This expanded piece originally appeared in the free Too Much TV newsletter. Subscribe at toomuchtv.substack.com.

In recent months, I have spent most of days having discussions about the differences between the old broadcast TV business model and the economics of streaming television, especially SVODs. I hear a lot of "tech bro" complaints from Hollywood veterans or arguments that tech industry executives don't "understand" how Hollywood works. And while that might be true to an extent, it's just as certain that most Hollywood industry types (especially those not on the studio side) don't much understand the vast differences between how the TV business determined value in the linear world vs. how it's figured in the digital world. 

I apologize in advance to some of you, because this is an extremely abbreviated explanation and I know I am glossing over many important things. But this is not a novella.

In the old broadcast and cable world, making money and determining value was complicated, but the general outlines are easy enough to be understood by most civilians. You produce some programming, and hopefully it draws enough viewers to allow the network to sell enough ads at a price where there's a profit. And yes, there was network branding that played into that as well as things such as carriage subscription fees once cable television rolled out. But because viewers could turn the channel whenever they wanted, the primary driver for any network was to get as many eyeballs at any one particular time as possible. That is how you made money.

SVODs have a business model that couldn't be more different. Because your viewers have to make the conscious decision to subscribe (and to keep subscribing), the economic factors that matter the most are the ones that revolve around the cost of finding the subscribers and keeping them happy enough to pay up every month. Simple viewing numbers don't provide much clarity on those two important metrics. So the focus is on something called "customer lifetime value."

You figure out your customer acquisition cost (CAC) - or what you have to spend for each person who subscribes - and measure that against the customer lifetime value and you have a pretty good metric to use to help determine how much you should be spending on everything from salaries and marketing to content production and overhead.

Simply put, the customer lifetime value is the total worth of each customer throughout the life of your relationship with them. That includes all sorts of data points, ranging from how long each subscriber is likely to stay before churning off, the price they're paying each month, etc. If you can accurately figure that out, you can compare the customer acquisition costs to the customer lifetime value and use that to help you predict a wide variety of future business decisions. 

It's not just whether or not you'll be profitable, but it helps you to make all sorts of related strategic decisions.  If accurate, it gives you a bird’s-eye view of your marketing expenses, efforts, campaigns, and strategies. You can use it to balance short and long-term financial goals. You can figure out which spending is bringing the best return and where to focus future efforts.

It can also help you identify high-value customers. In the case of SVODs, that means customers who are likely to stay subscribed for a long period of time. 

The related side of this is that you can also determine which decisions might help that overall customer lifetime value. Increasing that CLV at a rate lower than you are increasing spending is basically increasing your revenue stream and your profits.

When applied correctly, that CLV number can be used to help determine what content is most valuable to the bottom line. For instance, a show that draws in an above-average number of new subscribers (which lowers customer acquisition costs) would have more value to a streamer than another series that generates five times the views, but many fewer new subscribers. And as you can imagine, there are all sorts of variations of this equation.

Each streaming company has a different series of data points it tracks and none of the approaches seem to be compatible with each other. Streaming services can't even agree on what qualifies as a "view," much less come to a consensus on what CLV looks like in a streaming-forward world.

And the problem is exaberated at some of companies (Warner Bros. Discovery, I'm looking at you), when the decision is made to tweak the equations in order to justify business decisions you've already decided to make.

In the abstract, CLV is determined by this equation:

Customer Lifetime Value (CLV) = (ARPA × Gross Margin)÷ Churn Rate

In other words, you estimate the average revenue per account by the gross margin and divide by the estimated subscriber churn percentage each month. 

But while that formula sounds straight-forward enough, if you are wrong in any assumption, your bottom line can quickly go sideways.

Let's say that hypothetically you're a media company that has two subscription streaming services that are both somewhat complimentary but still competing with each other for subscribers. Company executives could decide to combine the two services and assign a series of values to the move that would end up lowering the customer acquisition costs while also lowering the churn rate. That would create a larger potential revenue stream and that company could spend extra money on content and marketing based on that estimated increase in revenue.

The problem is that if you spend the money before you learn whether or not your decision to combine the services resulted in the increases you anticipated, you are somewhat screwed if it turns out your strategy was wildly optimistic. You've now spent money on programming your business model can't support right now. And now you have to figure out how to "right-size" your bottom line.

This is just one very simplified example. But it also helps explain some of the business decisions you are seeing now in the streaming video business. Yes, the streaming business will never deliver the gross margins of the traditional linear TV business at its peak. But the economic problems are not the result of smaller gross margins. Instead, they are mostly caused by executives making strategic decisions that turned out to be not the wisest moves they could have made.

Netflix apparently tries to account for the tendency to prejudge data by expanding the measurement of customer lifetime value into a larger basket of data points.

A primary Netflix metric is called the "adjusted view share," which is a combination of more than 30 factors that attempt to assign an overall "value" for any piece of content. It's still a measurement of customer lifetime value, but done by using a very wide lens on customer behavior.

An example I was given was that it's possible to track which content was most watched by brand new subscribers last month. That content would be considered more valuable because it presumably was one of the reasons why viewers subscribed. But if those viewers exit after a month or two, that lessens the value of the content. The assumption being that some percentage of the canceled subscriptions came from people who subscribed primarily for a specific show.

It also depends on where people are watching. A show that is more popular in a region such as the U.S., where the ARPU (average revenue per user) is higher has a greater value than one that tracks more in regions where the ARPU is lower. Although that indicator is weighted less than some others and whether the content is attracting subscribers in a territory where subscriber retention costs are high also factors into the equation. Netflix also tracks how many people complete a TV show within a week, the percentage of people who re-watch a series (although if the number is too high, it's discounted as possible fan manipulation). And there are many more. Each of the factors is weighted differently and the weighting can apparently change as the company's strategy evolves.

This is why I try and counsel writers, actors, directors and other creatives to not become laser-focused on raw viewing numbers. Yes, they are an indicator of possible success. But the bottom line in streaming is much more complicated than simply measuring eyeballs.

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