B2B Marketing with Fexingo · 2026-07-10 · 11 min
In this episode, Lucas and Luna dive into the mechanics of predictive lead scoring for B2B enterprise sales. They break down how machine learning models assign scores based on firmographic, behavioral, and intent data, using a real example from a cybersecurity company that cut time-to-qualify by 40 percent. They discuss common pitfalls like garbage-in-garbage-out data hygiene and the tension between model complexity and sales team trust. The episode also covers how to align score thresholds with different sales motions - from inbound acceleration to ABM tiering. Listeners will learn one concrete framework: the trade-off between recall and precision in scoring models and why focusing on top-of-funnel conversion rates can mislead teams. A practical episode for any B2B marketer managing long sales cycles. #PredictiveLeadScoring #B2BMarketing #EnterpriseSales #DemandGen #ABM #MachineLearning #SalesPipeline #LeadScoring #MarketingOps #DataDrivenMarketing #SalesAndMarketingAlignment #Cybersecurity #B2BSales #MarketingAnalytics #RevenueOperations #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo
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