I routinely get asked questions like the following: What is a typical churn rate for SaaS? How much should I pay my SaaS sales reps? What is a good time frame to recover acquisition costs? A few years ago, the best answers I could give were simply based on my own experience and conversations with other SaaS colleagues. However, as SaaS has matured as a category, some high quality SaaS benchmark studies have appeared.

Recent conversations with Lauren Kelley over at OPEXEngine highlight for me how SaaS companies across the board struggle with customer acquisition costs (CAC) and churn. The 2010 OPEXEngine SaaS benchmark study shows a WIDE range of results across these critical performance metrics, indicating that there is no one right way to tackle these challenges that will work for SaaS companies across all sizes and sectors. But, there are plenty of wrong ways.

SaaS Benchmark Results – Customer Acquisition Cost

SaaS companies vary a lot in their willingness to invest in customer acquisition. For example, the OPEXEngine SaaS benchmark report gives an average payback period for CAC alone of about Read more »

I’ve wrapped up the highlights of my SaaS metrics series into a tidy SaaS Metrics Guide to SaaS Financial Performance. Like the original SaaS metrics series, this reference guide presents simple rules-of-thumb and graphic visualizations that capture the dynamic relationships between core SaaS metrics and SaaS financial performance.

It is NOT a comprehensive overview of SaaS metrics, but a deep dive into the most critical SaaS metrics with the goal of fostering intuition and deeper understanding of SaaS financial performance, including charts, formulas, definitions, sample calculations, and hyperlinks back to the full SaaS Metrics Rules-of-Thumb posts. Feel free to pass it along. Cheers! JY.

Click the image to download the
SaaS Metrics Guide to SaaS Financial Performance (PDF format)

Original SaaS Metrics Rules-of-Thumb Posts

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

For the life of me, I still can’t fathom how VCs value early stage startups. I think it is one part business logic and five parts voodoo (no offense to my VC friends, but you know what I mean). However, I’m guessing most SaaS-focused VCs know this SaaS company valuation principle in their gut even if they can’t reduce it to a financial projection: SaaS Customer Lifetime Value Drives SaaS Company Value. For what is a company if not the sum of its customers?

This is the final post in a series that aims to uncover the mysteries of SaaS financial metrics from a new angle, a little mathematics. In this installment, I’ll explore the important SaaS metric of customer lifetime value (CLTV) and introduce a new SaaS financial metrics rule-of-thumb that relates SaaS CLTV to SaaS company value.

Buyer Beware: The ideas presented in this installment of the SaaS metrics series are not meant to offer methods or models for evaluating the value of any particular SaaS company, but rather to offer credence to the gut reaction above. Use the formulas herein at your own discretion. Chaotic Flow, i.e., me, accepts no liability thereof.

SaaS Metrics Rule-of-Thumb #10
SaaS Customer Lifetime Value Drives SaaS Company Value

The financially accepted method for estimating the value of company is the calculation of the discounted value of its future cash flows, or net present value. Now, I’m not saying that anyone in InternetWorld actually uses this method, but for the sake of this series on SaaS financial metrics, this is the only approach that lends itself to mathematical analysis. So, I am stuck with it.

The exact mathematical statement of SaaS Metric Rule-of-Thumb #10 above is expressed as follows (see SaaS Metrics Math Notes below for the derivation):

SaaS Company NPV = CLTV x NEW_LTV

Where CLTV is the average SaaS customer lifetime value and NEW_LTV is an analogous measure for the lifetime value number of customers that represents Read more »

One of the mysteries I hoped to solve when I embarked upon this little SaaS metrics mathematical journey was the reality behind “The SaaS Company Magic Number” introduced by then Omniture CEO, Josh James, and immemorialized by my pal Lars Leckie over at Hummer Winblad. In principal, this number tells you how aggressively you should be spending to build up your customer base: “the key insight is that if you are below 0.75 then step back and look at your business, if you are above 0.75 then start pouring on the gas for growth because your business is primed to leverage spend into growth. If you are anywhere above 1.5 call me immediately.”-Lars Leckie’s Blog

In this installment of the SaaS metrics series, I will show why this benchmark works, and introduce what IMHO is the single most important SaaS financial metric for measuring the overall health of a SaaS business. Now, being as Josh and Lars have already laid claim to “The” SaaS Magic Number, I really have no alternative but to put all humility aside and dub my latecomer SaaS metric as “Joel’s” SaaS Magic Number (After all, I did similarly snag “The” Top Ten Do’s and Don’ts of SaaS, so it’s all good.)

SaaS Metrics Rule of Thumb #9 – Joel’s SaaS Magic Number

The truth be told I feel a bit guilty about the name, because Joel’s SaaS Magic Number is neither magic, nor mine really. It’s simply the the average customer rate of return, or rather the inverse of the average customer baseline break-even, 1/BE₀, that has so consistently popped up as a driver and a constraint in the SaaS metrics rules-of-thumb.

Where “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and “CAC” is the average customer acquisition cost. Customer rate of return is powerful, because it measures the economics that make a SaaS business work (or not), whereas the individual revenue and cost metrics are simply accounting figures that in isolation say little about the health of the business. Let’s recap some of the things we know about this nifty magic number from earlier SaaS metrics rules-of-thumb.

Intuitively, the long run profitability of SaaS companies requires
the recurring contribution of current customers to cover the acquisition cost of new customers,
therefore the average customer rate of return for SaaS companies
must exceed both the current customer churn rate and the new customer growth rate.

So, what is a good value for Joel’s SaaS Magic Number? Well, I don’t think anyone could argue with 1, a valiant goal, but rather optimistic. Read more »

Too much churn, you lose money. Grow too fast, you lose money. Customer acquisition cost too high, you lose money. Recurring cost of service too high, you lose money. Just shoot me now! How on earth do you make money in SaaS?

If you’ve been following this series on SaaS metrics, then you’ve probably worked your way up to just such a level of frustration. Because, that pretty much sums up the last four SaaS metrics rules-of-thumb on SaaS profitability:

• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service

It just can’t be! This is high tech. This is the Internet! Software, not hardware. SaaS can’t just be a low-cost commodity business. There must be a value-based approach. A SaaS revenue solution!

There is. But, it doesn’t mean you can ignore the fundamentals. Driving down total cost of service through automation and economies-of-scale is fundamental. SaaS executives that ignore this put the long term profitability of their SaaS businesses in peril. But, enough on lowering SaaS costs. Let’s talk increasing SaaS revenue!

The previous post in this SaaS metrics series entitled Growing Up Poor – How Foolish SaaS Companies Lose Money was a bold attempt to once and for all solve the mystery of why seemingly successful SaaS companies lose money…in excruciating detail (sorry for that). The cornerstones of the analysis were the relationships established between the values of churn, “a”, growth, “g”, and the baseline average customer break-even time, “BE₀” as follows:

BE₀ = CAC ÷ [ ARR - ACS ]

In the formula above, “CAC” is the average acquisition cost per customer, “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and the 0 attached to the BE is intended to indicate the absence of churn, i.e., the baseline break-even.

These constraints were the basis of SaaS metrics rules-of-thumb #6 and #7 which claim that both growth and churn, respectively, increase pressure to reduce total cost of service (CAC and ACS) in order to accelerate profitability (reduce BE₀) and to ensure that profitability is even possible (gBE₀,aBE₀ < 1). However, the viable SaaS revenue strategy of increasing average recurring revenue (ARR) without increasing total cost of service was carefully set aside for later examination. Leading us to...

SaaS Metrics Rule-of-Thumb #8
Upselling and Upgrades Accelerate SaaS Profitability

What exactly does it mean to increase average recurring revenue without increasing average customer acquisition cost or average recurring cost of service? First, no additional customer acquisition cost means that we must increase recurring revenue from current customers. Second, no increase in average recurring cost of service means that we must do so in the normal course of business with very little extra effort, preferably through customer self-service (self-selling!). In other words, SaaS companies can accelerate time to profit by upselling and upgrading current customers, but only if it follows an exceptionally low cost purchase process distinct from the new customer acquisition process. The chart below depicts the impact of upselling and upgrades on SaaS time to profit.

Upselling and upgrades leverage the initial investment of customer acquisition cost
to accelerate SaaS time to profit by countering the delays of both growth and churn.

The chart above depicts the effect of upselling on the two uglier examples presented Read more »

Over and over again, I see exciting headlines for SaaS companies like this…

That when I dig a little deeper, I end up having my bubble burst by a dismal financial statement that looks something like this…

Where is all the money going? Why do so many successful SaaS companies, startup and public alike, have such a difficult time turning a profit?

This is the fourth post in a series on SaaS metrics that will once and for all solve the mystery of why seemingly successful SaaS companies lose money by using a little mathematics. But, before I jump into the technical details, here is the short answer: foolish SaaS companies don’t seriously tackle the problem of reducing Total Cost of Service through automation and economies-of-scale, and they foolheartedly chase after the Recurring Revenue Mirage.

In the last installment in this series, I introduced the following two SaaS metrics rules-of-thumb:

• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even

Which in concert make the claim that the time to profit for a growing SaaS company will always be greater than the baseline break-even time for the average SaaS customer.

t_profit ≥ BE₀

BE₀ = CAC ÷ [ ARR - ACS ]

Where “CAC” is the average acquisition cost per customer, “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and the 0 attached to the BE is intended to indicate the absence of churn, i.e., the baseline break-even.

In this post, we’ll zero in on the interplay of growth and profitability with customer acquisition cost and recurring cost of service (collectively total cost of service), starting with…

SaaS Metrics Rule-of-Thumb #6
Growth Creates Pressure to Reduce Total Cost of Service

We know from the earlier SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn, that successful SaaS companies must strive to grow new customer acquisition at a percentage growth rate, “g”, that exceeds the churn rate. This growth model is quite general. It applies equally well when growth is slow and plodding with a small value of g and when growth is rapid and extremely viral with a high value of g. The only requirement is that our successful SaaS company grow consistently from year to year, which is of course what we all want. In this case, the relationship above between SaaS company profitability and SaaS customer break-even can be made much more exact (see math notes below):

Since no SaaS company in this universe will throttle back on growth, the only acceptable strategy is to reduce the value of BE₀ such that g x BE₀ is significantly less than 1, otherwise it may be a looooooong time to profit, perhaps well after the company stops growing altogether (gasp!).

This creates pressure to reduce total cost of service by lowering the average customer acquisition cost, CAC, and lowering the recurring cost of service, ACS. Since growth is the culprit, the surest and most effective defense is to fight fire with fire by reducing total cost of service through automation that provides cost-lowering economies-of-scale. (The one other viable solution, increasing ARR without increasing CAC or ACS will be the topic of the next post in the series entitled SaaS Revenue – The Beauty of Upselling and Upgrades) This latest SaaS metric rule-of-thumb is visually depicted in the chart below.

New customer acquisition costs are paid with the recurring contribution of current customers.
If a SaaS company grows rapidly, growing acquisition costs can outpace
the build-up of recurring contribution, such that profitability is impossible.

As outlined in the previous post on SaaS profitability, time to profit occurs when Read more »

Profitability, one would think, should come quite naturally to a successful, growing SaaS company.  But, SaaS startups have consistently struggled to reach profitability.  Unprofitable SaaS companies have gone public and remained unprofitable for years after their IPOs, even as they grow revenues into the hundreds of millions of dollars.  SaaS companies have eschewed economic convention, with management and investors alike calmly shrugging off the passe’ advice of their obsolete microeconomics professors who cry out in vain from their blackboards that “the role of the firm is to maximize profit.” Many authors have tried to make sense of this morass, two of the more interesting attempts are Bob Warfield’s post entitled Why do SaaS Companies Lose Money Hand Over Fist, and this really cool analysis by Christian Chabot of tech IPOs comparing software companies that were profitable to those that were not profitable at the time of their IPO.  And, I’ve certainly made no secret of my own opinion in posts like this one entitled SaaS Failures – The Recurring Revenue Mirage.

This is the third post in a series on SaaS metrics that will unravel the mystery of  SaaS profitability (and the lack thereof) from a different angle, a little mathematics.  Once and for all we’ll solve the puzzle of why seemingly successful SaaS companies lose money. So, even if you’re not a math junkie like me, please be patient and plough your way through the technical mumbo jumbo. I’ll guarantee some of these results will surprise you!

SaaS profitability is such an important topic that I’m breaking it up into three separate posts (this being the first) that will build on each other by examining three increasingly complex scenarios: 1) stable growth with churn, 2) viral growth, and 3) growth through upselling and upgrades.  Along the way, I’ll also introduce a number of new SaaS Metrics Rules-of-Thumb that highlight the impact of customer acquisition costs and recurring cost of service on long term SaaS profitability.
So, let’s get going…

SaaS Metrics Rule-of-Thumb #4
Company Time to Profit Follows Customer Break-Even

This subtle, strikingly simple rule will reverberate through all that comes to follow on SaaS profitability. And, it provides a simple sanity check for predicting when, if ever, your SaaS business will reach profitability. The gist of the rule is that your SaaS recurring revenue over time is nothing more than the sum of its parts. Therefore, the sooner you break even on a single customer, the sooner you will reach profitability as a company.

The chart below visually shows this principle for a SaaS company with a constant rate of customer acquisition eroded by churn which was closely examined in the first post in this SaaS metrics series.

The accumulated recurring contribution of a SaaS company at any time
mirrors the lifetime accumulation of the typical SaaS customer
directly linking company time to profit with customer break-even time.

The average break-even point for an individual customer without churn, “BE₀” is given by the following formula:

BE₀ = CAC ÷ [ ARR - ACS ]

Where “CAC” is the average acquisition cost per customer, “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and the 0 attached to the BE is intended to indicate the absence of churn, i.e., the baseline break-even.

Now let’s compare this simple individual customer SaaS metric with the more complex SaaS metric of company time to profit. Read more »

Everybody wants their Internet startup to go viral. But, just what does going viral mean? In his book, The Tipping Point, Malcolm Gladwell spells out the mechanics of how ideas spread virally by modeling the roles of key individuals that he calls connectors, mavens and salesmen (highly recommended on the Chaotic Flow blogroll Worthy Reads). When it comes to the Internet, Josh Kopelman eruditely points out that you can’t go viral by bolting it on as a last minute marketing program. You must apply SaaS Top Ten Do #5 and build viral growth into the product.

The aspiration of this post is not to add to the complexity of these theories of viral growth, but to uncover the simplicity of viral growth through a little mathematics. This is the second post in a series on SaaS metrics that explores the impact of viral growth in SaaS using a simple heuristic model with the goal of extending the list of SaaS Metrics Rules of Thumb started in the first post in the series regarding SaaS churn.

The mechanics of viral growth vary greatly by product, customer, market, and even culture. But, the mathematics pretty much boil down to the singular idea expressed so well in the kitschy Faberge shampoo commercial from the 70’s and 80’s.

Viral growth is customer growth that is proportionate to the number of customers.

C_{n + 1} = ( 1 + g ) x C_n

All the connectors, mavens, salesmen and friends are rolled into the little “g” (for growth rate) in the formula above, which states that the number of customers in the time period n + 1 is equal to the number of customers in the time period n, plus a multiple of those same customers. You can think of g as the percentage of friends who actually told two friends who actually then went out and bought some shampoo divided by the amount of time it took them all to complete this circuit.

Like churn, viral growth scales with the number of customers.
When the viral growth rate exceeds the churn rate,
growth explodes through the churn limit.

If you read the previous SaaS metrics post on SaaS churn, you might recognize this formula, because it is identical to the churn formula only the negative churn rate -a has been replaced with the positive viral growth rate g. Thankfully, we can skip over the algebra this time and jump to the solution, simply by replacing -a with (g-a). This quick slight-of-hand gives us the formula for the number of customers in the time period n, C_n, that incorporates viral growth as well as churn.

C_n = b⁄(g-a) x ( ( 1 + g -a )ⁿ -1)

In this formula, ”b” is the baseline constant customer acquisition rate prior to either viral growth or SaaS churn kicking in. The mirror-like relationship between viral growth and SaaS churn in the formula above leads us to our next SaaS metrics rule of thumb.

SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn

The previous SaaS Metrics Rule-of-Thumb #2 claimed that in order to break through the churn limit, new customer acquisition growth must outpace churn. Because churn increases in direct proportion to the number of customers, the surest approach is to drive growth at a higher rate that also increases in proportion to the number of customers, i.e., viraly.  Moreover, investors generally expect companies to increase revenue on a percentage basis year over year.  Holding products and prices constant, this again requires viral growth of your customer base.  Viral growth can come from many sources, but I like to classify it into the following three distinct stages.

Stage 1 Viral Growth – Brute Force Sales and Marketing  (small g)

In any given industry, most companies will spend a rather fixed percentage of revenue on sales and marketing, regardless of the size of the company.  When the effectiveness of these efforts scales Read more »

This is the first post in a series on SaaS metrics where I plan to develop a variety of SaaS financial metric models using simple mathematical heuristics. In the process, I hope to highlight important relationships between key SaaS metrics and develop a short list of valuable SaaS Metrics Rules-of-Thumb.

SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth

Consider a SaaS company that acquires new customers at the constant rate of “b” (for bookings), and has a percentage churn rate of “a” (for attrition). The number of customers after n periods of time “C_n” is given by the following formula:

C_n+1 = b + ( 1 – a ) x C_n

C_n = b + b (1-a) + b (1-a)² + b (1-a)³ … + b(1-a)^n-2 + b(1-a)^n-1

C_n = b⁄a x ( 1 – ( 1 -a )ⁿ )

This formula can be approximated at the two extremes of early growth and maturity.

These two boundaries are shown in the chart below along with the blue curve representing total customers over time.

As a SaaS company grows, absolute churn increases with the total number of existing customers and will limit growth if new customers are not added at a faster and faster rate.

In the early days, churn is small and the customer base grows unimpeded at the customer acquisition rate. As the customer base grows, the absolute value of churn increases and soon overwhelms new customer acquistion. When the customer acquisition rate, b, equals churn, a x C, then the number of customers coming in the door is exactly equal to the number leaving. At this point further growth is impossible, limiting the total customer base size to the new customer acquisition rate divided by the percentage churn rate. This limit might be more than satisfying if you run a bootstrapped, private SaaS business as your primary means of personal income. But, it is unlikely to satisfy investors if you are a VC-backed SaaS startup, bringing us to…

Read more »