B2B Marketing with Fexingo · 2026-08-06 · 11 min
In this episode of B2B Marketing with Fexingo, Lucas and Luna dive into how enterprise marketers are moving beyond static lead scoring to predictive account scoring. Using a real-world example from a mid-market SaaS company that cut its sales cycle by 20 percent, they break down the shift from demographic fit to behavioral intent, explain how to blend first-party and third-party data, and discuss where human judgment still matters. Lucas shares a framework for scoring accounts based on engagement velocity and org-fit signals, while Luna challenges the bias toward large accounts and suggests a tiered scoring model that balances risk and opportunity. They also talk about how to align marketing and sales around a shared definition of a 'fit' account, and why predictive scoring fails when it ignores the buying committee's internal dynamics. If you're trying to get your ABM program to focus on accounts that are actually likely to buy, this episode gives you a practical playbook - without the hype.
Other episodes covering the same guests and topics, from across The B2B Podcast Index.
The AI-Native GTM Playbook | Sam Blond, MonacoThe Peel with Turner Novak · on Account scoring79 / 100
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