Story of a lifelong customer

Music has always been a big part of my life. When I’m driving, when I’m commuting, when I’m working or studying, I always have music booming in my ears. As a undeliberate consequence, I’ve developed this magical ability to pinpoint the exact time of my life where I’ve been vibing a certain track sprouting a wave of nostalgia each time. When Spotify came out in closed alpha around 2007-2008 it wasn’t a surprise that I signed up immediately. For a while it was 100% all-you-can-eat for no charge and when the paid tier was eventually introduced it was pretty much optional, at least for the early users.

I didn’t mind the ads that were also eventually introduced as Spotify was figuring out its business model (are you OG enough to remember Jonathan from Spotify?), but I do remember that at some point in 2010-2011 they made the free-version so that you can only play your playlists in shuffle-mode effectively forcing you to pay up. Needless to say, being a music connosseur that I was I promptly opened up my wallets and have never looked back since.

That means I must’ve been a paying user of Spotify for over 10 years now. Easily the only service I’ve continuously been a subscriber of for so long. With quick math that equates to over $1,000 paid to Spotify which admittedly doesn’t feel much now that I wrote it out. Almost a steal considering the value it has added to my life. I’m also sure that I’ve bought individual songs through it (yes, did you know that was a thing on Spotify as well at one point) so add a few dollars on top of that grand.

Now, I’m probably an ideal customer of Spotify. They probably paid nothing to acquire me and I have been loyal to them for a extraordinarily long period of time. My entire cost to them is 75% of the $9 I pay for providing the platform and serving the content for me. I’d be willing to bet that my gross lifetime value of >$1,000 is quite likely in the top 5% of all the customers.

The point is, it’d be amazing if an average customer at Spotify looked like me. But reality is, that many are happy with the free version and even the paying users churn in a bit over 7 months , on average. That means Spotify requires >39% YoY growth just to make up for the lost customers. They can always spend more on marketing to grow and acquire new customers, but if Spotify doesn’t get that marketing investment back in 7 months (i.e. before the customer churns) the business turns into charity. And non-profits tend to be bad investments.

The simple theory of investing

The theory of investing is simple and goes as follows: Value of a business comes from the positive cash flows that it is expected to generate in the future for the people who own a piece of that business. In order to generate positive cash flows the cash inflows must be higher than the cash outflows. In order to generate net cash inflows each customer must generate well in excess of what it costs to acquire and serve that customer. And in order for that to happen, the unit economics must be positive. Without unit economics the business model is not sound.

Unit economics is the final individual ensemble of the macro-level business management. Once you are clear on your unit economics, you can probe in to its components much more in detail. Perhaps the poor economics are due to customers churning, or inefficient go-to-market. Or perhaps you are missing an upsell component or maybe you are underpricing. But if your starting point is any of the beforementioned, say the engagement or sales efficacy, without first understanding what your unit economics actually is, you are missing the forest from the trees. Below a simple framework that illustrates this extremely simple yet fundamental equation.

The simple theory of investing: Value of business is inherently linked to unit economics

The impact of unit economics

How one calculates unit economics depends on the business model. It used to be much easier with traditional goods and services companies where revenue and costs matched 1-1 with both recognized at the point of sale. That meant your gross margin immediately reflected profitability of the business: selling an artisan desk for $10 with the material costs being $4 resulted in $6 of net cash inflow that you can use however you want.

But the complexity has increased with the rise of tech and resulting popularity of SaaS and marketplace models. Now there are all these repeat purchases, lifetime spends, basket sizes, average contract sizes, supply-side economics, demand-side economics and so on and so on. The fundamentals never changed, however: Businesses must generate cash, and unit economics tell you how much net cash in aggregate you’re getting from a customer.

Let me demonstrate its importance using a simplified example of an enterprise SaaS company. Let’s call it the LTV Co. The firm has 20% R&D costs as % of sales and 5% G&A costs as % of sale. It also acquires ~10-15 customers per year and sells a software product with $30K annual contract value and 75% gross margin. To keep things simple I assume no upsell. The full model thus looks as follows

Hypothetical operating model of Simplified example of unit economics

Now then, let’s say the company either comes up with a product innovation that makes the customer compelled to stay longer on the platform or hires a genius marketer that lowers the customer acquisition costs significantly thus improving its LTV / CAC to 5.0x. With these improved unit economics the key value-drivers, growth and profitability, change tremendously:

The impact on growth and EBITDA are tangible with improved unit economics

By increasing the customer lifetime, the company boosts growth up to a 54% YoY in year 5 as it needs to replace fewer churned customers every year. By improving average sales price (e.g. moving upmarket) or lowering customer acquisition costs (e.g. more organic growth) LTV Co. can acquire profitability faster and reach up to 31% EBITDA margins in year 5.

Few special cases

Often you hear a 3.0x LTV / CAC cited as some kind of a rule-of-thumb, but I’d argue this all just depends on the company. Let’s explore few special cases:

1. Special case 1: a company with 10x LTV / CAC but some years with no new customer acquisition

The first is a very special case of a company that has an extremely high LTV / CAC of 10x, but acquires only a handful, or even no customers at all in a given year. Regardless, because its product comes with high average sales price and is extremely sticky for being mission critical it will grow nicely with the customer on a 20% net dollar retention rate reaching 40-50% EBITDA margins with some fluctuations here and there.

Although definitely more of an exception than a rule, I have seen few private equity backed specialist software companies following this kind of profile where stability of cash flow and stickiness of a client base is more important than just growth. Requires lots of diligence on contracts and individuals customers to get comfortable, however.

More often, this is something that emerges when unit economics are split between SMEs and enterprise clients. As it is a profile characteristical to the enterprise segment of a company’s customer base. Ideally, at least.

Small number of customers matter less if unit economics are exceptional

2. Special case 2: a 2x LTV / CAC company

Whenever we see low LTV / CACs, the first question we must ask is if it’s actually bad or is there anything artificially pulling it down such as free / freemium users who pay nothing. Especially with product-led enterprise SaaS there is a strong pareto-principle where 20% of customers bring in 80% of revenue, but if you look at blended unit economics they look awful because the other 80% of customers have $0 lifetime value.

Consumer software typically has naturally lower LTV / CACs than enterprise software for the reason that there are (a) lots of freemium users that push down the economics, (b) lower gross margins due to having to pay for content (few exceptions such as Match) and (c) for having naturally higher churn (consumers don’t have yearly budgets and commit for few months at a time).

To compensate, they tend to have much lower sales and marketing costs for the simple fact that they don’t need a heavy-weight sales team. As a result, their sales & marketing costs may be only 10-20% of revenue vs. enterprise SaaS at 40-50%. Hopefully at least.

But as shown with the Spotify example above, in order for them to make the economics work consumer software often needs much more customers and effectively need to replace their entire customer base each year.

Below a simple output of a hypothetical consumer subscription company that sells $9.99 / month subscription with 6 months average lifetime and 50% gross margins. It’s easy to see how in order to grow the company must be very aggressive with the new customer acquisition:

Seemingly low unit economics are not always bad and are typical to consumer software

So how can you spot positive unit economics in a public company? After all, only a few of us have access to full customer cubes or cohorts to perform detailed analysis of customer acquisition costs, lifetime or churn.

Perhaps the simplest way is to look at the path to profitability. If unit economics are positive, the math should make it so that the burn becomes smaller every year. Clear path to profitability. While not bulletproof (e.g. a company can simply cut down S&M and balance that with reasonable growth) it's a relatively good indicator of a sound business.

At least most enterprise SaaS companies tend to have blended ARPU, gross margin, net retention and fully-loaded customer acquisition costs from their 10Ks and 10Qs. And if they don’t report the total customer base at least you can approximate through their large >$100,000 per year customer base. And after that it just becomes a question of how to estimate lifetime. For that, one can try to infer something from net retention or try to google what is e.g. the average number of years a financial system gets replaced in an organization.

By Joel-Oskar Raisanen

Nov 8th 2024