Marketing is Too Important to be Left to the Marketing Department

Posted on March 28, 2016 | 22 comments

It was HP co-founder, David Packard, of all people, who came up with one of my favorite quotes on marketing, specifically that “marketing is too important to be left to the marketing department.”

This quote is often mentioned in the same breath as these famous Peter Drucker quotes:

  • “Because the purpose of business is to create a customer, the business enterprise has two – and only two – basic functions: marketing and innovation.”
  • “Marketing is not only much broader than selling, it is not a specialized activity at all.  It encompasses the entire business.  It is the whole business seen from the point of view of its final result, that is, from the customer’s point of view.”

I’ve always been a big believer in the last statement — that marketing is the whole business seen from the point of view of the customer — and that statement often guided me during my marketing career, including many years as a CMO.

Marketing isn’t just tactical — it’s also strategic — and the strategic part is why it’s too important to be left to the marketing department (alone).  The CEO can’t confuse delegation with abdication and move all strategy over the marketing department.  On the flip side, too many marketing departments “go tactical” and ignore their strategic obligations and opportunities.

If you distill a SaaS business down to two things, Drucker’s quote is pretty spot on:

  • We acquire customers
  • We deliver them a service

Marketing has both a strategic and tactical role in each.

  • Strategically, marketing can help define the target market, the buyer persona (i.e., the person who we sell to), what problem we solve for them, and why they might want to buy from us.  Marketing can also play an important role in definition of the service, not just looking out for customers (as sales and product management do already) but also by keeping an eye on competitors and market trends.
  • Tactically, over the past 20 years, marketing has been given more and more ownership for creating the sales pipeline.  (See Predictable Revenue or From Impossible to Inevitable.)  While CMOs of the past were largely strategic product marketers with some demandgen chops, CMOs of the future better be ambidextrous when it comes to skills and equally passionate about pipeline generation and product positioning.

Great marketers strive for and achieve a balance between tactical and strategic contribution.  Tactical is table stakes — if you can’t fill the pipeline, the salespeople will come for you with dogs and torches like the villagers in Frankenstein.

pitchforks

Sales preparing to give marketing feedback about insufficient pipeline coverage

But preventing that isn’t the point.

The point is to keep the villagers happy while making a strategic contribution to building a great company.  Which is the part of marketing that’s too important to be left to the marketing department — but which is the part that marketing itself shouldn’t abdicate.

 

22 Comments

Posted in Management, Marketing, Startups

Introducing a New SaaS Metric: The Hype Factor

Posted on March 22, 2016 | 27 comments

I said in yesterday’s post, entitled Too Much Money Makes You Stupid, that while I don’t have much of a beef with Domo, that I did want to observe in today’s fund-to-excess environment that any idea — including making a series of Alec Baldwin would-be viral videos — can sound like a good one.

While I credited Domo with creating a huge hype bubble through secrecy and mystery, big events, and raising tremendous amounts of money (yet again today) at unicorn valuations — I also questioned how much (as Gertrude Stein said of Oakland) “there there” Domo has when it comes to the company and its products.

Specifically, I began to wonder how to quantify the hype around a company.  Let’s say that, as organisms, SaaS companies convert venture capital into two things:  annual recurring revenue (ARR) and hype.  ARR has direct value as every year it turns into GAAP revenue.  Hype has value to the extent it creates halo effects that drive interest in the company that ultimately increase ARR. [1]

Hype Factor = Capital Raised / Annual Recurring Revenue

Now, unlike some bloggers, I don’t have any freshly minted MBAs doing my legwork, so I’m going to need to do some very back of the envelop analysis here.

  • Looking at some recent JMP research, I can see that the average SaaS company goes public at around $25M/quarter in revenue, a $100M annual run-rate, and which also suggests an ARR base of around $100M.
  • Looking at this post by Tomasz Tunguz, I can see that the average SaaS company has raised about $100M if you include everyone or $68M if you exclude companies that I don’t really consider enterprise software.

So, back of the envelope, this suggests that 1.5 (=100/68) is a typical capital-to-ARR ratio on the eve of an IPO.  Let’s look at some specific companies for more (all figures are approx as I’m eye-balling off charts in some cases and looking at S-1s in others) [2]:

  • NetSuite:  raised $125M, run-rate at IPO $92M  –> 1.3
  • Cornerstone:  raised $41M, run-rate $44M –> 1.0
  • Box:  raised $430M, run-rate $228M –> 1.8
  • Xactly:  raised $83M, run-rate $50M –> 1.7
  • Workday:  raised $200M, run-rate $168M –> 1.2

There are numerous limitations to this analysis.

  • I do not make any effort to take into account either how much VC was left over on the eve of the IPO or how much debt the company had raised.
  • Capital consumption per category may vary as a function of the category as a CFO friend of mine reminded me today.
  • Some companies don’t break out subscription and services revenue and the ARR run-rate calculations should only apply to subscription.

Since private companies raise capital and burn it down until an IPO, you should expect that the above values represent minima from a lifecycle perspective. (In theory, you’d arrive on IPO day broke, having raised no more cash than you needed to get there.)

So I’m going to rather subjectively assign some buckets based on this data and my own estimates about earlier stages.

  • A hype factor of 1-2 is target
  • A hype factor of 2-3 is good, particularly well before an IPO
  • A hype factor of 3-5 is not good, too much hype and too little ARR
  • A hype factor of 5+ suggests there is very little “there there” at all.

I know of at least one analytics company where I suspect the hype factor is around 10.   If I had to take a swag at Domo’s hype factor based on the comments in this interview:

  • Quote from the article:  “contracted revenue is $100M.”  Hopefully this means ARR and not TCV.
  • Capital raised:  $613M per Crunchbase, including today’s round.

This suggests Domo’s hype factor is 6.1 including today’s capital and 4.8 excluding it.  So if you’ve heard of Domo, think they are cool, are wowed by the speakers and rappers at Domopalooza, you should be.  As I like to say:  behind every marketing genius, there is usually a massive budget. [3]

Domo’s spending heavily, that’s for sure.  How efficient they are at converting that spending to ARR remains to be seen.  My instinct, and this rough math, says they are more efficient at generating hype than revenue. [4]

Time will tell.  Gosh, life was simpler (if less interesting) when companies went public at $30M.

# # #

Notes

[1] In a sense, I’m arguing that hype takes two forms:  good hype that drives ARR and wasted hype that simply makes the company, like the Kardashians, famous for being famous.

[2] And having some trouble making the different data sources foot.  For example, the SFSF S-1 indicates $45M in convertible preferred stock, but the Tunguz post suggests $70M.  Where’s my freshly minted MBA to help?

[3] You can argue that the first step in marketing genius is committing to spend large amounts of money and I won’t debate you.  But I do think many people completely overlook the massive spend behind many marketing geniuses and, from a hype factor perspective, forget that the purpose of all that genius is not to impress TechCrunch and turn B2B brands into household words, but to win customers and drive ARR.

[4] Note that Domo says they have $200M in the bank unspent which, if true, both skews this analysis and prompts the question:  why raise more money at a flat valuation in smaller quantity when you don’t need it?  While my formula deliberately does not take cash or debt into account (because it’s hard enough to just triangulate on ARR at private companies), if you want to factor that claim into the math, I think you’d end up with a hype factor of 3-4.  (You can’t exclude all the cash because every startup keeps cash on hand to fund them through to their next round.)

27 Comments

Posted in BI, Bubbles, Entrepreneurship, Startups, VC

Too Much Money Makes You Stupid — Let’s Make an Alec Baldwin Viral Video

Posted on March 21, 2016 | 2 comments

There are two sayings I like when it comes to the unicorn bubble:

  • “Too much money makes you stupid”
  • “Any idea’s a good one when you’ve got $100M burning a hole in your pocket.”

Startups are supposed to be focused.  Startups are supposed to need to prioritize ideas and opportunities.  Just as startups weren’t supposed to buy Superbowl ads, startups aren’t supposed to have hundreds of millions of dollars to plow through in the name of creating brand mystique either via huge-budget events like Domo’s Domopalooza or would-be viral videos, like the one below.

But wait, you protest, didn’t Salesforce always do aggressive marketing and wasn’t that risk-taking part of their greatness?  Well, yes and no.  A good part of their early marketing was guerrilla PR done on the cheap.  Yes, they also ran big events, but they mostly found a way to pay for them — Salesforce raised $53M in VC before going public.  Domo has raised nearly 10x that.

Now, I have no particular beef with Domo. Other than being next-generation BI, I must admit to always having had some trouble figuring out what they do — in part due to the abnormal secrecy they had in their early days.  I know they don’t compete with Host Analytics so I have no beef there.  I also know they have sexed-up the BI category a bit, and they’ve certainly done a great job of positioning themselves as a cool company and have created a lot of buzz in the market.

But at what cost?

Domo has raised $483M.  It does cause one to wonder about their capital-to-ARR ratio, which is a great overall capital efficiency metric and one that no ever seems to talk about.

  • While I don’t know in Domo’s case, I’d guess for many unicorns that this ratio is 10 to 20x — where the company is running a kind of perpetual motion machine strategy where you generate the Halo Effects hoping to drive the sales that justify the valuation that you got on your last financing.  This strategy, as many will discover, works well until it doesn’t.  If the epitaph of Bubble 1.0 was about Network Effects, that of Bubble 2.0 will be about Halo Effects.  Remember Warren Buffet’s famous quote:  “only when the tide goes out can you see who’s swimming naked.”
  • I know for a reasonably capital-efficient SaaS business the capital-to-ARR ratio might be 2-3x.  Perhaps an order of magnitude difference.

Back to our core topic — what’s an example of something that looks like a good idea when you have $483M burning a hole in your pocket that, well, might not look like such a good idea if you were forced to lead a more frugal marketing existence?

How about  a YouTube mini-series with Alec Baldwin?  That’s exactly what Domo did.

Here’s episode 1 about “rancid data” which, among several issues, breaks the fundamental rules about how to make a successful viral video.

2 Comments

Posted in BI, Branding, Bubbles, Marketing

CAC Payback Period:  The Most Misunderstood SaaS Metric

Posted on March 17, 2016 | 22 comments

The single most misunderstood software-as-a-service (SaaS) metric I’ve encountered is the CAC Payback Period (CPP), a compound metric that is generally defined as the months of contribution margin to pay back the cost of acquiring a customer.   Bessemer defines the CPP as:

bess cac

I quibble with some of the Bessemerisms in the definition.  For example, (1) most enterprise SaaS companies should use annual recurring revenue (ARR), not monthly recurring revenue (MRR), because most enterprise companies are doing annual, not monthly, contracts, (2) the “committed” MRR concept is an overreach because it includes “anticipated” churn which is basically impossible to measure and often unknown, and (3) I don’t know why they use the prior period for both S&M costs and new ARR – almost everybody else uses prior-period S&M divided by current-period ARR in customer acquisition cost (CAC) calculations on the theory that last quarter’s S&M generated this quarter’s new ARR.

Switching to ARR nomenclature, and with a quick sleight of mathematical hand for simplification, I define the CAC Payback Period (CPP) as follows:

kell cac

Let’s run some numbers.

  • If your company has a CAC ratio of 1.5 and subscription gross margins of 75%, then your CPP = 24 months.
  • If your company has a CAC ratio of 1.2 and subscription gross margins of 80%, then your CPP = 18 months.
  • If you company has a CAC ratio of 0.8 and subscription gross margins of 80%, then your CPP = 12 months.

All seems pretty simple, right?  Not so fast.  There are two things that constantly confound people when looking at CAC Payback Period (CPP).

  • They forget payback metrics are risk metrics, not return metrics
  • They fail to correctly interpret the impact of annual or multi-year contracts

Payback Metrics are for Risk, Not Return

Quick, basic MBA question:  you have two projects, both require an investment of 100 units, and you have only 100 units to invest.  Which do you pick?

  • Project A: which has a payback period of 12 months
  • Project B: which has a payback period of 6 months

Quick, which do you pick?  Well, project B.  Duh.  But wait — now I tell you this:

  • Project A has a net present value (NPV) of 500 units
  • Project B has an NPV of 110 units

Well, don’t you feel silly for picking project B?

Payback is all about how long your money is committed (so it can’t be used for other projects) and at risk (meaning you might not get it back).  Payback doesn’t tell you anything about return.  In capital budgeting, NPV tells you about return.  In a SaaS business, customer lifetime value (LTV) tells you about return.

There are situations where it makes a lot of sense to look at CPP.  For example, if you’re running a monthly SaaS service with a high churn rate then you need to look closely how long you’re putting your money at risk because there is a very real chance you won’t recoup your CAC investment, let alone get any return on it.  Consider a monthly SaaS company with a $3500 customer acquisition cost, subscription gross margin of 70%, a monthly fee of $150, and 3% monthly churn.  I’ll calculate the ratios and examine the CAC recovery of a 100 customer cohort.

saas fail

While the CPP formula outputs a long 33.3 month CAC Payback Period, reality is far, far worse.  One problem with the CPP formula is that it does not factor in churn and how exposed a cohort is to it — the more chances customers have to not renew during the payback period, the more you need to consider the possibility of non-renewal in your math [1].  In this example, when you properly account for churn, you still have $6 worth of CAC to recover after 30 years!  You literally never get back your CAC.

Soapbox:  this is another case where using a model is infinitely preferable to back-of-the-envelope (BOTE) analysis using SaaS metrics.  If you want to understand the financials of a SaaS company, then build a driver-based model and vary the drivers.  In this case and many others, BOTE analysis fails due to subtle complexity, whereas a well-built model will always produce correct answers, even if they are counter-intuitive.

Such cases aside, the real problem with being too focused on CAC Payback Period is that CPP is a risk metric that tells you nothing about returns.  Companies are in business to get returns, not simply to minimize risk, so to properly analyze a SaaS business we need to look at both.

The Impact of Annual and Multi-Year Prepaid Contracts on CAC Payback Period

The CPP formula outputs a payback period in months, but most enterprise SaaS businesses today run on an annual rhythm.  Despite pricing that is sometimes still stated per-user, per-month, SaaS companies realized years ago that enterprise customers preferred annual contracts and actually disliked monthly invoicing.  Just as MRR is a bit of a relic from the old SaaS days, so is a CAC Payback Period stated in months.

In a one-hundred-percent annual prepaid contract world, the CPP formula should output in multiples of 12, rounding up for all values greater than 12.  For example, if a company’s CAC Payback Period is notionally 13 months, in reality it is 24 months because the leftover 1/13 of the cost isn’t collected until the a customer’s second payment at month 24.  (And that’s only if the customer chooses to renew — see above discussion of churn.)

In an annual prepaid world, if your CAC Payback Period is less than or equal to 12 months, then it should be rounded down to one day because you are invoicing the entire year up-front and at-once.  Even if the formula says the CPP is notionally 12.0 months, in an annual prepaid world your CAC investment money is at risk for just one day.

So, wait a minute.  What is the actual CAC Payback Period in this case?  12.0 months or 1 day?  It’s 1 day.

Anyone who argues 12.0 months is forgetting the point of the metric.  Payback periods are risk metrics and measured by the amount of time it takes to get your investment back [2].  If you want to look at S&M efficiency, look at the CAC ratio.  If you want to know about the efficiency of running the SaaS service, look at subscription gross margins.  If you want to talk about lifetime value, then look at LTV/CAC.  CAC Payback Period is a risk metric that measures how long your CAC investment is “on the table” before getting paid back.  In this instance the 12 months generated by the standard formula is incorrect because the formula misses the prepayment and the correct answer is 1 day.

A lot of very smart people get stuck here.  They say, “yes, sure, it’s 1 day – but really, it’s not.  It’s 12 months.”  No.  It’s 1 day.

If you want to look at something other than payback, then pick another metric.  But the CPP is 1 day.  You asked how long it takes for the company to recoup the money it spends to acquire a customer.  For CPPs less than or equal to 12 in a one-hundred percent annual prepaid world, the answer is one day.

It gets harder.  Imagine a company that sells in a sticky category (e.g., where typical lifetimes may be 10 years) and thus is a high-consideration purchase where prospective customers do deep evaluations before making a decision (e.g., ERP).  As a result of all that homework, customers are happy to sign long contracts and thus the company does only 3-year prepaid contracts.  Now, let’s look at CAC Payback Period.  Adapting our rules above, any output from the formula greater than 36 months should be rounded up in multiples of 36 months and, similarly, any output less than or equal to 36 months should be rounded down to 1 day.

Here we go again.  Say the CAC Payback Period formula outputs 33 months.  Is the real CPP 33 months or 1 day?  Same argument.  It’s 1 day.  But the formula outputs 33 months.  Yes, but the CAC recovery time is 1 day.  If you want to look at something else, then pick another metric.

It gets even harder.  Now imagine a company that does half 1-year deals and half 3-year deals (on an ARR-weighted basis).  Let’s assume it has a CAC ratio of 1.5, 75% subscription gross margins, and thus a notional CAC Payback Period of 24 months.  Let’s see what really happens using a model:

50-50

Using this model, you can see that the actual CAC Payback Period is 1 day. Why?  We need to recoup $1.5M in CAC.  On day 1 we invoice $2.0M, resulting in $1.5M in contribution margin, and thus leaving $0 in CAC that needs to be recovered.

While I have not yet devised general rounding rules for this situation, the model again demonstrates the key point – that the mix of 1-year and 3-year payment structure confounds the CPP formula resulting in a notional CPP of 24 months, when in reality it is again 1 day.  If you want to make rounding rules beware the temptation to treat the average contract duration (ACD) as a rounding multiple because it’s incorrect — while the ACD is 2 years in the above example, not a single customer is paying you at two-year intervals:  half are paying you every year while half are paying you every three.  That complexity, combined with the reality that the mix is pretty unlikely to be 50/50, suggests it’s just easier to use a model than devise a generalized rounding formula.

But pulling back up, let’s make sure we drive the key point home.  The CAC Payback Period is the single most often misunderstood SaaS metric because people forget that payback metrics are about risk, not return, and because the basic formulas – like those for many SaaS metrics – assume a monthly model that simply does not apply in today’s enterprise SaaS world, and fail to handle common cases like annual or multi-year prepaid contracts.

# # #

Notes

[1] This is a huge omission for a metric that was defined in terms of MRR and which thus assumes a monthly business model.  As the example shows, the formula (which fails to account for churn) outputs a CAC payback of 33 months, but in reality it’s never.  Quite a difference!

[2] If I wanted to be even more rigorous, I would argue that you should not include subscription gross margin in the calculation of CAC Payback Period.  If your CAC ratio is 1.0 and you do annual prepaid contracts, then you immediately recoup 100% of your CAC investment on day 1.  Yes, a new customer comes with a future liability attached (you need to bear the costs of running the service for them for one year), but if you’re looking at a payback metric that shouldn’t matter.  You got your money back.  Yes, going forward, you need to spend about 30% (a typical subscription COGS figure) of that money over the next year to pay for operating the service, but you got your money back in one day.  Payback is 1 day, not 1/0.7 = 17 months as the formula calculates.

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Posted in Enterprise, Entrepreneurship, Finance, FP&A, Metrics, SaaS, Silicon Valley, Startups, VC

Thoughts on Jeff Weiner’s “Pay No Attention to the Stock” Message

Posted on February 24, 2016 | 1 comment

From everything I’ve heard for a long time, Jeff Weiner is a wonderful guy and great CEO.  In addition, LinkedIn is certainly a great company, so please don’t view this post as dissing either Jeff or the company.

I will say, however, that I found media coverage of Jeff’s now famous all-hands speech after the stock fell nearly 50% in a day (and the company lost $11B in market cap) to both be rather fawning and to miss one absolutely critical point.

Here’s the video:

http://www.slideshare.net/linkedin/jeff-at-company-all-hands

 

What Jeff Got Right

  • He faced the issue directly.
  • He communicated quickly.  (Conveniently they seem to have biweekly all-hands meetings already in place which made that easier.)
  • He made good arguments (e.g., this happens in public markets; we are the same company we were yesterday, with the same vision and the same team; we are well positioned against macro trends)
  • He spoke with great delivery and articulation
  • He was authentic and sincere

What the Media Missed
Jeff’s basic message — when you strip to the core — is “ignore the stock price.”  This is absolutely the right message.  Markets are fickle, stocks go up and down seemingly without reason, markets over-correct punishing errors severely (particularly for companies price-for-perfection liked LinkedIn) — having worked at several public companies and often with insider status, I can assure you that (1) daily fluctuations are usually inexplicable from the inside and (2) employees will go crazy if they pin their emotions to the ups and downs of the stock market.  So the best advice is:  ignore it.

However, the place where most CEOs fail is that they only want to ignore the stock price when it goes down.  You can’t send emails celebrating* a big uptick, have a party when you break $50/share, or anything like that and then have an ounce of credibility when delivering the message that Jeff so successfully did.

I know Jeff Weiner is very smart, so I’m guessing that LinkedIn never put employee focus on the stock price on the way up, so Jeff’s message is credible on the way down.

But the question isn’t how beautifully your CEO can say “ignore the 50% drop in the stock price” the day after the stock goes down.  The question is what the CEO says and how he or she behaves on the way up.

# # #

* I’m OK with celebrating IPOs as long as you celebrate liquidity and not the day-one stock uptick.  One way to see the day-one uptick is the amount of value left on the table that the company did not capture for itself in the IPO pricing process.  Some of that is normal and part of the process; too much of that is, well, nothing to celebrate.

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Posted in IPO, Management, Silicon Valley, VC