> - the KPI "do-more-users-leave-our-platform-earlier-if-our-matching-algo-is-just-too-good" - I promise: In alle the years, this question WAS NEVER - NEVER!!!!!!! - raised, regardless wich Manager or which Exec. This metric isnt even debated.

What labels do they use for training their algos though? What is their definition of a successful match, is it a date, a recurring date, or something closer to a long-term relationship?

If matches predominantly result in "failure" they might just not have enough "long-term success" labels to go by, and their proxy labels will be biased towards short-term successes.

Wrong approach; at least until latest, NONE of the standard apps does apply any kind of "real AI" stuff, maybe this changed through the last 3 - 4 years.

All thi matching stuff like "match with X%" is just bullshit.

The only platform having a useful approach here was OKC years ago. (but even for their scoring you would not need any type of sophisticated tech)