Category Archives: Sales

I’ve Got a Crazy Idea:  How About We Focus on Next-Quarter’s Pipeline?

I’m frankly shocked by how many startups treat pipeline as a monolith.

Sample CMO:  “we’re in great shape because we have a total pipeline of $32M covering a forward-four-quarter (F4Q) sales target of $10M, so 3.2x coverage.  Next slide, please.”

Regardless of your view on the appropriate magic pipeline coverage number (e.g., 2x, 3x, 4x), I’ve got a slew of serious problems with this.  What do I think when someone says this?

“Wait, hang on.  How is that pipeline distributed by quarter?  By stage?  By forecast category?  By salesrep?  You can’t just look at it as a giant lump and declare that you’re in great shape because you have 3x the F4Q coverage.  That’s lazy thinking.  And, by the way, you probably don’t even need 3x  the F4Q target, but you sure as hell need 3x this quarter’s coverage [1] and better be building to start next quarter with 3x as well.  You do understand that sales can starve to death and we can go out of business – the whole time with 3x pipeline coverage — if it’s all pipeline that’s 3 and 4 quarters, out?”

I’ve got a crazy idea.  How about as a first step, we stop looking at annual pipeline [2] and start looking at this-quarter pipeline and, most importantly, next-quarter pipeline?

What people tell me when I say this:  “No, no, Dave.  We can’t do that.  That’s myopic.  You need to look further out.  You can’t drive looking at the hood ornament.  Plus, with a 90-day average sales cycle (ASC) there’s nothing we can do anyway about the short term.  You need to think big picture.”

I then imagine the CMO talking to the head of demandgen:  “Yep, it’s week 1 and we only have 2.1x pipeline coverage.  But with a 90-day sales cycle, there’s nothing we can do.  Looks like we’re going to hit the iceberg.  At least we made our 3x coverage OKR on a rolling basis.  Hey, let’s go grab a flat white.”

I loathe this attitude for several reasons:

  • It’s parochial. The purpose of marketing OKRs is to enable sales to hit sales OKRs.  Who cares if marketing hit its pipeline OKR but sales is nevertheless flying off a cliff?  Marketing just had a poorly chosen OKR.
  • It’s defeatist. If “when the going gets tough, the tough get a flat white” is your motto, you shouldn’t work in startup marketing.
  • It’s wrong. The A in ASC stands for average.  Your average sales cycle.  It’s not your minimum sales cycle.  If your average sales cycle is 90 days [3] then you have lots of deals that close faster than 90 days, so instead of getting a flat white marketing should be focused on finding a bunch of those, pronto [4].

Here’s my crazy idea.  Never look at rolling F4Q pipeline again.  It doesn’t matter.  What you really need to do is start every quarter with 3.0x [5] pipeline.  After all, if you started every quarter with 3.0x pipeline coverage wouldn’t that mean you are teed up for success every quarter?  Instead of focusing on the long-term and hoping the short-term works out, let’s continually focus on the short-term and know the long-term will work out.

This brings to mind Kellogg’s fourth law of startups:  you have to survive short-term in order to exist long-term.

This-Quarter Pipeline
This process starts by looking at the this-quarter (aka, current-quarter) pipeline.  While it’s true that in many companies marketing will have a limited ability to impact the current-quarter pipeline — especially once you’re 5-6 weeks in — you should nevertheless always be looking at current-quarter pipeline and current-quarter pipeline coverage calculated on a to-go basis.  You don’t need 3x the plan number every single week; you need 3x coverage of the to-go number to get to plan.  To-go pipeline coverage provides an indicator of confidence in your forecast (think “just how lucky to do we have to get”) and over time the ratio can be used as an alternative forecasting mechanism [6].

this qtr togo

In the above example, we can see a few interesting patterns.

  • We start the quarter with high coverage, but it quickly becomes clear that’s because the pipeline has not yet been cleaned up. Because salespeople are usually “animals that think in 90-day increments” [7], next quarter is effectively eternity from the point of view of most salesreps, so they tend to dump troubled deals in next-quarter [8] regardless of whether they actually have a next-quarter natural close date.
  • Between weeks 1 and 3, we see $2,250K of current-quarter pipeline vaporize as part of sales’ cleanup. Note that $250K was closed – the best way for dollars to exit the pipeline!  I always do my snapshot pipeline analytics in week 3 to provide enough time for sales to clean up before trying to analyze the data.  (And if it’s not clean by week 3, then you have a different conversation with sales [9].)
  • Going forward, we burn off more pipeline to fall into the 2.6 to 2.8 coverage range but from weeks 5 to 9 we are generally closing and burning off pipeline [10] at the same rate – hence the coverage ratio is running in a stable, if somewhat tight, range.

Next-Quarter Pipeline
Let’s now look at next-quarter pipeline.  While I think sales needs to be focused on this-quarter pipeline and closing it, marketing needs to be primarily focused on next-quarter pipeline and generating it.  Let’s look at an example:

next qtr pipe

Now we can see that next-quarter plan is $3,250K and we start this quarter with $3,500K in next-quarter pipeline or 1.1x coverage.  The 1.1x is nominally scary but do recall we have 12 weeks to generate more next-quarter pipeline before we want to start next quarter with 3x coverage, or a total pipeline of $9,750K.  Once you start tracking this way and build some history, you’ll know what your company’s requirements are.  In my experience, 1.5x next-quarter coverage in week 3 is tight but works [11].

The primary point here is that given:

  • Your knowledge of history and your pipeline coverage requirements
  • Your marketing plans for the current quarter
  • The trends you’re seeing in the data
  • Normal spillover patterns

That marketing should be able to forecast next quarter’s starting pipeline coverage.  So, pipeline coverage isn’t just an iceberg that marketing thinks we’ll hit or miss.  It’s something can marketing can forecast.  And if you can forecast it, then you adjust your plans accordingly to do something about it.

Let’s stick with our example and make a forecast for next-quarter starting pipeline [12]

  • Note that we are generating about $250K of net next-quarter pipeline per week from weeks 4 to 9.
  • Assume that we are continuing at steady-state the programs generating that pipeline and ergo we can assume that over the next four weeks we’ll generate another $1M.
  • Assume we are doing a big webinar that we think will generate another $750K in next-quarter pipeline.
  • Assume that 35% of the surplus this-quarter pipeline slips to next-quarter [13]

If you do this in a spreadsheet, you get the following.  Note that in this example we are forecasting a shortfall of $93K in starting next-quarter pipeline coverage.  Were we forecasting a significant gap, we might divert marketing money into demand generation in order to close the gap.

fc next qtr

All-Quarters Pipeline
Finally, let’s close with how I think about all-quarters pipeline.

all qtr

While I don’t think it’s the primary pipeline metric, I do think it’s worth tracking for several reasons:

  • So you can see if pipeline is evaporating or sloshing. When a $1M forecast deal is lost, it comes out of both current-quarter and all-quarters pipeline.  When it slips, however, current-quarter goes down by $1M but all-quarters stays the same.  By looking at current-quarter, next-quarter, and all-quarters at the same time in a compact space you can get sense for what is happening overall to your pipeline.  There’s nowhere to hide when you’re looking at all-quarters pipeline.
  • So you can get a sense for the size of opportunities in your pipeline.  Note that if you create opportunities with a placeholder value then there’s not much  purpose in doing this (which is just one reason why I don’t recommend creating opportunities with a placeholder value) [14].
  • So you can get a sense of your salesreps’ capacity. The very first number I look at when a company is missing its numbers is opportunities/rep.  In my experience, a typical rep can handle 8-12 current-quarter and 15-20 all-quarters opportunities [15].  If your reps are carrying only 5 opportunities each, I don’t know how they can make their numbers.  If they’re carrying 50, I think either your definition of opportunity is wrong or you need to transfer some budget from marketing to sales and hire more reps.

The spreadsheet I used in this post is available for download here.

# # #

Notes

[1] Assuming you’re in the first few weeks of the quarter, for now.

[2] Which is usually done using forward four quarters.

[3] And ASC follows a normal distribution.

[4] Typically, they are smaller deals, or deals at smaller companies, or upsells to existing customers.  But they’re out there.

[5] Or, whatever your favorite coverage ratio is.  Debating that is not the point of this post.

[6] Once you build up some history you can use coverage ratios to predict sales as a way of triangulating on the forecast.

[7] As a former board member always told me — a quote that rivals “think of salespeople as single-celled organisms driven by their comp plan” in terms of pith.

[8] Or sometimes, fourth-quarter which is another popular pipeline dumping ground.  (As is first-quarter next year for the truly crafty.)

[9] That is, one about how they are going to get their shit together and manage the pipeline better, the first piece of which is getting it clean by week 3, often best accomplished by one or more pipeline scrub meetings in weeks 1 and 2.

[10] Burning off takes one of three forms:  closed/won, lost or no-decision, or slipping to a subsequent quarter.  It’s only really “burned off” from the perspective of the current-quarter in the last case.

[11] This depends massively on your specific business (and sales cycle length) so you really need to build up your own history.

[12] Technically speaking, I’m making a forecast for day-1 pipeline, not week-3 pipeline.  Once you get this down you can use any patterns you want to correct it for week 3, if desired.  In reality, I’d rather uplift from week 3 to get day-1 so I can keep marketing focused on generating pipeline for day-1, even though I know a lot will be burned off before I snapshot my analytics in week 3.

[13] Surplus in the sense that it’s leftover after we use what we need to get to plan.  Such surplus pipeline goes three places:  lost/no-decision, next-quarter, or some future quarter.  I often assume 1/3rd  goes to each as a rule of thumb.

[14] As a matter of principle I don’t think an opportunity should have a value associated with it until a salesrep has socialized a price point with the customer.  (Think:  “you do know it cost about $150K per year to subscribe to this software, right?”)  Perversely, some folks create opportunities in stage 1 with a placeholder value only to later exclude stage 1 opportunities in all pipeline analytics. Doing so gets the same result analytically but is an inferior sales process in my opinion.

[15] Once you’re looking at opportunities/rep, you need to not stop with the average but make a histogram.  An 80-opportunity world where 10 reps have 8 opportunities each is a very different world from one where 2 reps have 30 opportunities each and the other 8 have an average of 2.5.

Kellblog's Greatest Hits 2016-2019 per the Appealie SaaS Awards

I’ll be speaking at the APPEALIE 2019 SaaS Conference and Awards in San Francisco on September 25th and I noticed that in their promotions the folks at APPEALIE had assembled their own Kellblog’s Greatest Hits album from 2016 to 2019, complete with its own cover art.
appealie
When I looked at the posts they picked, I thought they did a good job of identifying the best material, so I thought I’d share their list here.  They also called me “a GOAT software blogger” and after playing around with acronyms for about half an hour — maybe Groove, OpenView, AngelVC, Tunguz? — my younger son swung by and said, “they called you a GOAT?  Cool.  It means greatest of all time.”  Cool, indeed.  Thanks.
Here’s the APPEALIE Kellblog’s Greatest Hits 2016-2019 list:

 

Kellblog’s Greatest Hits 2016-2019 per the Appealie SaaS Awards

I’ll be speaking at the APPEALIE 2019 SaaS Conference and Awards in San Francisco on September 25th and I noticed that in their promotions the folks at APPEALIE had assembled their own Kellblog’s Greatest Hits album from 2016 to 2019, complete with its own cover art.

appealie

When I looked at the posts they picked, I thought they did a good job of identifying the best material, so I thought I’d share their list here.  They also called me “a GOAT software blogger” and after playing around with acronyms for about half an hour — maybe Groove, OpenView, AngelVC, Tunguz? — my younger son swung by and said, “they called you a GOAT?  Cool.  It means greatest of all time.”  Cool, indeed.  Thanks.

Here’s the APPEALIE Kellblog’s Greatest Hits 2016-2019 list:

 

Stopping Inception Churn: The Prospective Customer Success Review

I think for many sales-aggressive enterprise SaaS startups, a fair amount of churn actually happens at inception.  For example, back in 2013, shortly after I joined Host Analytics, I discovered that there were a number of deals that sales had signed with customers that our professional services (PS) team had flat out refused to implement.  (Huh?)  Sales being sales, they found partners willing to do the implementations and simply rode over the objections of our quite qualified PS team.

When I asked our generally sales-supportive PS team why they refused to do these implementations, they said, “because there was a 0% chance that the customer could be successful.”  And they, of course, were right.  100% of those customers failed in implementation and 100% of them churned.

I call this “inception churn,” because it’s churn that’s effectively built-in from inception — the customer is sent, along with a partner, on a doomed journey to solve a problem that the system was never designed to solve.  Sales may be in optimistic denial.  Pre-sales consulting knows deep down that there’s a problem, but doesn’t want to admit it — after all, they usually work in the Sales team. Professional services can see the upcoming trainwreck but doesn’t know how to stop it so they are either forced to try and catch the falling anvil or, better yet, duck out and a let partner — particularly a new one who doesn’t know any better — try to do so themselves.

In startups that are largely driven by short-term, sales-oriented metrics, there will always be the temptation to take a high-risk deal today, live to fight another day, and hope that someone can make it work before it renews.  This problem is compounded when customers sign two- or three-year deals [1] because the eventual day of reckoning is pushed into the distant future, perhaps beyond the mean survival expectation of the chief revenue officer (CRO) [2].

Quality startups simply cannot allow these deals to happen:

  • They burn money because you don’t earn back your CAC.  If your customer acquisition cost ratio is 1.5 and your gross margins are 75%, it takes you two years simply to breakeven on the cost of sale.  When a 100-unit customer fails to renew after one year, you spent 175 units [3], receive 100 units, and thus have lost 75 units on the transaction — not even looking at G&A costs.
  • They burn money in professional services.  Let’s say your PS can’t refuse to the implementation.  You take a 100-unit customer, sell them 75 units of PS to do the implementation, probably spend 150 units of PS trying to get the doomed project to succeed, eventually fail, and lose another 75 units in PS.  (And that’s only if they actually pay you for the first 75.)  So on a 100-unit sale, you are now down 150 to 225 units.
  • They destroy your reputation in the market. SaaS startup markets are small.  Even if the eventual TAM is large, the early market is small in the sense that you are probably selling to a close-knit group of professionals, all in the same geography, all doing the same job.  They read the same blogs.  They talk to the same analysts and consultants.  They meet each other at periodic conferences and cocktail parties.  You burn one of these people and they’re going to tell their friends — either via these old-school methods over drinks or via more modern methods such as social media platforms (e.g., Twitter) or software review sites (e.g., G2).
  • They burn out your professional services and customer success teams. Your PS consultants get burned out trying to make the system do something they know it wasn’t designed to do.  Your customer success managers (CSMs) get tired of being handed customers who are DOA (dead on arrival) where there’s virtually zero chance of avoiding churn.
  • They wreck your SaaS metrics and put future financings in danger. These deals drive up your churn rate, reduce your expansion rate, and reduce your customer lifetime value.  If you mix enough of them into an otherwise-healthy SaaS business, it starts looking sick real fast.

So what can we do about all this?  Clearly, some sort of check-and-balance is needed, but what?

  • Pay salespeople on the renewal, so they care if the customer is successful?  Maybe this could work, but most companies want to keep salespeople focused on new sales.
  • Pay the CRO on renewal, so he/she keeps an honest eye on sales and sales management?  This might help, but again, if a CRO is missing new sales targets, he/she is probably in a lot more trouble than missing renewals — especially if he/she can pin the renewal failures on the product, professional services, or partners.
  • Separate the CRO and CCO (Chief Customer Officer) jobs as two independent direct reports to the CEO.  I am a big believer in this because now you have a powerful, independent voice representing customer success and renewals outside of the sales team.  This is a great structure, but it only tells you about the problems after, sometimes quarters or years after, they occur.  You need a process that tells you about them before they occur.

The Prospective Customer Success Review Committee
Detecting and stopping inception churn is hard, because there is so much pressure on new sales in startups and I’m proposing to literally create the normally fictitious “sales prevention team” — which is how sales sometimes refers to corporate in general, making corporate the butt of many jokes.  More precisely, however, I’m saying to create the bad sales prevention team.

To do so, I’m taking an idea from Japanese manufacturing, the Andon Cord, and attaching a committee to it [4].  The Andon Cord is a cord that runs the length of an assembly line that gives the power to anyone working along the line to stop it in order to address problems.  If you see a car where the dashboard is not properly installed, rather than letting it just move down the line, you can pull the cord, stop the line, and get the problem fixed upstream, rather than hoping QA finds it later or shipping a defective product to a customer.

To prevent inception churn, we need two things:

  • A group of people who can look holistically at a high-risk deal and decide if it’s worth taking.  I call that group the Prospective Customer Success Review Committee (the PCSRC).  It should have high-level members from sales, presales, professional services, customer success, and finance.
  • And a means of flagging a deal for review by that committee — that’s the Andon Cord idea.  You need to let everyone who works on deals know that there is a mechanism (e.g., an email list, a field in SFDC) by which they can flag a deal for PCSRC review.  Your typical flaggers will be in either pre-sales or post-sales consulting.

I know there are lots of potential problems with this.  The committee might fail to do its job and yield to pressure to always say yes.  Worse, sales can start to punish those who flag deals such that suspect deals are never flagged and/or that people feel they need an anonymous way to flag them [5].  But these are manageable problems in a healthy culture.

Moreover, simply calling the group together to talk about high-risk deals has two, potentially non-obvious, benefits:

  • In some cases, lower risk alternatives can be proposed and presented back to the customer, to get the deal more into the known success envelope.
  • In other cases, sales will simply stop working on bad deals early, knowing that they’ll likely end up in the PCSRC.  In many ways, I think this the actual success metric — the number of deals that we not only didn’t sign, but where we stopped work early, because we knew the customer had little to no chance of success.

I don’t claim to have either fully deployed or been 100% successful with this concept.  I do know we made great strides in reducing inception churn at Host and I think this was part of it.  But I’m also happy to hear your ideas on either approaching the problem from scratch and/or improving on the basic framework I’ve started here.

# # #

Notes

[1] Especially if they are prepaid.

[2] If CROs last on average only 19 to 26 months, then how much does a potentially struggling CRO actually care about a high-risk deal that’s going to renew in 24 months?

[3] 150 units in S&M to acquire them and 25 units in cost of goods sold to support their operations.

[4] I can’t claim to have gotten this idea working at more than 30-40% at Host.  For example, I’m pretty sure you could find people at the company who didn’t know about the PCSR committee or the Andon Cord idea; i.e., we never got it fully ingrained.  However, we did have success in reducing inception churn and I’m a believer that success in such matters is subtle.  We shouldn’t measure success by how many deals we reject at the meeting, but instead by how much we reduce inception churn by not signing deals that we never should have been signed.

[5] Anonymous can work if it needs to.  But I hope in your company it wouldn’t be required.

Slides From My Presentation at a Private Equity S&M Summit

Just a quick post to share a slide deck I created for a session I did with the top S&M executives at a private equity group’s sales and marketing summit.  We discussed some of my favorite topics, including:

Here are the slides.  Enjoy.

Slides From My Presentation at a Private Equity S&M Summit

Just a quick post to share a slide deck I created for a session I did with the top S&M executives at a private equity group’s sales and marketing summit.  We discussed some of my favorite topics, including:

Here are the slides.  Enjoy.

My Final Verdict on Multi-Year, Prepaid Deals

(Revised 5/4/19, 10:41 AM.)

After years of experience with and thinking about multi-year, prepaid SaaS deals, my mental jury is back in the box and the verdict is in:  if you’re a startup that is within my assumption set below, don’t do them.

Before jumping in, let me first define precisely what I mean by multi-year, prepaid deals and second, detail the assumptions behind my logic in response to some Twitter conversations I’ve had this morning about this post.

What do I Mean by Multi-Year Prepaid Deals?
While there are many forms of “multi-year prepaid deals,” when I use the term I am thinking primarily of a three-year agreement that is fully prepaid.  For example, if a customer’s ARR cost is 100 units for a one-year deal, you might approach them saying something akin to:

By default, our annual contracts have a 10% annual increase built in [1].  If you sign and prepay a three-year agreement, i.e., pay me 300 units within 60 days, then I will lock you in at the 100 units per year price.

Some people didn’t know these kinds of deals were possible — they are.  In my experience, particularly for high-consideration purchases (where the customer has completed a thorough evaluation and is quite sure the system will work), a fairly high percentage of buyers will engage in this conversation.  (In a world where companies have a lot of cash, a 10% return is a lot better than bank interest.)

Multi-year prepaid deals can take other forms as well:

  • The duration can vary:  I’ve seen anything from 2 to 7 years.
  • The contract duration and the prepaid duration can decouple:  e.g., a five-year deal where the first three years are prepaid.

But, to make it simple, just think of a three-year fully prepaid deal as the canonical example.

What are My Underlying Assumptions?
As several readers pointed out, there are some very good reasons to do multi-year prepaid deals [11].  Most of all, they’re a financial win/win for both vendor and customer:  the customer earns a higher rate of return than bank interest and the vendor gets access to capital at a modest cost.

If you’re bootstrapping a company with your own money, have no intention to raise venture capital, and aren’t concerned about complicating an eventual exit to a private equity (PE) or strategic acquirer, then I’d say go ahead and do them if you want to and your customers are game.

However, if you are venture-backed, intend to raise one or more additional rounds before an exit, and anticipate selling to either a strategic or private equity acquirer, then I’d say you should make yourself quite familiar with the following list of disadvantages before building multi-year prepaid deals into your business model.

Why do I Recommend Avoiding Multi-Year Prepaid Deals?
In a phrase, it’s because they’re not the norm.  If you want to raise money from (and eventually sell to) people who are used to SaaS businesses that look a certain way — unless you are specifically trying to disrupt the business model — then you should generally do things that certain way.  Multi-year prepaid deals complicate numerous things and each of those complications will be seen not as endemic to the space, but as idiosyncratic to your company.

Here’s the list of reasons why you should watch out.  Multi-year prepaid deals:

  • Are not the norm, so they raise eyebrows among investors and can backfire with customers [2].
  • Complexify SaaS metrics.  SaaS businesses are hard enough to understand already.  Multi-year deals make metrics calculation and interpretation even more complicated.  For example, do you want to argue with investors that your CAC payback period is not 18 months, but one day?  You can, but you’ll face a great risk of “dying right” in so doing. (And I have done so on more than one occasion [3]).
  • Amplify churn rates. An annual renewal rate [4] of 90% is equivalent to a three-year renewal rate of 72%.  But do you want to argue that, say, 79% is better than 90% [5] or that you should take the Nth root of N-year renewal rates to properly compare them to one-year rates?  You can, but real math is all too often seen as company spin, especially once eyebrows are already raised.
  • Turn your renewals rate into a renewals matrix.  Technically speaking, if you’re doing a mix of one, two, and three-year deals, then your renewal rate isn’t a single rate at all, but a matrix.  Do you want to explain that to investors?

renewals matrix

  • Tee you up for price knock-off at sales time.  Some buyers, particularly those in private equity (PE), will look at the relatively large long-term deferred revenue balance as “cashless revenue” and try to deduct the cost of it from an acquisition price [6].  Moreover, if not discussed up front, someone might try to knock it off what you thought was a final number.
  • Can reduce value for strategic acquirers.  Under today’s rules, for reasons that I don’t entirely understand, deferred revenue seems to get written off (and thus never recognized) in a SaaS acquisition.  So, ceteris paribus, an acquirer would greatly prefer non-prepaid TCV (which it will get to recognize over time) to deferred revenues (which it won’t) [7].
  • Can give pause to strategic acquirers.  Anything that might cause the acquirer to need to start release pro forma financials has the potential to scare them off, particularly one with otherwise pristine financial statements.  For example, having to explain why revenue from a recently acquired startup is shrinking year-over-year might do precisely that [8].
  • Can “inflate” revenues.  Under ASC 606, multi-year, prepaid deals are seen as significant financing events, so — if I have this correct — revenue will exceed the cash received [9] from the customer as interest expense will be recorded and increase the amount of revenue.  Some buyers, particularly PE ones, will see this as another form of cashless revenue and want to deflate your financials to account for it since they are not primarily concerned with GAAP financials, but are more cash-focused.
  • Will similarly inflate remaining performance obligation (RPO).  SaaS companies are increasingly releasing a metric called RPO which I believe is supposed to be a more rigorous form of what one might call “remaining TCV (total contract value)” — i.e., whether prepaid or not, the value of remaining obligations undertaken in the company’s current set of contracts.  If this is calculated on a GAAP basis, you’re going to have the same inflation issue as with revenues when multi-year, prepaid deals are involved.   For example, I think a three-year 100-unit deal done with annual payments will show up as 200 units of RPO but the same deal done a prepaid basis will show up as 200-something (e.g., 210, 220) due to imputed interest.
  • Impede analysis of billings. If you want to go public or get acquired by a public company, financial analysts are going to focus on a metric called calculated billings [10] which is equal to revenue plus the change in deferred revenue for a given time period.  For SaaS purist companies (i.e., those that do only annual contracts with one-year prepays), calculated billings is actually a pretty good measure of new sales.  Multi-year prepays impede analysis of billings because deferred revenue ends up a mishmash of deals of varying lengths and is thus basically impossible to interpret [11].  This could preclude an acquisition by a SaaS purist company [12].

More than anything, I think when you take these factors together, you can end up with complexity fatigue which ultimately takes you back to whether it’s a normal industry practice.  If it were, people would just think, “that’s the complexity endemic in the space.” If it’s not, people think, “gosh, it’s just too darn hard to normalize this company to the ones in our portfolio [13] and my head hurts.”

Yes, there are a few very good reasons to do multi-year, prepaid deals [14], but overall, I’d say most investors and acquirers would prefer if you just raised a bit more capital and didn’t try to finance your growth using customer prepayments.  In my experience, the norm in enterprise software is increasingly converging to three-year deals with annual payments which provide many of the advantages of multi-year deals without a lot of the added complexity [15].

# # #

Notes

[1] While 10% is indeed high, it makes the math easier for the example (i.e., the three-year cost is 331 vs. 300).  In reality, I think 5-6% is more reasonable, though it’s always easier to reduce something than increase it in a negotiation.

[2] Especially if your competition primes them by saying — “those guys are in financial trouble, they need cash, so they’re going to ask you for a multi-year, prepaid deal.  Mark my words!”

[3] Think:  “I know the formula you’re using says ’18 months’ but I’m holding an invoice (or, if you wait 30 days, check) in my hand for more than the customer acquisition cost.”  Or, “remember from b-school that payback periods are supposed to measure risk, no return, and to do so by measuring how long your money is on the table.”  Or, “the problem with your formula is you’re producing a continuous result in a world where you actually only collect modulo 12 months — isn’t that a problem for a would-be ‘payback’ metric?”

[4] Renewal rate = 1 – churn rate

[5] That is, that a 79% three-year rate is ergo better than a one-year 90% renewal rate.

[6] Arguing that while the buyer will get to recognize the deferred revenue over time that the cash has already been collected, and ergo that the purchase price should be reduced by the cost of delivering that revenue, i.e., (COGS %) * (long-term deferred revenue).

[7] Happily, the deferred revenue write-down approach seems to be in the midst of re-evaluation.

[8] If the acquired company does a high percentage of multi-year, prepaid deals and you write off its deferred revenue, it will certainly reduce its apparent growth rate and possibly cause it to shrink on a year-over-year basis.  What was “in the bag revenue” for the acquired company gets vaporized for the acquirer.

[9] Or our other subsidiaries, for a strategic acquirer.

[10]  Known either as billings or calculated billings.  I prefer the latter because it emphasizes that it’s not a metric that most companies publish, but one commonly derived by financial analysts.

[11] We are testing the limits of my accounting knowledge here, but I suppose if deferred revenue is split into current and long-term you might still be able to get a reasonable guestimate for new ARR sales by calculating billings based only on current, but I’m not sure that’s true and worry that the constant flow from long-term to current deferred revenue will impede that analysis.

[12]  A purist SaaS company — and they do exist — would actually see two problems.  First, potential year-over-year shrinkage due to the write-down discussed in footnote [7].  Second, they’d face a dilemma in choosing between the risk associated with immediately transitioning the acquired company’s business to annual-only and the potential pollution of its otherwise pristine deferred revenue if they don’t.

[13] Minute 1:28 of the same video referenced in the prior link.

[14] Good reasons to do multi-year, prepaid deals include:  (a) they are arguably a clever form of financing using customer money, (b) they tend to buy you a second chance if a customer fails in implementation (e.g., if you’ve failed 9 months into a one-year contract, odds are you won’t try again — with a three-year, prepay you might well), (c) they are usually a financing win/win for both vendor and customer as the discount offered exceeds the time value of money.

[15] You do get one new form of complexity which is whether to count payments as renewals, but if everyone is doing 3-year, annual payment deals then a norm will be established.