WEBVTT
1
00:00:00.080 --> 00:00:15.600
[upbeat music] Hello, and welcome to another episode of Stream Wars, our thought leader series where we learn from industry experts about the latest trends and challenges from across the convergent TV space.
2
00:00:16.040 --> 00:00:27.020
Hosted by Michael Beach. Today, I'm joined by the Entertainment Strategy Guy. If you read State of the Screens and you're familiar with his or her work, since they are one of the most cited sources we've ever had.
3
00:00:27.940 --> 00:00:35.640
Uh, we've communicated for years via email and Twitter. Uh, we share a research assistant, but this is actually the first time, uh, you know, we've ever met in real time.
4
00:00:35.820 --> 00:00:39.810
Uh, ESG, you know, has fantastic insight, and we dig into a lot of that.
5
00:00:40.860 --> 00:00:48.980
Uh, one of the things that was most helpful to me was kind of understanding the overall business model of streaming versus linear TV, really how this is gonna dictate the future of content.
6
00:00:49.020 --> 00:00:51.620
You know, how much money is gonna get spent on content, what type of shows are gonna get made.
7
00:00:52.500 --> 00:01:01.200
Uh, and then we really get into the, the business model of streaming and, and kinda in particular, uh, the arrival of the FAST service, you know, the free ad-supported streaming TV.
8
00:01:02.380 --> 00:01:11.900
Uh, so with that, you know, please enjoy my conversation with the Entertainment Strategy Guy. All right, ESG, welcome to Screen Wars. Hey, Michael. Uh, glad to be here. Absolutely.
9
00:01:12.860 --> 00:01:24.520
Uh, you know, I've obviously been, uh, you know, a huge fan of your writing for a long time. You're probably, uh, you're the most quoted person, uh, in our newsletter over the past seven years.
10
00:01:24.980 --> 00:01:31.040
Um, one thing I've always found interesting is the, the point of view that you're able to offer from, you know, writing an anonymous account.
11
00:01:31.100 --> 00:01:41.160
What kind of is your background on thinking about that and, and kinda how's that, that worked out? Yeah. Um, first off, also, I'm a huge fan of your newsletter as well. I love the charts.
12
00:01:41.320 --> 00:01:51.740
I'm constantly pulling charts or finding new data sources from it as well. So, uh, there's definitely mutual fans on both sides here. Um, [clears throat]
13
00:01:52.000 --> 00:02:03.620
so the anonymity thing, uh, started out, I knew I wanted to write about strategy and entertainment, 'cause I, there weren't enough people, I thought, analyzing the entertainment industry and the strategies behind it.
14
00:02:04.340 --> 00:02:15.220
And I'd just been let go from another streamer, and so odds are I wouldn't be able to make the writing thing work, so I would be w- back at another entertainment industry.
15
00:02:15.640 --> 00:02:26.230
And I felt if I wanted to write the most freely about entertainment as possible, it made sense to be anonymous so that, you know, [chuckles] if like six months later I wasn't getting any traction, I could go back.
16
00:02:26.920 --> 00:02:38.340
Along the way, um, it did end up working out. The surprising thing is a lot of my customers actually told me, um... And whenever I throw up a poll on this, I say, "Should I stay anonymous or, like, reveal who I am?"
17
00:02:38.380 --> 00:02:47.040
It's 50/50. So half the people love it, half the people don't. So I've kept doing it for that reason. Along the way, I've also, I actually work on a lot of creative projects on the side.
18
00:02:47.340 --> 00:02:52.100
Um, some consulting projects with friends, some consulting projects with just other people.
19
00:02:52.769 --> 00:02:59.960
And so now that I write so heavily about streaming ratings as well, I actually think the anonymity piece sort of protects some of those projects.
20
00:03:00.020 --> 00:03:09.660
So again, I can write freely about what I think is working or not working in the industry. So, um, yeah, I, the anonymity thing is probably the number one question I get asked by people, "Why?"
21
00:03:09.760 --> 00:03:22.900
Um, but it's worked so far and been going with it ever since. Yeah, it's been interesting. I mean, the, you know, it seems like you wrote on your own for a while and then kind of moved to the Ankler a few years ago.
22
00:03:23.020 --> 00:03:31.240
Um, you know, what's it been like working with, you know, Richard Rushfield and the team? Richard Rushfield has been great. Actually, the entire team has been fantastic.
23
00:03:31.480 --> 00:03:48.040
Um, as soon as I discovered Richard's newsletter, I definitely felt him and I, where we come from different backgrounds, we sort of have the same approach, the same, uh, in some cases, like skeptical about what the studios are saying, sort of like digging beneath the, uh, surface.
24
00:03:48.620 --> 00:03:58.920
So was happy to join him. Uh, he had told me before w- before they launched the big Ankler redo last year and really expanded the operation, they were going in that direction.
25
00:03:59.480 --> 00:04:02.950
And so I was happy to start writing a column for them.
26
00:04:03.440 --> 00:04:18.570
And for me, it's been the best of both worlds in that I have my newsletter that continues to go out via Substack, but I also get exposure to the Ankler's great audience and get to work with Jan Essmann, who's also just a fantastic editor, um, and great sounding board for ideas.
27
00:04:18.700 --> 00:04:25.280
And so, yeah. That's amazing. You know, and the, the streaming ratings, I mean, I think that's the thing you're known for.
28
00:04:25.900 --> 00:04:32.680
Um, I've always been interested to ask what, I guess, what's the hardest part about putting that together?
29
00:04:32.780 --> 00:04:39.820
Uh, you know, it seems like you had the insight earlier than anybody else that the data was available to make consistent analysis here.
30
00:04:39.840 --> 00:04:48.440
But, you know, what's the hardest part and kinda what, what pieces are still missing? That's a fan-- Both those are fantastic questions.
31
00:04:48.700 --> 00:05:02.860
Um, the hardest part right now for me, just from a personal standpoint, is just still dealing with the, uh, known unknowns, you know, to quote, uh, Rumsfeld from way back in the day. But
32
00:05:03.940 --> 00:05:12.920
I started out, um, polling Nielsen's top 10 list. Um, I'd like to call it the streaming ratings era when it started in 2020.
33
00:05:13.600 --> 00:05:30.840
Um, it was like COVID happened, and all of a sudden a lot of the companies that were working on data hopped into the field at the same time, and the incident that I felt had the most, generated the most traffic was when Mulan came out on, uh, PVOD and everyone wanted to know, like, how well did it do?
34
00:05:31.340 --> 00:05:41.420
And so I noticed all of a sudden, and, and I'd been writing about strategy only for a few years, that there were like five different companies, including Nielsen, and then they started publishing their top 10 list.
35
00:05:42.180 --> 00:05:52.240
And my rule of thumb is always that content is about half of the entertainment battle. That's what you're trying to win. So I was all of a sudden like, "Wow, we now have the data. We can actually look at streaming."
36
00:05:52.280 --> 00:06:03.600
But that ties, that's still only a top 10 list, though. And, um, for someone who works outside of a major company or even for, for some of the people who work inside of a company, the big-
37
00:06:04.532 --> 00:06:08.992
Unknown data point is basically all those other data points for all those other competitors.
38
00:06:09.072 --> 00:06:17.092
And even the people who do provide that, like Nielsen or Samba TV or some of the other ones, they also have other blind spots, which gets to your second point, which is,
39
00:06:18.052 --> 00:06:28.832
one, um, no one actually knows what happens on the other side of the screen. So is it one person watching? Is it two people? Who in the household's actually watching? And that's where they have the test panels.
40
00:06:28.872 --> 00:06:44.172
But the problem with the test panels on the living room is tying that data over to phones, tying it over to mobile devices, laptops, and trying to figure out the who question is still the biggest piece that isn't solved and may not be solved for a while.
41
00:06:44.552 --> 00:07:01.812
And then as I know you've covered on the podcast before, in the future, there's gonna be even more pieces of content coming from user-generated spaces, YouTube, TikTok, and just getting-- translating all those and figuring out what works across every single thing, such a problem that, you know, may never be solved.
42
00:07:01.872 --> 00:07:14.052
So... Yeah, I find it interesting 'cause, you know, we start, you know, our core business on the advertising side, obviously we're using similar data sets, but how do you feel the
43
00:07:15.412 --> 00:07:27.352
-- on the content side about how they value everything? Um, you feel like the way you put the ratings t-together, that they have a, a view to, to properly value the content or is that still a black hole?
44
00:07:27.362 --> 00:07:39.692
'Cause we're -- the advertising side, it's definitely, uh, probably not getting properly valued. I don't think we're there yet, um, to have it be properly valued, but I think we're on the way there.
45
00:07:40.012 --> 00:07:51.532
Um, I don't think my streaming gradings reports alone could like provide the proper value just because we don't have enough data points that are public to provide those data points. I think we're gonna get there.
46
00:07:51.652 --> 00:08:00.192
Um, I also think once we have multiple sources at every company, I'm actually optimistic that'll provide essentially better double checks.
47
00:08:00.232 --> 00:08:07.492
So instead of having just Nielsen and a single point of failure, you can have multiple sources to see if they're all roughly telling a similar picture.
48
00:08:08.212 --> 00:08:12.732
Um, that said, I am optimistic we can get to what content is valuable,
49
00:08:13.692 --> 00:08:24.392
uh, simply because we have so much data that at some point it becomes overwhelming when we know what the hits are, or we know what the slightly lesser hits are, and we know what the pieces below those.
50
00:08:24.512 --> 00:08:31.622
Um, I still, as much as things have changed, I, I tend to revert back to the basic principles with entertainment.
51
00:08:32.252 --> 00:08:40.172
Um, so it's a hit-driven business, and if something's popular in one metric, it tends to be popular across the board in everything.
52
00:08:40.612 --> 00:08:55.441
So, you know, the example I love to use, like "Stranger Things," like "Stranger Things" is probably Netflix's most viewed show in terms of total hours, but probably also with unique customers, and its Wikipedia page views are very high, and so is its social media conversation.
53
00:08:55.912 --> 00:09:03.712
So all those things tend to be directional, and it has very high completion rate. So I think at some point we're gonna be able to get there.
54
00:09:04.092 --> 00:09:16.172
Um, you mentioned the advertising 'cause I know that's what you do day in and day out, and I think that has its own different challenges, especially with attribution and figuring out what's on what platform, which those problems are still going there.
55
00:09:16.212 --> 00:09:25.112
But do think we're gonna get better at telling what content works and then valuing how much that actually drives value f- down the value chain.
56
00:09:28.072 --> 00:09:33.432
Yeah, and I got, uh, you know, three kind of specific pieces of content that I've always wanted- Mm-hmm... to kind of get your background on.
57
00:09:33.472 --> 00:09:45.372
The first, you were kind of really early in calling the S- the Netflix kind of subscriber slowdown. Right. Um, can you kind of walk me through how you projected that? Yeah.
58
00:09:46.092 --> 00:10:00.552
So that, uh, I actually cribbed that from a business school professor who, in our entertainment strategy class, um, looked at Netflix back in, it was like '20, I don't wanna say what year, long time ago.
59
00:10:00.742 --> 00:10:04.212
And he actually said like, "Could we apply the Bass diffusion curve to it?"
60
00:10:04.252 --> 00:10:16.932
Which is the inter- the marketing 101 tool that basically says most new technologies have an adoption curve that starts out slow for a few years, picks up speed, and then slows down again. Also called an S curve.
61
00:10:16.972 --> 00:10:27.241
It looks like an S, sort of like with the two ends pulled out. And so, uh, when I was starting to look at Netflix and they started to have some quarters that were slowing down just slightly,
62
00:10:28.252 --> 00:10:36.852
I wondered, I was like, "Could [chuckles] we reapply this curve to Netflix," um, using them sort of as a stand-in for all streaming video.
63
00:10:37.272 --> 00:10:57.772
And sure enough, the curve actually fit pretty tightly and it, it still had some uncertainty, but it definitely looked that the idea that Netflix would get to 90 or 100, and I did this just in the US, but the idea that Netflix would get to 90 or 120 million subscribers, which if people remember all the way back to 2018, that was what a lot of people forecast in the US.
64
00:10:58.332 --> 00:10:59.332
And so I applied that.
65
00:10:59.432 --> 00:11:12.812
I had to do a ton of data searching 'cause Netflix changes their definitions of US subscribers like every three years, so I had to do some estimates, but it ended up working out, and the number to me was right around 65 to 70 million subscribers in the US.
66
00:11:13.572 --> 00:11:30.122
Netflix, like I said, later converted to US and Canada subscribers, but if you subtract out the 10% of the subscribers that are roughly from Canada, Netflix is right around, I forget off the top of my head, but something like 66 million subscribers, and so that's how I calculated that number.
67
00:11:30.212 --> 00:11:30.262
Um,
68
00:11:31.832 --> 00:11:44.672
I don't know that it would work for some of the other streamers because I think the streaming curve has been adopted now, but I'm definitely monitoring those streamers for if I see subscriber slowdowns in the future, that's gonna be sort of my guess for what happens.
69
00:11:47.032 --> 00:11:56.012
No, it's great just 'cause it, I mean, even if you just get Netflix right, the, uh, they're obviously the high end of the TAM- Yep... uh, for the US and, and so, you know, I think that just shifted.
70
00:11:56.832 --> 00:12:09.132
It was just such a good insight, you know, so early and, and, uh, you know, I keep going back to that about when you're, you know, the next time we get into this kind of bull market and people start, you know, making these lofty projections, I just thought that, that insight was incredible.
71
00:12:10.504 --> 00:12:23.024
Uh, appreciate that. It's actually, I think, worked for some other, uh... I think whenever you hear buzzy numbers in any field, uh, look up the Bass diffusion curve and basically look at it.
72
00:12:23.104 --> 00:12:28.804
You can just in some cases eyeball it, and you'll get the same thing. I would also say I noticed this with Fortnite.
73
00:12:28.984 --> 00:12:41.304
Um, I definitely saw the slow growth, and then it took off, and I looked at the same thing and said, like [chuckles], "So, is it headed to keep skyrocketing to a billion users, or is it gonna like top out?"
74
00:12:41.404 --> 00:12:54.504
And Fortnite would n- while it remained popular and has its user base, it definitely wasn't growing, like what- whatever year when it was like Fortnite summer, and then there were people who were like, "Will there be 500 million, you know, 600 million, a billion active users?"
75
00:12:54.544 --> 00:13:00.524
And it's like, "No, it'll probably slow down," because it was so fast on the uptake. So it's a, it's a fun tool to use.
76
00:13:00.634 --> 00:13:09.944
And the other one I would relate to with Netflix, which I, I feel like a corner I was on pretty early, as well as the, uh, the churn game, is just everything with them.
77
00:13:10.534 --> 00:13:18.784
And when you're trying to map things to cable, cable was an industry that didn't have churn, because if you wanted TV, you had to have cable.
78
00:13:19.464 --> 00:13:23.264
And with the streamers, you, you don't have to keep, stay subscribed to a streamer.
79
00:13:23.684 --> 00:13:32.784
And so that churn issue was really the thing I was trying to quantify, because I thought that was gonna lower the overall TAM, and again, think people disagreed. So, uh, yeah, thank you for that insight.
80
00:13:32.904 --> 00:13:44.084
That's the one I, I try and hang my hat on because it, it worked out so well and, you know, making predictions is a tough game. [chuckles] Yeah, another one, uh, you know, the algorithm is a lie. Yep.
81
00:13:44.094 --> 00:13:59.044
And I wanna get your insight, 'cause I think your probably intention was around using that, you know, assuming that, you know, uh, Netflix or, you know, Hollywood Studio uses, you know, data science just to pick what content to green light is more than the, um, [lip smacks]
82
00:13:59.164 --> 00:14:08.164
you know, the kinda, uh, the experience. But we also look at it on the, the content delivery to the consumer where- Mm-hmm... you've got a kinda algorithm that can deliver TV.
83
00:14:08.224 --> 00:14:18.644
Do you feel like bo- you apply it to both or just more one or the other? No, absolutely don't apply it to algorithms at, that surface content, with some caveats to that.
84
00:14:18.724 --> 00:14:26.544
I do think they definitely get over-hyped, and I definitely think certain social sites leverage algorithms even more strongly than, say, certain streaming sites.
85
00:14:26.624 --> 00:14:43.004
But for any of your readers who aren't familiar, so the algorithm is a lie is, it's sort of de jure for a lot of, uh, you know, critical reviews of streaming shows that if they don't like it, e- especially for Netflix, they're like, "I can't believe the algorithm picked this show."
86
00:14:43.124 --> 00:14:50.184
And, uh, the TV show "Barry" actually featured the algorithm said to cancel a show within six hours, right?
87
00:14:50.424 --> 00:14:58.704
Which has never happened because the algorithm wouldn't even have enough data, um, to really make the predictions in six hours. They would give some trends, but not predictions.
88
00:14:58.744 --> 00:15:12.564
So my argument is, is that it is true that the streamers and all the studios have more data than ever at their disposal to help guide the development process, to help see what's working, to help make some calls, and things like that.
89
00:15:13.224 --> 00:15:22.524
That said, there still isn't enough data to actually pick, say, "Hey, this script is going to be a hit TV show," right? You know, "If we cast this actress, it's gonna be a hit TV show."
90
00:15:22.544 --> 00:15:37.064
And I've tried to explain before, the main reason from a data perspective is that there's just not enough data points to be able to tell, because there's too many variables going into any individual TV project to say, "This thing's gonna be a huge hit," or, "This thing won't flop."
91
00:15:37.164 --> 00:15:43.304
And if, you know, studios did have algorithms, they wouldn't make bad shows and nothing would flop, but that's not the situation.
92
00:15:43.924 --> 00:15:51.434
So they have more data than ever before, and this includes, you know, Nielsen ratings, box office, social media, internet traffic, all those things.
93
00:15:52.564 --> 00:15:59.284
That is one bucket that content still has to be created by people, and they deserve all the credit, all the blame for all the content decisions.
94
00:15:59.704 --> 00:16:08.164
On the other side is the algorithmic delivery of content, especially for social media platforms. [clears throat] Something like YouTube,
95
00:16:09.124 --> 00:16:14.944
especially because their number of data points they have, besides millions of users, they have thousands of videos.
96
00:16:15.524 --> 00:16:25.624
Those are absolutely powered by algorithms that surface content to people and deliver those things, and they're powered by advanced, you know, machine learning algorithms, and those actually work.
97
00:16:25.944 --> 00:16:38.444
The one difference I would say between social media, and I always try and point this out with the streamers, um, when you have millions of data points like YouTube or Facebook or Twitter has to, or TikTok especially, right?
98
00:16:38.484 --> 00:16:46.604
To surface videos, the algorithms are even more important. A lot of the streamers, the algorithms are important, but they just don't have nearly as much content to surface.
99
00:16:47.104 --> 00:16:59.504
So if they say, "Hey, this customer likes X type of content," usually, and this is why people complain that there's nothing to watch, there's only 10, 20, 30 maybe examples to actually surface.
100
00:17:00.094 --> 00:17:05.404
Plus, most of the streamers have their fingers on parts of the scale of those algorithms, though they don't admit it.
101
00:17:06.204 --> 00:17:16.044
For example, putting something at the top of a homepage does a ton to drive traffic to it, which will boost its engagement, so automatically it's giving it a thumbs up.
102
00:17:16.164 --> 00:17:26.824
All those top spots on, like, Netflix or Disney+'s top row, those are not designed by the algorithm. Those are designed by the marketing team, and it's usually based off what's recently releasing or other times.
103
00:17:27.404 --> 00:17:35.584
So the algorithms on streaming, very important, but they're not quite as powerful as some of the algorithms out there in other websites.
104
00:17:35.624 --> 00:17:47.544
[lip smacks] Uh, and the last one that I had, you know, is my favorite, the American Viewer series you put out. Um, I just actually reread a lot of this recently. Um,
105
00:17:48.524 --> 00:18:00.083
I thought you had, you know, I mean, a, a ton of insight. You know, one was about how Hollywood, you know, kinda designs or develops creative for, you know, kind of the coast, um, and that's- Mm-hmm...
106
00:18:00.144 --> 00:18:10.224
you know, different than the overall American viewer. Kinda what, um, what kinda key takeaways in that project? Yeah. So I d- I love putting that together.
107
00:18:10.524 --> 00:18:20.554
Um, my, actually my r- I have a researcher who works with me, and he had the idea. Um, we actually cribbed it from Matthew Yglesias, who had a series called "Who Is the Average, uh, Voter?"
108
00:18:21.224 --> 00:18:31.724
And so I wanted to do sort of the same thing for the average TV watcher, with the one difference being, like, while a lot of people don't vote, basically everyone watches TV, so it ended up being across the board.
109
00:18:32.134 --> 00:18:42.064
That-- I mean, that being the main takeaway is that everyone watches a lot of TV, um, and that TV usage is pretty steady. Um, [lip smack] and so yeah, th-that one was a long time ago.
110
00:18:42.244 --> 00:18:51.684
I, I'll actually say one of the interesting things is the demographics question keeps coming up, especially with ratings. I get emailed that a lot with people asking questions.
111
00:18:51.824 --> 00:19:02.184
I don't have the data to dive into it, but it's definitely, you mentioned earlier, one of those areas to dig into. And it's a tough one because you need to have a good enough sample size, but demographics is one.
112
00:19:02.244 --> 00:19:11.364
So couple of the key takeaways that I thought were -- I would say, here are the ones I thought were most surprising, though I thought the whole thing was pretty good. First one is social media use. Um,
113
00:19:12.424 --> 00:19:21.524
it was amazing to me how big Facebook really is, and then YouTube would be the other one, and th-that question is, are they a video platform or are they a social media platform?
114
00:19:21.564 --> 00:19:33.914
But Facebook in particular is still far and away the king, even though I think most people, like say, on the coast would say it was either TikTok or especially Twitter. Most of the chattering classes tend to use Twitter.
115
00:19:34.424 --> 00:19:47.774
And so when you focus on the Twitter conversation, if I had to pick one social platform to only focus on for that c-conversation, it would be, uh, Facebook. The other one is the prevalence of living room TVs.
116
00:19:48.064 --> 00:19:57.384
I think a lot of times we think that a, a lot of video is being watched on phones, and I think a lot of video is, but it still dwarfs the living room TV.
117
00:19:57.604 --> 00:20:03.514
And I think people, and I know again, you've wr-you've written about and you do podcasts a lot about connected TVs.
118
00:20:03.584 --> 00:20:14.864
And so I would argue this is where I would focus a lot of my energy compared to phones, because I think the viewing experience is just different. Living room TV, you sit down, tend to watch it.
119
00:20:14.924 --> 00:20:18.684
You might still be on your phone, you might still be doing something else, but it's like a centerpiece.
120
00:20:19.224 --> 00:20:33.184
Where a lot of mobile viewing is either TikTok scrolling or it's watching a video on a webpage or, which I think YouTube actually benefits from, in some cases it's just music that's playing through like the YouTube app so you don't have to pay a song.
121
00:20:33.264 --> 00:20:35.924
So, uh, social media was a big one.
122
00:20:36.044 --> 00:20:49.404
Um, that-- Oh, the last one related to the coast, which, um, I think was really fascinating was that, uh, I think we still underplay how religious a lot of America is, and I think that type of content hasn't really been served.
123
00:20:50.104 --> 00:21:02.844
Um, and every so often you see a movie or a TV show like rise up and do really well at the box office or the ratings, and it's because there are actually more religious people, very diverse, different sets of beliefs.
124
00:21:02.864 --> 00:21:10.104
But I definitely think that's something that a lot of people in Hollywood can, or in the conversation about Hollywood can tend to forget.
125
00:21:14.064 --> 00:21:23.304
You know, another thing, uh, you know, interesting insight you talk about a lot is the, um, you know, the business model around streaming compared to the linear TV side.
126
00:21:23.324 --> 00:21:30.844
And a, a lot of this came ahe-to a head with, uh, the HBO Max kind of Discovery merger and, and kind of changes they made. Um,
127
00:21:32.444 --> 00:21:41.864
you know, I guess do you see this evening out over time or y-or are just the economics built into streaming, are they incapable of creating the same economics that they had in linear TV?
128
00:21:44.104 --> 00:21:56.104
I think they're incapable of creating the same economics. Um, especially if we look at the economics across the whole lifespan, um, of say like an individual film or a TV show.
129
00:21:56.924 --> 00:22:21.424
Um, I think too many of the windows have disappeared on the film side to ever recreate the same upside, especially compared to, I think, what we forget now was like the DVD boom in the early 2000s, where you had something there where films, if they could just like pay for the marketing budget, could make their production budget on DVD sales because people were buying DVDs for everything, and then everything else was gravy.
130
00:22:22.153 --> 00:22:28.834
[clears throat] When it comes to TV, my biggest concern, which I like had mentioned earlier, is still the churn piece.
131
00:22:29.604 --> 00:22:37.924
Um, when you're able to churn out, it just means that people are gonna pick and choose what they're watching at a given time.
132
00:22:38.563 --> 00:22:47.484
And right now, I think it's much more likely that Netflix is at the best case for that than Netflix is at like, say, the worst case that's gonna improve over time.
133
00:22:47.604 --> 00:22:56.904
I do think more people will cut the cord, but I think as those people cut the cord, I think they're gonna use a variety of free options or other streamers. I think we'll see some
134
00:22:57.964 --> 00:23:06.864
evolution as, like I know, uh, Zaslav, you had mentioned the HBO Max, he'd mentioned can we do like a big bundle with all the streamers at a lower price point.
135
00:23:07.844 --> 00:23:23.104
I, I th-see the logic for that, I just also see the incredible difficulty [chuckles] at convincing all these different studios to figure out who's worth what as they try and lower prices and, say, offer a year's subscription to people to get those prices lower.
136
00:23:23.194 --> 00:23:33.564
So I do think the economics are lower, and I think that, you know, for an individual TV show, I think the syndication window just won't be what it was. The second window licensing won't be what it was.
137
00:23:33.624 --> 00:23:43.504
The TVOD sales won't be there because people will churn in and out, so it's gonna be lower. The one bright side, 'cause I do wanna try and stay positive, especially [chuckles] like everything going on,
138
00:23:44.484 --> 00:23:49.004
I think the global opportunities will continue to be there in ways that they weren't before.
139
00:23:49.104 --> 00:24:03.024
I think that's actually what Netflix has really shown is that, you know, all the streamers in some cases, all the traditional studios in some cases had, say, some Latin American channels or they partnered with like European companies to sell their content.
140
00:24:03.824 --> 00:24:13.164
It really is with D2C, you really can go global with the content, with the caveat that you often need to make a lot of local content for all those new places.
141
00:24:13.684 --> 00:24:18.864
But I do think if the Hollywood studios can grab more of that global share, there will be some of that.
142
00:24:18.964 --> 00:24:29.076
But on individual market perspectives, like again in America I just, I don't think we'll see quite what we had, especially with the, say, maybe the revenues will equal the same.
143
00:24:29.256 --> 00:24:36.636
I don't think we'll see the same operating income or profit margins that we saw back in, say, the 20- 2000s or early 2010s.
144
00:24:38.996 --> 00:24:48.196
And one of the things, um, in the last couple months that's been in the news are these streamers actually removing content from their library. Uh, and it's kinda caught a lot of people,
145
00:24:49.316 --> 00:24:57.716
you know, outside of the kinda core industry off guard. What does the decision-making for that look like? Yeah.
146
00:24:57.776 --> 00:25:11.656
So this is one of those ones where, man, I wish I could be inside some of the streamers to hear some of those conversations in real life, um, because when I started in streaming, the idea that it's like, "We'll make a show and then pull it later" was, like, inconceivable.
147
00:25:11.896 --> 00:25:15.376
But having looked into it, I think there's a couple different pieces. First,
148
00:25:16.476 --> 00:25:30.576
um, the big one for a lot of the traditional studios is they're still looking for-- They're trying to get their profit margins under control, and the debt financing is just really not gonna be an option going forward.
149
00:25:30.776 --> 00:25:39.966
So if a show really, really, really underperforms, and you can essentially write off that value and take the tax losses, you can protect some of that revenue you have to send to the government.
150
00:25:40.256 --> 00:25:46.616
I think that's one of the biggest things, is getting those write-offs off the book so you can take the content and monetize it elsewhere.
151
00:25:47.196 --> 00:26:02.236
Related to that, I do think in the initial exuberance of the streaming wars, especially from the new entrants to catch up to Netflix, and honestly with the big tech firms, uh, with Netflix, is a lot of the deals just at their core probably weren't good deals in the first place.
152
00:26:02.856 --> 00:26:14.296
Um, again, if I'm right that the future TV ecosystem is smaller than the current TV ecosystem, then that means by definition the budgets have to come down or the amount of shows having made that.
153
00:26:14.356 --> 00:26:24.336
So in some cases, this is about deals that probably didn't make a lot of sense or weren't structured well enough that it gave the streamers flexibility for how to sell them in secondary markets.
154
00:26:24.766 --> 00:26:32.945
And then the last piece, even though it is very small, um, the streamers do pay residuals on a lot of content, um, or on streaming content.
155
00:26:33.036 --> 00:26:38.136
I know there's definitely been news stories that say the stre- that residuals are dead. This is not true for streaming.
156
00:26:38.556 --> 00:26:49.296
But the way it works for streaming, which again, like a lot of people don't know, is that it's one flat rate. So, um, and when you think about this, you can see why it would motivate some of these decisions.
157
00:26:49.716 --> 00:26:59.296
So Wednesday paid the same amount to its writers and actors in residuals that, um, The Rise of the Pink Ladies did, that just got removed from Paramount Plus.
158
00:27:00.176 --> 00:27:22.376
So when you consider that one of those shows was the biggest show on television or biggest Season One on television in 2022, and the other show just w- it never made any of the charts I tracked, that's why there's also this benefit that if you have to pay these recurring costs to keep content on the air, it might be cheaper to pull them off from a cash flow perspective, ignoring the sort of accounting pieces.
159
00:27:24.856 --> 00:27:29.296
Well, I guess, uh, two follow-ups to the point about the, the overall market being smaller.
160
00:27:29.336 --> 00:27:38.666
You know, one of the troubles -- I've been kinda working on a story about content spend and, uh, churn, and you're still looking at a lot of, like, you know, Morgan Stanley estimates and things like that, that are
161
00:27:39.616 --> 00:27:48.626
probably a little bit scaled back from where they were, but they're still- Mm-hmm... project growth into the future. Do you see content spend, one, being the same or smaller?
162
00:27:48.696 --> 00:28:04.876
It sounds like, um, my guess would be smaller. And if yes, is it a dramatic reduction in the number of shows or the spend per show? I do not have a strong take. I, I don't think it's gonna keep going up.
163
00:28:05.016 --> 00:28:21.236
Now, whether or not content spend as a total stays, goes down, I'm little-- I, I don't have a strong feeling on that, though I think we have seen across the board that it really does seem like a lot of people are trying to rightsize their content spend.
164
00:28:22.016 --> 00:28:32.396
Um, so I would definitely much more bank towards flat, which if you count inflation, is the same thing as making it smaller over time. I think both will be an option, though.
165
00:28:32.576 --> 00:28:41.115
To answer the second part of the question, what happens to the number of content? I think we've already seen budgets come down in certain cases. Um,
166
00:28:42.276 --> 00:28:51.816
l- for example, on the broadcast season, a lot of actors, they're g- having fewer actors per episode, smaller guarantees, doing smaller writer rooms, things like that.
167
00:28:52.216 --> 00:29:01.056
So I think they'll try and figure out ways to s- keep some of the content costs down. I think some of the reality TV shows will try and be squeezed too for sort of smaller budgets.
168
00:29:01.676 --> 00:29:06.416
Um, so I think we'll see a combination of both those things.
169
00:29:06.536 --> 00:29:17.536
I also think the other piece that's not really related to removals, but I think we might also see more examples where streamers are selling the same shows to other people, 'cause that's essentially a win-win.
170
00:29:17.566 --> 00:29:24.356
Another streamer gets a new show, and then the other streamer gets cash flow. So it's sort of more circular like that, so it's
171
00:29:25.276 --> 00:29:30.916
make-- providing different streamers new content, but not actually having to go out and pay full freight of a brand-new production.
172
00:29:34.496 --> 00:29:43.636
And with that, like, kinda last, um, business model question, are you a bull or bear on ad-supported streaming? I am a bull on it.
173
00:29:43.936 --> 00:29:55.315
Uh, especially with the free ad-supported streaming TV, um, I like, I call myself the entertainment strategy guy, so whenever possible, I try and come back to, like, the core strategy principles.
174
00:29:55.716 --> 00:30:00.916
And for me, like, my favorite chart is just a value creation model and ask, "How does this create value for the customers?"
175
00:30:01.716 --> 00:30:18.116
And with the free ad-supported streaming in particular, I think it really f- solves a customer need that the on-demand part of streaming really hasn't quite figured out, which is the idea that it's like, "I don't want to pick something heavy to watch right now.
176
00:30:18.636 --> 00:30:27.226
I just want something on in the background." And so it can be reruns of Friends or it can be, you know, or a, a movie midway through.
177
00:30:27.316 --> 00:30:40.892
Um, that's-- I know there's some residual implications for that, but- I've always thought that, for example, Disney+ misses a huge use case for why TNT and TBS and FX and USA Network have movies on all the time.
178
00:30:40.932 --> 00:30:49.292
It's not because you plan to start watching, like, "Avengers" from the beginning, but you see, "Okay, what scene is 'Avengers' on? Oh, I like this scene.
179
00:30:49.372 --> 00:30:55.652
I'm gonna, like, turn it on in the background, and I can go finish dishes," or something like that. So I'm a big believer in that.
180
00:30:55.812 --> 00:31:07.712
I also think, um, with the ad-supported streaming, in some cases it's just gonna lower cost, so it's gonna allow more customers to have different options for what to watch at the same price.
181
00:31:08.152 --> 00:31:28.742
The one caveat I have for the streamers doing it is the data I've seen is that the moment you put advertising on something, the customer value for that, again, back to the value creation model, really, really drops, and their willingness to pay goes way, way down when something is supported with ads than when it's, uh, you know, without ads entirely.
182
00:31:28.812 --> 00:31:36.411
Um, I just had a family member complaining to me about Netflix who d- doesn't even have an ad-supported, but he's like, "They're running trailers on things. I can't believe it."
183
00:31:36.472 --> 00:31:45.372
And it's like [chuckles] that's, like, the smallest thing you can do, and he's like, "What happened?" I'll admit, I, I have that with, uh... I, I know HBO Max it.
184
00:31:45.432 --> 00:31:53.792
I don't think I've seen it before, but HBO Max will run a trailer, and I'll be like, "What are you doing? Just go with the show." But old HBO used to do it all the time, but I think that is there.
185
00:31:53.972 --> 00:32:02.532
The-- But overall, I would still say I'm bullish with the idea that, uh, the monetization forecasts are probably what I'd be the most skeptical.
186
00:32:02.572 --> 00:32:11.242
I'm sure there's people who'd be like, "Oh, you know, take the line and draw it up to the moon," and I always tend to be skeptical of that. That's sorta, you know, I'm skeptical of every business model by nature.
187
00:32:13.972 --> 00:32:22.652
Yeah, our, our thesis is that they, you know, we look at the revenue per hour with that being the, the kind of most or all of, of their revenue from advertising,
188
00:32:23.632 --> 00:32:33.072
that they obviously have gotta create, um, more value in the ad unit unless they're gonna- Right... just recreate the kinda linear ad load.
189
00:32:34.012 --> 00:32:43.912
Um, and in, in order to do that they gotta kinda, you know, add your measurement and, you know, make it more impactful for the buyer, but also bring in more, more buyers.
190
00:32:43.932 --> 00:32:54.082
You know, there's only 250, you know, brands buy the do- the majority of national TV advertising, and there are, you know, probably a million video advertisers in the US, and, um, you know, really
191
00:32:55.472 --> 00:33:04.522
growing the demand side of the equation, that's, uh, an, uh, kind of a white space that we see in the market, uh, today. But, you know, it-- Do you think, kinda on a side note there,
192
00:33:05.572 --> 00:33:11.912
Fox, smart move by them only having a FAST and not having the other pieces, or is that, are they gonna fall behind because of that?
193
00:33:13.692 --> 00:33:34.232
I think it's a smart move for now because I think they're just really focused on the cash flow question, and I think, um, you know, one of my rules is not to bet against Rupert Murdoch because I think he actually has just done the thing where he buys -- Like everyone says, like, "Buy low and sell high," and I think he is one of the people [chuckles] who has lived that.
194
00:33:34.332 --> 00:33:38.381
As one of, uh, a person told me once, they said, "Rupert has a price for everything."
195
00:33:39.232 --> 00:33:50.812
And then he knows what he would sell everything at and he knows what he would buy everything at, and I think he judged that streaming was going up, sold at the right time, could come in and buy low while he's, like, building up this cash pile.
196
00:33:50.912 --> 00:34:03.462
So I think it's smart. That said, I think you identified the big key piece, um, because, you know, to go back to the traditional TV, right? While those 250 advertisers did buy the bulk of the advertising, right?
197
00:34:03.532 --> 00:34:12.432
Almost all local channels always did sell local ads to car dealerships, you know, uh, appliance shops, things like that. So there are definitely a lot of opportunities for that.
198
00:34:12.932 --> 00:34:20.692
I'd say I'm actually working on an article right now on AI, because, I mean, that subject's huge and how generative AI could impact everything.
199
00:34:21.232 --> 00:34:31.952
One of the pieces that I think would be interesting, I think, for the local people is can you make an ad that looks almost as good as nationally produced ads, but it's for local restaurants?
200
00:34:32.412 --> 00:34:45.752
And I think, uh, that could help solve one of those demand-- You're talking about the demand issue, but that could also help the supply, in that if the ad takes a company one day to make, it's way easier than having to go do a whole film shoot and pay someone something like that.
201
00:34:45.852 --> 00:34:52.732
But, um, I think the demand piece has to get solved, but I am still optimistic for it, uh, sort of the way you are.
202
00:34:54.252 --> 00:34:59.492
Yeah, they just gotta basically look at the ad unit now as not a spot running once everybody, but it's, you know,
203
00:35:00.412 --> 00:35:08.492
35,000 ad impressions and, you know, again, Facebook has just crushed this problem of figuring out how to get that ad impression in front of the person that finds it the most valuable. Right.
204
00:35:08.542 --> 00:35:14.352
[clears throat] And that could be location, that could be a direct consumer brand that's, you know, doesn't care where their customers come from.
205
00:35:14.392 --> 00:35:24.152
It could be still the, the national groups, but there's a demand part of this that, and when I talk to people that are-- come from the national ad side, they don't see, they don't think that way at all, right?
206
00:35:24.202 --> 00:35:34.582
'Cause they, they've been so successful at selling the one spot, the scarcity. [clears throat] But now, you know, you have an impressions, you could, you can sell this to anybody, right?
207
00:35:34.632 --> 00:35:44.242
Like it doesn't matter, and you, you really could onl- you know, you could figure it out. Like, you could just take 10% of your inventory, focus on that, let 90% go to, you know, the 250. Right.
208
00:35:44.272 --> 00:35:55.252
But I do think, and so, so I'm bullish on people that have not, like a Roku or, or a fast service that have not, aren't at the upfronts, like, you know, dominating that market today. Right.
209
00:35:56.432 --> 00:35:58.262
Yeah, I think that makes sense. Um,
210
00:35:59.312 --> 00:36:11.992
the one other hurdle, I think the connected TV market and basically anything digital, uh, 'cause I mentioned AI, I think, uh, fake views is the other big issue that I think has to get really handled.
211
00:36:12.052 --> 00:36:28.972
That, that's why when it comes to streaming ratings, I do tend to prefer any platform that has, uh, panels, 'cause I think it's a little more reliable than just tracking straight usage, because, you know, there are already stories about, you know, server farms out there, like, just trying to generate click-through on ads.
212
00:36:29.452 --> 00:36:35.532
So I think that is a big hurdle, but I think you have absolutely identified one of the opportunities.
213
00:36:35.572 --> 00:36:44.353
And again, that's what makes me why- I would say I'm bullish on ad-supported TV is because I think a lot of the traditional is gonna transition over.
214
00:36:44.424 --> 00:36:55.864
And to your point, you can do better targeting, better optimization for some of those ads for smaller people who would never have considered it before. All right, last question.
215
00:36:56.064 --> 00:37:09.824
What is one insight that you have that we're not talking about that we should? One insight that we're not talking about that we probably should. Um, I'll give you...
216
00:37:13.644 --> 00:37:21.964
Uh-huh. Okay. I probably should have had this prepared earlier, maybe cut some of this rambling. Um, okay, I'll restart.
217
00:37:22.024 --> 00:37:34.284
So the, one of the biggest pieces that, uh, continues to amaze me is that, you know, I write a lot about strategy, and so when we tend to think of strategy, I think most people tend to really look externally on strategy.
218
00:37:34.344 --> 00:37:41.684
So it's, um, you know, where is our product positioned against all the cust- what the customers want and what our competitors are doing.
219
00:37:41.764 --> 00:37:50.744
And very-- much fewer people look internally, um, at things, and I actually think one of the big revolutions is gonna be in how we work.
220
00:37:50.884 --> 00:38:01.084
I'm a pretty big believer in the books by Cal Newport, uh, Deep Work, Digital Minimalism, and so on. Uh, Wor- World Without Email would be the most applical- applicable to big organizations.
221
00:38:01.644 --> 00:38:20.204
And I think we're gonna see a big trend in the next 10 to 15 years where companies move away from managing most things in their inboxes, and I think most people listening are probably in their inbox right now, to project-based workflows, um, doing things, say, slower but at higher quality, managing less projects and things like that.
222
00:38:20.284 --> 00:38:25.764
So that's whenever anyone asks for me for a recommen- book recommendation, it's always Deep Work.
223
00:38:25.804 --> 00:38:36.444
But when it comes to an insight, it's, I think the way we're working is very much like when, um, factories were first electrified. This is an analogy Cal Newport makes.
224
00:38:36.984 --> 00:38:50.724
And it required rethinking how an entire factory floor was conceived, but that process took decades to actually realize that, you know, you had smaller motors, so you didn't have to have everything based around, like, a river turning a steam wheel.
225
00:38:51.264 --> 00:39:01.904
So that'll, I think, be one of the big changes in the next 10 years, and I don't think enough people are talking about it. All right, SG, I've loved this conversation. Where can our audi- audience find you?
226
00:39:02.944 --> 00:39:05.574
So I'm at entertainment.substack.com.
227
00:39:05.733 --> 00:39:17.024
That's my newsletter where you can get a weekly, uh, streaming gradings report, which is, uh, uses multiple data sources, uh, to provide a comprehensive look of what's working and what's not working in the streaming wars.
228
00:39:17.544 --> 00:39:31.944
I also publish regular strategy columns over there, um, as well. I publish, uh, every other week for theinkler.com, a strategy column as well. And I'm on all the, you know, social-- I'm on Twitter and LinkedIn as well.
229
00:39:31.984 --> 00:39:40.984
So if you wanna connect on LinkedIn, go ahead. I will post all in the show notes, but I'm, uh, grateful for your time, and this has been, been a blast. Yeah.
230
00:39:41.104 --> 00:39:51.864
I enjoyed talking to you, um, and I appreciate the invite on the podcast. [upbeat music] Thank you for joining us on this episode of Screen Wars. I hope you enjoyed the discussion.
231
00:39:52.084 --> 00:40:03.604
You can find out more about CrossScreen Media at crossscreenmedia.com. Please don't forget to sign up for our weekly newsletter, State of the Screens. You can find us on social media at CrossScreen Media.
232
00:40:03.624 --> 00:40:10.364
Join us next time for more insights and analysis straight from the experts. [upbeat music]
1
00:00:00.080 --> 00:00:15.600
[upbeat music] Hello, and welcome to another episode of Stream Wars, our thought leader series where we learn from industry experts about the latest trends and challenges from across the convergent TV space.
2
00:00:16.040 --> 00:00:27.020
Hosted by Michael Beach. Today, I'm joined by the Entertainment Strategy Guy. If you read State of the Screens and you're familiar with his or her work, since they are one of the most cited sources we've ever had.
3
00:00:27.940 --> 00:00:35.640
Uh, we've communicated for years via email and Twitter. Uh, we share a research assistant, but this is actually the first time, uh, you know, we've ever met in real time.
4
00:00:35.820 --> 00:00:39.810
Uh, ESG, you know, has fantastic insight, and we dig into a lot of that.
5
00:00:40.860 --> 00:00:48.980
Uh, one of the things that was most helpful to me was kind of understanding the overall business model of streaming versus linear TV, really how this is gonna dictate the future of content.
6
00:00:49.020 --> 00:00:51.620
You know, how much money is gonna get spent on content, what type of shows are gonna get made.
7
00:00:52.500 --> 00:01:01.200
Uh, and then we really get into the, the business model of streaming and, and kinda in particular, uh, the arrival of the FAST service, you know, the free ad-supported streaming TV.
8
00:01:02.380 --> 00:01:11.900
Uh, so with that, you know, please enjoy my conversation with the Entertainment Strategy Guy. All right, ESG, welcome to Screen Wars. Hey, Michael. Uh, glad to be here. Absolutely.
9
00:01:12.860 --> 00:01:24.520
Uh, you know, I've obviously been, uh, you know, a huge fan of your writing for a long time. You're probably, uh, you're the most quoted person, uh, in our newsletter over the past seven years.
10
00:01:24.980 --> 00:01:31.040
Um, one thing I've always found interesting is the, the point of view that you're able to offer from, you know, writing an anonymous account.
11
00:01:31.100 --> 00:01:41.160
What kind of is your background on thinking about that and, and kinda how's that, that worked out? Yeah. Um, first off, also, I'm a huge fan of your newsletter as well. I love the charts.
12
00:01:41.320 --> 00:01:51.740
I'm constantly pulling charts or finding new data sources from it as well. So, uh, there's definitely mutual fans on both sides here. Um, [clears throat]
13
00:01:52.000 --> 00:02:03.620
so the anonymity thing, uh, started out, I knew I wanted to write about strategy and entertainment, 'cause I, there weren't enough people, I thought, analyzing the entertainment industry and the strategies behind it.
14
00:02:04.340 --> 00:02:15.220
And I'd just been let go from another streamer, and so odds are I wouldn't be able to make the writing thing work, so I would be w- back at another entertainment industry.
15
00:02:15.640 --> 00:02:26.230
And I felt if I wanted to write the most freely about entertainment as possible, it made sense to be anonymous so that, you know, [chuckles] if like six months later I wasn't getting any traction, I could go back.
16
00:02:26.920 --> 00:02:38.340
Along the way, um, it did end up working out. The surprising thing is a lot of my customers actually told me, um... And whenever I throw up a poll on this, I say, "Should I stay anonymous or, like, reveal who I am?"
17
00:02:38.380 --> 00:02:47.040
It's 50/50. So half the people love it, half the people don't. So I've kept doing it for that reason. Along the way, I've also, I actually work on a lot of creative projects on the side.
18
00:02:47.340 --> 00:02:52.100
Um, some consulting projects with friends, some consulting projects with just other people.
19
00:02:52.769 --> 00:02:59.960
And so now that I write so heavily about streaming ratings as well, I actually think the anonymity piece sort of protects some of those projects.
20
00:03:00.020 --> 00:03:09.660
So again, I can write freely about what I think is working or not working in the industry. So, um, yeah, I, the anonymity thing is probably the number one question I get asked by people, "Why?"
21
00:03:09.760 --> 00:03:22.900
Um, but it's worked so far and been going with it ever since. Yeah, it's been interesting. I mean, the, you know, it seems like you wrote on your own for a while and then kind of moved to the Ankler a few years ago.
22
00:03:23.020 --> 00:03:31.240
Um, you know, what's it been like working with, you know, Richard Rushfield and the team? Richard Rushfield has been great. Actually, the entire team has been fantastic.
23
00:03:31.480 --> 00:03:48.040
Um, as soon as I discovered Richard's newsletter, I definitely felt him and I, where we come from different backgrounds, we sort of have the same approach, the same, uh, in some cases, like skeptical about what the studios are saying, sort of like digging beneath the, uh, surface.
24
00:03:48.620 --> 00:03:58.920
So was happy to join him. Uh, he had told me before w- before they launched the big Ankler redo last year and really expanded the operation, they were going in that direction.
25
00:03:59.480 --> 00:04:02.950
And so I was happy to start writing a column for them.
26
00:04:03.440 --> 00:04:18.570
And for me, it's been the best of both worlds in that I have my newsletter that continues to go out via Substack, but I also get exposure to the Ankler's great audience and get to work with Jan Essmann, who's also just a fantastic editor, um, and great sounding board for ideas.
27
00:04:18.700 --> 00:04:25.280
And so, yeah. That's amazing. You know, and the, the streaming ratings, I mean, I think that's the thing you're known for.
28
00:04:25.900 --> 00:04:32.680
Um, I've always been interested to ask what, I guess, what's the hardest part about putting that together?
29
00:04:32.780 --> 00:04:39.820
Uh, you know, it seems like you had the insight earlier than anybody else that the data was available to make consistent analysis here.
30
00:04:39.840 --> 00:04:48.440
But, you know, what's the hardest part and kinda what, what pieces are still missing? That's a fan-- Both those are fantastic questions.
31
00:04:48.700 --> 00:05:02.860
Um, the hardest part right now for me, just from a personal standpoint, is just still dealing with the, uh, known unknowns, you know, to quote, uh, Rumsfeld from way back in the day. But
32
00:05:03.940 --> 00:05:12.920
I started out, um, polling Nielsen's top 10 list. Um, I'd like to call it the streaming ratings era when it started in 2020.
33
00:05:13.600 --> 00:05:30.840
Um, it was like COVID happened, and all of a sudden a lot of the companies that were working on data hopped into the field at the same time, and the incident that I felt had the most, generated the most traffic was when Mulan came out on, uh, PVOD and everyone wanted to know, like, how well did it do?
34
00:05:31.340 --> 00:05:41.420
And so I noticed all of a sudden, and, and I'd been writing about strategy only for a few years, that there were like five different companies, including Nielsen, and then they started publishing their top 10 list.
35
00:05:42.180 --> 00:05:52.240
And my rule of thumb is always that content is about half of the entertainment battle. That's what you're trying to win. So I was all of a sudden like, "Wow, we now have the data. We can actually look at streaming."
36
00:05:52.280 --> 00:06:03.600
But that ties, that's still only a top 10 list, though. And, um, for someone who works outside of a major company or even for, for some of the people who work inside of a company, the big-
37
00:06:04.532 --> 00:06:08.992
Unknown data point is basically all those other data points for all those other competitors.
38
00:06:09.072 --> 00:06:17.092
And even the people who do provide that, like Nielsen or Samba TV or some of the other ones, they also have other blind spots, which gets to your second point, which is,
39
00:06:18.052 --> 00:06:28.832
one, um, no one actually knows what happens on the other side of the screen. So is it one person watching? Is it two people? Who in the household's actually watching? And that's where they have the test panels.
40
00:06:28.872 --> 00:06:44.172
But the problem with the test panels on the living room is tying that data over to phones, tying it over to mobile devices, laptops, and trying to figure out the who question is still the biggest piece that isn't solved and may not be solved for a while.
41
00:06:44.552 --> 00:07:01.812
And then as I know you've covered on the podcast before, in the future, there's gonna be even more pieces of content coming from user-generated spaces, YouTube, TikTok, and just getting-- translating all those and figuring out what works across every single thing, such a problem that, you know, may never be solved.
42
00:07:01.872 --> 00:07:14.052
So... Yeah, I find it interesting 'cause, you know, we start, you know, our core business on the advertising side, obviously we're using similar data sets, but how do you feel the
43
00:07:15.412 --> 00:07:27.352
-- on the content side about how they value everything? Um, you feel like the way you put the ratings t-together, that they have a, a view to, to properly value the content or is that still a black hole?
44
00:07:27.362 --> 00:07:39.692
'Cause we're -- the advertising side, it's definitely, uh, probably not getting properly valued. I don't think we're there yet, um, to have it be properly valued, but I think we're on the way there.
45
00:07:40.012 --> 00:07:51.532
Um, I don't think my streaming gradings reports alone could like provide the proper value just because we don't have enough data points that are public to provide those data points. I think we're gonna get there.
46
00:07:51.652 --> 00:08:00.192
Um, I also think once we have multiple sources at every company, I'm actually optimistic that'll provide essentially better double checks.
47
00:08:00.232 --> 00:08:07.492
So instead of having just Nielsen and a single point of failure, you can have multiple sources to see if they're all roughly telling a similar picture.
48
00:08:08.212 --> 00:08:12.732
Um, that said, I am optimistic we can get to what content is valuable,
49
00:08:13.692 --> 00:08:24.392
uh, simply because we have so much data that at some point it becomes overwhelming when we know what the hits are, or we know what the slightly lesser hits are, and we know what the pieces below those.
50
00:08:24.512 --> 00:08:31.622
Um, I still, as much as things have changed, I, I tend to revert back to the basic principles with entertainment.
51
00:08:32.252 --> 00:08:40.172
Um, so it's a hit-driven business, and if something's popular in one metric, it tends to be popular across the board in everything.
52
00:08:40.612 --> 00:08:55.441
So, you know, the example I love to use, like "Stranger Things," like "Stranger Things" is probably Netflix's most viewed show in terms of total hours, but probably also with unique customers, and its Wikipedia page views are very high, and so is its social media conversation.
53
00:08:55.912 --> 00:09:03.712
So all those things tend to be directional, and it has very high completion rate. So I think at some point we're gonna be able to get there.
54
00:09:04.092 --> 00:09:16.172
Um, you mentioned the advertising 'cause I know that's what you do day in and day out, and I think that has its own different challenges, especially with attribution and figuring out what's on what platform, which those problems are still going there.
55
00:09:16.212 --> 00:09:25.112
But do think we're gonna get better at telling what content works and then valuing how much that actually drives value f- down the value chain.
56
00:09:28.072 --> 00:09:33.432
Yeah, and I got, uh, you know, three kind of specific pieces of content that I've always wanted- Mm-hmm... to kind of get your background on.
57
00:09:33.472 --> 00:09:45.372
The first, you were kind of really early in calling the S- the Netflix kind of subscriber slowdown. Right. Um, can you kind of walk me through how you projected that? Yeah.
58
00:09:46.092 --> 00:10:00.552
So that, uh, I actually cribbed that from a business school professor who, in our entertainment strategy class, um, looked at Netflix back in, it was like '20, I don't wanna say what year, long time ago.
59
00:10:00.742 --> 00:10:04.212
And he actually said like, "Could we apply the Bass diffusion curve to it?"
60
00:10:04.252 --> 00:10:16.932
Which is the inter- the marketing 101 tool that basically says most new technologies have an adoption curve that starts out slow for a few years, picks up speed, and then slows down again. Also called an S curve.
61
00:10:16.972 --> 00:10:27.241
It looks like an S, sort of like with the two ends pulled out. And so, uh, when I was starting to look at Netflix and they started to have some quarters that were slowing down just slightly,
62
00:10:28.252 --> 00:10:36.852
I wondered, I was like, "Could [chuckles] we reapply this curve to Netflix," um, using them sort of as a stand-in for all streaming video.
63
00:10:37.272 --> 00:10:57.772
And sure enough, the curve actually fit pretty tightly and it, it still had some uncertainty, but it definitely looked that the idea that Netflix would get to 90 or 100, and I did this just in the US, but the idea that Netflix would get to 90 or 120 million subscribers, which if people remember all the way back to 2018, that was what a lot of people forecast in the US.
64
00:10:58.332 --> 00:10:59.332
And so I applied that.
65
00:10:59.432 --> 00:11:12.812
I had to do a ton of data searching 'cause Netflix changes their definitions of US subscribers like every three years, so I had to do some estimates, but it ended up working out, and the number to me was right around 65 to 70 million subscribers in the US.
66
00:11:13.572 --> 00:11:30.122
Netflix, like I said, later converted to US and Canada subscribers, but if you subtract out the 10% of the subscribers that are roughly from Canada, Netflix is right around, I forget off the top of my head, but something like 66 million subscribers, and so that's how I calculated that number.
67
00:11:30.212 --> 00:11:30.262
Um,
68
00:11:31.832 --> 00:11:44.672
I don't know that it would work for some of the other streamers because I think the streaming curve has been adopted now, but I'm definitely monitoring those streamers for if I see subscriber slowdowns in the future, that's gonna be sort of my guess for what happens.
69
00:11:47.032 --> 00:11:56.012
No, it's great just 'cause it, I mean, even if you just get Netflix right, the, uh, they're obviously the high end of the TAM- Yep... uh, for the US and, and so, you know, I think that just shifted.
70
00:11:56.832 --> 00:12:09.132
It was just such a good insight, you know, so early and, and, uh, you know, I keep going back to that about when you're, you know, the next time we get into this kind of bull market and people start, you know, making these lofty projections, I just thought that, that insight was incredible.
71
00:12:10.504 --> 00:12:23.024
Uh, appreciate that. It's actually, I think, worked for some other, uh... I think whenever you hear buzzy numbers in any field, uh, look up the Bass diffusion curve and basically look at it.
72
00:12:23.104 --> 00:12:28.804
You can just in some cases eyeball it, and you'll get the same thing. I would also say I noticed this with Fortnite.
73
00:12:28.984 --> 00:12:41.304
Um, I definitely saw the slow growth, and then it took off, and I looked at the same thing and said, like [chuckles], "So, is it headed to keep skyrocketing to a billion users, or is it gonna like top out?"
74
00:12:41.404 --> 00:12:54.504
And Fortnite would n- while it remained popular and has its user base, it definitely wasn't growing, like what- whatever year when it was like Fortnite summer, and then there were people who were like, "Will there be 500 million, you know, 600 million, a billion active users?"
75
00:12:54.544 --> 00:13:00.524
And it's like, "No, it'll probably slow down," because it was so fast on the uptake. So it's a, it's a fun tool to use.
76
00:13:00.634 --> 00:13:09.944
And the other one I would relate to with Netflix, which I, I feel like a corner I was on pretty early, as well as the, uh, the churn game, is just everything with them.
77
00:13:10.534 --> 00:13:18.784
And when you're trying to map things to cable, cable was an industry that didn't have churn, because if you wanted TV, you had to have cable.
78
00:13:19.464 --> 00:13:23.264
And with the streamers, you, you don't have to keep, stay subscribed to a streamer.
79
00:13:23.684 --> 00:13:32.784
And so that churn issue was really the thing I was trying to quantify, because I thought that was gonna lower the overall TAM, and again, think people disagreed. So, uh, yeah, thank you for that insight.
80
00:13:32.904 --> 00:13:44.084
That's the one I, I try and hang my hat on because it, it worked out so well and, you know, making predictions is a tough game. [chuckles] Yeah, another one, uh, you know, the algorithm is a lie. Yep.
81
00:13:44.094 --> 00:13:59.044
And I wanna get your insight, 'cause I think your probably intention was around using that, you know, assuming that, you know, uh, Netflix or, you know, Hollywood Studio uses, you know, data science just to pick what content to green light is more than the, um, [lip smacks]
82
00:13:59.164 --> 00:14:08.164
you know, the kinda, uh, the experience. But we also look at it on the, the content delivery to the consumer where- Mm-hmm... you've got a kinda algorithm that can deliver TV.
83
00:14:08.224 --> 00:14:18.644
Do you feel like bo- you apply it to both or just more one or the other? No, absolutely don't apply it to algorithms at, that surface content, with some caveats to that.
84
00:14:18.724 --> 00:14:26.544
I do think they definitely get over-hyped, and I definitely think certain social sites leverage algorithms even more strongly than, say, certain streaming sites.
85
00:14:26.624 --> 00:14:43.004
But for any of your readers who aren't familiar, so the algorithm is a lie is, it's sort of de jure for a lot of, uh, you know, critical reviews of streaming shows that if they don't like it, e- especially for Netflix, they're like, "I can't believe the algorithm picked this show."
86
00:14:43.124 --> 00:14:50.184
And, uh, the TV show "Barry" actually featured the algorithm said to cancel a show within six hours, right?
87
00:14:50.424 --> 00:14:58.704
Which has never happened because the algorithm wouldn't even have enough data, um, to really make the predictions in six hours. They would give some trends, but not predictions.
88
00:14:58.744 --> 00:15:12.564
So my argument is, is that it is true that the streamers and all the studios have more data than ever at their disposal to help guide the development process, to help see what's working, to help make some calls, and things like that.
89
00:15:13.224 --> 00:15:22.524
That said, there still isn't enough data to actually pick, say, "Hey, this script is going to be a hit TV show," right? You know, "If we cast this actress, it's gonna be a hit TV show."
90
00:15:22.544 --> 00:15:37.064
And I've tried to explain before, the main reason from a data perspective is that there's just not enough data points to be able to tell, because there's too many variables going into any individual TV project to say, "This thing's gonna be a huge hit," or, "This thing won't flop."
91
00:15:37.164 --> 00:15:43.304
And if, you know, studios did have algorithms, they wouldn't make bad shows and nothing would flop, but that's not the situation.
92
00:15:43.924 --> 00:15:51.434
So they have more data than ever before, and this includes, you know, Nielsen ratings, box office, social media, internet traffic, all those things.
93
00:15:52.564 --> 00:15:59.284
That is one bucket that content still has to be created by people, and they deserve all the credit, all the blame for all the content decisions.
94
00:15:59.704 --> 00:16:08.164
On the other side is the algorithmic delivery of content, especially for social media platforms. [clears throat] Something like YouTube,
95
00:16:09.124 --> 00:16:14.944
especially because their number of data points they have, besides millions of users, they have thousands of videos.
96
00:16:15.524 --> 00:16:25.624
Those are absolutely powered by algorithms that surface content to people and deliver those things, and they're powered by advanced, you know, machine learning algorithms, and those actually work.
97
00:16:25.944 --> 00:16:38.444
The one difference I would say between social media, and I always try and point this out with the streamers, um, when you have millions of data points like YouTube or Facebook or Twitter has to, or TikTok especially, right?
98
00:16:38.484 --> 00:16:46.604
To surface videos, the algorithms are even more important. A lot of the streamers, the algorithms are important, but they just don't have nearly as much content to surface.
99
00:16:47.104 --> 00:16:59.504
So if they say, "Hey, this customer likes X type of content," usually, and this is why people complain that there's nothing to watch, there's only 10, 20, 30 maybe examples to actually surface.
100
00:17:00.094 --> 00:17:05.404
Plus, most of the streamers have their fingers on parts of the scale of those algorithms, though they don't admit it.
101
00:17:06.204 --> 00:17:16.044
For example, putting something at the top of a homepage does a ton to drive traffic to it, which will boost its engagement, so automatically it's giving it a thumbs up.
102
00:17:16.164 --> 00:17:26.824
All those top spots on, like, Netflix or Disney+'s top row, those are not designed by the algorithm. Those are designed by the marketing team, and it's usually based off what's recently releasing or other times.
103
00:17:27.404 --> 00:17:35.584
So the algorithms on streaming, very important, but they're not quite as powerful as some of the algorithms out there in other websites.
104
00:17:35.624 --> 00:17:47.544
[lip smacks] Uh, and the last one that I had, you know, is my favorite, the American Viewer series you put out. Um, I just actually reread a lot of this recently. Um,
105
00:17:48.524 --> 00:18:00.083
I thought you had, you know, I mean, a, a ton of insight. You know, one was about how Hollywood, you know, kinda designs or develops creative for, you know, kind of the coast, um, and that's- Mm-hmm...
106
00:18:00.144 --> 00:18:10.224
you know, different than the overall American viewer. Kinda what, um, what kinda key takeaways in that project? Yeah. So I d- I love putting that together.
107
00:18:10.524 --> 00:18:20.554
Um, my, actually my r- I have a researcher who works with me, and he had the idea. Um, we actually cribbed it from Matthew Yglesias, who had a series called "Who Is the Average, uh, Voter?"
108
00:18:21.224 --> 00:18:31.724
And so I wanted to do sort of the same thing for the average TV watcher, with the one difference being, like, while a lot of people don't vote, basically everyone watches TV, so it ended up being across the board.
109
00:18:32.134 --> 00:18:42.064
That-- I mean, that being the main takeaway is that everyone watches a lot of TV, um, and that TV usage is pretty steady. Um, [lip smack] and so yeah, th-that one was a long time ago.
110
00:18:42.244 --> 00:18:51.684
I, I'll actually say one of the interesting things is the demographics question keeps coming up, especially with ratings. I get emailed that a lot with people asking questions.
111
00:18:51.824 --> 00:19:02.184
I don't have the data to dive into it, but it's definitely, you mentioned earlier, one of those areas to dig into. And it's a tough one because you need to have a good enough sample size, but demographics is one.
112
00:19:02.244 --> 00:19:11.364
So couple of the key takeaways that I thought were -- I would say, here are the ones I thought were most surprising, though I thought the whole thing was pretty good. First one is social media use. Um,
113
00:19:12.424 --> 00:19:21.524
it was amazing to me how big Facebook really is, and then YouTube would be the other one, and th-that question is, are they a video platform or are they a social media platform?
114
00:19:21.564 --> 00:19:33.914
But Facebook in particular is still far and away the king, even though I think most people, like say, on the coast would say it was either TikTok or especially Twitter. Most of the chattering classes tend to use Twitter.
115
00:19:34.424 --> 00:19:47.774
And so when you focus on the Twitter conversation, if I had to pick one social platform to only focus on for that c-conversation, it would be, uh, Facebook. The other one is the prevalence of living room TVs.
116
00:19:48.064 --> 00:19:57.384
I think a lot of times we think that a, a lot of video is being watched on phones, and I think a lot of video is, but it still dwarfs the living room TV.
117
00:19:57.604 --> 00:20:03.514
And I think people, and I know again, you've wr-you've written about and you do podcasts a lot about connected TVs.
118
00:20:03.584 --> 00:20:14.864
And so I would argue this is where I would focus a lot of my energy compared to phones, because I think the viewing experience is just different. Living room TV, you sit down, tend to watch it.
119
00:20:14.924 --> 00:20:18.684
You might still be on your phone, you might still be doing something else, but it's like a centerpiece.
120
00:20:19.224 --> 00:20:33.184
Where a lot of mobile viewing is either TikTok scrolling or it's watching a video on a webpage or, which I think YouTube actually benefits from, in some cases it's just music that's playing through like the YouTube app so you don't have to pay a song.
121
00:20:33.264 --> 00:20:35.924
So, uh, social media was a big one.
122
00:20:36.044 --> 00:20:49.404
Um, that-- Oh, the last one related to the coast, which, um, I think was really fascinating was that, uh, I think we still underplay how religious a lot of America is, and I think that type of content hasn't really been served.
123
00:20:50.104 --> 00:21:02.844
Um, and every so often you see a movie or a TV show like rise up and do really well at the box office or the ratings, and it's because there are actually more religious people, very diverse, different sets of beliefs.
124
00:21:02.864 --> 00:21:10.104
But I definitely think that's something that a lot of people in Hollywood can, or in the conversation about Hollywood can tend to forget.
125
00:21:14.064 --> 00:21:23.304
You know, another thing, uh, you know, interesting insight you talk about a lot is the, um, you know, the business model around streaming compared to the linear TV side.
126
00:21:23.324 --> 00:21:30.844
And a, a lot of this came ahe-to a head with, uh, the HBO Max kind of Discovery merger and, and kind of changes they made. Um,
127
00:21:32.444 --> 00:21:41.864
you know, I guess do you see this evening out over time or y-or are just the economics built into streaming, are they incapable of creating the same economics that they had in linear TV?
128
00:21:44.104 --> 00:21:56.104
I think they're incapable of creating the same economics. Um, especially if we look at the economics across the whole lifespan, um, of say like an individual film or a TV show.
129
00:21:56.924 --> 00:22:21.424
Um, I think too many of the windows have disappeared on the film side to ever recreate the same upside, especially compared to, I think, what we forget now was like the DVD boom in the early 2000s, where you had something there where films, if they could just like pay for the marketing budget, could make their production budget on DVD sales because people were buying DVDs for everything, and then everything else was gravy.
130
00:22:22.153 --> 00:22:28.834
[clears throat] When it comes to TV, my biggest concern, which I like had mentioned earlier, is still the churn piece.
131
00:22:29.604 --> 00:22:37.924
Um, when you're able to churn out, it just means that people are gonna pick and choose what they're watching at a given time.
132
00:22:38.563 --> 00:22:47.484
And right now, I think it's much more likely that Netflix is at the best case for that than Netflix is at like, say, the worst case that's gonna improve over time.
133
00:22:47.604 --> 00:22:56.904
I do think more people will cut the cord, but I think as those people cut the cord, I think they're gonna use a variety of free options or other streamers. I think we'll see some
134
00:22:57.964 --> 00:23:06.864
evolution as, like I know, uh, Zaslav, you had mentioned the HBO Max, he'd mentioned can we do like a big bundle with all the streamers at a lower price point.
135
00:23:07.844 --> 00:23:23.104
I, I th-see the logic for that, I just also see the incredible difficulty [chuckles] at convincing all these different studios to figure out who's worth what as they try and lower prices and, say, offer a year's subscription to people to get those prices lower.
136
00:23:23.194 --> 00:23:33.564
So I do think the economics are lower, and I think that, you know, for an individual TV show, I think the syndication window just won't be what it was. The second window licensing won't be what it was.
137
00:23:33.624 --> 00:23:43.504
The TVOD sales won't be there because people will churn in and out, so it's gonna be lower. The one bright side, 'cause I do wanna try and stay positive, especially [chuckles] like everything going on,
138
00:23:44.484 --> 00:23:49.004
I think the global opportunities will continue to be there in ways that they weren't before.
139
00:23:49.104 --> 00:24:03.024
I think that's actually what Netflix has really shown is that, you know, all the streamers in some cases, all the traditional studios in some cases had, say, some Latin American channels or they partnered with like European companies to sell their content.
140
00:24:03.824 --> 00:24:13.164
It really is with D2C, you really can go global with the content, with the caveat that you often need to make a lot of local content for all those new places.
141
00:24:13.684 --> 00:24:18.864
But I do think if the Hollywood studios can grab more of that global share, there will be some of that.
142
00:24:18.964 --> 00:24:29.076
But on individual market perspectives, like again in America I just, I don't think we'll see quite what we had, especially with the, say, maybe the revenues will equal the same.
143
00:24:29.256 --> 00:24:36.636
I don't think we'll see the same operating income or profit margins that we saw back in, say, the 20- 2000s or early 2010s.
144
00:24:38.996 --> 00:24:48.196
And one of the things, um, in the last couple months that's been in the news are these streamers actually removing content from their library. Uh, and it's kinda caught a lot of people,
145
00:24:49.316 --> 00:24:57.716
you know, outside of the kinda core industry off guard. What does the decision-making for that look like? Yeah.
146
00:24:57.776 --> 00:25:11.656
So this is one of those ones where, man, I wish I could be inside some of the streamers to hear some of those conversations in real life, um, because when I started in streaming, the idea that it's like, "We'll make a show and then pull it later" was, like, inconceivable.
147
00:25:11.896 --> 00:25:15.376
But having looked into it, I think there's a couple different pieces. First,
148
00:25:16.476 --> 00:25:30.576
um, the big one for a lot of the traditional studios is they're still looking for-- They're trying to get their profit margins under control, and the debt financing is just really not gonna be an option going forward.
149
00:25:30.776 --> 00:25:39.966
So if a show really, really, really underperforms, and you can essentially write off that value and take the tax losses, you can protect some of that revenue you have to send to the government.
150
00:25:40.256 --> 00:25:46.616
I think that's one of the biggest things, is getting those write-offs off the book so you can take the content and monetize it elsewhere.
151
00:25:47.196 --> 00:26:02.236
Related to that, I do think in the initial exuberance of the streaming wars, especially from the new entrants to catch up to Netflix, and honestly with the big tech firms, uh, with Netflix, is a lot of the deals just at their core probably weren't good deals in the first place.
152
00:26:02.856 --> 00:26:14.296
Um, again, if I'm right that the future TV ecosystem is smaller than the current TV ecosystem, then that means by definition the budgets have to come down or the amount of shows having made that.
153
00:26:14.356 --> 00:26:24.336
So in some cases, this is about deals that probably didn't make a lot of sense or weren't structured well enough that it gave the streamers flexibility for how to sell them in secondary markets.
154
00:26:24.766 --> 00:26:32.945
And then the last piece, even though it is very small, um, the streamers do pay residuals on a lot of content, um, or on streaming content.
155
00:26:33.036 --> 00:26:38.136
I know there's definitely been news stories that say the stre- that residuals are dead. This is not true for streaming.
156
00:26:38.556 --> 00:26:49.296
But the way it works for streaming, which again, like a lot of people don't know, is that it's one flat rate. So, um, and when you think about this, you can see why it would motivate some of these decisions.
157
00:26:49.716 --> 00:26:59.296
So Wednesday paid the same amount to its writers and actors in residuals that, um, The Rise of the Pink Ladies did, that just got removed from Paramount Plus.
158
00:27:00.176 --> 00:27:22.376
So when you consider that one of those shows was the biggest show on television or biggest Season One on television in 2022, and the other show just w- it never made any of the charts I tracked, that's why there's also this benefit that if you have to pay these recurring costs to keep content on the air, it might be cheaper to pull them off from a cash flow perspective, ignoring the sort of accounting pieces.
159
00:27:24.856 --> 00:27:29.296
Well, I guess, uh, two follow-ups to the point about the, the overall market being smaller.
160
00:27:29.336 --> 00:27:38.666
You know, one of the troubles -- I've been kinda working on a story about content spend and, uh, churn, and you're still looking at a lot of, like, you know, Morgan Stanley estimates and things like that, that are
161
00:27:39.616 --> 00:27:48.626
probably a little bit scaled back from where they were, but they're still- Mm-hmm... project growth into the future. Do you see content spend, one, being the same or smaller?
162
00:27:48.696 --> 00:28:04.876
It sounds like, um, my guess would be smaller. And if yes, is it a dramatic reduction in the number of shows or the spend per show? I do not have a strong take. I, I don't think it's gonna keep going up.
163
00:28:05.016 --> 00:28:21.236
Now, whether or not content spend as a total stays, goes down, I'm little-- I, I don't have a strong feeling on that, though I think we have seen across the board that it really does seem like a lot of people are trying to rightsize their content spend.
164
00:28:22.016 --> 00:28:32.396
Um, so I would definitely much more bank towards flat, which if you count inflation, is the same thing as making it smaller over time. I think both will be an option, though.
165
00:28:32.576 --> 00:28:41.115
To answer the second part of the question, what happens to the number of content? I think we've already seen budgets come down in certain cases. Um,
166
00:28:42.276 --> 00:28:51.816
l- for example, on the broadcast season, a lot of actors, they're g- having fewer actors per episode, smaller guarantees, doing smaller writer rooms, things like that.
167
00:28:52.216 --> 00:29:01.056
So I think they'll try and figure out ways to s- keep some of the content costs down. I think some of the reality TV shows will try and be squeezed too for sort of smaller budgets.
168
00:29:01.676 --> 00:29:06.416
Um, so I think we'll see a combination of both those things.
169
00:29:06.536 --> 00:29:17.536
I also think the other piece that's not really related to removals, but I think we might also see more examples where streamers are selling the same shows to other people, 'cause that's essentially a win-win.
170
00:29:17.566 --> 00:29:24.356
Another streamer gets a new show, and then the other streamer gets cash flow. So it's sort of more circular like that, so it's
171
00:29:25.276 --> 00:29:30.916
make-- providing different streamers new content, but not actually having to go out and pay full freight of a brand-new production.
172
00:29:34.496 --> 00:29:43.636
And with that, like, kinda last, um, business model question, are you a bull or bear on ad-supported streaming? I am a bull on it.
173
00:29:43.936 --> 00:29:55.315
Uh, especially with the free ad-supported streaming TV, um, I like, I call myself the entertainment strategy guy, so whenever possible, I try and come back to, like, the core strategy principles.
174
00:29:55.716 --> 00:30:00.916
And for me, like, my favorite chart is just a value creation model and ask, "How does this create value for the customers?"
175
00:30:01.716 --> 00:30:18.116
And with the free ad-supported streaming in particular, I think it really f- solves a customer need that the on-demand part of streaming really hasn't quite figured out, which is the idea that it's like, "I don't want to pick something heavy to watch right now.
176
00:30:18.636 --> 00:30:27.226
I just want something on in the background." And so it can be reruns of Friends or it can be, you know, or a, a movie midway through.
177
00:30:27.316 --> 00:30:40.892
Um, that's-- I know there's some residual implications for that, but- I've always thought that, for example, Disney+ misses a huge use case for why TNT and TBS and FX and USA Network have movies on all the time.
178
00:30:40.932 --> 00:30:49.292
It's not because you plan to start watching, like, "Avengers" from the beginning, but you see, "Okay, what scene is 'Avengers' on? Oh, I like this scene.
179
00:30:49.372 --> 00:30:55.652
I'm gonna, like, turn it on in the background, and I can go finish dishes," or something like that. So I'm a big believer in that.
180
00:30:55.812 --> 00:31:07.712
I also think, um, with the ad-supported streaming, in some cases it's just gonna lower cost, so it's gonna allow more customers to have different options for what to watch at the same price.
181
00:31:08.152 --> 00:31:28.742
The one caveat I have for the streamers doing it is the data I've seen is that the moment you put advertising on something, the customer value for that, again, back to the value creation model, really, really drops, and their willingness to pay goes way, way down when something is supported with ads than when it's, uh, you know, without ads entirely.
182
00:31:28.812 --> 00:31:36.411
Um, I just had a family member complaining to me about Netflix who d- doesn't even have an ad-supported, but he's like, "They're running trailers on things. I can't believe it."
183
00:31:36.472 --> 00:31:45.372
And it's like [chuckles] that's, like, the smallest thing you can do, and he's like, "What happened?" I'll admit, I, I have that with, uh... I, I know HBO Max it.
184
00:31:45.432 --> 00:31:53.792
I don't think I've seen it before, but HBO Max will run a trailer, and I'll be like, "What are you doing? Just go with the show." But old HBO used to do it all the time, but I think that is there.
185
00:31:53.972 --> 00:32:02.532
The-- But overall, I would still say I'm bullish with the idea that, uh, the monetization forecasts are probably what I'd be the most skeptical.
186
00:32:02.572 --> 00:32:11.242
I'm sure there's people who'd be like, "Oh, you know, take the line and draw it up to the moon," and I always tend to be skeptical of that. That's sorta, you know, I'm skeptical of every business model by nature.
187
00:32:13.972 --> 00:32:22.652
Yeah, our, our thesis is that they, you know, we look at the revenue per hour with that being the, the kind of most or all of, of their revenue from advertising,
188
00:32:23.632 --> 00:32:33.072
that they obviously have gotta create, um, more value in the ad unit unless they're gonna- Right... just recreate the kinda linear ad load.
189
00:32:34.012 --> 00:32:43.912
Um, and in, in order to do that they gotta kinda, you know, add your measurement and, you know, make it more impactful for the buyer, but also bring in more, more buyers.
190
00:32:43.932 --> 00:32:54.082
You know, there's only 250, you know, brands buy the do- the majority of national TV advertising, and there are, you know, probably a million video advertisers in the US, and, um, you know, really
191
00:32:55.472 --> 00:33:04.522
growing the demand side of the equation, that's, uh, an, uh, kind of a white space that we see in the market, uh, today. But, you know, it-- Do you think, kinda on a side note there,
192
00:33:05.572 --> 00:33:11.912
Fox, smart move by them only having a FAST and not having the other pieces, or is that, are they gonna fall behind because of that?
193
00:33:13.692 --> 00:33:34.232
I think it's a smart move for now because I think they're just really focused on the cash flow question, and I think, um, you know, one of my rules is not to bet against Rupert Murdoch because I think he actually has just done the thing where he buys -- Like everyone says, like, "Buy low and sell high," and I think he is one of the people [chuckles] who has lived that.
194
00:33:34.332 --> 00:33:38.381
As one of, uh, a person told me once, they said, "Rupert has a price for everything."
195
00:33:39.232 --> 00:33:50.812
And then he knows what he would sell everything at and he knows what he would buy everything at, and I think he judged that streaming was going up, sold at the right time, could come in and buy low while he's, like, building up this cash pile.
196
00:33:50.912 --> 00:34:03.462
So I think it's smart. That said, I think you identified the big key piece, um, because, you know, to go back to the traditional TV, right? While those 250 advertisers did buy the bulk of the advertising, right?
197
00:34:03.532 --> 00:34:12.432
Almost all local channels always did sell local ads to car dealerships, you know, uh, appliance shops, things like that. So there are definitely a lot of opportunities for that.
198
00:34:12.932 --> 00:34:20.692
I'd say I'm actually working on an article right now on AI, because, I mean, that subject's huge and how generative AI could impact everything.
199
00:34:21.232 --> 00:34:31.952
One of the pieces that I think would be interesting, I think, for the local people is can you make an ad that looks almost as good as nationally produced ads, but it's for local restaurants?
200
00:34:32.412 --> 00:34:45.752
And I think, uh, that could help solve one of those demand-- You're talking about the demand issue, but that could also help the supply, in that if the ad takes a company one day to make, it's way easier than having to go do a whole film shoot and pay someone something like that.
201
00:34:45.852 --> 00:34:52.732
But, um, I think the demand piece has to get solved, but I am still optimistic for it, uh, sort of the way you are.
202
00:34:54.252 --> 00:34:59.492
Yeah, they just gotta basically look at the ad unit now as not a spot running once everybody, but it's, you know,
203
00:35:00.412 --> 00:35:08.492
35,000 ad impressions and, you know, again, Facebook has just crushed this problem of figuring out how to get that ad impression in front of the person that finds it the most valuable. Right.
204
00:35:08.542 --> 00:35:14.352
[clears throat] And that could be location, that could be a direct consumer brand that's, you know, doesn't care where their customers come from.
205
00:35:14.392 --> 00:35:24.152
It could be still the, the national groups, but there's a demand part of this that, and when I talk to people that are-- come from the national ad side, they don't see, they don't think that way at all, right?
206
00:35:24.202 --> 00:35:34.582
'Cause they, they've been so successful at selling the one spot, the scarcity. [clears throat] But now, you know, you have an impressions, you could, you can sell this to anybody, right?
207
00:35:34.632 --> 00:35:44.242
Like it doesn't matter, and you, you really could onl- you know, you could figure it out. Like, you could just take 10% of your inventory, focus on that, let 90% go to, you know, the 250. Right.
208
00:35:44.272 --> 00:35:55.252
But I do think, and so, so I'm bullish on people that have not, like a Roku or, or a fast service that have not, aren't at the upfronts, like, you know, dominating that market today. Right.
209
00:35:56.432 --> 00:35:58.262
Yeah, I think that makes sense. Um,
210
00:35:59.312 --> 00:36:11.992
the one other hurdle, I think the connected TV market and basically anything digital, uh, 'cause I mentioned AI, I think, uh, fake views is the other big issue that I think has to get really handled.
211
00:36:12.052 --> 00:36:28.972
That, that's why when it comes to streaming ratings, I do tend to prefer any platform that has, uh, panels, 'cause I think it's a little more reliable than just tracking straight usage, because, you know, there are already stories about, you know, server farms out there, like, just trying to generate click-through on ads.
212
00:36:29.452 --> 00:36:35.532
So I think that is a big hurdle, but I think you have absolutely identified one of the opportunities.
213
00:36:35.572 --> 00:36:44.353
And again, that's what makes me why- I would say I'm bullish on ad-supported TV is because I think a lot of the traditional is gonna transition over.
214
00:36:44.424 --> 00:36:55.864
And to your point, you can do better targeting, better optimization for some of those ads for smaller people who would never have considered it before. All right, last question.
215
00:36:56.064 --> 00:37:09.824
What is one insight that you have that we're not talking about that we should? One insight that we're not talking about that we probably should. Um, I'll give you...
216
00:37:13.644 --> 00:37:21.964
Uh-huh. Okay. I probably should have had this prepared earlier, maybe cut some of this rambling. Um, okay, I'll restart.
217
00:37:22.024 --> 00:37:34.284
So the, one of the biggest pieces that, uh, continues to amaze me is that, you know, I write a lot about strategy, and so when we tend to think of strategy, I think most people tend to really look externally on strategy.
218
00:37:34.344 --> 00:37:41.684
So it's, um, you know, where is our product positioned against all the cust- what the customers want and what our competitors are doing.
219
00:37:41.764 --> 00:37:50.744
And very-- much fewer people look internally, um, at things, and I actually think one of the big revolutions is gonna be in how we work.
220
00:37:50.884 --> 00:38:01.084
I'm a pretty big believer in the books by Cal Newport, uh, Deep Work, Digital Minimalism, and so on. Uh, Wor- World Without Email would be the most applical- applicable to big organizations.
221
00:38:01.644 --> 00:38:20.204
And I think we're gonna see a big trend in the next 10 to 15 years where companies move away from managing most things in their inboxes, and I think most people listening are probably in their inbox right now, to project-based workflows, um, doing things, say, slower but at higher quality, managing less projects and things like that.
222
00:38:20.284 --> 00:38:25.764
So that's whenever anyone asks for me for a recommen- book recommendation, it's always Deep Work.
223
00:38:25.804 --> 00:38:36.444
But when it comes to an insight, it's, I think the way we're working is very much like when, um, factories were first electrified. This is an analogy Cal Newport makes.
224
00:38:36.984 --> 00:38:50.724
And it required rethinking how an entire factory floor was conceived, but that process took decades to actually realize that, you know, you had smaller motors, so you didn't have to have everything based around, like, a river turning a steam wheel.
225
00:38:51.264 --> 00:39:01.904
So that'll, I think, be one of the big changes in the next 10 years, and I don't think enough people are talking about it. All right, SG, I've loved this conversation. Where can our audi- audience find you?
226
00:39:02.944 --> 00:39:05.574
So I'm at entertainment.substack.com.
227
00:39:05.733 --> 00:39:17.024
That's my newsletter where you can get a weekly, uh, streaming gradings report, which is, uh, uses multiple data sources, uh, to provide a comprehensive look of what's working and what's not working in the streaming wars.
228
00:39:17.544 --> 00:39:31.944
I also publish regular strategy columns over there, um, as well. I publish, uh, every other week for theinkler.com, a strategy column as well. And I'm on all the, you know, social-- I'm on Twitter and LinkedIn as well.
229
00:39:31.984 --> 00:39:40.984
So if you wanna connect on LinkedIn, go ahead. I will post all in the show notes, but I'm, uh, grateful for your time, and this has been, been a blast. Yeah.
230
00:39:41.104 --> 00:39:51.864
I enjoyed talking to you, um, and I appreciate the invite on the podcast. [upbeat music] Thank you for joining us on this episode of Screen Wars. I hope you enjoyed the discussion.
231
00:39:52.084 --> 00:40:03.604
You can find out more about CrossScreen Media at crossscreenmedia.com. Please don't forget to sign up for our weekly newsletter, State of the Screens. You can find us on social media at CrossScreen Media.
232
00:40:03.624 --> 00:40:10.364
Join us next time for more insights and analysis straight from the experts. [upbeat music]
