Foreword to The Next CMO: A Guide to Marketing Operational Excellence

The folks at Plannuh, specifically Peter Mahoney, Scott Todaro, and Dan Faulkner, asked me to write the foreword for their new book, The Next CMO:  A Guide to Marketing Operational Excellence.  (Free download here.)

Here’s what I wrote for them.

CMO is a hard job. Early in my career I worked for CMOs, in sort of an endless revolving-door progression, at one point having 7 bosses in 5 years. I have been a CMO, for over 12 years at three different companies. I have managed CMOs, working as CEO for over a decade at two different companies. And I have guided CMOs, serving as an independent director on the board of five different companies.  Let’s just say I’ve spent a lot of time in and around the CMO role.

In the past two decades, no executive suite role has changed more and more quickly than the CMO. Marketers of yesteryear could focus on strategic positioning and branding, leaving such banalities as lead generation to sales-aligned field marketing teams, managing scraps of paper in cardboard boxes.

Sales and marketing automation systems changed everything. Concepts like pipeline, conversion rates, and velocity were born. From lead generation sprung lead nurturing. Attribution emerged to solve one of the world’s oldest marketing problems.

Artificial intelligence (AI) arrived at the scene, helping with areas like lead scoring and prioritization. The demand for analytics followed suit. Marketing ops arose as the cousin of sales ops.

Digital marketing changed everything again. Spend became even more accountable. Pay-per-click replaced pay-per-view which replaced just-pay. Targeting became more precise both via search and the rise of social media. Content marketing emerged to supplement declining traditional public relations. If yesterday’s marketing was leaflets dropped from airplanes, today’s is A/B-tested, laser-guided, call-to-action missiles.

Technology came at CMOs faster than they could keep up. Software could power your website, run your resource center, generate your landing pages, test your messaging, drive repeatable SDR processes, identify your ideal customer, drive account-based marketing, and even record and analyze prospect conversations.

What’s more, as CEOs and boards knew that entirely new classes of questions were becoming answerable, they started asking them.

  • What percent of the pipeline are prospects within our ideal customer profile?
  • What’s the stage-weighted expected value of the pipeline?
    Forecast-category weighted?
  • What’s our week 3 pipeline conversion rate for new logo vs upsell opportunities?
  • What’s our cost per opportunity and how does it vary by channel and geography?
  • What’s marketing’s contribution to our customer acquisition cost (CAC) ratio and how are we improving it?

And dozens and dozens more.

The hardest job in the C-suite got harder. Today’s CMOs need to be visionary strategists by day and operational tacticians by night. Operational marketing has become the sine qua non of modern marketing. If the website is optimized, if the demand generation machine is running effectively, if marketing events are executed flawlessly, if quality pipeline is being generated efficiently, if that pipeline is converting in line with industry benchmarks, and if and only if all that is being done within the constraints of the marketing budget — spending neither too little nor too much — then and only then does the CMO get the chance to be “strategic.”

Operational excellence is thus a necessary but not sufficient condition for CMO success. So it’s well worth mastering and this book is the ideal guide to building and managing your own integrated marketing machine.

There’s no one better to write this book than the leadership team at Plannuh, Peter, Scott, and Dan. With their experience running marketing teams from startups through multi-billion dollar public companies, teaching and mentoring generations of marketers, and now building a platform that codifies their thinking into a scalable SaaS platform, this guide is certain to raise the IQ of your marketing function.

– Dave Kellogg

Video of My SaaStr 2020 Presentation: Churn is Dead, Long Live Net Dollar Retention

Thanks to everyone who attended my SaaStr 2020 presentation and thanks to those who provided me with great feedback and questions on the content of the session.  The slides from the presentation are available here.  The purpose of this post is to share the video of the session, courtesy of the folks at SaaStr.  Enjoy!

 

Churn is Dead, Long Live Net Dollar Retention! Slides from my SaaStr 2020 Presentation

I just finished delivering my presentation at SaaStr Annual 2020, dubbed Churn Is Dead, Long Live Net Dollar Retention.  The presentation is about understanding SaaS businesses:  how to think about them, how to value them, how to use unit economics like CAC and churn to measure them, all with a particular focus on measuring the health of the annuity portion of a SaaS business, the installed base.

While the session is title is perhaps dramatized, if churn isn’t dead I think it’s at least wounded because there are too many ways to calculate it — and the downstream metrics based on it.  That, in turn, lends itself to gaming.  As I said in the presentation:  “there’s a reason PE firms recalculate all your metrics!”

While I generally think public company SaaS metrics are inferior to private company ones, I think the public company way of measuring churn/retention — i.e., net dollar retention (NDR) rate — is superior to LTV/CAC and similar metrics, and thus that private companies should start tracking NDR, too.

If NDR is going to be measured, it can be managed and I suggest both a good and a bad way to think about that.  I wrap up with a quick introduction to RPO (remaining performance obligation), another public company SaaS metric that I believe should and will catch on with private SaaS companies.

Appearance on the CFO Bookshelf Podcast with Mark Gandy

Just a quick post to highlight a recent interview I did on the CFO Bookshelf podcast with Mark Gandy.  The podcast episode, entitled Dave Kellogg Address The Rule of 40, EPM, SaaS Metrics and More, reflects the fun and somewhat wandering romp we had through a bunch of interesting topics.

Among other things, we talked about:

  • Why marketing is a great perch from which to become a CEO
  • Some reasons CEOs might not want to blog (and the dangers of so doing)
  • A discussion of the EPM market today
  • A discussion of BI and visualization, particularly as it relates to EPM
  • The Rule of 40 and small businesses
  • Some of my favorite SaaS operating metrics
  • My thoughts on NPS (net promoter score)
  • Why I like driver-based modeling (and what it has in common with prime factorization)
  • Why I still believe in the “CFO as business partner” trope

You can find the episode here on the web, here on Apple Podcasts, and here on Google Podcasts.

Mark was a great host, and thanks for having me.

SaaStr 2020 Session Preview: Churn is Dead, Long Live Net Dollar Retention!

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Reunited with old friend Tracy Eiler on the speaker page

The SaaStr Annual conference was delayed this year, but Jason & crew know that the show must go on.  So this year’s event has been rechristened SaaStr Annual @ Home and is being held in virtual, online format on September 2nd and 3rd.  The team at SaaStr have assembled a strong, diverse line-up of speakers to provide what should be another simply amazing program.

The purpose of this post is to provide a teaser to entice you to attend my session, Churn is Dead, Long Live Net Dollar Retention Rate, bright and early on Wednesday, September 2nd at 8:00 AM.

“I eat SaaS metrics for breakfast,” he thinks.  Or at least, “with.”

In this session, we’ll cover:

  • Separating a SaaS business into its two component parts
  • What makes SaaS companies so interesting for PE buyers
  • The SaaS leaky bucket of ARR
  • SaaS unit economics 101:  CAC, LTV, LTV/CAC, and CAC payback period
  • The three, fairly lethal problems with churn rates
  • Why “ARR is a fact and churn is an opinion”
  • Cohort analysis basics and survivor bias
  • Net dollar retention (NDR) rate definition and benchmarks
  • Explanatory power of NDR vs. ARR growth and the Rule of 40 in determining valuation multiples
  • The NDR implications of Goodhart’s Law
  • Applying Goodhart’s Law to NDR
  • The next frontier:  remaining performance obligation (RPO)

While the topic might seem a little dry, the content is critically important to any SaaS executive, and I can assure you the presentation will be fast-paced, fun, and anything but dry.

I hope you can attend and I look forward to seeing you there.

How To Get Sales and Marketing Working Together (Presentation)

I spoke this morning to a private equity (PE) firm’s gathering of portfolio company CEOs, CROs, and CMOs.  Our topic, one of my favorites, was how to get sales and marketing working together to drive business results.  While I talked about the predictable subject of alignment, I covered it with an interesting three-level angle (philosophical, strategic, operational).  I prefaced the alignment discussion with examples of what typically goes wrong in the sales/marketing relationship, later revealing that I believe most of the commonly-observed “problems” between sales and marketing are, in fact, symptoms of four underlying problems:

  • Unrealistic plans
  • Function-led mentality
  • Blame culture
  • Non-alignment

I’ve embedded the presentation below and it’s also available on Slideshare.

Are We Due for a SaaSacre?

I was playing around on the enterprise comps [1] section of Meritech‘s website today and a few of the charts I found caught my attention.  Here’s the first one, which shows the progression of the EV/NTM revenue multiple [2] for a set of 50+ high-growth SaaS companies over the past 15 or so years [3].

meritech saas multiples

While the green line (equity-value-weighted [4]) is the most dramatic, the one I gravitate to is the blue line:  the median EV/NTM revenue multiple.  Looking at the blue line, you can see that while it’s pretty volatile, eyeballing it, I’d say it normally runs in the range between 5x and 10x.  Sometimes (e.g., 2008) it can get well below 5x.  Sometimes (e.g., in 2013) it can get well above 10x.  As of the last data point in this series (7/14/20) it stood at 13.8x, down from an all-time high of 14.9x.  Only in 2013 did it get close to these levels.

If you believe in regression to the mean [5], that means you believe the multiples are due to drop back to the 5-10 range over time.  Since mean reversion can come with over-correction (e.g., 2008, 2015) it’s not outrageous to think that multiples could drop towards the middle or bottom of that range, i.e., closer to 5 than 10 [6].

Ceteris paribus, that means the potential for a 33% to 66% downside in these stocks. It also suggests that — barring structural change [7] that moves baseline multiples to a different level — the primary source of potential upside in these stocks is not continued multiple expansion, but positive NTM revenue surprises [8].

I always love Rule of 40 charts, so the next fun chart that caught my eye was this one.  meritech r40 score While this chart doesn’t speak to valuations over time, it does speak to the relationship between a company’s Rule of 40 Score and its EV/NTM revenue multiple.  Higher valuations primarily just shift the Y axis, as they have done here, uplifting the maximum Y-value by nearly three times since I last blogged about such a chart [9].  The explanatory power of the Rule of 40 in explaining valuation multiple is down since I last looked, by about half from an R-squared of 0.58 to 0.29.  Implied ARR growth alone has a higher explanatory power (0.39) than the Rule of 40.

To me, this all suggests that in these frothy times, the balance of growth and profit (which is what Rule of 40 measures) matters less than other factors, such as growth, leadership, scarcity value and hype, among others.

Finally, to come back to valuation multiples, let’s look at a metric that’s new to me, growth-adjusted EV/R multiples.

meritech r40 growth adjusted

I’ve seen growth-adjusted price/earnings ratios (i.e., PEG ratios) before, but I’ve not seen someone do the same thing with EV/R multiples.  The basic idea is to normalize for growth in looking at a multiple, such as P/E or — why not — EV/R.  For example, Coupa, trading at (a lofty) 40.8x EV/R is growing at 21%, so divide 40.8 by 21 to get 1.98x.  Zoom, by comparison looks to be similarly expensive at 38.3x EV/R but is growing at 139%, so divide 38.3 by 139 to get 0.28x, making Zoom a relative bargain when examined in this light [10].

This is a cool metric.  I like financial metrics that normalize things [11].  I’m surprised I’ve not seen someone do it to EV/R ratios before.  Here’s an interesting observation I just made using it:

  • To the extent a “cheap” PE firm might pay 4x revenues for a company growing 20%, they are buying in at a 0.2 growth-adjusted EV/R ratio.
  • To the extent a “crazy” VC firm might pay 15x revenues for a company growing at 75%, they are buying in at a 0.2 growth-adjusted EV/R ratio.
  • The observant reader may notice they are both paying the same ratio for growth-adjusted EV/R. Given this, perhaps the real difference isn’t that one is cheap and the other free-spending, but that they pay the same for growth while taking on very different risk profiles.

The other thing the observant reader will notice is that in both those pseudo-random yet nevertheless realistic examples, the professionals were paying 0.2.  The public market median today is 0.7.

See here for the original charts and data on the Meritech site.

Disclaimer:  I am not a financial analyst and do not make buy/sell recommendations.  I own positions in a wide range of public and private technology companies.  See complete disclaimers in my FAQ.

# # #

Notes 
[1] Comps = comparables.

[2] EV/NTM Revenue = enterprise value / next twelve months revenue, a so-called “forward” multiple.

[3] Per the footer, since Salesforce’s June, 2004 IPO.

[4] As are most stock indexes. See here for more.

[5] And not everybody does.  People often believe “this time it’s different” based on irrational folly, but sometimes this time really is different (e.g., structural change).  For example, software multiples have structurally increased over the past 20 years because the underlying business model changed from one-shot to recurring, ergo increasing the value of the revenue.

[6] And that’s not to mention external risk factors such as pandemic or election uncertainty.  Presumably these are already priced into the market in some way, but changes to how they are priced in could result in swings either direction.

[7] You might argue a scarcity premium for such leaders constitutes a form of structural change. I’m sure there are other arguments as well.

[8] To the extent a stock price is determined by some metric * some multiple, the price goes up either due to increasing the multiple (aka, multiple expansion) or increasing the metric (or both).

[9] While not a scientific way to look at this, the last time I blogged on a Rule of 40 chart, the Y axis topped out at 18x, with the highest data point at nearly 16x.  Here the Y axis tops out at 60x, with the highest data point just above 50x.

[10] In English, to the extent you’re paying for EV/R multiple in order to buy growth, Zoom buys you 7x more growth per EV/R point than Coupa.

[11] As an operator, I don’t like compound operational metrics because you need to un-tangle them to figure out what to fix (e.g., is a broken LTV/CAC due to LTV or CAC?), but as investor I like compound metrics as much as the next person.