Do people feel that Netflix has a large enough catalog that its recommendation system really matters? The only useful feature it ever had for me was the ‘new this week’ category that seems to have been retired.
Really matters could be interpreted different ways. Expressed in startup-metric terms, it might be "% of users that watch something" or "time spent browsing before watching something." Any real improvement on such is probably important.
Think of it like Google's famous obsession with speed. Did returning search results 17ms faster really matter? It's hard to say for sure, but I suspect it did.
That said, I agree personally. I don't like Netflix' UI. I suspect you could hand code a browsing/ranking UI of similar value, from a casual users' perspective.
>> large enough catalog
I think this is a case where Netflix didn't end up where they expected the. I think they expected to have a vast catalogue... a "spotify of movies." It just didn't go that way.
You could also reverse the question. Does netflix have a big enough dataset to make a great recommendation system? I think this might be the more pertinent question. Google & FB have their vast ad-centric datasets. I suspect these could be used to make a recommendation engine that's a lot better.
They haven't really done this for youtube though. The priority is to match ads to users. For this, they're willing to push the envelope on how they use user data. For youtube recommendations, it doesn't seem that youtube gets access to much data from outside of youtube.
Their online selection was enormous ~2010 when they still had the DVD business, and crucially all of the movie studies still thought online was a fad and were happy to cut deals to stream their entire catalogs for pennies. Netflix was unbelievable back then and felt like it had every movie in existence. Over the years all of that back catalog has been clawed back and Netflix morphed into more of a showcase for their own content. But for a few golden years it was amazing to go in and like/dislike a bunch of stuff to see it just start recommending and streaming tons of classic films I always wanted to see.
As of last year when I finally quit, the DVD catalogue was still great, but service was so slow that it costs less to rent movies to stream individually.
Think of it like Google's famous obsession with speed. Did returning search results 17ms faster really matter? It's hard to say for sure, but I suspect it did.
That said, I agree personally. I don't like Netflix' UI. I suspect you could hand code a browsing/ranking UI of similar value, from a casual users' perspective.
>> large enough catalog
I think this is a case where Netflix didn't end up where they expected the. I think they expected to have a vast catalogue... a "spotify of movies." It just didn't go that way.
You could also reverse the question. Does netflix have a big enough dataset to make a great recommendation system? I think this might be the more pertinent question. Google & FB have their vast ad-centric datasets. I suspect these could be used to make a recommendation engine that's a lot better.
They haven't really done this for youtube though. The priority is to match ads to users. For this, they're willing to push the envelope on how they use user data. For youtube recommendations, it doesn't seem that youtube gets access to much data from outside of youtube.