9 top SaaS related articles for entrepreneurs

I’ve just come across the forEntrepreneurs website with some really useful articles about growing your business from David Skok. So I thought I would return the favour and publish their suggested articles below, with a strong emphasis on SaaS:

Also worth checking out on the SaaS side is the metrics definitions page, I have copied and paste, starting with unit economics.

The post below on unit economics goes into some mathematical details. I was recently made aware of this quick calculator from Nickelled, which helpfully automates calculations for some of the below – if maths makes your head hurt, it might be worth a shot. I myself commissioned the creation of an ROI calculator to support sales content for Causeway Technologies, so I appreciate how useful they can be:

Calculating LTV and CAC for a SaaS startup

Unit Economics is a very powerful way to analyze the long term profitability of a SaaS business.

I am often asked for the details of how to compute the various elements, such as CAC and LTV. This post gives the formulae.

CAC – Cost to Acquire a Customer

CAC is defined as follows:

There is a problem with using this formula in the early days, as you may several expensive people in the team that should scale to handle a far number of customers as you grow. In that case, your CAC will be too high. I suggest doing a very simple adjustment to the Sales & Marketing expenses to take only a portion of those salaries and expenses in the early days. That will give a better indication of how CAC will look in the future when you are at scale.

If you start with a cohort of 100 customers and apply a constant churn rate every month, you’ll get an exponential decay, as shown in the following graph (which uses a 3% monthly churn rate):

Mathematically this can be simplified to the following formula to find the average Customer Lifetime:

Note that if the Customer Churn rate is a monthly % or yearly %, then the Customer Lifetime will be for the same time period. Here is a monthly and annual example to illustrate the point:

a) If the Monthly customer churn rate is 3%, then the Customer Lifetime will be 1/0.03 which is 33 months.

b) if the Annual customer churn rate is 20%, then the Customer Lifetime will be 1/0.20 which is 5 years.

In the situation where there is no expansion revenue expected over the lifetime of a customer, you can use this simple formula:

which can also be expressed as follows:

Once again if ARPA is monthly, the churn rate should be monthly.

To truly get an accurate picture of LTV, you should take into consideration Gross Margin. i.e.

However in most SaaS businesses, the gross margin % is high (above 80%), and it’s quite common to use the simpler version of the formula that is not Gross Margin adjusted.

Ron Gill, NetSuite: I’m surprised at how often I see a SaaS product architected in a way that means they’ll never clear a decent gross margin. Including GM in the calc is a great way for you to see there is a big lever on LTV/CAC that is worth focusing on.

For NetSuite, we’ve not only calculated LTV/COCA, but also calculated r-squared of each of the components (to see what has driven improvement) and sensitivity analysis on them (to see what might drive it in the future). GM is an important component.

More complex case
In the specific situation where you expect ARPA to change over the lifespan of the customer due to expansion revenue, this simple version of the formula will not work. We ran into this situation with ZenDesk, where there is a pretty reliable increase in revenue over the life of a customer.

Here’s a graph showing what would happen if you had a cohort of 100 customers that initially started paying you \$100 a month, but increased their payment by \$5 every month. The monthly Customer Churn Rate is 3%:

As you can see the expansion revenue initially is greater than the losses from churn, but over time the churn takes over and brings down the value of that cohort.

I asked my partner, Stan Reiss, to help with the math to calculate LTV in this more complex situation. Here is what he came up with:

Variables:
a = initial ARPA per month ( x GM %, if you prefer)
m = monthly growth in ARPA per account
c = Customer Churn Rate % (in months)

(This formula makes an assumption that revenue increases at a roughly fixed rate every month for the entire lifetime of the customer. That probably doesn’t hold true for many SaaS businesses, but the goal is to get a rough idea, not to have the absolute perfect answer.)

LTV : CAC Ratio

Our guideline for a successful SaaS business is that this number should be higher than 3.

Ron Gill, NetSuite: It is most important to track this metric over time to make sure you’re driving improvement. And, look at investment and how it will impact.

(The guideline assumes you are using the simpler LTV formula that does not include a Gross Margin adjustment, and that you have a Gross Margin of 80% or higher.)

Months to recover CAC

To be perfectly accurate, this should include a Gross Margin adjustment as follows:

However in our guideline which states that Months to Recover CAC should be less than 12, we are assuming that you are using the simpler formula, and have a Gross Margin of 80% or higher.

Bookings, Billings and Revenue – An example

Since there can be some confusion around the difference between bookings, billings and revenue, here is a simple example to help clarify them: Imagine you signed a new contract with a customer with a one year term, specifying that you provide your service to them for \$1,000 per month, with an upfront payment of six months:

• Your bookings would be \$12,000 (the entire contract value)
• You would bill \$6,000 in the first month, then \$1,000 per month from the seventh month onwards.
• You would recognized \$1,000 in revenue for each month of the contract. (This is dictated by GAAP accounting policy.)

For the example above, the balance sheet and income statement impact of these items is as follows:

• Bookings do not affect either the balance sheet or the income statement.
• When you bill \$6,000 in the first month, but can only recognize \$1,000 in revenue (income statement), and the other \$5,000 goes into deferred revenue on the balance sheet (a liability).
• Each month thereafter until another \$1,000 can be recognized as revenue (income statement), and that reduces the deferred revenue liability on the balance sheet.

The Metrics for Churn (Renewals)

The following shows the metrics to understand Churn:

• Here’s a related post I wrote comparing CBA vs ROI with a slideshare on social media metrics – consistency the most visited article on this website.

The key difference between traditional software and software as a service: Growth hurts (but only at first)

In the traditional software world, companies like Oracle and SAP do most of their business by selling a “perpetual” license to their software and then later selling upgrades. In this model, customers pay for the software license up front and then typically pay a recurring annual maintenance fee (about 15-20% of the original license fee). Those of us who came from this world would call this transaction a “cashectomy”: The customer asks how much the software costs and the salesperson then asks the customer how much budget they have; miraculously, the cost equals the budget and, voilà, the cashectomy operation is complete.

This is great for old-line software companies and it’s great for traditional income statement accounting. Why? Because the timing of revenue and expenses are perfectly aligned. All of the license fee costs go directly to the revenue line and all of the associated costs get reflected as well, so a \$1M license fee sold in the quarter shows up as \$1M in revenue in the quarter. That’s how traditional software companies can get to profitability on the income statement early on in their lifecycles.

Now compare that to what happens with SaaS. Instead of purchasing a perpetual license to the software, the customer is signing up to use the software on an ongoing basis, via a service-based model — hence the term “software as a service”. Even though a customer typically signs a contract for 12-24 months, the company does not get to recognize those 12-24 months of fees as revenue up front. Rather, the accounting rules require that the company recognize revenue as the software service is delivered (so for a 12-month contract, revenue is recognized each month at 1/12 of the total contract value).

Yet the company incurred almost all its costs to be able to acquire that customer in the first place — sales and marketing, developing and maintaining the software, hosting infrastructure — up front. Many of these up-front expenses don’t get recognized over time in the income statement and therein lies the rub: The timing of revenue and expenses are misaligned.

The income statement alone therefore can no longer tell us everything we need to know about valuing a SaaS business.

Even more significantly (since cash is the lifeblood of any business), the cash flow timing is also misaligned: The customer often only pays for the service one month or year at a time — but the software business has to pay its full expenses immediately.

Thus, as with many innovative new businesses, cash flow is a lagging not a leadingindicator of the business’s financial health.

Take a look at the cumulative cash flow for a single customer under a SaaS model — the company doesn’t even break even on that customer until after a year:

And as the company starts to acquire more customers, the cash flow becomes even more negative. However, the faster the company acquires customers, the larger it grows its installed base and the better the curve looks when it becomes cash flow positive:

For the full post please read: Understanding SaaS: Why the Pundits Have It Wrong | Andreessen Horowitz.