Introducing Lambda, a "new" SaaS metric designed to be useful for founders

LTV:CAC is a mainstay of SaaS analysis. Dozens of VC-marketing-blog posts have been written about its features and limitations, but they are generally theoretical. I get the sense that the concepts they discuss are implemented when it comes time to raise a round and present to investors but not embedded in the day to day operations of most early-stage companies. This is a shame, because as I discussed in my last post on ForEntrepreneurs, the question that LTV:CAC analysis aims to solve at the company level is crucial: how efficient is the go-to-market, and what is the right level of sales/marketing investment?

Unfortunately, many founders I've met with don't have a clear answer to either question. They may have calculated their LTV:CAC (which somehow often seems to be just slightly above 3, a commonly recommended value), but when it comes to operationalizing the metric day to day there is a chasm between investors' favorite metric and the typical monthly KPIs of bookings and ARR. I've thought lots about this disconnect, and I think for many companies a new variable called λ is part of a potential answer. Used appropriately, it can help management teams make quick decisions, help align more junior employees to the unit economics of the business and serve as a crucial mental model for internal and external communication purposes. So what is it?

λ is the ratio of LTV:New Customer ARR. It answers the question "how much is a given dollar of New Customer ARR worth?" in a simple, easy to remember and reference ratio.

There are many articles on how to calculate customer lifetime value. My preferred method involves a churn rate, a discount rate, a gross margin assumption and then a separate, probability weighted calculation for potential upsells. You can see the exact math in the attached excel spreadsheet (Lambda), which calculates LTV and divides it by New ARR to calculate λ. Here is a table showing how this looks for four sample companies (here's the excel sheet with explanations of each variable):

So what does this tell us? λ can vary massively across SaaS models and even for different customers of a given startup, with gross churn and upsell potential being the major drivers. Company D, with 33% churn and no chance to upsell, has a λ of just 2.1x => every dollar of new customer ARR is worth $2.10 of LTV. Company D looks very much like an SMB-focused software company with a single "nice to have” product. Company A, on the other hand, has a λ of 8.3x, driven by just 5% churn and a solid probability of upselling. It looks like a typical enterprise software company with a "need to have" product and room to expand within its customer base.

None of this tells us which is a good business or not- Company D may have a killer go-to-market that brings in customers at very low cost, whereas company A could have tortuous and lumpy enterprise sales cycles. It does tell us, though, that company A can afford to spend significantly more to acquire a company, and it helpfully adds some numeracy to the word "significantly." Comparing the λs it is easy to see that Company A can afford to spend about 4x as much, holding the preferred LTV:CAC multiple equal.

It is useful within companies as well: if there is an opportunity to sell a $100k ARR customer with λ of 6, and the company is aiming for an LTV:CAC of 3, then the company can afford to spend $100k*6/3 = $200k through the sales cycle to acquire that customer. All of the messy math in LTV:CAC calculations is condensed into a single multiple.

So rather than using intuition to map ARR to LTV, management teams can use this simple ratio with clear assumptions. It is a great tool for back of the envelope math like "If we hire 3 reps, they will cost $300k/year and we expect them to bring in $500k of new ARR. Our λ is ~3, so that is $1.5m of LTV or an LTV:CAC ratio of 5" or "if we devote 100 hours of engineering time, we can win a customer- is that worth it?"

Consider having an idea of your company’s λ in mind as a practical way to ground discussions and decisions in the underlying economic reality of a subscription business.

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