Category Archives: SaaS

Detecting and Eliminating the Rolling Hairballs in your Sales Pipeline

Quick:  what’s the biggest deal in this quarter’s sales pipeline?  Was that the biggest deal in last quarter’s pipeline?  How about the quarter before?  Do you have deals in your pipeline older than your children?

If you’re answering yes to these questions, then you’re probably dealing with “rolling hairballs” in your pipeline.  Rolling hairballs are bad:

  • They exaggerate the size of the pipeline.
  • They distort coverage and conversion ratios.
  • They mess up expected-value forecasts, like a forecast-category or stage-weighted sales forecast.

Maybe they’re real deals; maybe they’re figments of a rep’s imagination.  But, if you’re not careful, they pollute your pipeline and your metrics.

Let’s define a rolling hairball

A rolling hairball is a typically large opportunity that sits in your current-quarter pipeline every quarter, with a close date that slips every quarter.  At 2 quarters it’s a suspected rolling hairball; at 3 or more quarter’s it’s a confirmed one.

Rolling Hairball Detection

The first thing you need to do is find rolling hairballs.  They’re tricky because salesreps always swear they’re real deals that are supposed to finally close this quarter.  What makes rolling hairballs obvious is their ever-sliding close dates.  What makes them dangerous is their size (including an accumulation of them that aggregate to a material fraction of the pipeline).

If you want to find rolling hairballs, look for opportunities in the current-quarter pipeline that were also in last-quarter’s pipeline.  That will find numerous bona fide slipped deals, but it will also light-up potential rolling hairballs.  To determine if an opportunity is  a rolling hairball, for sure, you can do one of two things:

  • See if it also appeared in the current-quarter pipeline in any quarters prior to the previous one.
  • Look at its stage or forecast category.  If either of those suggest it won’t be closing this quarter, it’s another big hairball indicator.

The more sophisticated way to find them is to examine “stuck opportunity” reports that light-up deals that are moving through pipeline stages too slowly compared to your norms.

But typically, the hairball is a big opportunity hiding in plain sight.  You know it was in last quarter’s pipeline and the quarter before that.  You’ve just been deluded into believing it’s not a hairball.

Fixing Rolling Hairballs

There are two ways to fix rolling hairballs:

  • Fix the close date.  Reps are subtly incented to put deals in the current quarter (e.g., to show they’re working on something, to show they might bring in some big sales this quarter). The manager needs to get on the phone with the customer and, after having verified it’s a real opportunity, get the real timeframe in which it might close.  Assigning a realistic close date to the opportunity makes your pipeline more real and reminds the rep that they need to be working on other shorter-term opportunities as well.  (There is no mid-term if you fail enough in the short term.)  The deal will still remain in the all-quarters pipeline, but it won’t always be in the current-quarter pipeline, ever-sliding, and distorting metrics and ratios.

 

  • Fix the size. While a realistic close date is the best solution, what makes rolling hairballs dangerous is their size.  So, if the salesrep really believes it’s a current-quarter opportunity, you can either reduce its size or split it into two opportunities (particularly if that’s a possible outcome), a small one in the current quarter along with an upsell in the future.  Note that this approach can be dangerous, with lots of little hairball-lets flying below radar, so you should only try if it you’re sure your salesops team can produce the reports to find them and if you believe it reflects real customer buying patterns.

Don’t let rolling hairballs pollute your pipeline metrics and ratios.  Admit they exist, find them, and fix them.  Your sales and sales forecasting will be more consistent as a result.

A Look at the Tintri S-1

Every now and then I take a dive into an S-1 to see what clears the current, ever-changing bar for going public.  After a somewhat rocky IPO process, Tintri went public June 30 after cutting the IPO offering price and has traded flat thus far since then.

Let’s read an excerpt from this Business Insider story before taking a look at the numbers.

Before going public, Tintri had raised $260 million from venture investors and was valued at $800 million.

With the performance of this IPO, the company is now valued at about about $231 million, based on $7.50 a share and its roughly 31 million outstanding shares, (if the IPO’s bankers don’t buy their optional, additional roughly 1.3 million shares.)

In other words, this IPO killed a good $570 million of the company’s value.

In other words, Tintri looks like a “down-round IPO” (or an “IPO of last resort“) — something that frankly almost never happened before the recent mid/late stage private valuation bubble of the past 4 years.

Let’s look at some numbers.

tintri p+l

Of note:

  • $125M in FY2017 revenue.  (They have scale, but this is not a SaaS company so the revenue is mostly non-recurring, making it easier to get to grow quickly and making the revenue is worth less because only the support/maintenance component of it renews each year.)
  • 45% YoY total revenue growth.  (On the low side, especially given that they have a traditional license/maintenance model and recognize revenue on shipment.)
  • 65% gross margins  (Low, but they do seem to sell flash memory hardware as part of their storage solutions.)
  • 87% of revenue spent on S&M (High, again particularly for a non-SaaS company.)
  • 43% of revenue spent on R&D  (High, but usually seen as a good thing if you view the R&D money as well spent.)
  • -81% operating margins (Low, particularly for a non-SaaS company.)
  • -$70.4M in cashflow from operating activities in 2017 ($17M average quarterly cash burn from operations)
  • Incremental S&M / incremental product revenue = 73%, so they’re buying $1 worth of incremental (YoY) revenue for an incremental 73 cents in S&M.  Expensive but better than some.

Overall, my impression is of an on-premises (and to a lesser extent, hardware) company in SaaS clothing — i.e., Tintri’s metrics look like a SaaS company, but they aren’t so they should look better.  SaaS company metrics typically look worse than traditional software companies for two reasons:  (1) revenue growth is depressed by the need to amortize revenue over the course of the subscription and (2) subscriptions companies are willing to spend more on S&M to acquire a customer because of the recurring nature of a subscription.

Concretely, if you compare two 100-unit customers, the SaaS customer is worth twice the license/maintenance customer over 5 years.

saas compare

Moreover, even if Tintri were a SaaS company, it is quite out of compliance with the Rule of 40, that says growth rate + operating margin >= 40%.  In Tintri’s case, we get -35%, 45% growth plus -81% operating margin, so they’re 75 points off the rule.

Other Notes

  • 1250+ customers
  • 21 of the Fortune 100
  • 527 employees as of 1/31/17
  • CEO 2017 cash compensation $525K
  • CFO 2017 cash compensation $330K
  • Issued special retention stock grants in May 2017 that vest in the two years following an IPO
  • Did option repricing in May 2017 to $2.28/share down from weighted average exercise price of $4.05.
  • $260M in capital raised prior to IPO
  • Loans to CFO and CEO to exercise stock options at 1.6% to 1.9% interest in 2013
  • NEA 22.7% ownership prior to opening
  • Lightspeed 14.5% ownership
  • Insight Venture Partners 20.2% ownership
  • Silver Lake 20.4% ownership
  • CEO 3.8% ownership
  • CFO 0.7% ownership
  • $48.9M in long-term debt
  • $13.8M in 2017 stock-based compensation expense

Overall, and see my disclaimers, but this is one that I’ll be passing on.

 

The New 2017 Gartner Magic Quadrants for Cloud Strategic CPM (SCPM) and Cloud Financial CPM (FCPM) – How to Download; A Few Thoughts

For some odd reason, I always think of this scene — The New Phone Book’s Here – from an old Steve Martin comedy whenever Gartner rolls out their new Magic Quadrants (MQ) for corporate performance management (CPM). It’s probably because all of the excitement they generate.

Last year, Gartner researchers John Van Decker and Chris Iervolino kept that excitement up by making the provocative move of splitting the CPM quadrant in two — strategic CPM (SCPM) and financial CPM (FCPM). Never complacent, this year they stirred things up again by inserting the word “cloud” before the category name for each; we’ll discuss the ramifications of that in a minute.

Free Download of 2017 CPM Magic Quadrants

But first, let me provide some links where you can download the new FCPM and SCPM magic quadrants:

Significance of the New 2017 FPCM and SCPM Magic Quadrants

The biggest change this year is the insertion of the word “cloud” in the title of the magic quadrants.  This perhaps seemingly small change, like a butterfly effect, results in an entirely new world order where two of the three megavendors in the category (i.e., IBM, SAP) get displaced from market leadership due to the lack of the credibility and/or sophistication of their cloud offerings.

For example:

  • In the strategic CPM quadrant, IBM is relegated to the Visionary quadrant (bottom right) and SAP does not even make the cut.
  • In the financial CPM quadrant, IBM is relegated to the Challenger quadrant (top left) and SAP again does not even make the cut.

Well, I suppose one might then ask, well if IBM and SAP do poorly in the cloud financial and strategic CPM magic quadrants, then how do they do in the “regular” ones?

To which the answer is, there aren’t any “regular” ones; they only made cloud ones.  That’s the point.

So I view this as the mainstreaming of cloud in EPM [1].  Gartner is effectively saying a few things:

  • Who cares how much maintenance fees a vendor derives from legacy products?
  • The size of a vendor’s legacy base is independent of its position for the future.
  • The cloud is now the norm in CPM product selection, so it’s uninteresting to even produce a non-cloud MQ for CPM. The only CPM MQs are the cloud ones.

While I have plenty of beefs with Oracle as a prospective business partner — and nearly as many with their cloud EPM offerings — to their credit, they have been making an effort at cloud EPM while IBM and SAP seem to have somehow been caught off-guard, at least from an EPM perspective.

(Some of Oracle’s overall cloud revenue success is likely cloudwashing though they settled a related lawsuit with the whistleblower so we’ll never know the details.)

Unlikely Bedfellows:  Only Two Vendors are Leaders in Both FCPM and SCPM Magic Quadrants

This creates the rather odd situation where there are only two vendors in the Leaders section of both the financial and strategic CPM magic quadrants:  Host Analytics and Oracle.  That means only two vendors can provide the depth and breadth of products in the cloud to qualify for the Leaders quadrant in both the FCPM and SCPM MQ.

I know who I’d rather buy from.

In my view, Host Analytics has a more complete, mature, and proven product line – we’ve been at this a lot longer than they have — and, well, oligopolists aren’t really famous for their customer success and solutions orientation.  More infamous, in fact.  See the section of the FCPM report where it says Oracle ranks in the “bottom 25% of vendors in this MQ on ‘overall satisfaction with vendor.’”

Or how an Oracle alumni once defined “solution selling” for me:

Your problem is you are out of compliance with the license agreement and we’re going to shut down the system.  The solution is to give us money.

Nice.

For more editorial, you can read John O’Rourke’s post on the Host Analytics corporate blog.

Download the 2017 FCPM and SCPM Magic Quadrants

Or you can download the new 2017 Gartner CPM MQs here.

# # #

Notes:

[1] Gartner refers to the category as corporate performance management (CPM).  I generally refer to it as enterprise performance management (EPM), reflecting the fact that EPM software is useful not only for corporations, but other forms of organization such as not-for-profit, partnerships, government, etc.  That difference aside, I generally view EPM and CPM as synonyms.

The Role of Professional Services in a SaaS Business

I love to create reductionist mission statements for various departments in a company.  These are designed to be ultra-compact and potentially provocative.  My two favorite examples thus far:

I like to make them based on real-life situations, e.g., when someone running a department seems confused about the real purpose of their team.

For example, some police-oriented HR departments seem to think their mission is protect employees from management.  Think: “Freeze, you can’t send an email like that; put your hands in the air and step away from the keyboard!”

I think otherwise. If the HR team conceptualizes itself as “helping managers manage,” it will be more positively focused, help deliver better results, and be a better business partner — all while protecting employees from bad managers (after all, mistreating employees is bad management).

Over the past year, I’ve developed one of these pithy mission statements for professional services, also known as consulting, the (typically billable) experts employed by a software company who work with customers on implementations after the sale:

Professsional services exists to maximize ARR while not losing money.

Maximizing ARR surprises some people.  Why say that in the context of professional services?  Sales brings in new ARR.  Customer Success (or Customers for Life) is reponsible for the maintenance and expansion of existing ARR.  Where does professional services fit in?  Shouldn’t they exist to drive successful implementations or to achieve services revenue targets?  Yes, but that’s actually secondary to the primary mission.

The point of a SaaS business is to maxmize enterprise value and that value is a function of ARR.  If you could maximize ARR without a professional services team then you wouldn’t have one at all (and some SaaS firms don’t).  But if you’re going to have a professional services team, then they — like everybody else — should be there to maximize ARR.  How does professional services help maximize ARR?  They:

  • Help drive new ARR by supporting sales — for example, working with sales to draft a statement of work and by building confidence that the company can solve the customer’s problem.  If you remember that customers buy “holes, not bits” you’ll know that a SaaS subscription, by itself, doesn’t solve any business problem.  The importance of the consultants who do the solution mapping is paramount.
  • Help preserve/expand existing ARR by supporting the Customer Success (aka, the Customers for Life) team, either by repairing blown implementations or by doing new or expanded implementations at existing customers.  This could entail anything from a “save” to a simple expansion, but either way, professional services is there maximizing ARR.
  • Help do both by enabling the partner ecosystem.  Professional services is key to enabling partners who can both provide quality implementation services for customers and who can extend the vendor’s reach through go-to-market partnering.

Or, as our SVP of Services at Host Analytics says, “our role is to make happy customers.”

I prefer to say “maximize ARR without losing money” but we’re very much on the same page.  Let’s finish with the “not losing money” part.  In my opinion,

  • A typical on-premises software vendor drove 25% to 30% gross margins on professional services.  Those were the days one big one-shot license fees and huge multi-million dollar implementations.  In those days, customers weren’t necessarily too happy but the services team had a strong “make money” aspect to its mission.
  • A typical SaaS vendors have negative 20% to negative 10% gross margins on services (and sometimes a lot more negative than that).  That’s because some vendors subsidize their ARR with free or heavily discounted services because ARR recurs whereas services revenue does not.

I believe that professional services has real value (e.g., our team at Host Analytics is amazing) and that if you’re driving 0% to 5% gross margins with such a team that you are already supporting the ARR pool with discounted services (you could be running 25% to 30% margins).  Whether you make 0% or 10% doesn’t much matter — because it won’t to someone valuing your company — but I think it’s a mistake to shoot for the 30% margins of yore as well as a mistake to tolerate -50% margins and completely de-value your services.

Don’t Start a Customer Relationship with a Lie

As a manager, I like to make sure that every quarter that each of my direct reports has written, agreed-to goals.  I collect these goals in a Word document, but since that neither scales nor cascades well, I’ve recently been looking for a simple SaaS application to manage our quarterly Objectves and Key Results (OKRs).

What I’ve found, frankly, is a bit shocking.

Look, this is not the world’s most advanced technical problem.  I want to enter a goal (e.g., improve sales productivity) and associate 1-3 key results with that goal (e.g., improve ARR per salesrep from $X to $Y).  I have about 10 direct reports and want to assign 3-5 OKRs per quarter.  So we’re talking 30-50 objectives with maybe 60-100 associated key results for my little test.

I’d like some progress tracking, scoring at the end of the quarter, and some basic reporting.  (I don’t need thumbs-ups, comments, and social features.)  If the app works for the executive team, then I’ll probably scale it across the company, cascading the OKRs throughout the organization, tracking maybe 1,200 to 1,500 objectives per quarter in total.

This is not rocket science.

Importantly, I figure that if I want to roll this out across the entire team, the app better be simple enough for me to just try it without any training, presentations, demos, or salescalls. So I decide to go online and start a trial going with some SaaS OKR management providers.

Based on some web searches, PPC ads, and website visits, I decide to try with three vendors (BetterWorks, 15Five, and 7Geese).  While I’m not aiming to do a product or company comparison here, I had roughly the same experience across all three:

  • I could not start a free trial online
  • I was directed to an sales development rep (SDR) or account exec (AE) before getting a trial
  • That SDR or AE tried to insist on a phone call with me before giving me the trial
  • The trial itself was quite limited — e.g., 15 or 30 days.

At BetterWorks, after getting stuck with the SDR, I InMailed the CEO asking for an SDR-bypass and got one (thanks!) — but I found the application not intuitive and too hard to use.  At 7Geese, I got directed to an AE who mailed me a link to his calendar and wanted to me to setup a meeting.  After grumbling about expectations set by the website, he agreed to give me a trial.  At 15Five, I got an SDR who eventually yielded after I yelled at him to let me “follow my own buyer journey.”

But the other thing I noticed is that all three companies started our relationship with a lie of sorts.  What lie?  In all three cases they implied that I’d have easy access to a free trial.  Let’s see.

If you put a Free Trial button on your website, when I press it I expect to start an online process to get a free trial — not get a form that, once filled, replies that someone will be in touch.  That button should be called Contact Us, not Free Trial.

7Geese was arguably more misleading.  While the Get Started button down below might imply that you’re starting the process of getting access to a trial, the Get Started Now button on the top right says, well, NOW.

Worse yet, if you press the Get Started Now button on 7Geese, you get this screen next.

Tailored tour?  I pressed a button called Get Started Now.  I don’t want to setup a demo.  I want to get started using their supposedly “simple” OKR tracking app.

15Five was arguably the most misleading.

When you write “14 days free. No credit card needed.” I am definintely thinking that when I press Get Started that I’ll be signing up for a free 14-day trial on the next screen.  Instead I get this.

I didn’t ask to see if 15Five was right for my company.  I pressed a button that advertised a 14-day free trial with no credit card required.

Why, in all three cases, did these companies start our relationship by lying to me?  Probably, because in all three cases their testing determined that the button would be clicked more if it said Get Started or Frial Trial than if it said something more honest like Contact Us or  Request Free Trial.

They do get more clicks, I’m sure.  But those clicks start the relationship on a negative note by setting an expectation and immediately failing to meet it.

I get that Free Trials aren’t always the best way to market enterprise software.  I understand that the more complicated the application problem, the less a Free Trial is effective or even relevant.  That’s all fine.  If you haven’t built a viral product or work in a consumer-esque cateogry, that’s fine.  Just don’t promise a Free Trial on your website.

But when you’re in a category where the problem is pretty simple and you promise a Free Trial on your website, then I expect to get one.  Don’t start our relationship with a lie.  Even if your testing says you’ll get more clicks — because all you’ll be doing is telling more lies and starting more customer relationships on the wrong foot.

The Evolution of Marketing Thanks to SaaS

I was talking with my friend Tracy Eiler, author of Aligned to Achieve, the other day and she showed me a chart that they were using at InsideView to segment customers.  The chart was a quadrant that mapped customers on two dimensions:  renewal rate and retention rate.  The idea was to use the chart to plot customers and then identify patterns (e.g., industries) so marketing could identify the best overall customers in terms of lifetime value as the mechanism for deciding marketing segmentation and targeting.

Here’s what it looked like:

saas-strategic-value

While I think it’s a great chart, what really struck me was the thinking behind it and how that thinking reflects a dramatic evolution in the role of marketing across my career.

  • Back two decades ago when marketing was measured by leads, they focused on how to cost-effectively generate leads, looking at response rates for various campaigns.
  • Back a decade ago when marketing was measured by opportunities (or pipeline), they focused on how to cost-effectively generate opportunities, looking at response and opportunity conversion rates.
  • Today, as more and more marketers are measured by marketing-sourced New ARR, they are focused on cost-effectively generating not just opportunities, but opportunities-that-close, looking all the way through the funnel to close rates.
  • Tomorrow, as more marketers will be measured on the health of the overall ARR pool, they will be focused on cost-effectively generating not just opportunities-that-close but opportunities that turn into the best long-term customers. (This quadrant helps you do just that.)

As a company makes this progression, marketing becomes increasingly strategic, evolving in mentality with each step.

  • Starting with, “what sign will attract the most people?” (Including “Free Beer Here” which has been used at more than one conference.)
  • To “what messages aimed at which targets will attract the kind of people who end up evaluating?”
  • To “who are we really looking to sell to — which people end up buying the most and the most easily – and what messages aimed at which targets will attract them?”
  • To “what are the characteristics of our most successful customers and how can we find more people like them?”

The whole pattern reminds me of the famous Hubspot story where the marketing team was a key part forcing the company to focus on either “Owner Ollie” (the owner of a <10 person business) or “Manager Mary” (a marketer at a 10 to 1000 person business).  For years they had been serving both masters poorly and by focusing on Manager Mary they were able to drive a huge increase in their numbers that enabled cost-effectively scaling the business and propelling them onto a successful IPO.

hubspot

What kind of CMO does any CEO want on their team?  That kind.  The kind worried about the whole business and looking at it holistically and analytically.

A Fresh Look at How to Measure SaaS Churn Rates

[Editor’s note:  revised 3/27/17 with changes to some definitions.]

It’s been nearly three years since my original post on calculating SaaS renewal rates and I’ve learned a lot and seen a lot of new situations since then.  In this post, I’ll provide a from-scratch overhaul on how to calculate churn in an enterprise SaaS company [1].

While we are going to need to “get dirty” in the detail here, I continue to believe that too many people are too macro and too sloppy in calculating these metrics.  The details matter because these rates compound over time, so the difference between a 10% and 20% churn rate turns into a 100% difference in cohort value after 7 years [2].  Don’t be too busy to figure out how to calculate them properly.

The Leaky Bucket Full of ARR

I conceptualize SaaS companies as leaky buckets full of annual recurring revenue (ARR).  Every time period, the sales organization pours more ARR into the bucket and the customer success (CS) organization tries to prevent water from leaking out [3].

This drives the leaky bucket equation, which I believe should always be the first four lines of any SaaS company’s financial statements:

Starting ARR + new ARR – churn ARR = ending ARR

Here’s an example, where I start with those four lines, and added two extra (one to show a year over year growth rate and another to show “net new ARR” which offsets new vs. churn ARR):

leaky

For more on how to present summary SaaS startup financials, go here.

Half-Full or Half-Empty:  Renewals or Churn?

Since the renewal rate is simply one minus the churn rate, the question is which we should calculate?  In the past, I favored splitting the difference [4], whereas I now believe it’s simpler just to talk about churn.  While this may be the half-empty perspective, it’s more consistent with what most people talk about and is more directly applicable, because a common use of a churn rate is as a discount rate in a net present value (NPV) formula.

Thus, I now define the world in terms of churn and churn rates, as opposed to renewals and renewal rates.

Terminology: Shrinkage and Expansion

For simplicity, I define the following two terms:

  • Shrinkage = anything that makes ARR decrease. For example, if the customer dropped seats or was given a discount in return for signing a multi-year renewal [5].
  • Expansion = anything that makes ARR increase, such as price increases, seat additions, upselling from a bronze to a gold edition, or cross-selling new products.

Key Questions to Consider

The good news is that any churn rate calculation is going to be some numerator over some denominator.  We can then start thinking about each in more detail.

Here are the key questions to consider for the numerator:

  • What should we count? Number of accounts, annual recurring revenue (ARR), or something else like renewal bookings?
  • If we’re counting ARR should we think at the product-level or account-level?
  • To what extent should we offset shrinkage with expansion in calculating churn ARR? [6]
  • When should we count what? What about early and late renewals?  What about along-the-way expansion?  What about churn notices or non-payment?

Here are the key questions to consider for the denominator:

  • Should we use the entire ARR pool, that portion of the ARR pool that is available to renew (ATR) in any given time period, or something else?
  • If using the ATR pool, for any given renewing contract, should we use its original value or its current value (e.g., if there has been upsell along the way)?

What Should We Count?  Logos and ARR

I believe the two metrics we should count in churn rates are

  • Logos (i.e., number of customers). This provides a gross indication of customer satisfaction [7] unweighted by ARR, so you can answer the question:  what percent of our customer base is turning over?
  • This provides a very important indication on the value of our SaaS annuity.  What is happening to our ARR pool?

I would stay completely away from any SaaS metrics based on bookings (e.g., a bookings CAC, TCV, or bookings-based renewals rate).  These run counter to the point of SaaS unit economics.

Gross and Net Shrinkage; Account-Level Churn

Let’s look at a quick example to demonstrate how I now define gross and net shrinkage as well as account-level churn [8].

gross and net shrinkage

Gross shrinkage is the sum of all the shrinkage. In the example, 80 units.

Net shrinkage is the sum of the shrinkage minus the sum of the expansion. In the example, 80-70 = 10 units.

To calculate account-level churn, we proceed, account by account, and look at the change in contract value, separating upsell from the churn.  The idea is that while it’s OK to offset shrinkage with expansion within an account that we should not do so across accounts when working at the account level [9].  This has the effect of splitting expansion into offset (used to offset shrinkage within an account) and upsell (leftover expansion after all account-level shrinkage has been offset).  In the example, account-level churn is 30 units.

Make the important note here that how we calculate you churn – and specifically how we use expansion ARR to offset shrinkage—not only affects our churn rates, but our reported upsell rates as well.  Should we proudly claim 70 units of upsell (and less proudly 80 units of churn), 30 units of churn and 20 of upsell, or simply 10 units of churn?  I vote for the second.

While working at the account-level may seem odd, it is how most SaaS companies work operationally.  First, because they charter customer success managers (CSMs) to think at the account level, working account by account doing everything they can to preserve and/or increase the value of the account.  Second, because most systems work at and finance people think at the account level – e.g., “we had a customer worth 100 units last year, and they are worth 110 units this year so that means upsell of 10 units.  I don’t care how much is price increase vs. swapping some of product A for product B.” [11]

So, when a SaaS company reports “churn ARR,” in its leaky bucket analysis, I believe they should report neither gross churn nor net churn, but account-level churn ARR.

Timing Issues and the Available to Renew (ATR) Concept

Churn calculations bring some interesting challenges such as early/late renewals, churn notices, non-payment, and along-the-way expansion.

A renewals booking should always be taken in the period in which it is received.  If a contract expires on 6/30 and the renewal is received in on 6/15 it should show up in 2Q and if received on 7/15 it should up in 3Q.

For churn rate calculations, however, the customer success team needs to forecast what is going to happen for a late renewal.  For example, if we have a board meeting on 7/12 and a $150K ARR renewal due 6/30 has not yet been happened, we need to proceed based on what the customer has said.  If the customer is actively using the software, the CFO has promised a renewal but is tied up on a European vacation, I would mark the numbers “preliminary” and count the contract as renewed.  If, however, the customer has not used the software in months and will not return our phone calls, I would count the contract as churned.

Suppose we receive a churn notice on 5/1 for a contract that renews on 6/30.  When should we count the churn?  A Bessemer SaaS fanatic would point to their definition of committed monthly recurring revenue (CMRR) [12] and say we should remove the contact from the MRR base on 5/1.  While I agree with Bessemer’s views in general — and specifically on things like on preferring ARR/MRR to ACV and TCV — I get off the bus on the whole notion of “committed” ARR/MRR and the ensuing need to remove the contract on 5/1.  Why?

  • In point of fact the customer has licensed and paid for the service through 6/30.
  • The company will recognize revenue through 6/30 and it’s much easier to do so correctly when the ARR is still in the ARR base.
  • Operationally, it’s defeatist. I don’t want our company to give up and say “it’s over, take them out of the ARR base.” I want our reaction to be, “so they think they don’t want to renew – we’ve got 60 days to change their mind and keep them in.” [13]

We should use the churn notice (and, for that matter, every other communication with the customer) as a way of improving our quarterly churn forecast, but we should not count churn until the contract period has ended, the customer has not renewed, and the customer has maintained their intent not to renew in coming weeks.

Non-payment, while hopefully infrequent, is another tricky issue.  What do we do if a customer gives us a renewal order on 6/30, payable in 30 days, but hasn’t paid after 120?  While the idealist in me wants to match the churn ARR to the period in which the contract was available to renew, I would probably just show it as churn in the period in which we gave up hope on the receivable.

Expansion Along the Way (ATW)

Non-payment starts to introduce the idea of timing mismatches between ARR-changing events and renewals cohorts.  Let’s consider a hopefully more frequent case:  ARR expansion along the way (ATW).  Consider this example.

ATW expansion

To decide how to handle this, let’s think operationally, both about how our finance team works and, more importantly, about how we want our customer success managers (CSMs) to think.  Remember we want CSMs to each own a set of customers, we want them to not only protect the ARR of each customer but to expand it over time.  If we credit along-the-way upsell in our rate calculations at renewal time, we shooting ourselves in the foot.  Look at customer Charlie.  He started out with 100 units and bought 20 more in 4Q15, so as we approach renewal time, Charlie actually has 120 units available to renew (ATR), not 100 [14].  We want our CSMs basing their success on the 120, not the 100.  So the simple rule is to base everything not on the original cohort but on the available to renew (ATR) entering the period.

This begs two questions:

  • When do we count the along-the-way upsell bookings?
  • How can we reflect those 40 units in some sort of rate?

The answer to the first question is, as your finance team will invariably conclude, to count them as they happen (e.g., in 4Q15 in the above example).

The answer to the second question is to use a retention rate, not a churn rate.  Retention rates are cohort-based, so to calculate the net retention rate for the 2Q15 cohort, we divide its present value of 535 by its original value of 500 and get 107%.

Never, ever calculate a retention rate in reverse – i.e., starting a group of current customers and looking backwards at their ARR one year ago.  You will produce a survivor biased answer which, stunningly, I have seen some public companies publish.  Always run cohort analyses forwards to eliminate survivor bias.

Off-Cycle Activity

Finally, we need to consider how to address off-cycle (or extra-cohort) activity in calculating churn and related rates.  Let’s do this by using a big picture example that includes everything we’ve discussed thus far, plus off-cycle activity from two customers who are not in the 2Q16 ATR cohort:  (1) Foxtrot, who purchased in 3Q14, renewed in 3Q15, and who has not paid, and (2) George, who purchased in 3Q15, who is not yet up for renewal, but who purchased 50 units of upsell in 2Q16.

big picture

Foxtrot should count as churn in 2Q16, the period in which we either lost hope of collection (or our collections policy dictated that collection we needed to de-book the deal). [15]

George should count as expansion in 2Q16, the period in which the expansion booking was taken.

The trick is that neither Foxtrot nor George is on a 2Q renewal cycle, so neither is included in the 2Q16 ATR cohort.  I believe the correct way to handle this is:

  • Both should be factored into gross, net, account-level churn, and upsell.
  • For rates where we include them in the numerator, for consistency’s sake we must also include them in the denominator. That means putting the shrinkage in the numerator and adding the ATR of a shrinking (or lost) account in denominator of a rate calculation.  I’ll call this the “+” concept, and define ATR+ as inclusive of such additional logos or ARR resulting from off-cycle accounts [16].

Rate Calculations

We are now in the position to define and calculate the churn rates that I use and track:

  • Simple churn rate = net shrinkage / starting period ARR * 4.  Or, in English, the net change in ARR from existing customers divided by starting period ARR (multiplied by 4 to annualize the rate which is measured against the entire ARR base). As the name implies, this is the simplest churn rate to calculate. This rate will be negative whenever expansion is greater than shrinkage. Starting period ARR includes both ATR and non-ATR contracts (including potentially multi-year contracts) so this rate takes into account the positive effects of the non-cancellability of multi-year deals.  Because it takes literally everything into account, I think this is the best rate for valuing the annuity of your ARR base.
  • Logo churn rate = number of discontinuing logos / number of ATR+ logos. This rate tells us the percent of customers who, given the chance, chose to discontinue doing business with us.  As such, it provides an ARR-unweighted churn rate, providing the best sense of “how happy” our customers are, knowing that there is a somewhat loose correlation between happiness and renewal [16].  Remember that ATR+ means to include any discontinuing off-cycle logos, so the calculation is 1/16 = 6.3% in our example.
  • Retention rate = current ARR [time cohort] / time-ago ARR [time cohort]. In English, the current ARR from some time-based cohort (e.g., 2Q15) divided by the year-ago ARR from that same cohort.  Typically we do this for the one-year-ago or two-years-ago cohorts, but many companies track each quarter’s new customers as a cohort which they measure over time.  Like simple churn, this is a great macro metric that values the ARR annuity, all in.
  • Gross churn rate = gross shrinkage / ATR+. This churn rate is important because it reveals the difference between companies that have high shrinkage offset by high expansion and companies which simply have low shrinkage.  Gross churn is a great metric because it simply shows the glass half-empty view:  at what rate is ARR leaking out of your bucket before offset it with refills in the form of expansion ARR.
  • Account-level churn rate = account-level churn / ATR+. This churn rate foots to the reported churn ARR in our leaky bucket analysis (which uses account-level churn), partially offsets shrinkage with expansion at an account-level, and is how most SaaS companies actually calculate churn.  While perhaps counter-intuitive, it reflects a philosophy of examining, at an account basis, what happens to value of our each of our customers when we allow shrinkage to be offset by expansion (which is what we want our CSM reps doing) leaving any excess as upsell.  This should be our primary churn metric.
  • Net churn rate = net shrinkage / ATR+.  This churn rate offsets shrinkage with expansion not at the account level, but overall.  This is similar to the simple churn rate but with the disadvantage of looking only at ATR and not factoring in the positive effects of non-cancellability of multi-year deals.    Ergo, I prefer using the simple churn rate to the net churn rate in valuing the SaaS annuity.

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Notes

[1] Replacing these posts in the process.

[2] The 10% churn group decays from 100 units to 53 in value after 7 years, while the 20% group decays to 26.

[3] We’ll sidestep the question of who is responsible for installed-based expansion in this post because companies answer it differently (e.g., sales, customer success, account management) and the good news is we don’t need to know who gets credited for expansion to calculate churn rates.

[4] Discussing churn in dollars and renewals in rates.

[5] For example, if a customer signed a one-year contract for 100 units and then was offered a 5% discount to sign a three-year renewal, you would generate 5 units of ARR churn.

[6] Or, as I said in a prior post, should I net first or sum first?

[7] And yes, sometimes unhappy customers do renew (e.g., if they’ve been too busy to replace you) and happy customers don’t (e.g., if they get a new key executive with different preferences) but counting logos still gives you a nice overall indication.

[8] Note that I have capitulated to the norm of saying “gross” churn means before offset and thus “net” churn means after netting out shrinkage and expansion.  (Beware confusion as this is the opposite of my prior position where I defined “net” to mean “net of expansion,” i.e., what I’d now call “gross.”)

[9] Otherwise, you can just look at net shrinkage which offsets all shrinkage by all expansion.  The idea of account-level churn is to restrict the ability to offset shrinkage with expansion across accounts, in effect, telling your customer success reps that their job is to, contract by contract, minimize shrinkage and ensure expansion.

[10] “Offset” meaning ARR used to offset shrinkage that ends up neither churn nor upsell.

[11] While this approach works fine for most (inherently single-product) SaaS startups it does not work as well for large multi-product SaaS vendors where the failure of product A might be totally or partially masked by the success of product B.  (In our example, I deliberately had all the shrinkage coming from downsell of product A to make that point.  The product or general manager for product A should own the churn number that product and be trying to find out why it churned 80 units.)

[12] MRR = monthly recurring revenue = 1/12th of ARR.  Because enterprise SaaS companies typically run on an annual business rhythm, I prefer ARR to MRR.

[13] Worse yet, if I churn them out on 5/1 and do succeed in changing their mind, I might need to recognize it as “new ARR” on 6/30, which would also be wrong.

[14] The more popular way of handling this would have been to try and extend the original contract and co-terminate with the upsell in 4Q16, but that doesn’t affect the underlying logic, so let’s just pretend we tried that and it didn’t work for the customer.

[15] Whether you call it a de-booking or bad receivable, Foxtrot was in the ARR base and needs to come out.  Unlike the case where the customer has paid for the period but is not using the software (where we should churn it at the end of the contract), in this case the 3Q15 renewal was effectively invalid and we need to remove Foxtrot from the ARR base at some defined number of days past due (e.g., 90) or when we lose hope of collection (e.g., bankruptcy).

[16] I think the smaller you are the more important this correction is to ensure the quality of your numbers.  As a company gets bigger, I’d just drop the “+” concept whenever it’s only changing things by a rounding error.

[17] Use NPS surveys for another, more precise, way of measuring happiness.  See [7] as well.