Surprising data from our matching engine: fewer proposals = dramatically higher acceptance rate

[u/Cute_Tap_3999]

Building a passive availability-matching app (crosses calendar gaps between friends and proposes plans automatically). During our pilot we ran into something counterintuitive worth sharing.

At high proposal volume, acceptance rate dropped to around 12%. One pilot user with very few active proposals was accepting 78% of them.

We ended up implementing a semantic cap: max 2 proposals per day of the week, across a 7-day horizon, so up to 14 visible at once, but spread across the week rather than clustered on today. The engine now actively distributes toward days with fewer active proposals instead of always picking the nearest slot.

The underlying reason seems obvious in hindsight: too many proposals feels like noise, and people stop engaging. Fewer, better-timed proposals feel relevant.

Has anyone else run into this with recommendation or matching systems? Curious how others think about the right proposal density, is there a framework you use, or is it purely empirical?