Consumption signal. You paused. You approved. You moved on. The algorithm counted it. You forgot it before the next scroll.
Intent signal. You stopped. You thought: I will come back to this. I will use it. I will share it with someone. That intention does not fade the way a like does.
Most content is built to be seen.
The question worth asking: is it built to be kept?
Reach. Engagement rate. Follower count. None of these tell you if your writing is becoming an asset.
Not opinion. A corpus. Intentionally biased toward quality: we wanted to study what good looks like, not the average.
Product-news content. The algorithm amplified it. Nobody saves a feature announcement for later. Events-reactive content does not age into reference.
Smaller reach. But 1.73 people saved this for every 1 who liked it. That is 73% more bookmarks than likes. A reference, not a reaction.
Before you recommend anything, list the places your idea fails. Hassid calls it "where it falls short (I promised honesty)." Five honest failure modes before the recommendation. Readers save articles that do not oversell because they trust them enough to return.
Three-tier paid funnel at the end of every article. Optimises for conversion. Sends the signal: this was a sales vehicle. Readers save sales vehicles less.
The close lands the argument and stops. No funnel. No CTA stack. The article feels complete, not transactional. The two outlier reach articles in the corpus both close this way.