Develop a hybrid lead scoring framework that blends demographic/firmographic fit and behavioural intent for [CompanyName] in [Region] across [ProductLine]. Define the Ideal Customer Profile (ICP) using [Industry], company size, technographics, and buying centre roles. Specify behavioural signals (website depth, content type, event attendance, product trial actions) and assign weights reflecting signal strength and recency. Calibrate the model to target an MQL rate of [MQLTarget] with downstream targets of [MQLtoSQLRate] and [WinRate]. Ensure the framework is implementable in [CRMPlatform] using native fields and automation.
Output format:
Executive Summary (bullets) with business rationale and KPIs;
Scoring Rubric Table listing attribute, value bands, points, recency decay (half-life), and data source;
Scoring Formula (clear algebraic definition) including caps, minimum data rules, and tie-breakers;
JSON Config (key:value pairs for fields, thresholds, and decay settings);
Operational Playbook covering MQL > SAL handoff, SLA timings, and ownership.
Optimise for interpretability, minimal data latency, and auditability. Include assumptions, risks, and a plan to retrain quarterly during [Timeframe].