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.

The Metrics to help understand Bookings

 MRR The Monthly Recurring Revenue at the end of each month. Computed by taking the MRR from the previous month and adding Net New MRR. ARR Annualized Run Rate = MRR x 12ARR is annual run-rate of recurring revenue from the current installed base. This is annual recurring revenue for the coming twelve months if you don’t add or churn anything. ACV Annual Contract Value of a subscription agreement. New MRR/ACV The increase in MRR from new customers in the current month. Churned MRR/ACV The lost MRR from churning customers in the current month. Expansion MRR/ACV The increase in MRR from expansion in your installed base in the current month. Net New MRR/ACV Net New MRR = New MRR + Expansion MRR – Churned MRRThis is the sum of the three different components that will change MRR during each month. Bookings The total dollar value of all new contracts signed. Usually taken as an annualized number even if the contract period is longer than one year.Since the bookings number might have a mix of different durations (e.g. month-to-month;  6 months; 12 months) this number is not very helpful for understanding the business.To really understand what is going on in your SaaS Business, you should look at the following components:a) What happened with new customers: New MRR/ACV from new customer contracts b) What happened in your installed base: Renewals Churned MRR/ACV Expansion bookings The sum of all of the above: Net New MRR/ACV Billings Billings is the amount that you have invoiced that is due for payment shortly. Revenue Revenue is amount of money that can be recognized according to accounting policy. Even if it is paid for upfront, usually subscription revenue can only be recognized ratably over time as the service is delivered.If more money has been paid than can be recognized, the difference goes into a balance sheet item called Deferred Revenue. Average Contract Length Assuming a mix of different contract lengths, this gives you the average duration in months or years. Months up front Average of months (or years) of payment received in-advance with new bookings. Getting paid in advance has a big positive impact on cash flow. This metric has been used at both HubSpot and NetSuite in the past as a way to incent sales people to get more paid up front when a new customer is signed. However asking for more money up front may turn off certain customers, and result in fewer new customers, so be careful how you balance these two conflicting goals. ARPA – Average monthly recurring Revenue per Account This number is tells you the average monthly revenue per customer. It is useful to look at this for just the new customers booked in the month. Plot a trend line to show you the average price point that your new customers have chosen.

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:

 # of new Customers The number of new customers added this month # of churned Customers The number of customers lost due to churn this month Net New Customers Net New Customers = # of new Customers – # of churned CustomersThis is the net number of new customers added once lost customers due to churn has been taken into account. % Customer Churn % MRR Churn Defined as lost revenue due to churned customers as a percentage of total recurring revenue.(See below for a description of why this is different to % Customer Churn.) % MRR Expansion Defined as the expansion revenue from existing customers as a percentage of total revenue. % Net MRR Churn This is the number that will go negative if the Expansion revenue from existing customers starts to outstrip the lost revenue from churn. Getting to negative Net MRR Churn is a great goal for a SaaS company. Customer Renewal Rate It can be confusing to look at both your renewal rate (which should be just 1- Churn) in addition to churn. However in a model where you have yearly contracts being renewed, the two numbers can actually be different. For example, in the early days of a startup, you might have low churn because many of your customers have not yet reached the point where they could drop your service because of the length of their contract. In that situation, your churn number will not accurately predict what is really going to happen when you reach steady state. So a better number to look at is how many of your customers are renewing at the point where their contract expires. That is what this number measures.When you reach steady state, this number should be equal to 1 – % Customer Churn. Renewal Rate (\$’s) Similar to the number above, but instead of looking at the number of customers, it looks at the dollar value of the renewed contracts. It’s important to look at both, as they each tell an useful part of the story. If you were losing a lot of customers, you’d want to know why. Similarly, if you were only losing a few customers, but they were your biggest \$ value customers, you’d also want to know that as well. DRR (Dollar Renewal Rate) Similar to the metric above, but also takes into consideration Expansion MRR:If your Dollar Renewal Rate is greater than 100%, you have negative churn, which is a very good thing to have achieved.Example: If you are looking at DRR on an annual basis, another way to think about what DRR represents, is to think of a specific month’s cohort (e.g. the January cohort). Asa an example, let’s say that at the end of January the revenue from this cohort is \$100k. A year later, you will have lost some customers, (for example let’s say \$10k of that cohort’s revenue), but the remaining customers have also purchased \$20,000 more from you (Expansion MRR). So we will have \$110k of revenue left from that January cohort a year later. This means that our DRR is equal to 110%.
• 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.

Likes, Comments, Shares / Posts = Engagement

It’s true that Average Post Engagement Rates can range from 0.01% to 1%, but people keep forgetting thats the people interacting, and that its for every post. If 1% of people interact with EVERY one of your posts, that means a majority of your fans have seen it. So it’s the exact reason why Engagement Rate is a metric worth monitoring!

Nice post/graphic from Social Bakers, to which I left a comment to ask for an example of how to the non-mathematicians amongst us it can appear to be true that “if 1% of people interact with EVERY one of your posts, that means a majority of your fans have seen it”. Here’s their visual response, with an explanation in terms of the relationship between engagement and reach:

And then it of course you could chart your engagement and reach posts against their ideal in a simple x/y graph and see if that helps guide you, to see if you’re doing things correctly. Too much reach, but not enough engagement, check the actuals vs my simple info-graphic?

PS: Here’s the calcs_examples I promised with their simple formulas. Enjoy!