This guide will help you understand what goes into a comprehensive and reliable LTV measure. Read our guide The Business Logic of LTV to understand why its so important to subscription companies.
LTV is a measure of how much profit you expect to make from any given customer in the future. It conceptually comprises of four key factors:
The first element that goes into an LTV calculation is the life expectancy of your customer. Each of your customers will stay with your service a different amount of time. Some, who are dissatisfied and exhibit account health risk factors, may churn this renewal period; others, who are healthy and happy, will go on to renew for many renewal periods to come.
In order for customer lifetime value to have real meaning, Zuora recommends you estimate churn rate individually for each of your customers based on their unique behaviors, demographics, pricing, packaging, billing, and payment histories. At Zuora, some of our most sophisticated customers have moved beyond simple predictions based on a few intuitive factors to sophisticated statistical models that predict individual account churn rates by modeling the top factors responsible for past churns.
Once you have established a churn rate for your customers, then you can estimate life expectancy according to the following formula:
Life Expectancy = 1 / Churn Rate
For example, a customer whose renewal period is annual with an estimated churn rate of 32% will have a life expectancy of 1 / 0.32 or approximately 3.1years. As you estimate life expectancy, you will want to express your life expectancy using a consistent time period that corresponds to your subscription renewal cycles. For example, if your business has contracts that renew annually, then your LTV calculation will estimate how many years you expect to keep each customer.
It goes without saying that how much value you think you will earn from your customer in future periods is largely dependent on the revenue you expect from your customers. To estimate this, you not only need to look at current bookings (or revenue under contract), but you also need to estimate how the revenue you get from your customers is expected to change over time. Do you expect your customer to buy an upsell, continue to pay the same amount, or downsell?
A good way to estimate future changes in current subscription revenue is to use your Net MRR Retention rate. Net MRR Retention is defined as the dollar amount of your renewals divided by the dollar amount up for renewal. It gives you an aggregate measure of upsells relative to downsells and churns across your entire customer base.
In an attempt to find better alternatives to using Net MRR Retention in the revenue expectancy element of LTV, Zuora is currently experimenting with a few new methods aimed at improving the state-of-the-art by attempting to estimate revenue expectancy individually, by customer. These methods attempt to go beyond using just standard Net MRR Retention to a more personalized estimation. The idea holds promise. For example, Apple Music offers three plans:
Inherent in this packaging structure are two predictable upgrade paths (Student to Individual, and Individual to Family). Modeling those upgrade paths into individualized estimates of upgrade or downgrade likelihood could prove quite effective at improving LTV accuracy beyond a wholesale average net retention factor.
The third element of lifetime value is estimating how much it costs you to deliver your product or service. Each of your subscription products has a particular contribution margin associated with it that needs to be estimated. Contribution margin represents the variable costs that go into providing your product and is a measure of the profitability of your subscription products. Some businesses leave out cost expectancy from LTV, but doing so leaves out an important element if you plan to make spending decisions based on LTV.
The final element of LTV is estimating how much risk your future revenue streams face. Risk expectancy is critically important because LTV is an estimate of what will happen in the future. Your estimates of the future can be conservative or aggressive. A common mistake that many make in calculating LTV is that they do not sufficiently account for future risks.
Zuora recommends you strive to underestimate LTV for customers err toward a conservative LTV. Why? Lets say you overestimate the average customer LTV at $2000 and it winds up being $1500. Lets say based on the $2000 number, you decided to spend $1750 to acquire a customer. Your overestimate would have cost you $250 per customer instead of earning you $250. When working with LTV, you always want to estimate for the worst case.
How should you estimate for the worst case? First, you first want to discount LTV with prevailing interest rates since a dollar in todays money will be less than a dollar in the future. Also, in addition to interest rate discounting, you need to factor in risk discounting. Wall Street investors offer a compelling model to follow when thinking about appropriate levels of risk discounting. On Wall Street, investments are always discounted by higher rates than just the interest rate. The additional percent discount is a risk adjustment commonly called the spread. The further out in the future cash is expected from a customer, the more that could go wrong. Additional risk could include changes in economic conditions, competitive landscape, and regulatory changes.
In essence, all reasons that future cash might not be paid by a customer gets rolled into the spread. Spread is roughly the percent change of catastrophic loss per payment period. For those with finance backgrounds, this is the very same concept as corporate bond spreads high-grade corporate bonds have spreads of 1-5% and low-grade corporate bonds (junk status) have spreads between 5-25%. Factoring all these risks together, Zuora recommends you use a conservative discount rate and we often work with our customers to determine the right number for their business.
For more, check out our guide The Best LTV Formula for Subscription Businesses