Why Prospects Ignore You (And What to Do About It) | Jean-Philippe Schepens van Thiel - 1921
Episode
33 min
Read time
2 min
AI-Generated Summary
Key Takeaways
- ✓Signal-Based Timing: Monitor hundreds of millions of daily signals across company websites, LinkedIn, patents, trade shows, and news to predict buying intent before competitors detect it, enabling outreach when prospects actually need solutions rather than guessing.
- ✓Three-Sixty Degree Data Cocktail: Combine multiple real-time data points into predictive signals rather than relying on single triggers like CEO changes or funding announcements. Ten relevant signals from 500 available data points create accurate predictions for specific sales scenarios.
- ✓Human-AI Validation Loop: Sales reps validate machine predictions to train the system on market-specific patterns, creating dynamic signal cocktails that adapt daily. This approach doubled a UK chamber of commerce's yearly revenue in one quarter by targeting Belgian companies before UK expansion.
- ✓Relevance Over Volume: Prospects receive 150-plus daily LinkedIn messages, creating saturation. Success requires describing customer problems better than they can themselves using behavioral signals, positioning sellers as experts rather than requiring prospects to educate them on their own needs.
What It Covers
Jean-Philippe Schepens van Thiel explains how sales teams can use AI-powered signal analysis and real-time data to identify prospects at the exact moment they're ready to buy, replacing spray-and-pray outreach methods.
Key Questions Answered
- •Signal-Based Timing: Monitor hundreds of millions of daily signals across company websites, LinkedIn, patents, trade shows, and news to predict buying intent before competitors detect it, enabling outreach when prospects actually need solutions rather than guessing.
- •Three-Sixty Degree Data Cocktail: Combine multiple real-time data points into predictive signals rather than relying on single triggers like CEO changes or funding announcements. Ten relevant signals from 500 available data points create accurate predictions for specific sales scenarios.
- •Human-AI Validation Loop: Sales reps validate machine predictions to train the system on market-specific patterns, creating dynamic signal cocktails that adapt daily. This approach doubled a UK chamber of commerce's yearly revenue in one quarter by targeting Belgian companies before UK expansion.
- •Relevance Over Volume: Prospects receive 150-plus daily LinkedIn messages, creating saturation. Success requires describing customer problems better than they can themselves using behavioral signals, positioning sellers as experts rather than requiring prospects to educate them on their own needs.
Notable Moment
A nonprofit refurbishing IT equipment for African education doubled device collection from 150,000 to 350,000 units in three months by predicting which companies with green ESG propensities would lay off employees and calling before restructuring announcements.
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