This page is a supplement to the the SaaS Metrics 2.0 blog post. It provides detailed definitions for each of the key metrics used in that post.
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.
Lifetime Value of Customer
For a more detailed blog post dedicated to the topic of how to calculate LTV, see the following blog post: What’s your TRUE customer lifetime value (LTV)? – DCF provides the answer. The following provides a simple intro to the topic:
In the situation where all customers have roughly the same ARPA, and 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.
However in situations where you have widely differing ARPA across the customer base, this would not take into consideration the difference between losing a high value customer versus a low value customer. So a more accurate formula would be:
To truly get an accurate picture of LTV, it is important to also take Gross Margin into consideration. i.e.
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:
a = initial ARPA per month x GM %
m = monthly growth in ARPA per account x GM% (note this is a $ figure, not a percentage)
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.)
But there are other complexities such as as the following:
- Your churn doesn’t follow an exponential decay curve
- Your customers don’t follow a simple linear revenue expansion
To handle these more complex cases, please refer to this more detailed post on how to calculate LTV: What’s your TRUE customer lifetime value (LTV)? – DCF provides the 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:
Months to recover CAC gives you a very good sense of how much capital you will burn if you start growing the business. The lower this number, the less capital you will consume. In our guidelines provided in the SaaS Metrics 2.0 Blog post, we suggest that Months to Recover CAC should be less than 12 months. That guideline was written back in 2011, when it was hard to raise capital. Since then the investment community has realized the power of the SaaS business model, and many SaaS companies have gone public and performed well. As a result, it is now possible to raise much larger amounts of capital, and therefore you can afford to have a longer time to recover CAC than just 12 months. In many enterprise businesses, where there is a Land and Expand model, Months to recover CAC can be around 20 months, and the model works fine. In practice, it is very rare to find Months to recover CAC as less than 12.
Months to recover CAC is one of the four key metrics to evaluate the health of a SaaS business. The other three are Growth rate for Net New ARR, Burn Rate and Net Retention Rate, NRR). If you are able to manage the business to have good values for these metrics, you will know that you are building a healthy SaaS business.
Sales Efficiency and the “Magic Number” metrics are different ways of evaluating pretty much the same thing as Months to Recover CAC. The thought process behind both of these metrics is to figure out how efficient is a business’s sales and marketing spend. To do that these metrics ask the question: for every dollar of spend on sales and marketing, how much new revenue does that bring in?
There are two versions of Sales Efficiency, Gross and Net. Gross Sales Efficiency simply looks at Gross New ARR (which does not include churn), while Net Sales Efficiency measures Net New ARR, which is reduced by Churn. Here are the two formulae:
Gross New ARR = New ARR from new customers + Expansion ARR from existing customers.
You could think of this as the output from sales and marketing without paying any attention to how well the company does at retaining and growing those customers.
We use the prior quarters spend on sales and marketing with the thought that there is likely to be a delay between the spending of money and effort on sales and when the deal closes. However if your business has a short sales cycle you could use the same quarter’s sales and marketing spend.
Net New ARR = New ARR from new customers + Expansion ARR from existing customers – Churned ARR.
So Net Sales Efficiency measures not just Sales and Marketing, but also how effective the company is at retaining and growing those customers.
The shortcoming of Sales Efficiency is that it does not take into consideration Gross Margin %. A business with a high gross margin of say 80% is a dramatically better business than a business with the same Sales Efficiency number but a Gross Margin % of only 40%.
The Relationship between Sales Efficiency and Months to recover CAC
If we ignore Gross Margin, a Sales Efficiency of 1, implies that Months to recover CAC is 12 months. As Sales Efficiency drops to 0.5, your Months to recover CAC increases to 24 months.
I tend to prefer “Months to recover CAC” as the name of the metric is self-explanatory, which makes everyone clear what it is that you are measuring. It also has one other advantage, which is that it takes into consideration Gross Margin %
The one problem with both Months to recover CAC and Sales Efficiency is that public SaaS companies do not reveal these metrics. Given that it would be nice to find a way to create a standardized metric that could be used to benchmark all SaaS companies, Scale Ventures came up with the idea of modifying Sales Efficiency to create what they called the Magic Number.
This is very similar to Net Sales Efficiency. It replaces Net New ARR in the current quarter, with the increase in GAAP Revenue in the current quarter multiplied by 4 to bring it closer to ARR (which is an annual number, not a quarterly number). Anyone is now able to compute a metric that is now very close to Net Sales Efficiency using data that all public SaaS companies report, and therefore we have a standardized benchmark.
There are two shortcomings of the Magic Number that are worth knowing:
- It does not take into consideration Gross Margin %. We have already pointed out that if you have low gross margins, you really need to have much higher sales efficiencies to make up for that.
- It does not take into consideration the mix between Subscription Revenue and Services Revenue, which is far less valuable, and typically lower margin.
The Metrics to help understand Bookings
In a traditional, non-SaaS, software business, Bookings are one of the most important metrics. However it turns out that in a SaaS business, you need to look closely at what is the right way to measure Bookings. To understand the nature of the problem, let’s say that in one month we sign two deals: both sign up for the same product, at $1,000 per month, but one signs up for one month commitment, and the other signs up for 12 months. In that situation, how should you compute Bookings?
An interesting thing can happen with those same two customers: the customer who signed up for only one month at a time, might stay with you for four years, but the customer who signed up for one year, might leave at the end of that one year. So what initially looked like the more valuable booking turns out over time to be the less valuable booking.
The answer is that we need to stop looking at Bookings in the old way, and replace it with Net New ARR. This is the most important metric to run a SaaS business by from month to month, quarter to quarter. It takes in to consideration most of the key elements that you need to drive to grow your business:
Net New ARR is the sum of the following three components:
|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 ARR||The increase in MRR from new customers in the current month.|
|Churned ARR||The lost MRR from churning customers in the current month.|
|Expansion ARR||The increase in MRR from expansion in your installed base in the current month.|
|Net New ARR||Net New ARR = New ARR + Expansion ARR – Churned ARR
This 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:
b) What happened in your installed base:
The sum of all of the above:
|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: