It’s a common pattern for teams building B2B analytics and AI products: the proof-of-concept goes well, the buyers sound excited, and everyone assumes the deal is about to close—until it quietly stalls out. The assumption is usually that sales needs to follow up harder or marketing needs more enablement material. But often, the real issue is that the product itself cannot communicate its value without humans in the room explaining it.

I call this the Invisible Intelligence Gap. Buyers may understand the promise during a guided demo, but once the sales engineers leave, customers are left trying to figure out workflows, use cases, trust concerns, integrations, and organizational fit on their own. This gets even harder with broad, general-purpose AI tools and chat-based interfaces that sometimes assume users already know what to ask.

The solution isn’t simply shipping more features or training content. It’s designing products that clearly reveal their value, reduce customer effort, and continue selling themselves after the POC ends, and getting that design right starts with the right product strategy. 

 

Highlights/ Skip to:

  • First principles thinking - add sales effort or fix the product? (0:43)
  • How the POC phase supports sales efforts (3:28)
  • The role of the Invisible Intelligence Gap (5:38)
  • What is “buyer’s block” and how to avoid it (6:26)
  • Avoiding the “Two-Costs Model” and what that model is! (11:34)
  • Overcoming a stalled sales process (13:42)
  • Understanding the problem, users, outcomes, and boundaries (14:41)
  • Three product strategy moves you can make (17:50)
  • Always ask how customers are experiencing the product and if it sells itself (24:04)

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Podden och tillhörande omslagsbild på den här sidan tillhör Brian T. O’Neill from Designing for Analytics. Innehållet i podden är skapat av Brian T. O’Neill from Designing for Analytics och inte av, eller tillsammans med, Poddtoppen.