6 Essential Lessons for Building Great Data Products

Image by the author

After over a decade in data and writing a book on the subject, I’ve distilled 7 essential lessons for creating data-powered products.

For much more on those lessons, check out the book on it: “The 7 Data Product Strategies” packed with lots of examples and hundreds lessons more.

Let’s get straight to it:

1. Collect Unique Data

According to Marc Andreessen, the big challenge of venture capital is not to tell good from bad investments but rather to tell good from great ones.

Because for better or for worse, the very best VCs collect fast amounts of companies, most of which will go absolutely bust. But there is a power law to their returns, meaning the Top 3 of their successes basically dwarf every other win, and then the top 3–10 again dwarf everything else.

So, what does a great VC really do? He collects a vast amount of companies, knowing almost all of them will go bust and not return a penny. He’s willing to do so because he knows some will be a gold mine.

Adobe took this approach with data. They collected everything — small, seemingly insignificant pieces of user interaction data. Years later, those seemingly minor investments became the foundation of their AI kingdom. A kingdom that by…