Latest / Bulletproof Screenwriting™ Podcast / BPS 287: Screenwriting for Netflix's Algorithm with Stephen Follows

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BPS 287: Screenwriting for Netflix's Algorithm with Stephen Follows · Bulletproof Screenwriting™ Podcast

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Slash Free. Now, guys, today we have returning champion Steven Follows.
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Many of you might remember Stephen as the dataman, the man who crunches the
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film data like nobody else in the world, and he has been on the
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show multiple times and my favorite episode, of course is when we finally proved
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for once and for all that Diehard is the greatest Christmas movie all time,
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and we looked at the numbers to prove it. Now Steven's back on the
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show because he has launched a new website called vod Clickstream, and what he's
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done is remarkable. He's been able to go inside of Netflix to see what
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is actually going on in all of their data. He's been able to come
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up with answers for questions like does Netflix have a long tail? How do
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romantic comedies perform on Netflix? How do scipher films perform on Netflix? Did
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American audience stream international TV shows? How did The Office truly perform on the
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platform? Which TV genres are the most popular on Netflix? And so so
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many more. When I heard about this, I called up Stephen. I
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said, Stephen, you got to come back on the show. We need
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to get this information out to the tribe because it's just, again a snapshot
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of what Netflix was doing during the time of twenty sixteen two end of middle
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of twenty nineteen. But it is better than nothing, when before all that
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information had been hidden behind the walls of Netflix. But we have been able
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to get inside of that. Now I do have to have a disclaimer for
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this episode. All this information is wholly independent research and is not affiliated with
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Netflix or any other streaming platform or studio. Just wied to make that very
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very clear. So without any further ado, please enjoy my eye opening conversation
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with Stephen follows. I like to welcome back to the show, returning champion
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Stephen Follows. How are you doing, Stephen Dan? Very well? You
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say that every time, and I'm starting to believe you. Well, that's
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what I'm trying to do. A little by little, I'm building. I'm
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building you up. So I'm building you up. I'd like it to be
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back. And your audience are always awesome as well. Every time I'm on
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the podcast, people reach out to me and say, hey, I heard
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you. I'm part of the tribe. I heard you an Alex's podcast,
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Hey I got And every single one so far has been like really polite but
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also with a really interesting question or perspective, and yeah, you've got a
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great tribe. So I'm always happy to come back. Thank you, man,
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I appreciate that. And last time we were on the show, we
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did that die Hard episode which was fairly controversial. Sir, oh was it
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did you get pushback? No, well, a couple of people, A
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couple of people. I got a couple of dry members of like really Alex
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an entire episode about my heart and I'm like, yes it is. But
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you know, funny enough is that when I m h where when I m
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talk to people now about Diehard because now I'm you know, I'm I'm an
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evangelist. Um, I go, you know, you know that hurts it
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Christmas movie, and they'll push back up like no, no, no,
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no, no, I have data. I have proof that dieharded. So
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I appreciate you doing the hard work on that. And so now at parties
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or at least Zoom meetings, nowadays, I get to I get to say,
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no, no, I have got data, here's the link, and
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I send them to our interview and people are just like amazing, and I
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just it's always the thing you want to hear a party when you're having a
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conversation with someone, when they go, no, no, I have the
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data. I know exactly. It's just your life of the party. You
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are the life of the party without without question. Um. And then I
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just released a link of the top twelve screenplays of unconventional Christmas movies, and
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of course Diehards on the top of that list, but I had lethal Weapon
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on there. Um, what else did we have on their lethal Weapon?
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Gremlins, Gremolin's too good Night? Which one? What's the one with from
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ninety seven with oh oh Davis, Oh No, Longest good Night? Yes,
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Longest gons Longest good Night is on there as well. A bunch of
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a bunch of Shane Black, A bunch of Shane A bunch of Shane Black
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episode whatch I'm gonna call it screenplays because he's he just loves, absolutely loves
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writing. I mean, I could argue Iron Man three, but I prefer
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not. Um, you know, Disney do do list that? And on
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Disney Plus on the Christmas movies? Oh, I genuine yeah, I genuinely
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don't know if they're doing it to try and stir up controversy or do they
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genuinely believe it. And before we start on our current interview, I have
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to I'm going to list off the list of Christmas h Christmas unconventional Christmas movies,
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Die Heart, Lethal Weapon, Kiss Kiss Bang Bang, Uh, Gremlins,
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Gremlins to Batman Returns. Yeah, eyes wide shut, Oh you really
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went I went there, sir, Yes, Edwards, scissor Hands, blon
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Kids, good Night, bad Santa, Black Christmas, and Prampus. Yes,
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yes, all quite a list. That is that. That was.
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It took me a minute to put it together. But I had to.
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I had to. I had to. I had to. I had to
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give them love. So so just Leaven, man. I mean, I'm
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always so impressed with everything you do. I love. You're just an insane,
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insane, insane human being. Um. In the way and the same
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way you call me insane for what I do. It's it's a mutual admiration
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because I can never do what you do in in twenty lifetimes, I don't
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think I'll be able to ever do what you do. Um, But I
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was, I was. I don't know where I saw it, because you
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kept it, you kept this to yourself. I have to I have to
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keep this. I have to. I have to give you props for this.
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You told me that you were working on something big, and I'm like,
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what is it. He's like, I can't, man, I gotta
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keep it. I gotta keep it quiet. And I'm like, all right,
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fine, I do the same thing. That's fine. And then I
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think I saw a pop up. Somewhere like a few weeks later and this
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thing called VOD click Stream showed up. I'm like what And I clicked on.
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I'm like, what is this? And and I didn't get Honestly,
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I didn't connect that it was yours for a second till I till because I
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literally had no idea what this was. And then I went to the about
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and the team and I'm like, oh, son of up, this is
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this is Stevens. And I emailed you right away. I'm like, what
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is this? What's going on? So can you tell? But yeah,
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so so I did. Actually I think it's like, what the f So
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can you tell the audience what VOD click Stream is? Yeah, definitely.
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I'll give you the simple pitch, and then I'll make it more complicated than
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nuance because it's got some weird sort of qualities to it. But the simple
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pitch is that I've got an access to a huge data set which reveals what
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people have been watching on Netflix over a three and a half year period.
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So this is yeah, I know, it's It's something I've been chasing for
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a while. And we can talk, you know, in a minute about
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the history of the whole thing. But it's been something I've been chasing for
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a while, and it's it feels it's like almost more of a mission for
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me than than just a stats project, because I don't like that we don't
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know what's going on on that spot, and I think it matters, I
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think, and I think it matters, you know, for your audience and
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my audience, which are very similar. We'll be right back after a word
9:46
from our sponsor and now back to the show. Like, the studios must
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have a better idea than the average filmmaker, and we don't have the kind
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of of openness and transparency that we have on theatrical or in other areas.
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And crucially, everyone's experience of s FOD is so different. My wife and
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I share a Netflix account, but we have our own profiles, but they're
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so different. If we're accidentally locked one with hers, I'm like, oh
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my god, it's all pink, white Sonutri Bullock and everything. Mind,
10:18
Like, why is everything so sad and exploding? And the thing is what
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that means is that even two people who like live together still can't get a
10:26
sense from their own experience. Whereas when you go to the theater and you
10:30
see if it's full. You see lines, you know, you hear about
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it, and we have the same shared experience. So because of that,
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because of the s FOD is so highly personalized, you can't get any clues
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how things are doing. And they started to release a little bits more data
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in the last few months and stuff, but compared to what we're used to
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getting on the box office, and even that's not enough. Like how a
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filmmakers supposed to know what to do, what people want to watch? Like,
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what is this new realm that is dominant eating so much of the value
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chain is only going to dominate more of it. And obviously COVID and LEFT
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I just don't know how else we're supposed to do this. So this is
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an answer to that. I guess it's not perfect, but it's it's pretty
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unusual and I think really powerful. And we've only just begun. Really,
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this isn't a project where I've launched a finished thing. Here's a report,
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go read it. It's like, okay, the work begins now. So
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this is essentially the wholy gril. This is, this is this is El
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Dorado for you as far as data. As far as data is concerned,
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no, it's neither is the Holy Neither is the Holy Gril or El Dorado
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for that matter. I get the WiFi is terrible in Eldorado. It's horrible.
11:37
It really, I've been there. It's not it's not pleasant. Is
11:41
that why you left? Yeah? Yeah, I just left. I mean
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I grabbed a couple of things along the way, but left. But yeah.
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So it's like it's been really exciting. And the volume of data and
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the complexity of the data is it's an order of magnitude, much bigger than
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I'm used to dealing with. So it's not just me. I've had some
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help from some amazing data signs. And most of them, I mean two
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of them have PhDs and theoretical physics, you know, they deal with things
12:07
like dark matter and whether the standard model of the universe as we understand it
12:11
is correct or not. And then I start talking to them about like what
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we know about Netflix and and they're like, Wow, we know more about
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dark matter. We know more about the origins of the universe than we know
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about what a film performed on Netflix. And I was like, ah,
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do you want to like join the team, Let's figure something out. And
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you're India. You're Indiana, Jones and you're putting together a team. They're
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almost all physicists, like we're the team is more I think it has more
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theoretical physicists than people who are not a theoretical physicist. And by the way,
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I'm one of them not And so it's been kind of bonkers because not
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only are they very talented data scientists, but also they're used to dealing with
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abstract ideas and abstract numbers, and actually you need to deal with that.
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I mean, we'll talk about this later on. I'm sure some of the
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ideas in how you analyze this get quite abstracted quite quickly, because it's not
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as simple as like, you know, box office. You say how much
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money did it make? Even that's a bit flat because you don't know if
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it was lots of kids or fewer adults, or peak time or off.
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But generally it's comparative, you account for inflation, you can sort of sort
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of out with this data. It's so much more complicated than that to try
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and get straightforward, simple answers, and so that's why they were so they
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just had all the right training for it, and it was just a joy
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to work with those just incredibly smart talented people and sort of see if we
13:35
can do something interesting for the film community. I have a theory, see
13:39
if it. I feel that the reason why people take you seriously, it's
13:43
not only because of your work ethic and your talent, but I truly believe
13:46
it's you. It's your it's your accent. Because everything you say I mean,
13:50
I mean it's it sounds so legit. Like if you if you would
13:56
like, listen, my friend, I have some land to sell you,
13:58
some swampland to sell you in Florida. I'd be continue. But you know
14:03
that you have a voice for excitement. Let me tell you something exciting.
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I'll be like, Oh, so if we joined forces, Stephen, we
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could rule the war or we could ruin each other. Very true, very
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true, served very very true. Okay, So how okay, so you're
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essentially going inside the algorithm of Netflix's ex something like that. Not quite that.
14:28
So, so this it doesn't come from Netflix themselves. There's no data
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breach. We haven't scraped it, we haven't taken it from them in any
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sense. What's happened is it utilizes this sort of type of data called click
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stream data. And what click stream data is is that people have volunteered,
14:46
they've signed up, they've opted in to install plugins and services and things like
14:52
that in their browser and other things like that, and that these let's say
14:56
plugins are really useful, you know, they maybe they're a really good trend
15:00
later tool, or they just do a certain thing really well, and they're
15:03
free for the users. And the deal is that in return for that,
15:07
the users agree that they're anonymized history. Their click stream, all the clicks
15:11
they made essentially can be sent to a server and put into a big bucket
15:16
and that sort of fire hose of millions and millions of people. They're anonymized
15:22
history allows us to see what the journey they made around the web. And
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so the actual raw click stream which I don't have, which is the full,
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like epic amounts of data. You can imagine millions of people clicking constantly
15:35
or around the world. That is so valuable to so many people in so
15:39
many different ways. You know, you could get a sense of how popular
15:41
something is before the quarterly reports come out. You could see how people are
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buying things on Amazon. All that what I wanted was the tiniest slice of
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it, and I just wanted I actually wanted all the spot streamers, but
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Netflix was, for various reasons, the best one to go for. And
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I've been chasing these guys for a while, and I was like, because
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I've known about this for a few years, and I have said, look,
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just give me access to the Netflix slice Netflix dot com because it could
16:07
be really instructive and very useful for filmmakers and stuff like that. And because
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of the nature of the click stream industry, it's a small industry that makes
16:15
highly expensive content data, and so they were quoting massive figures, like five
16:21
figures a month, a massive high end, and it was just impossible.
16:23
And then so I've been talking to them every six months or so, I
16:26
catch up and go, hey, have you suddenly sort of decided that your
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data is worth far less than it was? And they're like nope. And
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then around the summer of twenty nineteen, there was a sort of big shift
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in the click stream data world where there was a there was a sort of
16:42
a perfect storm of a few different things, like some of the brows that
16:48
the big browsers changed some of their rules about what their plugins and extensions could
16:52
do and what data they could share. Generally, people were getting tighter on
16:56
privacy and so things that they were happy to share in the past they were
16:59
less happy to share now. And just so all these sort of things came
17:02
together and so the clixtream industry transformed and sort of what a lot of the
17:04
business models they had imploded, and some of the companies are still around doing
17:08
other things, but basically it kind of that version of it kind of ended
17:12
in the summer or twenty nineteen, and so towards the end of last year,
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in the beginning of this year, so the beginning of twenty twenty,
17:21
I went back to them and said, look, you've got this now of
17:22
static data set, and I can't offer you load of money. I can't
17:27
there's no I don't know if the values in that, and I can't do
17:30
much with it, but I know that it's fascinating and for filmmakers and could
17:34
be very instructive. Please can you basically give me the Netflix data? So
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I worked out a deal with them, which didn't which was possible to do,
17:44
and then so then they gave me about two thirds of a billion data
17:49
points. And so first of all, it was it's just the volume is
17:56
like it's just and you know, they get they gave me a sample.
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You can only have a million rows in Excel before it crashes, and before
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it didn't won't load any more rows. And they gave me a sample of
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the data and it was like day one, hour one. An Xcel was
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like, that was an hour. It was day one, But an excelent
18:15
can't can't look at anymore. And so that that volume is amazing because it's
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it's really granular. And so what I ended up with was, these are
18:23
anonymized users. So each user has a randomly generated ID which resets over a
18:29
certain period, and I know what country they're in, and I know what
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you r l. They clicked on exactly the time and the day, and
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that's pretty much it. There's a bit of metadata that's pretty much it.
18:37
And so in and of itself, a click isn't doesn't mean anything, but
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when you add them together you can infer meaning. So you could say this
18:45
person clicked on the Netflix link that is the watch page for a bit of
18:51
content, and the content of twenty two minutes long. They waited twenty two
18:53
minutes and then they clicked on the next one. Well that you can reasonably
18:56
assume that they viewed it right, And you also can see what people have
19:00
searched for and things like that. So we have all this data. It
19:03
has sort of three big limitations. The first is it's historical, so our
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data starts in the beginning of twenty sixteen and ends in the summer or two
19:12
nineteen, so it's like three and a half years. It's a shame it's
19:15
not live that everyone asks me, can it be live? And the answer
19:18
is always sadly not. But if it were live, I wouldn't be able
19:22
to get access to it, So it's kind of it's this or nothing.
19:25
Secondly, it's only desktop and laptop users, which Netflix say are about twenty
19:30
five percent of their audience, and so we didn't know if that would have
19:34
a skew or not, like whether people watch fundamentally different content on their desktop
19:38
and laptop than they do another on TV or tablets or whatever. We'll be
19:44
right back after a word from our sponsor, and now back to the show.
19:52
So the first thing we did was that we went about recreating the stats
19:57
that Netflix had announced during that period. So when they've said bird Box got
20:02
x number of views or was the number one film within the first two weeks
20:04
or whatever, whatever, it was like any data point that they said in
20:10
a press release, we would go back to our data and try and recreate
20:14
it. You know, we would perform the same analysis, and time and
20:15
time again we were getting the same answers they were getting. So because of
20:19
that analysis, I'm very very confident that the big picture we have is a
20:26
very very good model of what they have. There'll always been cases where it's
20:29
slightly different or whatever, but fundamentally, considering we're starting with nothing, I
20:33
think we're very happy with that was wracking period. So then you don't know
20:37
how many people actually watched Koba Kai or Tagger Kick, no exactly. That's
20:41
what's so interesting is so what we have is we do have a number for
20:45
how many people within these panel of users watched it, but we don't know
20:48
exactly how that scales up. So what we've had to do is if we
20:52
had every single click on Netflix dot Com, then you'd have your viewing figures,
20:56
right, you'd have a raw number. But because we have a flecture
21:00
eating panel and we've had to account for like different factors, Like first of
21:03
all, over the course of these three and a half years, this size
21:07
of Netflix subscriber base has changed it's basically grown and it's paunched in different countries.
21:12
That the number of people using these plugins and services has changed, gone
21:17
up and down, and maybe they break into a new country or a tool
21:19
gets taken off, and so that's changed. And then also, how you
21:23
compare a piece of content that, let's say it was only available for one
21:26
year in twenty sixteen, how do you compare the performance of that film with
21:32
another film that was out in twenty nineteen or something, or two and eighteen
21:34
or whatever. How do you compare them because they weren't available at the same
21:37
time. And so what we had to do is basically normalize all of these
21:42
views per day, per country, per type. What that basically means is,
21:48
for every single country, we've said, on this particular day, what
21:52
was the most watched film, and then comparing all the other films to that
21:57
film, So like film number two, the second most popular film got seventy
22:00
percent of the views, the first one did and the third one got sixty
22:03
percent or whatever. And then that then gives us comparable things because you can
22:08
say, within all the films that are available, how did each of them
22:11
perform? And then that allows us to then create scores overall over those three
22:17
and a half year period. So this is where the scientists were really useful
22:18
because they're you know, comparing this content across time and space and different planel
22:23
sizes in the dark matter and then the beginnings of the universe and so getta
22:29
Okay, So all right, So the last the last limitation is that we
22:33
don't have demographic information. We don't have IP addresses, we don't know age,
22:36
gender, like we know what country they're in. But that's it's all
22:40
right, So all right, so let's um, let's let's ask some some
22:45
tough questions and see what you can do to help us, because the reason
22:48
why filmmakers are listening is like, we find this very fascinating how you're getting
22:52
this data about how does this helped me? So, um, does Netflix
22:56
have a long tail? Is that something that that you were able to come
23:00
on That's exactly something we're able to look at. So the long tail idea
23:04
was was made sort of most famous by an article in Wide in two thousand
23:08
and four, and it was this prediction based on the idea of growing digital
23:15
platforms like Amazon selling books and DVDs at the time, but the idea being
23:19
that previously, when you have a physical shop, you make most of your
23:23
money from the top titles, top ten, top hundred, whatever the ones
23:27
you can have in the front of the store, right and that's where you
23:30
make your money. The concept of the long tail is that the way at
23:33
Amazon in the future will make their money is actually through all of the other
23:37
inventory, the other hundred thousand titles, some of which that only sell one
23:41
or two every every year or whatever, but there's enough of them on total,
23:47
and so it becomes about the misses, not the hits, you know.
23:52
And so this was an idea that was put out there and some people
23:53
support it to people don't. And how it relates to us is that we
23:57
already know that the box office doesn't really have a long tail. We know
24:03
that three quarters of all of the money made in the box office goes to
24:07
the top fifty films each year. Like it's heavily, heavily skewed towards these
24:11
top movies. So the other however, many you know, seven eight hundred
24:15
movies released that year are competing for the final quarter. And that is not
24:21
great because it makes it very hard for us to compete because we're if you're
24:26
not big, You're nothing, right. So one of the first things we
24:30
wanted to test was, Okay, well, we know that the movie industry
24:33
is already top heavy, already massively disproportionately supports the big films. But if
24:38
we took on this long tail idea, maybe Netflix would be a place where
24:41
lots of the smaller movies would do well everyone, which is something different,
24:45
but it doesn't matter overall because Netflix are happy, and maybe that's our savior,
24:52
you know, maybe it's a fairer space for us all to compete in
24:56
and loads of tiny movies can equally survi. So that was a big thing
25:02
for me to look at, and I gotta say it's disappointing but not surprising
25:06
news. So basically, the viewing patterns on Netflix are slightly more skewed towards
25:14
big films than the box office, which means that most people on Netflix are
25:19
watching a small amount of massive bits of content, which was mostly in the
25:25
US, it was mostly Disney films. Like Disney, they had a deal
25:29
with Netlik which is now finished, but that accounted for a huge proportion of
25:33
Netflix's views, and it really was a problem for Netflix when Disneys ended that
25:40
deal. I don't know the ins and outs of the deals, but what
25:44
I can tell you is that they lost their best performing content in a number
25:48
of different realms. Yeah, and the Office and the Office as well got
25:52
last because it went over to is it an HBO Max or somewhere else?
25:56
Presumably it's peacock because it's right right, right, yeah, And so yeah,
26:00
the Office is The Office is a great example because the Office allows us
26:04
we've got all the stats on the episodes of the Office, and because all
26:08
episodes of the Office were available across our entire time period, it's actually really
26:12
easy for us to compare the performance of different episodes. We actually don't have
26:17
to worry about accounting for time and availability and stuff. And so we've actually
26:22
used that as as a good example to look at how might the nature of
26:27
s VOD viewing change the way we think about filmed content. What I mean
26:34
is right, So in TV we're used to having seasons, you know,
26:37
because of the way that they're funded and broadcast and just the way that it's
26:41
evolved. We are used to having a piece of content. So having a
26:45
series that has got a beginning, middle, and end. Maybe it's got
26:48
an arc across the season, and the beginning and the end of the season
26:51
is significant and then we wait and whatever. But that doesn't there's time is
26:56
less of a factor with things like Netflix, like it's not relevant, but
27:00
it's far less of It doesn't matter whether it's summer or winter. You just
27:03
watch them, binging them. So when we looked at all the viewing figures
27:07
of all of the episodes of the Office, we noticed a couple of really
27:10
fascinating things, which is, first of all, the most popular season was
27:15
season four, not seasons one or two, which is kind of interesting and
27:19
I think it's about that was where it really hits stride and where people start
27:22
watching it or maybe where they rewatch it as well. But we couldn't see.
27:29
If you have a look at the chart of viewing figures across, you
27:30
know, on the left hand side you've got season one, episode one,
27:33
on the right hand one, you've got the last one in season eight or
27:36
nine, whenever the last one was, And you have all the viewing figures
27:38
as a line, sort of a line going up and down across across those
27:41
two points. You can't see where the seasons begin and end. You know,
27:48
they may make them as seasons, but people don't watch them as seasons,
27:52
so it's much more like a podcast than a radio series. Right,
27:56
So you might think a radio series has got a season, and only in
28:00
the UK the BBC have like, okay, this will be six or maybe
28:03
ten episodes of a radio series. Then they'll be a hiatus and then they'll
28:07
come back, whereas podcasts you just think are always going to continue, right
28:11
you just it's a long stream of content. It's like a soap opera rather
28:14
than a mini series, and that's how people watch the content. And so
28:18
I don't know how long it will be, but it seems inevitable based on
28:22
data we have that when people start making more content for Netflix, they're going
28:26
to move more and more to this sort of soap world where they're always making
28:30
them like a churn, like even the expensive ones. From the way people
28:36
watch them, it makes sense to just drop a new episode every two weeks
28:41
forever. Then it does to quickly go and make ten of them. I
28:44
mean, the economics of the production costs might be different. You might want
28:47
to film all in one location, but the production costs are not a big
28:52
concern if you get a Netflix hit. So maybe we're going to start seeing
28:56
seasons of indefinite lengthy break breaking down like how long episodes are, Like I've
29:03
just been watching them. There's some brilliant comedians called Auntie Donna, Australian comedians.
29:07
They've got a Netflix series it's just come out, which is incredible.
29:11
But they some of their episodes are like seventeen minutes long, and it's great
29:15
because every second is great, but they don't have to stretch it to twenty
29:19
two thirty minutes whatever it would have to be for TV. So, you
29:25
know, So with with all this information, are you seeing because I've been
29:30
reading a lot that Netflix, you know, is infamous for just canceling shows.
29:34
Um, some of the people's favorite shows just get canceled. And they're
29:37
like, you know what's grew you. We don't care because we're gonna get
29:40
We're gonna put out twenty new shows this month. We'll be right back after
29:45
a word from our sponsor, and now back to the show. And they
29:53
generally don't go past three four seasons, you know, five. I mean,
29:57
I think frank Grace and Frankie is one of the longest running shows on
30:03
Netflix. Oranges a New Black got canceled ended eventually and they don't seem to
30:10
care about letting things go on and on and on and on, because they
30:15
just rather just starts filthing from scratch. And I think it's because mostly because
30:18
of the talent costs and and thing it's going to say, I don't I
30:22
have no inside track to Netflix, and the data doesn't give me all of
30:26
what I'm saying here. So some of this is filling in the gaps or
30:30
my opinions, sure, but I would say that the cancelation for most of
30:33
these things comes down to exactly what you'd expect, which is number one cost
30:38
and number two talent, which is a related to cost because they are they
30:41
asking for more money each season, and crucially, do they want still want
30:45
to do it? And obviously Netflix are going to cancel shows that they don't
30:51
think are performing, but they could do with more content almost always, And
30:56
if you think about it, what they actually really want. They obviously want
31:00
content that everybody watches that's amazing, that would be great, But one of
31:03
the other things that's actually really important for their business model is content that's important
31:07
to some people, like really important. So let's say that hypothetically, you
31:12
and I both have a Netflix account and let's say that you watch loads of
31:15
different TV shows every every month, you watch thirty different shows. If I
31:21
watch just two shows every month, but both of us pay the same fee,
31:26
that those two shows are that I watch are more valuable to Netflix because
31:30
if they canceled those two, or maybe even just one of them, maybe
31:33
I would leave. But if they canceled ten of the thirty that you watch,
31:37
you've probably be watched the other twenty and maybe some other ones. So
31:41
the model that they're having to use here is not just not just the number
31:45
of people watching it, but it's how valuable they are to that particular audiences.
31:52
Yeah, exactly, So that's what I mean. It's a whole different
31:56
business model. Whereas on television you're saying how many people are watching it and
32:00
what demographic are they in, Like, that's that's what's driving content on television,
32:05
um, and what's driving content on Netflix is different, completely different.
32:12
And so what I have to ask the question, what does the lowly independent
32:17
filmmaker? How did their stats work? I mean, obviously you said that
32:21
they're mostly skewed towards the big movies or big stars. I mean I saw
32:27
an interview or an article discussing why Adam Sandler is one of the biggest stars
32:34
on Netflix and that's and like people like, why does he keep making these
32:37
movies? Why why does Netflix keep giving him money? Why? I mean,
32:42
like, I'm personally a fan of Adams, so I love his stuff.
32:44
Um, not everything, but most of his stuff. And the thing
32:47
that they said was in the article was was really interesting and it made a
32:52
whole lot of sense. Was the reason why Adam Sandler is is given these
32:58
kind of movies and these kind of deals, Because when you're scanning through an
33:02
spot platform, there's just so much content that when you see something familiar,
33:09
when you see an Adam Sandler movie, you know what you're going to get,
33:14
Like there's there's no mystery about Like, I think he just in this
33:17
Halloween. They just released Hawley something or other Halloween, Hawley Halloween or something
33:22
like that, which was a huge, huge hit. They're going to do
33:25
a sequel to it because so many people watched it and it's the same you
33:29
know, it's the same stuff Adam Sandler has been doing since Billy Madison and
33:32
Happy Gilmore. But because of people's comfortability with they know what they're going to
33:37
get. People watch and watch and watch. We see a lot of that.
33:42
I mean, there's a lot of brands that do very well in a
33:45
brand, Adam Sandler being a brand hit that does very well on Netflix,
33:47
and I think that some of it is down to is absolutely what you're saying.
33:51
I think with him, there's also not that much competition. You know,
33:55
there aren't many substitutes. What's the Adam Sandlers substitute. Well, Kevin
34:00
James is in most of Adam Sandler's films, so is David Spade. There
34:05
isn't a lot of competition. And I think that there's something you touched on
34:07
there which is incredibly important, which is the way that people invest in the
34:13
time they're spending watching stuff on squad is a lot more about relax time and
34:17
not making a decision and stuff like that. And I think that speaks to
34:22
why Adam Sandler's popular, but also why it's the same film as people are
34:24
watching, and they're watching the same TV shows again and again rather than watching
34:28
new ones. And I think that actually doesn't help independent filmmakers because we're making
34:34
stuff that doesn't have famous people, doesn't have existing brands, and more often
34:37
than not, is trying to challenge something. I'm not suggesting we're all trying
34:42
to pass on a message or communicating, but it's not the same. It's
34:45
not the kind of soccer and stuff you might get from Transformers or a Disney
34:49
movie or Adam Sandler, where you're like, Okay, I'm just going to
34:51
go with the flow. Most independent filmmakers are making something a bit spikier than
34:54
that, and I think that doesn't suit most of the way people watch Netflix.
35:00
And so I think when your question about what is assuming that Netflix is
35:06
what we've learned so far from Netflix, it applies to the other platforms and
35:08
continues broadly in the future, I'd say that it's not great for selling independent
35:15
content because first of all, what these platforms like Netflix want is the MCU.
35:22
They want the Marvel Cinematic Universe because the people will watch it. They
35:25
also can do one deal and get loads of it, and that will get
35:28
most their views. They don't want to do individual deals. The audience aren't
35:32
watching that content the other the independent content, so there's not much of a
35:37
drive for that, and so I think that's not great. However, what
35:40
I would say is in the same way right now, I wouldn't invest in
35:45
any of the companies that own theaters. I would still invest in the concept
35:50
of theater going because I think people go on dates, they see their mates.
35:53
It's a cheap for it's it's the cheapest, most social form of going
35:57
out with the lowest effort. And I think that what's happening right now,
36:00
I mean I just happened. I was reading a few days ago that Netflix
36:02
have spent two billion pounds in the UK alone on content this year on production.
36:07
So independent filmmakers might have many more roots to being employed than they would
36:15
have had previously, as in if their previous roots were big movies or TV
36:17
shows, they now have a whole new realm they could compete in. I
36:21
don't know how, I don't know how fair that system is. I don't
36:22
know, but certainly there's got to be more and more entry level people because
36:28
there's just more concurrent, more content being made complently. Oh yeah, here
36:30
in me here in New Mexico, they're they're expanding. Netflix just got approval
36:36
from the state to expand their studios. They're building out a massive studio complex
36:42
in that's going to hire people, it's going to high create of course below
36:45
the line, and so as filmmakers like that's and also there are some interesting
36:50
things Netflix is. It's very easy to think of them as a studio and
36:52
they're actually fundamentally not. They are a technology company and they bring a lot
36:57
of different values into what they're doing. I mean, I would argue that
37:00
they are one of the most forefront of HR in the film industry human resources,
37:07
like they actually are able normally when you if you work on if you're
37:10
below the line crew member, and you work on six different independent productions in
37:15
a year, you can expect to have six different relationships and no concurrent,
37:19
no sort of handover really beyond a mild relationship and the sense there's something bad
37:22
happens, you just try your luck again and the next one. Whereas here,
37:25
because there's a continuity of people being the higher end, you know,
37:30
Netflix care whether there's a complaint about somebody, and this is great for things
37:35
like sexual harassment or unfair treatment or discrimination. I'm not saying they're going to
37:38
solve everything, but there is a continuity there. I mean some of the
37:42
studios have tried that. Warner have been doing that for a bit, and
37:45
Disney to some degree, but no one to the extent Netflix are doing this,
37:49
so they are doing some things very differently, and as individuals it might
37:52
be a good thing. As people buying and selling content the way we've used
37:58
to doing it, I just can't see it being better than it was because
38:04
it's also an oligopoly, you know. I don't I'm not suggesting they're acting
38:07
in any way to blisters, but when you have five or six possible maybe
38:13
even let's say three or four, actually no, hold them. So Apple
38:15
aren't buying existing content. So let's say that it's Amazon and Netflix. Let's
38:21
say that they're the only two that could you could sell your content too in
38:22
any big way. That's not going to engender you fair prices. And you're
38:28
doing a single deal in perpetunity for the world. Maybe maybe, And so
38:32
that's that's a simpler to sale. If you get a good price, then
38:36
that's that's amazing. But will you get a good price? And I also
38:40
think there's some worrying practices. I don't think any of them are illegal,
38:45
but I don't like them. It's all I can say. So for example,
38:47
I was talking to a lawyer recently who's sort of looked over a lot
38:51
of deals to one of the big streamers. I won't say which one,
38:54
And this lawyer said, look, one of the problems is that part of
38:58
the terms and conditions of the deal between the distributor and the platform is that
39:02
the distributor is not allowed to tell the filmmakers how their film is performing.
39:07
There has to be some sense of aggregation of the numbers. And you know,
39:12
yeah, so it's horrible that. Not only is that horrible in a
39:15
human sense, that is also terrible for that deal, and it also and
39:19
stifles long term growth, like how can you have a sustainable career on as
39:23
you get feedback and your feedback can't be We did a deal, but I
39:27
can't tell you anymore. And that brings us full circle back to the Vietly
39:31
click stream because that's what we're trying to get a sliver of light in a
39:37
dark room. Like it's not like we can illuminate everything, but we're trying
39:39
to understand these things that filmmakers need, this feedback loop that needs to happen
39:45
with the audience. We'll be right back after a word from our sponsor,
39:53
and now back to the show. Now do now our American ARTI this streaming
40:00
a lot of international shows because I personally watched a bunch of international shows um
40:07
recently because they've been popping up on my on my my feed, so I'm
40:10
like, oh, that looks interesting, Oh that looks interesting. And sometimes
40:14
they'll they'll pitch me something. I'm like, yeah, no, no,
40:15
thank you, I need yea. And it just depends. Like you know,
40:21
I'll watch subtitled movies, but not normally because I want to relax when
40:27
I'm watching movies unless I'm watching it for for cinematic purposes. But if I'm
40:31
just chilling, I don't want to read. I just well, also,
40:36
you don't want to be challenged. Like there are some movies that I would
40:38
in a heartbeat recommend to other people that I've only ever seen once. I
40:43
might see again once in the future, but only to introduce it to someone
40:46
else, or because you know some bizarres at second stongs. Yeah, there
40:50
are bad movies that I will acknowledge that are bad. That I've seen The
40:52
Meg twice. Right, it's you that's the wrong ratio. It is it
41:00
is the wrong ratio. And you know what the Meg. You know,
41:01
I watched The Meg as well, and it's just a it's a popcorn movie.
41:07
It's you know, it's there, it's the it's the reason why I
41:08
just it's the reason why my wife and I just sat down and watched all
41:13
four lethal weapons in a row because we watched the first one because I hadn't
41:16
seen the first one forever, and I'm like, oh my god, that's
41:19
so brilliant. Well we have to watch two, Oh, we have to
41:21
watch three. Well, well let's just let's just go. Let's make it
41:23
the fall four. And in four days we watched for all four of them,
41:28
and we're just like, what's next, Let's watch Tango in Cash,
41:30
you know, like, like I haven't seen that in twenty years, so
41:35
it's like, I'm going But it actually says exactly what you've been saying,
41:38
is I'm doing that because I know that I'm comfortable. Those are comfortable viewing
41:45
habits, and I'm like, oh, let me go revisit that again because
41:47
I haven't seen that and forever I remember here and there, but I haven't
41:52
seen it. So that is the true response to being overwhelmed with content,
41:55
because you know that there are so many movies been out there, and if
41:59
you had to create a list, how would you find brilliant movies you hadn't
42:01
seen. It would take you seconds. IMDb score, Meta score one the
42:06
best screenplay, and there's loads of movies that you'd be like, Wow,
42:08
I'm sure I heard that's amazing, I've not seen it. But that all
42:10
takes a lot more effort and commitment than most people are willing to give.
42:15
And this is something that I think filmmakers, really independent filmakers really need to
42:19
either embrace or realize you're not going to embrace it, and then find other
42:22
roots. Both are valid. Like I'm not actually saying make popcorn movies.
42:25
I'm just saying you can't make challenging movies and expect them to then survive in
42:30
a mainstream environment called world, because that's not how people watch that content,
42:36
right, It's just fundamentally and I think the growth of content, sorry,
42:40
the evolution of content, and the growth of platforms are massively interlinked. And
42:45
the best example I can give you is outside of the film world, but
42:49
is kind of makes a lot of sense, which is that the rise of
42:52
Kindle the kindled eReader was a massive part of the success of fifty Shades of
42:59
Gray, and fifty stades degree was a massive part of success of the Kindle
43:02
because you could be on the train reading something, reading basically soft porn and
43:07
no one would know. And both of those two things sort of coincided at
43:10
the same sort of time. And it's not that everyone reading stuff and Mkindle
43:15
was porn, but it did mean that you could read private things. And
43:19
it's the same with the rise of sort of portable devices and podcasting. You
43:22
know, these things are interlinked, right, And so what we're seeing,
43:25
what we're starting to understand with s food is that people don't watch content in
43:30
a curated way the way that they might when they go to a certain type
43:36
of theater or they go to like you know, they could Draft House,
43:38
or they or they watch or they buy a Blue Ray or the Criterion collection.
43:43
You know, they considered centiphile way. That's not what people are largely
43:46
doing on these big platforms. They're sitting down watching stuff that's comfortable, that
43:52
it's easy to understand, that won't challenge them, that they can pause when
43:55
there's someone at the door, or they want a cup of coffee or something
43:59
that is Adam Sandler through and through. No, there's no there's no question,
44:02
I mean. And the other thing is like you're saying movies that challenge
44:06
you, you should also you can make movies that challenge you, but you've
44:08
got to do it on a budget. If you you know, if you
44:10
if you have any hopes of recouping that money, like you can't make it
44:15
two or three million dollars. You know Indie film that five people want to
44:19
watch, she's just irresponsible. So there's more, you know, the more
44:22
it just makes sense. The more you spend them, more you've got to
44:24
recoup. But I and I totally agree with that. I think the other
44:28
thing that I know you've been screaming at this at people for since way before
44:31
Netwix, but it's even more the case now, which is you have to
44:35
know your distribution route before you make it. I'm not saying do the deal,
44:38
because I appreciate that it's very hard to walk into room and say,
44:40
I haven't met, you don't know me, you don't know my movie,
44:44
and I haven't made it, but can I have a deal. I appreciate
44:45
that as kind of pre sales and happened, but you can't hope that you're
44:49
just going to throw it in with the with the sort of stream of content
44:53
and including the streamers and it will get swept up and then it will rise
44:57
to the surface. It just from the data I've seen here, that just
45:00
doesn't happen. That's just not the case. You can't write a book and
45:05
expect it to be on the front page of Amazon or in the in the
45:08
front of the bookshops, right, we know, and yet filmmakers still think
45:13
if it's good enough, it will break through. And I do worry somewhat
45:16
that the way the squad platforms are working now, through no fault of theirs,
45:21
they're just chasing the subscribers in the bottom line is that it isn't It
45:27
doesn't reward films the way that the previous system would to some degree. You
45:32
know, maybe we'll see fewer breakouts. Maybe it will be that the where
45:38
you really break out is on a much smaller platform, like for example,
45:43
film festivals, whether they're physical or online, or maybe it's niche sites like
45:47
Shutter or something like that. I don't know why I don't have anything on
45:50
that side, but that is nowhere near the volume that Netflix does or Netflix
45:55
Compartion appears. So there is we all know that there's huge amounts up in
46:00
the air. Partly it was happening anyway, and then COVID accelerated and things
46:04
like that, and it hasn't landed yet. But we don't yet know what
46:07
this model will be for independent filmmakers. I am absolutely confident independent film will
46:12
exist, because it's not It's never been supply and demand. It's always been
46:15
supply right where can I find the demand? And that's been part of the
46:19
joy of like movies, they've not been made. Some of the best movies
46:22
have been made because they want to be made rather than because I know.
46:24
I know, I already have a deal in place, but things are going
46:28
to get tougher until we figure out what they are. But if I have,
46:30
it's never been easy. And you look at some you know, the
46:34
crash of cinema tickets in the nineteen fifties, you look at the crash of
46:38
DVD, and you look at the uncertainty of sward and all this stuff there.
46:43
We'll find a way, but just don't know what that is yet.
46:47
And it's not the one. It's not the easy one that's in front of
46:51
us, you know. And so you are asking earlier on about TV because
46:55
we have we have data for movies for TV and for comedy specials, and
47:00
for TV it's it's it's the same pattern in a different format. So what
47:05
we saw with movies is that the most watched movies by a huge degree are
47:09
the big, famous ones. And when it comes to television, what we
47:14
tend to find is that it is the big shows, but also it's the
47:17
more familiar shows. So if you go on if you're in the US and
47:22
you go on Netflix, there's content from many different countries you could choose to
47:24
watch. But what do people watch. They watch it from their own country,
47:30
you know, and generally yeah, yeah, exactly. And certainly if
47:34
you look at the like the top shows, like the top fifty shows,
47:38
they're almost all produced in the US. And you have to even the top
47:42
five hundred most watched shows not episodes shows on Netflix over this period, almost
47:47
three quarters of them were US produced. The UK does very well, but
47:52
that's largely down to the Great British Baking Show and things like things. David
47:58
Adam, I would have to say, I've seen both. Well. I
48:02
think it's so interesting is that, first of all, I was as proud
48:05
as like, great, these these Brits are surviving and competing against that,
48:08
and I was like, oh, notes two shows. There's an example like
48:13
what this means is though there's an interesting like thought process that goes on here.
48:17
If you were being rational, you would say it would make more sense
48:22
rather than trying to make three films or trying to make one film that competes
48:25
in three areas. It's quite good, it's quite scary, it's got some
48:29
films. It makes more sense based on this data alone, to compress all
48:34
of your resources and that includes time and money and passion and whatever into one
48:38
thing. You know, do one thing incredibly well. And because of the
48:45
power law and the sort of nature that if you go from being the second
48:49
most the third most popular to the second most popular will mean so much more
48:53
for you than going from fourth to fifth, from from fifth to fourth,
48:58
that it would argue it's better to make something that's extremely one thing. And
49:02
you see this, I mean that we're recording this before Christmas, and you
49:07
look at how many Hallmark Christmas shows there are. They're good or well made
49:12
or enjoyable. I'm sure one or two are, but what they are is
49:15
feel good Christmas like. They are absolutely that. There there's a formula and
49:20
again the comfortability factor for a specific demographic of people. That's why those films
49:27
generally have a Mario Lopez or or a Dean Kane or a face that people
49:34
feel comfortable with because they remember them from you know, they're just comfortable.
49:37
They've watched their films or watched their TV shows over the years, and they'll
49:40
watch it because it's like, oh, you know what, I want to
49:43
feel good. I want to feel good Christmas. Ee, and oh great,
49:47
this is a new movie. We'll be right back after a word from
49:52
our sponsor, and now back to the show. And there you go,
50:00
and all of us like I knew that. I know that Mario Lopez Christmas
50:04
movie exploded on Hallmark apparently because people love Mario Lopez because you know it's later.
50:10
But and here's here's this thought that we I haven't heard expressed very much.
50:16
I'm sure it's not a brand new thought. But in the last ten
50:20
years of being an independent filmmaker and working with independent filmmakers and chatting to them,
50:23
I've heard people talk about, oh my god, do we have to
50:25
hire people actors who've got a bigger social media following or whatever people A people
50:30
have often complained, do they have to way up talent and appropriness for the
50:36
role on the one and fame on the other. What I haven't heard many
50:39
people talk about, but I would argue is perhaps the battle that we're going
50:43
for in the next five years is in familiarity, not fame, but how
50:49
comfortable are people with that person. So it's like, you know, one
50:52
of the reasons that George Bush got in over Goore is that people were happy
50:57
to have a drink with George Bush. It wasn't about politics to some for
51:00
some people. And I know this because I know some people that vote for
51:02
him who actually I think their politics are slightly strange, and they were like,
51:06
yeah, I just don't like algor I'm going to have a drink with
51:07
Bush. And so when you think about actors, it's not so much their
51:13
fame, although obviously that's not a bad thing, and it's not so much
51:15
their talent. Although do you feel comfortable do you think your audience would go
51:20
yeah, okay without thinking about it, you know, And that's why you
51:23
look at actors like, I mean, almost every one of Adam Sanders movies
51:29
as a comedy, to the point to which people have been watching uncut gems
51:32
and been appalled, whereas there are other actors who you just don't know what
51:37
their movie is going to be because they play such a wide spectrum of ca
51:42
Yeah. Yeah, Tom Hanks is Tom Hanks, Like he'll play everything.
51:45
You know, He's definitely that Adams. Yeah, it's his brand, but
51:46
that's fine. But you also feel comfortable within Tom Hanks, or with Meryl
51:51
Street. Mill Street plays everything. She's going to be in a musical this
51:53
month on Netflix, but yet you know she she also was on HBO Max
51:59
doing another film with Steven Starderberg, and you know she she does everything,
52:04
but that's her brain, and you feel comfortable. I studied this a while
52:07
ago. I studied on my blog like how broad the act the roles the
52:12
actors had played across genres, and I found Adam Sandler was the most siloed.
52:16
Most of his films have been in one genre. And the actor I
52:20
only looked at sort of a couple of hundred really big actors, but the
52:22
actor I saw that who had the broadest as in like, who had the
52:25
least siloed in one genre was Ron Perlman. Yeah, you know, and
52:31
you take there's no one genre that accounts for more than a third of the
52:36
roles he's done. So he's done some comedy, but he hasn't done mostly
52:39
comedy. He's done some kids stuff, he's done some horror, he's done
52:42
some fantasy. And so Ron Perlman as an example here, who I think
52:45
is a terrific actor and seems like a good bloke, he is a perhaps
52:49
a metric slightly less attractive to hire because he doesn't have that whatever we're going
52:53
to call it, comfortability effect, whereas someone like Adam Sandler, who I
52:59
wouldn't obviously Ron Perlman take on Ron Perlman take on some certain drama roles over
53:02
Adam Sander, but Adam Sander would be a more comfortable watch for more people.
53:07
So I don't know what we'll do with that. It's it's it's very
53:09
interesting the way this whole, this whole thing is. But I'm really I'm
53:14
really happy that you're doing what you've done um with with vo D clickstream H
53:20
and I'm I'm just impressed, like I always am with everything you do.
53:24
Man, You're insane for what you do, and I know that you're going
53:28
to be digging through that data and continuing the league grow and build out more
53:34
of a data. Yeah, you just started to go through that, and
53:37
that's a good It's it's not exactly what's going on, but man, it's
53:40
it's more than we had before. And it's definitely a direction to aim at.
53:44
It might not be pinpoint, but man, it's better than you know,
53:47
like, hey, I'm gonna go throw a football into a stadium,
53:52
I have no idea where it's gonna Now, at least you'll get it on
53:54
the field, and maybe you could even get it within a few yards,
53:58
you know, maybe, And that's the goal. And also, you know,
54:00
filmmakers should use all of these data points and all of these things they
54:05
hear and then they know themselves and they talk, they hear on your podcast
54:07
interviews. All of these are things you need to weigh up yourself and weigh
54:10
them against everything else. No one person or one system can tell you what
54:14
to do. And I'm just glad that we have at least one set of
54:17
signals about SPOT that doesn't come from the PR Department platform. Well, and
54:23
I appreciate you are fighting the good fights are and getting this information to the
54:27
filmmakers. Where where can people go and get this infilm? So it's at
54:30
via d clickstream dot com. It's entirely free. You if you want to
54:35
read more than the beginning of the articles, you need to sign up,
54:37
but it's free. But that's the reason we put that barrier in is that
54:38
we have got forums that anyone can join, and we wanted to make sure
54:43
that there was there was some effort you had to put in, and that
54:45
effort is signing up and accepting your email just and what that means is that
54:52
we have forums where people can post suggestions because we're still working out what to
54:57
do with all of this data, you know, some of it. We
54:59
have plenty of ideas and we're churning away at them, but then there's some
55:01
deeper things that we don't know what to look at. Yeah, and the
55:06
best suggestions for the research I've done over the years have come from audiences.
55:09
Like it. If I was to think of the sort of most exciting things
55:12
I've studied, they almost all of them come from audience suggestions. So that's
55:16
what we're looking to have is like, what have you always wanted to nerve
55:20
about squad? I can't give you an immediate answer, and I might not
55:22
be able to answer at all, but maybe probably I'm the best shot most
55:25
people have, and I'd be delighted to follow those threads and suggestions that we've
55:30
had from people. Well, man, I appreciate everything you do, Stephen.
55:34
Thank you so much. We have to we have to come back on
55:37
the show and talk about our twelve unconventionable Christmas movies and do another episode next
55:43
year, but I appreciate everything you do. Brother, thanks again for coming
55:47
on and sharing very valuable knowledge with the Tribe. And so thanks again thanks
55:53
for inviting me. It's always a pleasure to be here. I want to
55:58
thank Stephen for coming on this show and dropping the knowledge data bombs on the
56:02
Tribe today. Thank you so much, Stephen. If you want to get
56:06
links to anything we spoke about in this episode, including how to check out
56:09
the free service vod clickstream, head over to the show notes at Bulletproof Screenwriting
56:15
dot tv for it Slash two eighty seven, Thank you so much for listening
56:19
to guys. As always, keep on writing no matter what. I'll talk
56:22
to you soon. Thanks for listening to the Bulletproof Screenwriting podcast at Bulletproof Screenwriting
56:29
dot tv.