Truth be told, I started learning about the business in earnest only after getting a masters degree in business and engineering. It started with regularly digesting newsletters, blogs and podcasts from Ben Thompson, Horace Dediu, Tom Tunguz and others. It really started picking up momentum when I learned how to use Tech Twitter productively, and discovered folks like Tren Griffin, Josh Wolfe, Patrick O’Shaughnessy and others. I’m quite pleased that I have managed to situate myself within so many different information flows today (twitter, twitter DMs, newsletters, whatsapp groups), that I have a lot more content to go through than time!
Just take a look at my reading list right now:
(I find Pocket invaluable because I always find interesting stuff faster than I can consume it)
All of this to say that without using the Internet to enroll myself in a lifelong business school education, I would have never learned that you can’t really understand business strategy without understanding unit economics. My fascination with unit economics only started last year leading up to the Lyft and Uber IPOs. There were two extreme, diametrically opposed narratives at play – the techno-optimist one that high growth rates and large markets justify high burn rates and the more conventional one that questioned if these companies could ever turn EBITDA positive. The first one focused on revenues and the second on profits and meanwhile, tech twitter was inundated with superficial articles focused on how much money these companies were making or losing.
I started having a million questions about the notion of a ‘business making money’, something I hadn’t really thought about deeply before. I’d always figured that as long as a startup sold something for more than it bought that thing, and had a large enough market and enough cash to burn as it grew, it would end up successful. It turns out, figuring out whether a startup has a viable business model is a lot more complicated than that, and it starts with unit economics.
It also turns out that while there is a relatively straightforward and well-defined theoretical framework for understanding the unit economics of a business, doing so in practice is a lot harder. Getting the right data, even from public companies, can be problematic. Each company can also report the same underlying metrics differently, making benchmarking an issue.
In this post, I’ve briefly described the theoretical framework I’ve learned over the last year. My plan initially was very academic — I wanted to study the framework’s history and how it’s formulae were devised. But as I dug deeper, I realized that to really understand how unit economics make or break a business, you need to study actual businesses (obviously).
That’s why I plan on studying the unit economics of different types of subscription businesses in subsequent posts.
The Theory
Why do unit economics matter?
A business has bad unit economics if it’s selling a product or service for lower than it’s true cost — the proverbial ‘selling dollars for 90 cents’. As Fred Wilson points out:
“Where I come out on this issue, and always have, is that growth has to be responsible (positive unit economics on growth spend) and that the path to profitability needs to be well in sight. I would add to those two constraints that a management team ought to be able to get a business profitable in a pinch without killing the business, if necessary. Clearly these “rules” should not apply to very early stage companies. They become relevant and possible once a business has a growing customer base and revenue stream.”
What does positive unit economics on growth spend mean? Turns out, there are a number of variables that ultimately decide the true cost of product or service delivery. The best place to learn about unit economics on the Internet is Tren Griffin’s blog 25iq. In fact, to write this piece, I tried reading everything he’s said on the subject. I’ll probably be rereading it from time to time. It’s so information dense that you can read it from a different perspective each time and learn more.
In this post analyzing the economics of Amazon Prime, he points out that the unit economics of a business consists of the following factors:
- A customer acquisition cost (CAC)
- An average revenue per user (ARPU)
- A gross margin
- A customer lifetime (which is a function of customer retention/churn)
- A discount rate.
A business has viable unit economics if it has a positive customer lifetime value or LTV. In his now famous post on the dangers of mistaking LTV maximization as business strategy, Bill Gurley describes the following equation for calculating LTV:
The gross margin (sometimes also described as contribution margin) is the difference between the revenue contributed by a user in a certain time period and the cost to deliver the product or service to the user, and decides how much cash each user is periodically contributing to the business. The SAC or subscriber acquisition cost is the same as CAC or customer acquisition cost. ‘N’ here is the customer lifetime and WACC is the weighted average cost of capital, also generically referred to as the discount rate.
How can businesses control their unit economics?
The short answer is they can’t, at least not directly. It’s extremely important to separate the process of finding viable unit economics from the formula itself. Building a business around optimizing the formula is bound to blow up in your face because key input variables — revenue per user, customer lifetime and customer acquisition costs are interdependent, not independent. Trying to move one variable usually ends up moving another, and usually not in the direction you’d want. As Gurley points out in the same post:
“Some people wield the LTV model as if they were Yoda with a light saber; “Look at this amazing weapon I know how to use!” Unfortunately, it is not that amazing, it’s not that unique to understand, and it is not a weapon, it’s a tool. Companies need a sustainable competitive advantage that is independent of their variable marketing campaigns. You can’t win a fight with a measuring tape.”
Tren Griffin offers the following advice to startups specifically:
“If you’re an early stage SaaS startup, still trying to get product/market fit, or experimenting with different ways to make your marketing and sales predictably repeatable and scalable, it is useful to play around with CAC and LTV to get a feel for where you are. But it’s important to note that these formulae will only yield meaningful results when your sales and marketing process and costs are predictable and scalable. Instead of spending too much time obsessing over CAC and LTV, rather focus your energies on solving the problems of improving product/market fit, and making your customer acquisition repeatable, scalable and profitable.”
Churn and payback period
The payback period is the time it takes to recover CAC. Shorter payback periods are always better because they make it possible to use operating revenues to fund growth, allowing the business to preserve cash on the balance sheet. They also tend to have a flywheel effect where the more you spend the faster you grow because each incremental customer brings in more revenue that you can spend on growth. There’s one caveat though — it only makes sense to compare payback periods between businesses selling similar products or services. Larger transaction sizes result in larger CACs and longer payback cycles. Just because the payback period of a subscription streaming service is a lot smaller than that of an enterprise software product doesn’t mean it has better unit economics.
However, it’s really important that regardless of the type of business, the payback period is shorter than the LTV. If customers churn before they are able to pay back their acquisition costs, the business is in big trouble. It has what’s known as a ‘leaky bucket’ problem. In this scenario, continuing to invest in customer acquisition is actually detrimental to the company, since each new customer eventually sucks cash out of the business!
Subscription duration, retention and the value of optionality
Convincing customers to subscribe requires providing a product or service that is more valuable to them than the combined value of the next best alternative available and the optionality of not commiting to a monthly fee.
That’s why a lot of businesses offer a free trial, allow customers to cancel any time and rarely require a longer commitment than one month. The greater the perceived commitment, the more the business must spend on customer acquisition to convince the customer to subscribe.
Tren Griffin again puts it best:
“Why do some businesses sell subscriptions but allow a customer to cancel at any time? Because the longer the customer is asked to commit to the periodic relationship, the more financial incentive the customers must be given to do so or the more in sales and marketing will be required to acquire the gross customer addition. In other words, the longer the commitment and the higher the commitment in terms of dollars, the higher the customer acquisition cost (CAC) will be.”
In Practice
I’m going to test these concepts by examining the unit economics of a few well-known public subscription businesses in the consumer and B2B spaces. Luckily for me, a lot of people have done fantastic work dissecting their business models. What follows in subsquent posts is a mostly my commentary on their analysis. I’ll be starting off by looking at Peloton.
Dysposition 