> So you want them to watch a few exclusive shows a year so they feel like they got their money's worth, while not actually costing netflix much.
No, that's not what the strategy is and they're quite open about it - the strategy is to maximize user consumption for every user, because that keeps them subscribed. I think a lot of people think that they use sophisticated analytics and machine learning etc to decide what to greenlight, but they don't. They use the judgment (and politics, and egos) of Hollywood studio executives (and often the same Hollywood execs that a few years ago were employed in "legacy" media). Although I will grant that they've been innovative in producing/distributing international content, this is really just globalization and labor arbitrage (it is cheaper produce content not in Hollywood, that's not news - they just spend the extra $$$ localizing international content to different global target distribution markets but again, this flow has happened forever, it's just typically been Hollywood -> localization -> foreign market rather than foreign production -> localization -> Anglophone market).
Where analytics and ML does come into play is deciding which things out of their enormous catalogue they push to individual users at any one time - that process is highly reactive, individualized, dynamic - that's why strange and seemingly random media become big hits on Netflix while being largely ignored by the commentariat, and vice versa, why series with dedicated fanbases don't get renewed (the analytics tell you that, despite the apparent success, further investment will not improve user engagement with the platform by enough to be worth the spend).
> Where analytics and ML does come into play is deciding which things out of their enormous catalogue they push to individual users at any one time […]
Except they don't. Only Netflix has a vague reminiscence of ML/analytics-driven recommendations. The rest of streaming platforms offer anything but personalisation, which is particularly bewildering considering the financial and engineering resources available to the streaming behemoths. I do not have subscriptions for each streaming platform out there, but out of the several ones I do, Disney+ and especially Prime are the worst offenders that throw random trash either into the home screen or into the «personalisation» section, e.g. «because you have watched The Expanse, we thought you would like an NBA season / rugby World Cup» and stuff like that. You would think that obsessively clicking the «Like» button after watching something you actually liked would influence the personalisation, except it does not. Disney+, again, fills up the home screen with garbage I would never fathom could even exist.
The thing is that with the currently available technology, building a capable (it does not have to be perfect) recommendation is not that hard. At work, we almost daily design and build solutions that employ semantic similarity search / something, and with the current crop of multimodal LLM's that can generate vector embeddings with ease, it is relatively easy to build out a recommendation engine or algorithm tailored for the needs of a specific streaming platform.
Granted, specific optimisations are required and there will be unique new challenges in there; however, crafting such a solution is well within the realm of possibility. And the amount of money required is not even that high considering that many building blocks are available as mature, managed services, or creating a bespoke and tailored in-house solution does not require starting off from the clean slate by leveraging the prior art. That was not the case, say, back in 2018, but in 2025 it is a reality. For a bizarre reason that is beyond my comprehension, almost no streaming platforms do that.
> […] that process is highly reactive, individualized, dynamic […]
That is the aspiration and the high ideal; however, something else is going on, and it is not entirely inconceivable that the marketing department is complicit in the foul play.
To be clear, I was talking about Netflix, not Disney+. That's a completely different company with a different model and conflating the two is your mistake, not mine.
No, that's not what the strategy is and they're quite open about it - the strategy is to maximize user consumption for every user, because that keeps them subscribed. I think a lot of people think that they use sophisticated analytics and machine learning etc to decide what to greenlight, but they don't. They use the judgment (and politics, and egos) of Hollywood studio executives (and often the same Hollywood execs that a few years ago were employed in "legacy" media). Although I will grant that they've been innovative in producing/distributing international content, this is really just globalization and labor arbitrage (it is cheaper produce content not in Hollywood, that's not news - they just spend the extra $$$ localizing international content to different global target distribution markets but again, this flow has happened forever, it's just typically been Hollywood -> localization -> foreign market rather than foreign production -> localization -> Anglophone market).
Where analytics and ML does come into play is deciding which things out of their enormous catalogue they push to individual users at any one time - that process is highly reactive, individualized, dynamic - that's why strange and seemingly random media become big hits on Netflix while being largely ignored by the commentariat, and vice versa, why series with dedicated fanbases don't get renewed (the analytics tell you that, despite the apparent success, further investment will not improve user engagement with the platform by enough to be worth the spend).