Something happened this month that stung more than any bad launch.
A platform I'd been active on started rejecting every post I made. No links, no promotion, just genuine questions rejected anyway. I emailed support expecting a bug. The answer was worse: my account had stopped reading as a human. It read as a channel.
Not banned for anything specific. Just quietly reclassified. And when I went back and counted, I couldn't argue. Over three months I'd posted about my product ~30 times there. Every post individually sincere. All of them, underneath, the same move me talking about my thing, to people I'd never once talked with.
I thought I was building in public. I was broadcasting in public. From the inside those feel identical, which is exactly why I couldn't see it. Every single post felt genuine, so I never questioned the pattern the posts added up to.
The uncomfortable lesson: I optimized every individual post and never once checked the ratio. How many times I showed up for someone else's thing vs. showed up with my own. Mine was indefensible.
What gets me is that a dumb automated filter spotted a pattern in my behavior that I was far too close to see myself. Which is the exact thing I keep claiming tools should do for founders.
So, genuinely asking the room: for those of you who post in communities as part of building what's your actual show-up-for-others vs. post-about-yourself ratio? Do you track it at all, or did you also only find out the hard way?
I’m new to these communities and started with almost no network, so most of what I’ve done so far is respond to other people’s work, with only occasional posts about my own project. I haven’t tracked a fixed ratio, but your point about the visible pattern mattering more than the intention makes me think I should. Did the platform say whether changing that pattern could reverse the classification?
I like that you separated the intention behind each post from the pattern those posts created over time.
I'll be interested to see whether changing that ratio also changes the kinds of conversations you end up having. Those patterns will probably reveal more about community trust than engagement metrics ever could.