SaaS Metrics

There are others that have spent much more time thinking about metrics in SaaS. I am enjoying watching the community develop better and better ways about thinking about these new businesses. They make up the majority of the models that we are investing in at Storm today.

Dave Kellog, who is CEO at SaaS company Host Analytics, put together a great post titled “The Ultimate SaaS Metric: The Customer Lifetime Value to Customer Acquisition Cost Ratio (LTV/CAC)

I like the fact that Dave is a fan of actually looking at the financial model as well – I think this is critical because any one metric or combination of metrics can be misleading (positive or negative) especially early in a company’s life – but even can cause confusion for public companies. As an entrepreneur (or investor), understanding the model is critical. Its guaranteed to be wrong but it gives you a framework. He references a SaaS metric periodic table from Insight Venture Partners which I thought was creative and generally accurate.

Unlike Dave, I don’t think all four financial statements matter – at least on a regular basis. A statement of retained earnings really doesn’t tell you much about running the business – but cash flow, income and balance sheets do.

He makes the point that one of the best ratios to looks at is lifetime value / CAC. I agree – though with a caveat. The biggest problem with it early on with a business is LTV and CAC are dubious calculations because the datasets are small – and the ratio therefore is just as potentially flawed. And Dave recognizes some of the limitations as well like calculating churn which has another great post on here. But the basic point is right on – a business should value what is willing to pay for a customer (CAC) based in some way to what that customer is worth (LTV).

The CAC ratio captures the cost of acquiring customers. In plain English, the CAC ratio is the multiple you are willing to pay for $1 for annual recurring revenue (ARR). With a CAC ratio of 1.5, you are paying $1.50 for a $1 of ARR, implying an 18 month payback period on a revenue basis and 18-months divided by subscription-GM on a gross margin basis.

Lifetime value (LTV) attempts to calculate what a customer is worth and is typically calculated using gross margin (the profit from a customer after paying the cost of operating the service) as opposed to simply revenue. LTV is calculated first by inverting the annual churn rate (to get the average customer lifetime in years) and then multiplying by subscription-GM.

For example, with a churn rate is 10%, subscription GM of 75%, and a CAC ratio of 1.5, the LTV/CAC ratio is (1/10%) * 0.75 / 1.5 = 5.0.

The general rule of thumb is that LTV/CAC should be 3.0 or higher, with of course, the higher the better.

Happy modeling!

2 Comments

  1. I have been doing a great deal of thinking about LTV of customers. For some SaaS companies, it is not possible to calculate the LTV of a customer since they have very low churn and have not lost many customers over the years. Therefore how do you know who long you may have a customer. Perhaps some enterprise software companies will hold onto customers for more than 20 years. For instance, how long do customers use SAP or Oracle before they churn out? I would guess many customers of SAP and others will never churn out.

    So it seems to me some calculations of LTV are just a WAG (wild ass guess), which means then the rest of the chain of calculations to valuation are not really possible. Just a thought.

    1. You are right that a huge dependency is being able to make a calculation of LTV of a customer. Its especially hard for startups without many customers and without years of operations. However, I think it can still be very useful. For example, if your CAC exceeds your LTV you know you are not in a good place. So often what we are really talking about is how aggressive a company wants to be with its assumptions around LTV- since as you point out there often are some assumptions. The calculus then has a lot to do with things like capitalization, size of company, strategy, competitive landscape etc. Thanks for the comment – its easy to get lulled into thinking you can drive by the numbers. Its always more complicated than that in my experience.

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