Directly giving the users predictions that are based on latent factors has a huge problem -- is there ever really a case where the latent factors have very high

Directly giving the users predictions that are based on latent factors has a huge problem -- is there ever really a case where the latent factors have very high prediction ability, but an analyst can't simply see what's driving the preferences by looking at those factors, and then create something better by targeting that interaction directly? Better to analyze the latent factors, and then use that analysis to gain engineering-type insights into the structure of the problem, and target specifically what's driving people to like something. Exactly as Netflix has been doing in recent years. Exactly as people have done when writing books or developing other entertainment content for centuries. Just dumping unsupervised clustering on the end users is a poor technique that should stay in the 1990's where it belongs.