GoT vs LoTR vs Narnia – Appendix: Subscription Video Economics… Explained! Part 1)

(This is an “Appendix” to a multi-part series answering the question: “Who will win the battle to make the next Game of Thrones?” Previous articles are here:

Part I: The Introduction and POCD Framework
Appendix: Licensed, Co-Productions and Wholly-Owned Television Shows…Explained!
Appendix: TV Series Business Models…Explained! Part 1
Appendix: TV Series Business Models…Explained Part 2)

Consider my current relationship with HBO’s Sunday night programming. Right now, I record two plus hours of content to watch during the week: first, Game of Thrones, then Barry and finally Last Week Tonight with John Oliver. Then, for the rest of the week, I don’t record any other HBO shows, but will watch the occasional blockbuster I didn’t see in theaters. (In full disclosure, that included The Meg and Skyscraper. Don’t judge me.) Oh, and on Saturday mornings, we often watch Sesame Street. To access this content, I pay $15 a month to my cable company. 

So the fun question is…

…if I were HBO, how much credit do I give each series?

This is not a trivial question or easily answered. Sure it seems simple—the highest rated shows are the most valuable—but quantifying that value is the tricky part. In fact, this requires teams of finance folks and economists and statisticians running “big data” analysis. Literally measuring millions of customer accounts engaging with billions of pieces of content across potentially hundreds of categorical variables. (Unless, of course, you don’t have streaming data, in which case HBO doesn’t actually know what shows I watch, because I’m DVRing them for later.)

The current HBO lineup is a good illustration of how personal motivations can be obscured over the millions of people watching HBO. I’d definitely subscribe to HBO only for Game of Thrones, but would I subscribe to keep watching John Oliver when GoT goes on hiatus? What about Barry? Is it enough to make me stayed subscribed? Probably not on its own. Of course I will wait for Silicon Valley and Westworld and maybe Watchmen and/or His Dark Materials…so…I mean I don’t have an answer for you.

Multiply my anecdote by millions of individuals—all with different profiles and behaviors, and you see the challenge facing both cable channels and streaming networks. Throw in the fact that I’ve now been a loyal subscriber for 5+ years, and it can be hard nee impossible to determine which, if any, specific show kept me on board versus built up brand loyalty and/or inertia

Yet, this question will be crucial to our three streamers to determine the winner in this future-of-TV-series I’m calling “The battle for the next Game of Thrones”. The goal for these three series is to bring in and retain new customers to help win the streaming wars. Since strategy is numbers, I need to quantify those subscribers.

That’s the goal of today’s article. Streaming video economics. With my usual caveat that this is a subject that we could write books on. (Though, it’s obscure enough that there aren’t actually a lot of books on it.) My plan is to…

…Explain a brief history of content libraries and why this is a contemporary problem.
…Briefly remind everyone that for decades TV and movie studios tried to value libraries poorly on purpose.
…Then, I’ll debunk three bad ways to do this. 

Tomorrow, I’ll show my way, but mainly to describe the incredible amount of assumptions I’ll need to make to pull it off. And guess what? I’ll dig into a valuation of a current TV series. Or better said, a just ended TV series.

The Growing Importance of Valuing Content Libraries

When I built my TV production model, I debated making bespoke models for the four main types of TV, broadcast, cable, premium and streaming video. Ultimately, though, I realized that I didn’t have to because among those four business models, there are really just two types of revenue, advertising and subscription, and each model is just on a spectrum for how much they rely on each: 

Spectrum Ad vs SubscriptionThat’s a fun table and way to look at it because over time, we’re moving more and more to streaming. But as we move there, we also see that the ability to determine which piece of content is the most valuable went from “easy and/or not necessary” to “much harder and/or crucial to growing subscribers”. Let’s describe that in the various phases.

Phase 1: Broadcast starts with all Advertising

At the dawn of TV, life was simple. All broadcasters had to do was look at ratings. The higher the ratings, the more money made from advertisers. The math here is pretty simple for networks: keep the highest rated TV shows. And since Nielsen kept a scorecard for everyone, they didn’t even need to do this math themselves. 

Phase 2: Cable starts collecting retransmission fees

This was really the first time that channels needed to start considering TV series as more than just advertising revenue drivers. As cable expanded, the channels insisted on fees per subscribers. Eventually these fees—the per subscriber fee a cable company paid each channel to air its content—surpassed advertising for cable channels as the largest source of income. 

The best example that comes to my mind was the dual Mad Men/Breaking Bad success of AMC, followed by The Walking Dead. Those three shows allowed AMC to drastically increase their retransmission fees, and it wasn’t all related to viewership/ratings. Mad Men was never a monster in ratings, but its fans were diehards and it was critically acclaimed, so it was of outsized importance to AMC. They used this to negotiate higher retrains fees. Since individual customers don’t pay retransmission fees, you still, as a cable company, didn’t need to value individual shows precisely, though. Just general feelings fit in, and still most cable companies ended up buckling in retrains battles.

Phase 3: Premium cable doesn’t have any advertising, so libraries are a bit more important

Really, HBO was the first subscription TV company. For years, it justified its extra cost by being exactly what its name portends, the “home box office”. The home for theatrical movies before broadcast and cable. With no commercials.

Then, it bolstered this with The Sopranos and Sex and The City. They weren’t the first series on HBO, but the ones that put them on the map. Really, this is the first time a platform had to grapple with how to value their TV series versus the rest of their content. But HBO didn’t really have the data to do this. It didn’t know if someone who watched The Sopranos was the same subscriber as someone who watched their movies.

It also didn’t really matter, because HBO wasn’t selling the subscriptions in the first place. The cable companies were, so it just needed to give off the imprimatur of value and keep people subscribing. Which it did. To guide its behavior, it could also keep using ratings data in general as guides to what is profitable and what isn’t.

Phase 4: Streaming means direct-to-consumer, which means valuing content libraries

The rise of streaming meant that most of those old limitations on valuing a library were gone. First, the “direct to consumer” aspect means that the streamers know who is buying and when. There is no intermediary. Second, the streamers had all the data themselves. No longer did they have to wonder if new subscribers watched a series; they can answer it directly themselves. (Unless, of course, Amazon or another vMVPD doesn’t provide that type of granular data. Think about that streamers.)

But it all gets even more complicated when you consider that the streamers also have WAY more content than ever before. When SVODs have tens of thousands of shows and movies, how do they figure out what matters for customers? It’s not like customers are time shifting from DVRied content, now they can search through tens of thousands of movies and TV show episodes to watch, whenever they want. In other words, the amount of series that could be “responsible” for a new customer went from the dozens on the air to thousands.

One Note: Studios Tried to Value Libraries Improperly In the Past

It’s worth noting that the ability to value content libraries was, in some ways, a skill movie studios didn’t want to learn.  A classic example of “Hollywood accounting” was for studios to deliberately misvalue their content libraries. By underselling these values, they could avoid paying profit to talent. If the talent and/or agents knew they knew how valuable movies and TV shows were, they could subpoena that data for lawsuits.

Here’s how that applies to libraries. Say you sell your entire film library to a TV network or premium cable channel for a limited number of runs. If you value each title individually, you have to pay a lot more to talent if a film has broken even already. Instead, the film studios pretended they valued each film equally. The obvious counter is that this makes no sense since box office is a pretty good guide to what was popular and hence valuable. The result was often a total price on an overall deal, with each side valuing the pieces separately, and usually the studio would still undersell the value of their library content.

Three Bad Ways to Value Streaming Content Libraries

The trouble with this history is really for us, the journalists. Since we don’t have teams of statisticians—or even the data itself—we often have to rely on “back of the envelope” math to value these huge swings by Amazon and Netflix and HBO. 

While you won’t find a bigger “back of the envelope” guy than me, the problem I repeatedly run into is that streaming back of the envelope math often features a basic accounting error. Because of this, commentators routinely overestimate the value of individual shows to streaming networks. (And yeah, this is mainly aimed at Netflix and Amazon datecdotes.)

(And if you’re an eagle-eyed reader, you’ve read a version of this before by me. When I took on the challenge to explain why Disney would keep releasing Star Wars films—and by extension Marvel/big animated films—in theaters. There’s been a change to the “sub-optimal method 3” because for this estimate, it actually is the best model for this future gazing series.)

Sub-optimal Way 1 – Multiply Customers per Series by Price Per Month

The math on this goes like this: if Prime Membership costs about $12 a month and 100 million people watch Amazon Prime/Studio/Video’s Lord of the Rings series, then Amazon just made a billion dollars. Success! Here’s that math for Amazon with Game of Thrones’ current season for comparison:

Suboptimal 1

There are a bunch of problems with this method, starting with the $12. Unfortunately, there are costs to acquiring customers so $12 every month (or $120 a year) isn’t really $12. Distributors or marketing partners often pay bounties for new customers. But more than anything, it implies that those 100 million customers didn’t watch anything else on the platform during the month, which is obviously wrong. (Or it should be, if you’re programming your platform right!) Even this, though, undercounts the “lifetime value” of new customers. You don’t subscribe to any service for just one month, but several or multiple years, in Amazon Prime’s case. 

Sub-optimal Way 2 – Multiply Customers per Series by Lifetime Value

So why not just multiply by lifetime value? As I showed with Star Wars, this can result in astronomical valuations for series. Take Amazon. Everyone knows they actually charge $120 a year for Prime. So if you just multiply the hypothetical 100 million future LoTR viewers—which is a number I heard on a podcast once and isn’t unreasonable for a huge series like this—well the results are incredible. By spending a billion dollars, Amazon can make $12 billion.

Suboptimal 2

Of course, the math problem is easy to see with this annual total. Say Jack Ryan nets 40 million Prime Customers. The Grand Tour nets 20 million more. Marvelous Miss Maisel gets another 12 million. And the NFL gets 14 million…

Suboptimal 2 example

Well, now I’m at 180 million Prime Subscribers worldwide…

…which is more subscribers than Prime has worldwide. Hmm. By about 86 million. And look, that number is enormous at $22 billion. If we assume the lifetime value is actually 2 years, well than Amazon had made $44 billion on Prime Video. But they haven’t. Nowhere close. And this type of quick analysis ignores that if you suddenly stopped releasing new content, the lifetime value would shrink.

But the more common problem is double counting. This is the challenge with using CLV —customer lifetime value—in general. A “lifetime” is the value for that customers, um, “lifetime”. So if you count them once, well you can’t count them again. That’s a simple accounting principle: don’t count things twice. And again, this math implies every piece of content is worthless except for our most valued piece of content, which clearly makes no sense. If you want to use CLV, you need to keep the attributed customers really, really small lest you double count constantly and way over-inflate your value.

Sub-Optimal Way 3 – Attribute All Value Equally By Hours Watched

I really wanted to provide three sub-optimal ways to value content, to hit the rule of three, but then I took my sub-optimal method 3 from before and made it my optimal way for currently airing series. (Really, whether a method is good or bad can be all about context.) So I cast my mind back to some of the ways I have seen content valued, and the “attributing value equally” method leapt to mind. This is a method companies may be tempted to use, but we as journalists can’t.

To use my example from above for HBO, basically, HBO would say—if it knew exactly what my family watched—that Game of Thrones gets 40% of my value, Barry gets 20%, John Oliver gets 20% and Sesame Street gets 20%. You could attribute this by customer or by hours watched, but the point is to basically assign all value equally to viewership. With general ratings, this is sort of how some journalists approach the problem. Distribute all ratings equally.

The problem with this is that hours do necessarily equal value. GoT proves this. Yeah, I only watched 6 hours of it, but it is my favorite thing on HBO by far. Sure, I watched Deadpool 2 for six hours too…but only one of those two pieces of content will keep me hooked on HBO. I’ll admit, this type of analysis is useful on a bulk level, but it still doesn’t get us quite to where we need to go.

Some Other Bad Ways to Value Content

Once you start tying detailed viewing behavior to viewership, you can come up with all sorts of new ways to try to value content, many of them bad. Here’s another great (as in bad) way: price equals value. In general, this is true. Especially in competitive markets. But for a content company, it basically means you keep your own scorecard. The more you pay for a TV show—like the exorbitant Lord of the Rings costs—by definition, the more valuable it is. So price is related to value, but clearly isn’t its value. (And this doesn’t help you with licensed content either for how much you should pay.)

Related to this is the “trust in [Company X]” approach. It goes, “Well if they paid for it and they’re doing well, they must know what they are doing.” Honestly, I shouldn’t have to say anything more to debunk that. But I see this too. All the time. “Well, if Netflix paid 2x market rates, they must have a plan.” Don’t do that.

So far, I feel like Mr. Negativity. Don’t do this. Don’t do that. It all fails! To quote TV pitchmen, there has to be a better way! And I’ll give my take on Wednesday.

  1. […] Part I: The Introduction and POCD Framework Appendix: Licensed, Co-Productions and Wholly-Owned Television Shows…Explained! Appendix: TV Series Business Models…Explained! Part 1 Appendix: TV Series Business Models…Explained Part 2 Appendix: Subscription Video Economics…Explained Part 1) […]

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  2. […] Part I: The Introduction and POCD Framework Appendix: Licensed, Co-Productions and Wholly-Owned Television Shows…Explained! Appendix: TV Series Business Models…Explained! Part 1 Appendix: TV Series Business Models…Explained Part 2 Appendix: Subscription Video Economics…Explained Part 1) […]

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  3. […] Part I: The Introduction and POCD Framework Appendix: Licensed, Co-Productions and Wholly-Owned Television Shows…Explained! Appendix: TV Series Business Models…Explained! Part 1 Appendix: TV Series Business Models…Explained Part 2 Appendix: Subscription Video Economics…Explained Part 1) […]

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  4. […] true value of a TV show. It’s so “sub-optimal” that in my articles on subscription revenue, it didn’t even get its own “not-explanation”. I just dismissed using costs as a stand-in for value. Here’s this demonstrated for Game of […]

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  5. […] is where I wish I could link to my article explaining how to value content libraries (versus series, which I did here), and my take on which service has the most valuable content library. But, um, I haven’t written […]

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