In my experience, they usually start much earlier, when events are loosely defined, named inconsistently, or never written down at all.
When definitions aren’t clear, numbers can be technically correct and still misleading. Everyone thinks they’re measuring the same thing, but the intent behind the data isn’t aligned.
Over time, this made me realize that documentation isn’t overhead. It’s what turns analytics into something teams can actually trust.
That’s the problem I’m trying to solve with EventDocs.io.
What usually goes wrong first in analytics?