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On today's episode, we sit down with lead scoring consultant Lucas Winter to explore a refreshing, data-first perspective on building lead scoring models—one that challenges the conventional wisdom and AI hype alike. With storytelling flair and practical insights, Lucas discusses how marketers can uncover true buying intent and dramatically improve sales efficiency.
Tune in to hear:
- "Moneyball" Meets Marketing Ops: Lucas applies the Moneyball philosophy to lead scoring—focusing on what actually drives conversions versus what sales or execs think looks good. It’s about looking for patterns in customer behavior, not just traditional job titles or industries.
- AI’s Limitations in Lead Scoring: While AI has promise, Lucas outlines how AI-driven models often misinterpret causation (e.g., recommending “retired” contacts) and require human oversight to avoid absurd conclusions.
- Gold, Silver, Bronze > Arbitrary Scores: Ditch complex scoring ranges like “0-100” and opt for intuitive models like “gold, silver, bronze, junk”—making it easier for sales teams to understand and adopt.
- Why Gmail Isn’t Garbage: Contrary to common assumptions, personal email addresses like Gmail can indicate serious buyers—especially in early-stage startups. But to gain sales trust, these leads must “work harder” to earn high scores.
- Start Simple, Stay Iterative: Don’t wait for perfect data or fall into “overreactive” model changes. Build a solid draft, validate with real outcomes, and evolve based on performance—not opinions.
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