CLV Series Part I: The Unexamined Life is Not Worth Living

Published in
5 min readDec 20, 2021


Photo by Austin Distel on Unsplash

By: David Smith

At TheVentureCity, we coach the startups we work with to take a data-driven approach to formulating business strategy whenever possible. This means we analyze user event logs, customer transactions, and marketing attribution data looking for patterns. Then we take what those patterns tell us to develop ideas for growing the business: product features, marketing campaigns, and other initiatives to test with the customer base.An important tool in our toolkit is Customer Lifetime Value, or “CLV.” Hewing to the Socrates quote in this post’s title, we strive to examine all of our customers’ lives. This post is the first of a series of posts designed to walk startup founders through how we think about CLV, how we calculate it, and then how to use it for the benefit of their businesses.


Customer — To simplify this discussion, we are defining a customer as someone who spends money with our business. In situations in which customers do not spend money with our company, we can consider a customer someone who does a valuable action in the product, such as posting a photo, taking a course, sharing a link, etc.

Lifetime — Customers are “born,” transact with our business for some period of time, and then “die.” Lifetime is thus a measure of the length of time between birth and death. For active customers, the time of death is at some unknowable point in the future, meaning forecasting and prediction are inherently part of calculating the length of an active customer’s lifetime and, thus, lifetime value. It is also important to note that sometimes you can observe when a customer “dies” — like when they cancel their subscription. In other situations, there’s no way to observe a definitive “death.” In fact, we may never be absolutely sure that the customer is never coming back. We will look at how to handle such situations.

Value — Since we’re talking about customers who are spending money with our business, the dollars (or pesos, reais, euros, pounds, etc.) that those transactions bring to the business is the contribution margin: revenues less variable costs. The illustrations below will help clarify this definition.

Calculating CLV: A Visual Walk-Through

In this sequence, we are charting a single customer as she spends business with our company over time. The plot below shows her cumulative money spent (revenue) with us at each time period (such as a quarter). In her first time period, Period 0, she spent $80. Then in Period 1, she spent another $80 to drive the cumulative sum up to $160. That process has continued at different periodic spending amounts through Period 4, where the total has reached $280.

A customer’s value is not from gross revenue, but instead from the money that flows into the company net of variable costs. Below is what this customer’s curve looks like once we subtract variable costs.

Next comes a prediction about what the customer will spend in the future. There are various ways to think about calculating this prediction, from simple linear extrapolation to Bayesian probabilistic models to machine learning predictions. In future posts in this series, we will go into some of the more popular methods.

Since we are projecting future cash flows, the concept of “time value of money” tells us to apply some discount rate so we can express CLV in today’s dollars.

CLV is defined as the dollar value where the curve flattens out. The effect of the discount rate pulls all such curves to a horizontal shape eventually.

The CLV can be broken out into its components. Historical Customer Value is what we have already empirically observed. Residual Customer Value (RCV) is the amount that we expect to receive in the future (again, expressed in today’s dollars). For decision making about existing customers, we want to use RCV because it represents our expectations of the future. For future customers, yet to be acquired, the entire CLV is a prediction. In other words, CLV = RCV.

When trying to predict the future, it is often helpful to calculate a 95% confidence interval to quantify the range of possible future scenarios. Below is what our confidence interval might look like.

This Series of Blog Posts

From the building blocks described above, we can use CLV as the basis for defining business strategy. This post kicks off a series of blog posts that will take readers through how to think in a customer centric way about building value in your startup business. Here are links to the other installments in this series:




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