Rebecca, analytics engineer at an industrial supply company

I started this book for the numbers. I stayed for the structure.

Most business books sprinkle a few percentages over the usual anecdotes and call it data-driven. This one does the opposite. The numbers aren't decoration — they're the spine. The Uber Eats chapter cites an 18–25% uplift in cross-sell conversion, sourced to a specific podcast appearance. The ActiveCampaign chapter pins a 12% conversion lift to a company blog post that I actually went and read. I recognize good data hygiene when I see it, and the author has it.

What I didn't expect was how useful the non-data parts would be for my actual job. I work on internal tooling at a B2B company, not customer-facing product. I picked up the book because I was curious about the psychology. By Chapter 3, I was redesigning our internal catalogue schema for spare parts. The argument that relevance flows from attribute granularity isn't just an ecommerce insight — it's a general truth about any system that needs to match supply to demand. Our procurement team's search accuracy improved because I added structured fields for compatibility and use-case. That's not an upsell. But it's the same architecture.

The prose won't win literary prizes, but it's clean and patient. The author assumes intelligence without showing off. I've already passed my copy to a colleague.