Focusing on features with high demonstrability and proprietary data creates clear, defensible positioning that improves conversion and raises the barrier to competitor imitation. This method turns customer evidence into precise targeting and messaging that drive faster adoption and stronger sales outcomes.
The presenter outlines a go-to-market framework that maps product features along two axes—value to the customer and demonstrability—to prioritize messaging around features that are both high-value and easy to prove. Using an IoT sensor platform as an example, he shows how a feature that reveals precise, machine-level actions ('what to adjust and why') becomes uniquely defensible when backed by proprietary internal data. He recommends reverse-engineering why existing customers bought (using external public data and tools like ChatGPT) and mining internal customer conversations to derive repeatable insights. Those insights become the basis for highly targeted, evidence-backed outreach that competitors can’t easily replicate.
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