Disclaimer: I started working at FB recently. Consider the following model scenario. You are a PM at a discussion board startup in Elbonia. There are too many discussions at every single time, so you personalize the list for each user, showing only discussions she is more likely to interact with (it's a crude indication of user interest, but it's tough to measure it accurately). One day, your brilliant data scientist…
And even if it was supported by research, I would think about the long tail. What does this mean for my user engagement in the long run. This list might satisfy them now, but it necessarily leads to a narrowing down of the content pool in the long run. I would ask my marketing sciences unit or my data science unit, whatever I have, to try to forecast or simulate a model that tells us what would the dynamic of user engagement be with intervention A and intervention B.
I feel this is one of the biggest problems of program management today. Too much reliance on short-term A/B testing, which, in most cases, can only solve very tactic problems, not strategic problems with the platform. Some of the best products out there rely much less on user testing, and much more on user research and strategic thinking about primary drivers in people.
If you were to use this approach - you might see that actually, the product you have with choosing to optimise for short-term engagement brings less user growth and less opportunity for diverse marketing - which, it is important to note, is one of the main purpose of reach-building marketing campaigns.
I would say the way this whole problems is phrased shows that the PM, or the company indeed, is only concerned with optimising frequency of marketing campaigns, rather than the quality, reach and engagement with marketing campaigns.
Obviously, hindsight 20/20 and generals after battle and all that. I'm still pretty sure I would've thought more strategically than "how do I increase frequency of showing ads".