[B-Con]

I have a theory: They realized the right approach is to focus purely on the yes/no of what you choose to consume, rather than trying to optimize the consumption experience itself.

Remember how YouTube and Netflix used to let you rate things on 1-5 stars? That disappeared in favor of a simple up/down vote.

Most services are driven by two metrics: consumption time and paid subscriptions. How much you enjoy consuming something does not directly impact those metrics. The providers realized the real goal is to find the minimum possibly thing you will consume and then serve you everything above that line.

Trying to find the closest match possible was actually the wrong goal, it pushed you to rank things and set standards for yourself. The best thing for them was for you to focus on simple binary decisions rather than curating the best experience.

They are better off having you begrudgingly consume 3 things rather than excited consuming 2.

The algorithmic suggestion model is to find the cutoff line of what you're willing to consume and then surface everything above that line ranked on how likely you are to actually push the consume button, rather than on how much you'll enjoy it. The majority of which (due to the nature of a bell curve) is barely above that line.

[ozbonus]

I think Netflix realized that reducing ratings to a simple thumbs up/down was a bad idea after all. A while back they introduced the ability to give double thumbs up which, if you can treat non-rating as a kind of rating, means they're using a four point scale: thumbs down, no rating, thumbs up, double thumbs up.

[xnorswap]

Netflix are right that 5-stars is too many, it translates to a 6 point scale when you include non-rating, and I don't think there is a consistent view on what "3 stars" means, and how it's different to either 4 stars or 2 stars ( depending on the person ).

For some people 3 stars is an acceptable rating, closer to 4 stars than 2 stars. For others, 3 stars is a bad rating, closer to 2 stars than 5 stars. And for others still, it doesn't give signal beyond what a non-rating would be, it's "I don't have a strong opinion about this".

Effectively chopping out the 3-star rating, leaves it with a better a scale of:

   - Excellent, I want to put effort into seeking out similar content
   - Fine, I'd be happy to watch more like it
   - Bad, I didn't enjoy this
   - Terrible, I want to put effort into avoiding this

With the implicit:

    - I have no opinion on this

But since it's not a survey, it doesn't need to be explicit, that's coded into not rating it instead.

These are comparable to a 5 point Likert scale:

    "I enjoy this content"

   - Strongly agree
   - Agree
   - Neither Agree nor Disagree
   - Disagree
   - Strongly Disagree

The current Netflix scale effectively merges Disagree and Strongly Disagree, and for matters of taste that may well be fine.

It would be interesting to conduct social science with a similar scale with merged Disagree and Strongly disagree to see if that gave it any better consistency.

[encom]

YouTube doesn't have ratings any more, because people disliked the wrong things which made Susan very sad.

I stopped rating things on Netflix, because after doing so for a long time, Netflix still thinks I'd enjoy Adam Sandler movies, so what's the point?

[johannes1234321]

YouTube got ratings, you may still up- and downvote. They however don't show down votes anymore.

[Spooky23]

Yes! It started changing when the shifted from DVD which are sold based on the physical asset to the contract deal for content.

Their objective shifted to occupying your time, and TV you’ll accept vs. movies you’ll love is a cheap way to do that.

[_petronius]

I mean, if you read about how current industry-standard recommendation systems work, this is pretty bang on, I think? (I am not a data scientist/ML person, as a disclaimer.)

If e.g. retention correlates to watch time (or some other metric like "diversity of content enageged with"), then you will optimize for the short list of metrics that show high correlation. The incentive to have a top-tier experience that gets the customer what they want and then back off the platform is not aligned with the goal of maintaining subscription revenue.

You want them to watch the next thing, not the best thing.