The quality of Netflix's recommendation engine went downhill quickly after their move away from the 1-5 star rating system last March. I put a lot of time into picking the right values for each of the movies I watched and was constantly amazed and how good its recommendations were. Still a happy subscriber, just a little less so.
Netflix used to want to give people the "perfect movie for them", expecting that eventually they would run out of perfect movies, and move onto just "pretty well-fit movies", and then run out of those too, and probably unsubscribe at that point.
Nowadays, Netflix seem to want to keep people subscribing by making them feel like they have a chance of finding the "perfect movie for them", but only after Netflix has recommended a bunch of those "pretty well-fit" and even some "not-so-well-fit" movies. This is "better" (from Netflix's perspective) for two reasons:
1. it gives people the impression that Netflix's library still has plenty of "perfect" movies to offer them (by stretching them out);
2. it gives variable-scheduled rewards, rather than constant rewards, making people more addicted.
I'm betting the new algorithm works much better at keeping people subscribed, despite seeming to work worse. Netflix is a very data-driven company, and wouldn't have switched to an algorithm that could be observed to hurt.