Category: Explained!

Don’t Cross the Streams: Streaming Video Metrics…Explained!!!

A few months ago I briefly tried to explain the distinction between “customers” and “views” to help explain why Twitch is often over-hyped. Since I’ve spent a lot of the last two weeks banging my head against the Twitter wall insisting that we stop letting Netflix use misleading data, it seems time to break out that explanation into its own post.

To see the need for this, let’s look at a handful of recent Netflix announcements. They provide a case study for how a service can use multiple metrics that all kind of mean the same thing but all don’t. Worse, a lot of the journalism covering these reports mix up the different words. In 2018, at some point, Netflix has said…

80 million customer accounts watched a type of movie.

Customers watched 20 million streams of a single movie.

80 million customers watched a type of movie 300 million times.

In one day, Netflix had a total of 35 million hours viewed.

In those four datecdotes, we have, really, three different concepts: streams, hours and customers. The key is understanding how they all interact so we don’t use them haphazardly or misleadingly. If this explanation comes across as obvious, well apologies in advance. But as I think about it, I didn’t know it before I worked at a streaming video company, did I? Nope, and I spent a lot to time explaining to senior leadership what our numbers did and didn’t mean. 

So let’s get started at the smallest level. 

The Starting Point: An entry in a database

To understand where all the streaming numbers come from, you first have to understand that every data point for a streaming video company comes from somewhere. That somewhere is a single entry in a database. 

Yeah, it seems obvious, but worth mentioning. There is a database that holds the record of every customer’s every interaction with Netflix, Hulu, Amazon, CBS All-Access, Showtime, DC Universe and Youtube. And any new streaming service down the road. That’s where all the data comes from. A massive database that tracks every interaction.

The key is that lowest level, “the interaction”. The specific details around the record will differ by company and for different reasons. But the general broad strokes are the same. These interactions are then complied and collated and analyzed to develop all the other advanced metrics.

A Sample Entry Explained

The best way to visualize an interaction is to see a sample. So let’s see what a sample database entry looks like. This way you can understand the specific pieces of knowledge the companies can track. It starts with the “Five W’s” (who, what, when, where) and builds out from there. (The “why” is the key to good decision-making, and simple statistics can’t tell you that.)

Streaming Entry

An entry is generated when you—the user—clicks on a show or movie to watch on a streaming platform. That something can be a movie, TV show, trailer, commercial or whatever. Or piece of music for a streaming service. But the click via mouse click, remote control tap, voice command or finger tap starts the process.

Let’s just go through each piece. Start with the “who”. Every customer is tracked by some sort of customer ID number. This means that it tracks everything related to one account. I called this a “customer”, but you could call it users or customer accounts. Notably, it could be different than a “profile”, which Netflix has. (And if you have a “kids” section, then you are subject to COPPA regulations, and shouldn’t track identifying data, a different issue.)

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Disney-Lucasfilm Deal – Appendix: Feature Film Finances Explained!

(This is an “Appendix article” to a multi-part series answering the question: “How Much Money Did Disney Make on the Lucasfilm deal?” Previous sections are here:

Part I: Introduction & “The Time Value of Money Explained”
Appendix: Feature Film Finances Explained!
Part II: Star Wars Movie Revenue So Far
Part III: The Economics of Blockbusters
Part IV: Movie Revenue – Modeling the Scenarios
Part V: The Analysis! Implications, Takeaways and Cautions about Projected Revenue
Part VI: The Television!
Part VII: Licensing (Merchandise, Like Toys, Books, Comics, Video Games and Stuff)
Part VIII: The Theme Parks Make The Rest of the Money)

So after a planned family vacation and an unplanned family emergency, I’m back with my series estimating how much money Disney has made on the Lucasfilm acquisition. The next place to go is movies. How much will Disney make on the new Star Wars films?

Well…

Listen, I was all set to dive into the economics of Star Wars movies. Then I realized some readers may not know how movie accounting really works (or doesn’t work?). Before I can get into the specifics of these films, I feel like I should explain all feature film economics.

Can I explain it all? Given that some professionals spend their lives working on this and books have been written on it and courses taught on it, no. What I think I can do—what I will try to do—is provide enough of a summary right now that you’ll know how I calculated the movie returns, and you’ll have an idea for how this works.

I also decided that this isn’t really “Part II” of my series. If I were writing a report on this, I’d put this section in the Appendix. You don’t have to know it to get to the conclusion, but you may want to read it. And if you don’t know it, you’d want to read it before Part II. So here is is: my explanation for how film economics works and my confidence in various pieces.

A Brief Movie Windowing Model
A movies’ finances breaks down into four rough areas: costs, revenues, studio fees and back end. They appear (either going out or coming in) in roughly that order, which is also important. (As I wrote in Part I about the time value of money, you can skip ahead if you know this, but you may still enjoy it.)

A note before I start. I call this a “windowing” model, but I’ve heard it called all sorts of things. If you make it before the film is released, then you’d call it a “greenlight” model. It’s called that because you forecast all the numbers to give a movie the “greenlight” to release. It’s called a windowing model because each phase comes in successive windows. Otherwise it could be called an accounting statement for purposes of talent.

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How much money will Disney make (or lose) on the Lucasfilm deal? Part I

(This is Part I of a multi-part series answering the question: “How Much Money Did Disney Make on the Lucasfilm deal?” Previous sections are here:

Part I: Introduction & “The Time Value of Money Explained”
Appendix: Feature Film Finances Explained!
Part II: Star Wars Movie Revenue So Far
Part III: The Economics of Blockbusters
Part IV: Movie Revenue – Modeling the Scenarios
Part V: The Analysis! Implications, Takeaways and Cautions about Projected Revenue
Part VI: The Television!
Part VII: Licensing (Merchandise, Like Toys, Books, Comics, Video Games and Stuff)
Part VIII: The Theme Parks Make The Rest of the Money)

Let me take you into the mind of a business school student. While in school, you’re taught to be super critical of any business presented to you in the form of a Harvard case study. Even if things look super rosy, there are some bad numbers hidden in the appendix you need to find.

At the same time, you’re taught to be super positive for any business that is doing well on the stock market at the moment. You don’t have appendices to go searching through to find flaws. It’s a weird dichotomy of simultaneous criticism and optimism.

The company that was flying high when I was at business school—and has been a darling of Harvard case studies since the 1990s—was The Walt Disney Company. During my first year as an MBA student, Disney acquired Lucasfilm, the maker of Star Wars and Indiana Jones (if somehow you didn’t know that). I was so enthused by the deal that I used it as my topic for our speech class. To call me “enthusiastic” would undersell my opinion: I thought it was a guaranteed home run.

So when I came up with my first “analysis” article for this website: “How Much Money Has Disney Made on the Lucasfilm deal?” I remembered I’d already tried to answer that question. In that presentation above.

So I pulled out the presentation. I searched for my numbers to see what I said. I only found one slide with any numbers on it. I laid out the challenge for The Walt Disney Company: to make a good return on its investment, Disney would need to earn nearly $550 million per year to make up its money.

Slide1

That’s a huge number. So did my speech predict how much money Disney would eventually make on the deal?

Nope.

If I could make one change to the entertainment business press—and I’d make a few—it would probably be to enforce this rule: You don’t have a strategy if you don’t have any numbers. Looking back on that presentation in speech class, I didn’t obey my own rule! My presentation didn’t have any numbers. Well that’s not quite true, I had some tables showing that Disney does well at the box office and international growth is important, but I didn’t project how much money I thought Disney would make or lose by that deal. I just said I loved it and listed some general strategic points.

That’s what most of us do day in and day out in business, and I want to change that.

Strategy is numbers, and today I want to look back at that deal. It feels like a good time to update our thoughts on the Lucasfilm acquisition. While the last film was a box office smash (the number one movie in 2017), it had the worst customer feedback since The Phantom Menace. Worse, Solo had a troubled production, worrying fans on the Twitter/Reddit. And when Disney announced a new trilogy with Benioff and Weiss, it was met with a giant “Eh” and articles worrying about “saturation”.

Today, as a business analyst who loves Disney’s model and a Star Wars fan who loves the franchise, I want to combine these two things and answer a question I haven’t seen anywhere else: How much money will Disney make on the Lucasfilm deal?

Blink and Gut Analysis
When I write an “analysis” article, I’m going to try out an approach different from most other analysts. I laid out my rationale here, but to summarize, too often when we think about complex questions (like the one I laid out above) we don’t clearly own up to our initial reactions and gut thinking, even though that inevitably informs our final analysis. To combat that, I’m putting my “blink” and “gut” reactions right up front, then seeing how they change as I run the numbers. Read More