidence from enrichment signals.

    Each signal source contributes independently.
    A single strong signal (job posting naming the
    ERP) is enough to route; multiple weak signals
    accumulate to medium confidence.
    """
    weights = {
        "job_posting_keyword":  0.45,
        "vendor_directory":     0.30,
        "trade_show_exhibitor": 0.15,
        "technographic_match":  0.10,
    }

    erp_scores: dict[str, float] = {}
    for signal_type, matches in signals.items():
        w = weights.get(signal_type, 0.05)
        for erp_name, strength in matches.items():
            erp_scores[erp_name] = (
                erp_scores.get(erp_name, 0)
                + w * strength
            )

    if not erp_scores:
        return {
            "erp": None,
            "confidence": 0,
            "route": "manual_qualification",
        }

    best = max(erp_scores, key=erp_scores.get)
    conf = min(erp_scores[best], 1.0)
    return {
        "prospect_id": prospect_id,
        "erp": best,
        "confidence": round(conf, 2),
        "route": (
            "demo_track" if conf >= 0.6
            else "manual_qualification"
        ),
    }