Price cuts don’t fail by chance — they fail by math. Here’s the checkpoint almost everyone forgets. 😯 Two checkpoints In a previous post (Part 1), we looked at the first checkpoint: ➡️ Required volume growth: 15%+ is challenging, 25%+ extremely hard  But there is also a second checkpoint: ➡️ Price elasticity A simple guide 🟩 Low elasticity (1.0–1.5) Buyers care less about price Stronger differentiation e.g., branded clothing, specialty coffee, toiletries 🟨 Medium elasticity (1.5–2.5)...

Price cuts are easy to implement and welcomed by customers, but rarely deliver the results we expect. In a previous post , we examined why price cuts typically fail to generate the required revenue growth. Now, let’s extend the same logic to profit  — and here’s where things become even more challenging. When it comes to profit, one additional parameter changes the entire story: 👉 Your current margin. How Margin Shapes profit growth when discounting A single formula links margin and profit,...

Most people think yes — reality says otherwise 👇 Many teams believe they need perfect data before using AI in pricing (or anywhere else). More data helps — but waiting for perfection delays results. You can start now and still create impact. Here’s where AI fails due to data — and where it shines. 👇 ❌ Areas where AI is unlikely to work ➡️ Limited accessibility:  Data is scattered across systems (ERP, CRM, etc.) with restricted or no access to key information. ➡️ Corrupted data:  Data has...