Do you think part of this is that Netflix has assumed zero effort from user model? My experience has been that Netflix does an ok job of recommendations, but fails at overall discovery experience. There is no way for me to drive or view content from different angles easily. I end up googling for expert opinions or hitting up rotten tomatoes to get better reviews. Netflix knows a ton about me and their content, but seems to do a poor job of making their content browseable/discoverable overall. I do like their "more like this" feature where I can see similar titles.
Perhaps its because its a niche that isn't worth investing the resources into? Sometimes narrow problem spaces are harder for a company to justify because of the cost to reward ratio. I agree with what you want and would like it myself for music (Spotify, Amazon Music, etc.) but it's a complex problem (recommenders, custom UI and the glue between) that is hard to justify compared to incremental small improvements to existing general purpose recommendations.
It just seems like there's a paucity of signal from which Netflix could come up with anything intelligent. Movies are many hours long, and there are many reasons I could be watching something. What does it mean that I allowed a movie to play to completion? Was I even paying attention? Did I decide I hated it 3/4s of the way through, but finished it just because I cared about the plot?
TikTok, on the other hand, has way more data. Things like time-to-swipe, shares, comments presumably form the basis of some sentiment metric.
Google TV has the best content discovery I've come across so far. Recommendations across most streaming services based on overall similar movies, different slices of the genre, and movies with similar directors/cast members. Plus as soon as you select another movie, you can see all the same "similar" recommendations for that movie.
>Do you think part of this is that Netflix has assumed zero effort from user model?
Talking w/a friend who works at Netflix, it sounds like this is a warranted assumption. The way he told it, they were tearing their hair out at one point b/c users wouldn't put much into it.
What I don't understand about their response is: why not make it configurable? Admittedly this is my philosophy for almost every product I work on - "make it maximally configurable, but make the defaults maximally sane" – but I'm baffled every time I hear someone talking about this 'dilemma'.
You just keep your simple interface, but allow the power users to, say, click through to a particular menu and change their setting – the setting in this case being ~"let me provide feedback / configure how recommendations work". For that kind of user, finding a 'cheat code' is actually a gratifying product experience anyway.
I think its because the complexity of allowing configurability isn't always worth it. Verifying it works for all configurations becomes exponentially harder.
I believe it can also have performance implications especially for things like recommender systems where you are depending a lot on caching, pre computation and training.
I agree, but as aleksiy123 suggests there is an additional complexity burden and it is a long journey to teach users to make use of a new technology. I think a lot of "advanced" features get de-prioritized as not many people use them and it seems like resources could be better spent helping the masses. I think that the importance of "advanced" features is often under rated by traditional engagement models. Wikipedia is a great example of where less than 1% of users click on the edit button, but that 1% adds all the value for the other 99%.
