Three complete scoring model templates for the most common B2B GTM motions. Each model uses a 0-100 scale split between a fit sub-score (0-50) and a behavioral
The Scoring Models skill provides three comprehensive lead scoring templates tailored to the most common B2B go-to-market motions: SaaS sales, product-led growth (PLG), and enterprise account-based marketing (ABM). Each model scores prospects on a 0-100 scale, dividing points between a fit sub-score (0-50) based on firmographic and technographic attributes, and a behavioral sub-score (0-50) reflecting engagement or product usage signals. These models include detailed attribute weights, decay mechanisms for behavioral signals, and score thresholds that guide qualification and routing decisions.
This skill helps marketers quantify lead quality using concrete criteria like industry vertical, company size, job role, and specific engagement actions such as demo requests or product activations. It also incorporates disqualifiers to exclude poor fits or competitor signals. The models serve as a starting framework requiring validation against your own closed-won data to ensure accurate prioritization and sales handoff timing.
This skill is designed for growth leads and performance marketers managing B2B GTM motions who need consistent, data-driven lead qualification. It suits SDR teams and marketing strategists working with SaaS products that rely on scoring to prioritize outreach and automate lead routing. Agency strategists supporting clients with PLG or enterprise sales models will find the scoring templates valuable to align marketing automation with sales engagement windows and account-based marketing tactics.
It is particularly useful for those overseeing multi-touch attribution and lead lifecycle management, where clear thresholds for MQL, PQL, and SAL status improve sales collaboration and pipeline velocity.
Practitioners first map their ideal customer profile attributes—industry, company size, seniority, technographic signals—and assign fit sub-scores accordingly, adjusting weights based on historical win rates. Next, they integrate behavioral tracking, mapping actions like demo requests, pricing page visits, or product milestones into the behavioral sub-score with appropriate decay rates to reflect engagement freshness.
After establishing scoring rules, marketers validate thresholds for qualification stages such as MQL, PQL, or enterprise flags by correlating scores with closed-won deals. Finally, they operationalize the scoring by defining routing protocols and outreach timing—for example, routing hot leads (80+) immediately to account executives or nurturing lower-scored leads with automated campaigns.
How do I validate the attribute weights for my business? Adjust and test weights against historical closed-won deal data to ensure the scoring model accurately predicts conversion likelihood. Can I combine fit and behavioral scores for routing? Yes, the models rely on combined scores with defined thresholds for routing to sales or marketing automation. What if a lead falls into an excluded industry or competitor domain? Those leads receive a fit score of zero or disqualification, effectively removing them from active scoring and outreach.
Attach the Scoring Models skill to a Metaflow agent task responsible for lead qualification or routing to enable automated score calculation based on your input attributes and engagement signals. The agent will apply the chosen GTM motion template and output a numeric score with fit and behavioral subtotals, along with qualification status flags. You can then build workflows that trigger actions like SDR outreach or marketing nurture sequences based on score bands and thresholds. This skill integrates seamlessly with your data sources to provide ongoing, real-time lead prioritization and qualification.
For broader context, see our roundup of claude skills for marketing, and read ultimate guide to Claude marketing skills for related setup guidance.