Category Archives: SaaS

Marketing Targeting: It’s Not Just Where You Fish, It’s What You Put on the Hook

Back in the day I was taught that marketers do three things, memorized via the acronym STP:  segment, target, position.

  • Divide the audience into different segments.  For example, dividing consumers by demographics or dividing businesses by size or industry.
  • Select the segments that the company wishes to target for its marketing.  For example, choosing small and medium businesses (SMB) as your target segment.
  • Position the product in the mind of the consumer, ideally in a unique way, providing differentiation and/or benefit [1].  For example, positioning your offering for the SMB segment as easy to deploy and inexpensive to own.

I’ve always thought of targeting as the answer to the question, “what list do I want to buy?”  Do I want buy a list of marketing directors at SMBs or a list of chief data officers (CDOs) at Fortune 1000 companies?

The list-buying metaphor extends nicely to events (what shows do these people attend), PR (what publications do they read), AR (to which influencers do they listen), some forms of digital advertising (e.g., LinkedIn where you have considerable targeting control), if not Google (where you don’t [2]).

For many people, that’s where the targeting discussion ends.  When most people think of targeting they think of where on the lake they want to fish.

While an angler would never forget this, marketers too often miss that what you put on the hook matters, too.  Fishing in the same part of the lake, an angler might put on crayfish for largemouth bass, worms for rainbow trout, or stinkbait for catfish.

It’s not just about who you’re speaking to; it’s about what you tell them — the bait, if you will, that you put on the hook.

Perhaps this is too metaphorical, so let’s take an example — imagine we sell financial planning and budgeting software to businesses and our target segment is small businesses between $0M to $50M in revenue.  Via some marketing channels we can communicate only to people in this segment, but through a lot of other important channels (e.g., Google Ads, SEO, content marketing), we cannot.  So we need to rely not only on our targeting, but our message, to control who we bring into the lead funnel.

Consider these two messages:

  • Plan faster and more efficiently with OurTool
  • End the misery and mistakes of planning on Excel

The first message pitches a generic benefit of a planning system and is likely to attract many different types of fish.  The second message specifically addresses the pains of planning on Excel.  Who plans on Excel?  Well, smaller businesses primarily [3].  So the message itself helps us filter for the kind of companies we want to attract.

Now, let’s pretend we’re targeting large enterprises, instead.  Consider these two messages.

  • End the misery and mistakes of planning on Excel
  • Integrate your sales and financial planning

The first message, as discussed above, is going to catch a lot of small fish.  The second message is about a problem that only larger organizations face — small companies are just trying to get a budget done, whereas larger ones are trying to get a more holistic view.  The second message far better attracts the enterprise target that you want.  As would, for example, a message about the pain and expense of budgeting on Hyperion.

I’ll close in noting that marketers who measure themselves [4] by the number of fish they catch — as opposed to the conversion of those fish into customers — will often resist the more focused message because you won’t set attendance records with the more selective bait.  So, as you perform your targeting, always remember three things:

  1. It’s about where you put the boat
  2. It’s also about the bait you put on the hook
  3. It’s not about the number of fish you catch, but the number of right fish that you catch.

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Notes

[1] The decision to emphasize differentiation or benefit is covered in The Two Archetypal Marketing Messages:  “Bags Fly Free” and “Soup is Good Food.”

[2] In a B2B sense, at least.

[3] Amazingly, a lot of large and very large businesses also plan on Excel, but let’s not confuse the exception for the rule or the point of the example — different messages attract different buyers.

[4] Either literally by putting KPIs on high-funnel metrics such as MQLs or, more subtly and more dangerously, by getting too much inner joy from high-funnel metrics (“look how many people came to our webinar!”)

Should Your SDRs Look for Projects or Pain?

There’s a common debate out there, it goes something like this:

“Our sales development representatives (SDRs) need to look for pain: finding business owners with a problem and the ability to get budget to go fix it.”

Versus:

“No, our SDRs need to look for projects: finding budgeted projects where our software is needed, and ideally an evaluation in the midst of being set up.”

Who’s right?

As once was once taught to me, the answer to every marketing question is “it depends” and the genius is knowing “on what.”  This question is no exception.  The answer is:  it depends.  And on:

  • Whether you’re in a hot or cold market.
  • Whether your SDR is working an inbound or outbound motion

I first encountered this problem decades ago rolling out Solution Selling (from which sprung the more modern Customer-Centric Selling).  Solution Selling was both visionary and controversial.  Visionary in that it forced sales to get beyond selling product (i.e., selling features, feeds, and speeds) instead focusing on the benefits of what the product did for the customer.  Controversial in that it uprooted traditional sales thinking — finding an existing evaluation was bad, argued Bosworth, because it meant that someone else had already created the customer’s vision for a solution and thus the buying agenda would be biased in their favor.

While I think Bosworth made an interesting point about the potential for wired evaluation processes and requests for proposal (RFPs), I never took him literally.  Then I met what I could only describe as “fundamentalist solution seller” in working on the rollout.

“OK, we we’re working on lead scoring, and here’s what we’re going to do:  10 points for target industry, 10 points for VP title or above, 10 points for business pain, -10 points for existing evaluation, and -10 points for assigned budget.”

Wut?

I’d read the book so I knew what Bosworth said, but, but he was just making a point, right?  We weren’t actually going to bury existing evaluations in the lead pile, were we?  All because the customer knew they wanted to buy in our category and had the audacity to start an evaluation process and assign budget before talking to us?

That would be like living in the Upside Down.  We couldn’t possibly be serious?  Such is the depth of religion often associated with the rollout of a new sales methodology.

Then I remembered the subtitle of the book (which everyone seems to forget).

“Creating buyers in difficult selling markets.”  This was not a book written for sellers in Geoffrey Moore’s tornado, it was book for written for those in difficult markets, tough markets, markets without a lot of prospects, i.e., cold markets.  In a cold market, no one’s out shopping so you have no choice but find potential buyers in latent pain, inform them a solution exists, and try to sell it to them.

Example:  baldness remedies.  Sure, I’d rather not be bald, but I’m not out shopping for solutions because I don’t think they exist.  This is what solution sellers call latent pain.  Thus, if you’re going to sell me a baldness remedy, you’re going need to find me, get my attention, remind me that I don’t like being bald, then — and this is really hard part — convince me that you have a solution that isn’t snake oil.  Such is life in cold markets.  Go look for pain because if you look for buyers you aren’t going to find many.

However, in hot markets there are plenty of buyers, the market has already convinced buyers they need to buy a product, so the question sellers should focus on is not “why buy one” but instead, “why buy mine.”

I’m always amazed that people don’t first do this high-level situation assessment before deciding on sales and marketing messaging, process, and methodology.  I know it’s not always black & white, so the real question is:  to what extent are our buyers already shopping vs. need to be informed about potential benefits before considering buying?  But it’s hard to devise any strategy without having an answer to it.

So, back to SDRs.

Let’s quickly talk about motion.  While SDR teams may be structured in many ways (e.g., inbound, outbound, hybrid), regardless of team structure there are two fundamentally different SDR motions.

  • Inbound.  Following-up with people who have “raised their hand” and shown interest in the company and its offerings.  Inbound is largely a filtering and qualification exercise.
  • Outbound.  Targeting accounts (and people within them) to try and mutate them into someone interested in the company and its offerings.  In other words, stalking:  we’re your destiny (i.e., you need to be our customer) and you just haven’t figured it out, yet.

In hot markets, you can probably fully feed your salesforce with inbound.  That said, many would argue that, particularly as you scale, you need to be more strategic and start picking your customers by complementing inbound with a combination of named-account selling, account-based marketing, and outbound SDR motion.

In cold markets, the proverbial phone never rings.  You have no choice but to target buyers with power, target pains, and convince them your company can solve them.

Peak hype-cycle markets can be confusing because there’s plenty of inbound interest, but few inbound buyers (i.e., lots of tire-kickers) — so they’re actually cold markets disguised as hot ones.

Let’s finally answer the question:

  • SDRs in hot markets should look for projects.
  • SDRs in cold markets should look for pain.
  • SDRs in hot markets at companies complementing inbound with target-account selling should look for pain.

 

Unlearning As You Scale: Presentation from a VC Portfolio CEO Summit

The good people of Costanoa Ventures invited me to speak at their summit where they gather portfolio company CEOs to participate in an impressive set of sessions related to building and scaling startups.  I was honored to be in the company of friends and respected colleagues like Nick Mehta and Rob Reid as presenters at the conference.

Costanoa asked me to speak about un-learning at this year’s un-summit and, as a (sometimes, some might say frequent) contrarian, I was only too happy to do so.  The slides from the presentation are below.  I focused on 4 topics:

  • The sensible application of the popular Silicon Valley adage, “the folks who got you here aren’t the ones who will get you to the next level,” and how to reconcile it with an older, even more popular adage:  “dance with who brung ya.”
  • Generalizing the next-level adage beyond people to systems, processes, and operational strategies.
  • Things to do and pitfalls to avoid in recruiting next-level executives, with a particular focus on avoiding very successful people caught in the lather/rinse/repeat trap.
  • Critically thinking whether you have been successful because of, in spite of, or independent of a list of your company’s practices, values, and deeply held beliefs

This slides are here and embedded below.

Thanks to Greg Sands, Martina Lauchengco, and Rachel Quon for inviting me and giving me such a great topic to work with.

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!

 

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.

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.