This is the fifth article in a series on novel ideas for SaaS metrics, which started with The unprofitable SaaS business model trap, COC: a new metric for cancellations, The mistake of 1/c in LTV, and SSEBITDA: Steady-state profit metric.
Metrics summarize tons of processes, causes, and effects into a single number. It’s a two-edged sword.
It’s powerful because it lets you reason about complex systems, especially how it’s changing. It helps you focus on what’s important at a macro level.
But it’s dangerous when it combines so many disparate and disjoint processes and systems that the number loses precision. Because then you think you understand something that you don’t. That’s how bad decisions are made with confidence.
I argue that for many SaaS businesses, the incorrectness of the LTV metric outweighs the value it supposedly confers.
(LTV is defined here if this is greek to you.)
Using LTV in a business decision — like how much we can spend to acquire a new customer — implies that the lifetime gross revenue from a customer is know-able today. Clearly, though, it isn’t.
Every component of LTV changes over time:
- MRR — changes due to how systematic you are at upgrades, your ability to cross-sell, growing/shrinking the install base inside one customer, per-use charges.
- GPM — efficiency of the service, which for small companies can change by 30% in a year and even large stable companies can move by 1% per year.
- Cancellation Rate — hopefully shrinking as the company improves the product and service to address the causes of cancellation, but over a timeframe of years, this can change dramatically with advent of new competitors, shrinking market, different technology, or mixing different customer demographics as you grow into adjacent markets.
If cancellations are under control, then LTV will necessarily be computed assuming 4-6 years of future revenue. But in the timescale of “years,” we know for a fact that all the components of LTV will change! You don’t know how quickly, or when, or by how much.
For example, Hubspot famously had a low LTV, but increased in 3x in 18 months. (Documented in this great SaaS metrics overview by David Skok.) That’s a big swing in a metric that’s supposed to be able to “see four years into the future.”
Three variables, all changing, unpredictably, which you multiply together and…. you expect the result to mean something?
When you believe a number means something solid, when in fact it doesn’t, you make poor decisions. So for example when you read “An LTV:CAC ratio of 3:1 is healthy,” if your LTV metric can’t be trusted, neither can that formula. Your might believe you’re being efficient in acquiring customers, only to find that your SaaS company isn’t profitable even at scale.
What should you do instead?
I don’t think there’s anything LTV is used for that you can’t use other metrics to do just as intelligently, but without the incorrect assumptions.
For example, LTV is often employed to answer the question: “What’s a reasonable CAC?” The typical answer is “LTV/CAC should be at least 3 for healthy companies, and 5 is very good.”
It turns out you can compute the same ratio using GPM and COC (Cost of Cancellations), neither of which pretend to be able to look out years into the future. Here’s the derivation (with p = CAC/MRR defined in that COC article):
Another way to answer the question about “reasonable” CAC is to think in terms of pay-back period p = CAC/MRR — the number of months it takes to earn back in revenue the cost to acquire the customer. Or better in my opinion, CAC/MRR/GPM so that we’re accounting for the costs to serve those customers.
A good rule of thumb with pay-back period is that 6 months is fine, 3 months is fantastic, and 10+ months is poor unless (1) there’s indirect strategic benefit, e.g. branding, (2) efficiency is improving so we want to stick with it, (3) a mature company can plausibly justify 5+ years of revenue per customer.
Another use of LTV is as a general notion of the dollar value extracted by the company, and thus something that ought to be going up over time. True, but in practice I find you always need to know the values of the individual components to truly know whether the company is healthy.
For example, if LTV is steady, is that OK? If all the components are steady, maybe that’s OK. But what if GPM is improving due to investment in cost-cutting measures while cancellations are increasing, and thus LTV is stable. Is that good? Heck no! Your customers are pissed.
Thus, measuring MRR, cancellations, GPM, and CAC individually are always necessary. Sure you can combine them into a number, but I think that only serves to hide data, hide insights, not help “get a handle on the business.”
What else?
What else do we actually use LTV for, besides desiring it to go up in general? Let’s continue the debate in the comments.