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CLV Part I: Laying the Foundation



For operators, there's two primary ways to make more money:


  1. Grow the number of customers.

  2. Increase the value of those customers.


While certainly not easy to do, growing customers is an easy concept to grasp and track. Determining the value of your customers is a bit more nuanced. At the heart of it is a single, all-encompassing metric: customer lifetime value ("CLV"). 

CLV is often misunderstood or, like most buzzwords, known nominally. We are going to define and unpack CLV to drive towards a deep understanding. We’ll use this as a foundation to explore big decisions, like the below:


  • What's the right approach to pricing, plans (monthly vs. discounted annual), and tiers (free vs. paid and variations of paid)?

  • How do I build a budget and set goals for my product?

  • What's the right level of investment in growth for my product? When, if ever, should I start to build out a team?

  • What are the pros & cons of bundling my product with other operators / brands?

  • When, if ever, is the right time to leave platforms (i.e. Substack) and create an owned property?


Let's start with a high-level definition. We'll then explore the primary CLV drivers and their relationship with each other. Then, to drive it all home, we'll build a CLV model for a hypothetical product.


A brief aside before diving in. The majority of initial posts in CLV will focus on subscription products. There’s no doubt most creators will have wide distribution and more than one revenue stream. To introduce CLV, we'll focus on subscriptions first. Future posts will discuss how to add new products & revenue streams (which may be more transactional) to boost CLV.


Definition of Customer Lifetime Value


Customer lifetime value ("CLV") is the cumulative contribution profit earned during a customer's relationship with your product. I know, a mouthful - let's start to unpack it. The sections below are a high-level overview of CLV. As you will notice, rabbit holes abound, many of which we'll revisit in future posts.


Cumulative Contribution Profit (Not Revenue!)


Contribution profit is revenue minus the variable costs that increase alongside revenue growth. These costs can be easy to identify when they have a direct relationship with revenue growth. For example, Apple's 30% or Substack's 10% revenue share. Other costs can have a close, but not necessarily direct, relationship with revenue. 


Let's sidestep some of the complexity for now: the key here is to not look at revenue. We use contribution profit to make sure we're making money on a per-customer basis. If we're losing money on each customer, we're screwed. More volume of customers or improvements in retention lead to steeper losses. Negative per-user contribution profit can be a key ingredient to vicious cycles. Only using revenue is a common way to fool ourselves as this is happening.


That said, many start-ups or products in a hyper-growth phase will have a negative contribution profit. That can be okay, as long as there's a viable pathway towards positive per-user economics. In later posts, we'll explore how to approach a CLV analysis for products with a negative contribution profit. 


Even if we dodge the revenue mistake, there's another common mistake. We shouldn't mistake contribution profit for operating profit. We need to remove fixed costs to arrive at operating profit. Contribution profit helps us understand how much incremental cash each customer brings in, which we then use to pay off our fixed costs. In this way, contribution profit can help identify how many subs we need to break-even on fixed costs.


Customer Lifetime


"Customer lifetime" is an estimate of how many times a customer will buy your product during a period of time. For subscription products, we're guessing the average point when a customer will cancel. 


Usually, subscribers are most likely to cancel earlier in their subscription. And the likelihood of cancelling decreases rapidly the longer someone stays subscribed. In other words, the probability of a sub cancelling drops exponentially, not linearly, over time.



We can use these cancel rates to produce a customer decay curve. The curve shows the probability that someone remains subscribed at a given point. "Average customer lifetime", as a number, is shorthand for the shape of the customer decay curve. As we will see, the shape is far more important than the calculated number. We must obsess over elevating the curve, one of our best levers to drive growth and higher earnings.


The Dangers of CLV: It’s an Estimate and an Average


Because it's an “estimate”, it’s important to understand CLV is a projection, a prediction of the future. It’s not factual & shouldn't be considered scripture. When you model out CLV, know that it's future earnings, and far from accurate & guaranteed. This is why it's even more important to understand CLV as a concept, not so much to calculate CLV.


CLV is also a per-sub metric, not an aggregate-level metric. Because it is a summary of all your customers, it's an average metric. As we’ll walk through later, this is helpful with a few important high-level applications. But beyond that, we quickly dance into the danger of averages. CLV becomes most actionable and valuable as we segment our audience. 


Let’s turn our attention towards unpacking the key elements above into the core drivers of CLV. And perhaps most important of all, exploring the relationship between those core drivers.

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