The Three Types of Bad Data

Bad data isn't just useless, it's actively dangerous, because it gives you false confidence to build the wrong thing. The three types: compliments, fluff (generics, hypotheticals, the future), and ideas.

A conversation full of 'that's awesome' and 'I would totally use that' feels like a win and is actually a failed meeting. You walked out with zero facts about their life and a head full of encouragement.

The tell is who did the talking. If you talked most of the meeting, you were pitching. If you leave able to describe their workflow, their last attempt to solve the problem, and what it cost them, you have real data.