Category Archives: CAC

A CEO’s High-Level Guide to GTM Troubleshooting

I’ve written about this topic a lot over the years, but never before integrated my ideas into a single high-level piece that not only provides a solution to the problem, but also derives it from first principles. That’s what I’ll do today. If you’re new to this topic, I strongly recommend reading the articles I link to throughout the post.

Scene: you’re consistently having trouble hitting plan. Finance is blaming sales. Sales is blaming marketing. Marketing is blaming the macro environment. Everyone is blaming SDRs. Alliances is hiding in a foxhole hoping no one remembers to blame them. E-staff meetings resemble a cage fight from Beyond Thunderdome, but it’s a tag-team match with each C-level tapping in their heads of operations when they need a break. Numbers are flying everywhere. The shit is hitting the proverbial fan.

The question for CEOs: what do I do about this mess? Here’s my answer.

First:

  • Avoid the blame game. That sounds much easier than it is because blame can vary from explicit to subtle and everyone’s blame sensitivity ears are set to eleven. Speak slowly, carefully, and factually when discussing the situation. You might wonder why everyone is pointing fingers, and the reason might well be you.
  • Solve the problem. Keep everyone focused on solving the problem going forward. Use blameless statements of fact when discussing historical data. For example, say “when we start with less than 2.5x pipeline coverage, we almost always miss plan” as opposed to “when marketing fails on pipeline generation, we miss plan unless sales does their usual heroic job in pipeline conversion.”)

Then reset the pipeline discussion by constantly reminding everyone of these three facts:

  • How do you make 16 quarters in a row? One at a time.
  • How do you make one quarter? Start with sufficient pipeline coverage.
  • And then convert it at your target conversion rate.

This reframes the problem into making one quarter — the right focus if you’ve missed three in a row.

  • This will force a discussion of what “sufficient” means
  • That is generally determined by inverting your historical week 3 pipeline conversion rates
  • And adjusting them as required, for example, to account for the impacts of big deals or other one-time events
  • This may in turn reveal a conversion rate problem, where actual conversion rates are either below targets and/or simply not viable to produce a sales model that hits the board’s target customer acquisition cost (CAC) ratio. For example, you generally can’t achieve a decent CAC ratio with a 20% conversion rate and 5x pipeline coverage requirement. In this case, you will need to balance your energy on improving both conversion rates and starting coverage. While conversion rates are largely a sales team issue, there is nevertheless plenty that marketing and alliances can do to help: marketing through targeting, tools, enablement, and training; alliances through delivering higher-quality opportunities that often convert at higher rates than either inbound or SDR outbound.

It also says you need to think about each and every quarter. This leads to three critical realizations:

  • That you must also focus on future pipeline, but segmented into quarters, and not on some rolling basis
  • That you need to forecast pipeline (e.g., for next quarter, if not also the one after that)
  • That you need some mechanism for taking action when that forecast is below target

The last point should cause you to create some meeting or committee where the pipeline forecast is reviewed and the owners of each of the four to six pipeline sources (i.e., marketing, AE outbound, SDR outbound, alliances, community, PLG) can discuss and then take remedial measures.

  • That body should be a team of senior people focused on a single goal: starting every quarter with sufficient pipeline coverage.
  • It should be chaired by one person who must be seen as wearing two hats: one as their functional role (e.g., CMO) and the other as head of the pipeline task force. That person must be empowered to solve problems when they arise, even when they cross functions.
  • Think: “OK, we’re forecasting 2.2x starting coverage for next quarter instead of 2.5x, which is a $2M gap. Who can do what to get us that $2M?”
  • If that means shifting resources, they shift them (e.g., “I’ll defer hiring one SDR to free up $25K to spend on demandgen”).
  • If that means asking for new resources, they ask (e.g., I’ll tell the CEO and CFO that if we can’t find $50K, then we think we’ve got no chance of hitting next quarter’s starting coverage goals).
  • If that means rebalancing the go-to-market team, they do it. For example, “we’ve only got enough pipeline to support 8 AEs and we’ve got 12. If we cut two AEs, we can use that money to invest in marketing and SDRs to support the remaining 10.”
  • Finally, if you need to focus on both pipeline coverage and conversion rates, then this same body, in part two of the meeting, can review progress on actions design to improve conversion.

Teamwork and alignment is not about behaving well in meetings or only politely backstabbing each other outside them. It’s about sitting down together to say, “well, we’re off plan, and what are we going to do about it?” And doing so without any sacred cows in the conversation. Just as no battle plan survives first contact with the enemy, no pipeline plan survives first contact with the market. That’s why you need this group and that’s what it means to align sales, marketing, alliances, and SDRs on pipeline goals. It’s the translation of the popular saying, “pipeline generation is a team sport.”

Notice that I never said to heavily focus on individual pipeline generation (“pipegen”) targets. Yes, you need them and you should set and track them, but we must remember the purpose of pipegen is to hit starting pipeline coverage goals. So just as we shouldn’t overly focus on other upstream metrics — from dials to alliances-meetings to MQLs — we shouldn’t overly focus on pipegen targets to the point where they become the end, not the means. While pipegen is certainly closer to starting coverage than MQLs or dials, it is nevertheless an enabler, in this case, one step removed.

Yes, tracking upstream metrics is important and for marketing I’d track both MQLs and pipegen (via oppty count, not dollars), but I’d neither pop champagne nor tie the CMO to the whipping post based on either MQLs or pipegen alone.

Don’t get me wrong — if your model’s correct, it should be impossible to consistently hit starting pipeline coverage targets while consistently failing on pipegen goals. But in any given quarter, maybe the AEs are short and marketing covers or marketing’s short and alliances covers. The point is that if the company hits the starting coverage goal, we’re happy with the pipeline machine and if we don’t, we’re not. Regardless of whether individual pipeline source X or Y hit their pipegen goals in a quarter. Ultimately, this point of view drives better teamwork because there’s no shame in forecasting a light result against target or shame in asking for help to cover it.

Finally, I’d note an odd situation I sometimes see that looks like this:

  • Sales consistently achieves bookings targets, but just by a hair
  • Marketing consistently underachieves pipeline targets

For example, sales consistently converts pipeline at 25% off 4x coverage and that 25% conversion rate is just enough to hit plan. But, because the CRO likes cushion, he forces the CMO to sign up for 5x coverage. Marketing then consistently fails to deliver that 5x coverage, delivering 4x coverage instead.

This is an unhealthy situation because sales is consistently succeeding while marketing is consistently failing. If you believe, as I do, that if sales is consistently hitting plan then, definitionally marketing has provided everything it needs to (from pipeline to messaging to enablement), then you can see how pathological this situation is. Sales is simply looking out for itself at the expense of marketing. That’s good for the company in the short term because you’re consistently hitting plan, but bad in the long term because there will be high turnover in the marketing department that should impede their ability to deliver sufficient pipeline in the future.

For more on this topic, please listen to our podcast episode of SaaS Talk with the Metrics Brothers entitled: Top-Down GTM Troubleshooting, Dave’s Method.

Board-Level Questions On The Marketing Budget

Since many of you are in the midst of presenting your annual marketing budgets to your CEO, CFO, and board, I thought I’d write a quick post to remind people what board members actually care about when it comes to the marketing budget.

I understand that, in the throes of budgeting, CMOs can get dragged down into a lot of detail. Diving to a deep level of detail is important, because that’s usually the difference between a real plan and a basic budget.

But, remember people: when we’re talking to the board, we need to be board level. Otherwise, they’re going to mistake you for the VP of marketing operations. (Was the CMO out sick today?)

The board doesn’t want:

  • Vapid marketing cheerleading, particularly if the company is missing plan
  • Overwhelming volume (e.g., 28 slides with a 15-slide appendix)
  • “Banker slides” that overload them with numbers
  • Recycled QBR slides, built for a different audience and purpose

While I’m all in favor of a few introductory slides that present current-year marketing performance, they should be sober and matter of fact. Too often, when CMOs try to present such slides, they end up sounding like this:


So what does the board want?

  • A short deck, maybe 5-8 slides (with a slide on 2024 performance, a list of key objectives, an organization chart, and an overall budget)
  • Some slicing-and-dicing of the demandgen budget that discusses both coverage and efficiency
  • Slides that are custom built for the board audience

And what are the questions that are actually on their mind?

  • What are marketing’s key objectives for the year? Do they align to corporate strategy? Do they align to sales? Are they the right objectives?
  • Where did the budget come from?  Was it trended off last year or built from a bottom-up model?
  • If it was trended, is the total spend growing slower than revenue? Could it be growing slower still? Should it be growing faster?
  • If it was built off a model, who built the model? Are they any good? Is there a single model for sales, marketing, and finance, or is there a cage fight behind the scenes? Can we hit plan if we rely on this model?
  • What does marketing spend look like as a percent of revenue? As a percent of new ARR bookings? Are those percents going down over time? How do they compare to benchmarks?
  • What is our CAC ratio and CAC payback period? How much is marketing contributing to each? Is marketing’s relative contribution going down or up?
  • And if they’re good, what is the sales/marketing expense ratio and how has that trended over time? How does it compare to industry benchmarks? On whose back are we placing the GTM efficiency monkey, and what risks does that entail?
  • Where does the CMO want to spend the marketing money?  How much is going to people vs. programs vs. infrastructure? How has that mix changed over time?
  • Is there any marketing money outside marketing? Does the CEO carry a pet-projects budget for billboards? Do we run a massive user conference? If that money’s not in the budget I’m looking at, then where is it?
  • Do the CRO and CMO seem aligned on the marketing budget and priorities? If not, where do they differ? Does the CMO seem caught in the middle between CEO and CRO priorities?
  • Does the company have an overall model for who generates how much pipeline? That is, pipeline generation targets by pipeline source (aka, “horseman”) by quarter?
  • Has each pipeline owner accepted clear responsibility for their portion of the pipeline and a have a clear plan to deliver it?
  • Does marketing have a plan for how they are going to spend the proposed demandgen dollars? Can I compare that plan to our historical performance to see if it’s realistic?
  • Is marketing focused solely on pipeline generation or do they also worry about pipeline coverage?
  • Does the marketing plan show pipe/spend and cost/oppty ratios? How does the plan compare to our historical performance? Are we increasing efficiency? Is that spreadsheet magic or are there actual reasons why those ratios should increase?
  • Where are we looking at using AI to improve marketing efficiency? What are we experimenting with? How big an improvement can we expect? Have we looked at AI SDRs?
  • How much money is going into squishy things like branding? Can the CMO defend that proposed expense? Do the CEO and CRO agree that this squishy spend is a priority?
  • Can I trust the CMO to execute this plan? If we give them what they ask, will they deliver on the pipeline generation goals and key objectives?

I’m not suggesting that you proactively answer each of these questions in your eight slides. But these are the questions you should be ready for. In terms of how I’d map these to slides:

  1. Current-year marketing performance. Metrics on the left, OKRs on the right.
  2. Next-year proposed OKRs.
  3. Next-year proposed organization chart.
  4. Top-down S&M analysis, e.g., CAC, CPP, sales/marketing expense ratio, history, benchmarks.
  5. Top-down marketing budget analysis, e.g., spend by people/programs/infra, headcount, total cost/oppty.
  6. Overall pipegen and coverage model, e.g., targets by horseman, how pipegen ensures coverage
  7. Demandgen budget analysis, e.g., spend by channel, pipe/spend, DG cost/oppty, coverage.
  8. Menu of 3-5 optional programs with benefits and costs — i.e., try to sell the top ideas you couldn’t fit into the baseline plan in a quest for incremental money.

(Edited 12/2/24 at 9:04am to include last section on slide mapping.)

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!

 

Number 7 on the All-Time Top SaaStr Podcasts: On the Importance of LTV/CAC

Just a quick post to say I’m honored to have made number seven on the countdown of the top ten most downloaded podcasts of all time on the SaaStr Podcast.

The podcast in question is an interview performed by Harry Stebbings of The Twenty Minute VC where we sat down to talk about the importance of the lifetime value to customer acquisition cost ratio (LTV/CAC) and why, if you could only know one SaaS metric about a company, that LTV/CAC would be it.

Of course with Harry it’s easy to end up in a wide-ranging conversation, as we did, and we thus discussed many other fun topics including:

  • How I got into enterprise software and SaaS.
  • The biggest challenge as a leader in a high-growth company (hanging on).
  • Why, for a public SaaS company, I’d probably take billings growth as the single metric, because LTV/CAC isn’t available.
  • LTV/CAC and the idea that it’s a powerful (if compound) metric that weights what you pay for something vs. what’s it worth.
  • Which churn metric to use as the basis for calculating LTV.
  • Upsell and how to design your packaging to enable both incremental upsell and major cross-sell.
  • Pricing and how to ensure your pricing is linked to at least one metric that always increases.
  • Bookings and the perils of TCV in SaaS companies, including my favorite self-quote from the podcast: “beware of Greeks bearing gifts as you would beware SaaS companies talking TCV.”
  • Multi-year deals and to what extent they should be prepaid.
  • How once, at Business Objects, we once sold a customer more licenses than they had employees (on the broader topic of vendor/customer interest alignment).
  • How sales and customer success should work together on renewals and upsells — and importance of putting farmers vs. farmers and hunters vs. hunters when it comes to competition.
  • How you can’t analyze churn by analyzing churn — i.e., gathering a list of churned customers and looking for commonalities.
  • The 90 day rule when it comes to new managers.

I hope you enjoy listening to it if you haven’t already. And for those who have, thanks for helping me make the top 10 list!

Bookings vs. Billings in a SaaS Company

Financial analysts speak a lot about “billings” in a public SaaS companies, but in private VC-backed SaaS companies, you rarely hear discussion of this metric.  In this post, we’ll use a model of a private SaaS company (where we know all the internal metrics), to show how financial analysts use rules of thumb to estimate and/or impute internal SaaS metrics using external ones – and to see what can go wrong in that process.

For reference, here’s an example of sell-side financial analyst research on a public SaaS company that talks about billings [1].

saas1-zen

Let’s start with a quick model that builds up a SaaS company from scratch [1].  To simplify the model we assume all deals (both new and renewal) are for one year only and are booked on the last day of the quarter (so zero revenue is ever recognized in-quarter from a deal).  This also means next-quarter’s revenue is this-quarter’s ending annual recurring revenue (ARR) divided by 4.

saas13

Available to renew (ATR) is total subscription bookings (new and renewal) from four quarters prior.  Renewal bookings are ATR * (1 – churn rate).  The trickiest part of this model is the deferred revenue (DR) waterfall where we need to remember that the total deferred revenue balance is the sum of DR leftover from the current and the prior three quarters.

If you’re not convinced the model is working and/or want to play with it, you can download it, then see how things work by setting some drivers to boundary conditions (e.g., churn to 0%, QoQ sales growth to 0, or setting starting ARR to some fixed number [2]).

 The Fun Part:  Imputing Internal Metrics from External Ones

Now that we know what’s going on the inside, let’s look in from the outside [3]:

  • All public SaaS companies release subscription revenues [4]
  • All public SaaS companies release deferred revenues (i.e., on the balance sheet)
  • Few SaaS companies directly release ARR
  • Few SaaS companies release ATR churn rates, favoring cohort retention rates where upsell both masks and typically exceeds churn [5]

It wasn’t that long ago when a key reason for moving towards the SaaS business model was that SaaS smoothed revenues relative to the all-up-front, lumpy on-premises model.  If we could smooth out some of that volatility then we could present better software companies to Wall Street.  So the industry did [6], and the result?  Wall Street immediately sought a way to look through the smoothing and see what’s really going on in the inherently lumpy, backloaded world of enterprise software sales.

Enter billings, the best answer they could find to do this.  Billings is defined as revenue plus change in deferred revenue for a period.  Conceptually, when a SaaS order with a one-year prepayment term is signed, 100% of it goes to deferred revenue and is burned down 1/12th every month after that.  To make it simple, imagine a SaaS company sells nothing in a quarter:  revenue will burn down by 1/4th of starting deferred revenue [7] and the change in deferred revenue will equal revenue – thus revenue plus change in deferred revenue equals zero.  Now imagine the company took an order for $50K on the last day of the quarter.  Revenue from that order will be $0, change in deferred will be +$50K, implying new sales of $50K [8].

Eureka!  We can see inside the SaaS machine.  But we can’t.

Limitations of Billings as a SaaS Metric

If you want to know what investors really care about when it comes to SaaS metrics, ask the VC and PE folks who get to see everything and don’t have to impute outside-in.  They care about

Of those, public company investors only get a clear look at subscription gross margins and the customer acquisition cost (CAC) ratio.  So, looking outside-in, you can figure out how efficiency a company runs its SaaS service and how efficiently it acquires customers [9].

But you typically can’t get a handle on churn, so you can’t calculate LTV/CAC or CAC Payback Period.  Published cohort growth, however, can give you comfort around potential churn issues.

But you can’t get a precise handle on sales growth – and that’s a huge issue as sales growth is the number one driver of SaaS company valuation [10].  That’s where billings comes into play.  Billings isn’t perfect because it shows what I call “total subscription bookings” (new ARR bookings plus renewal bookings) [11], so we can’t tell the difference between a good sales and weak renewals quarter and a bad sales and a good renewals quarter.

Moreover, billings has two other key weaknesses as a metric:

  • Billings is dependent on prepaid contract duration
  • Companies can defer processing orders (e.g., during crunch time at quarter’s end, particularly if they are already at plan) thus making them invisible even from a billings perspective [12]

Let’s examine how billings depends on contract duration.  Imagine it’s the last day of new SaaS company’s first quarter.  The customer offers to pay the company:

  • 100 units for a prepaid one-year subscription
  • 200 units for a prepaid two-year subscription
  • 300 units for a prepaid three-year subscription

From an ARR perspective, each of the three possible structures represents 100 units of ARR [13].  However, from a deferred revenue perspective, they look like 100, 200, 300 units, respectively.  Worse yet, looking solely at deferred revenue at the end of the quarter, you can’t know if 300 units represents three 100-unit one-year prepay customers or a single 100-unit ARR customer who’s done a three-year prepay.

In fact, when I was at Salesforce we had the opposite thing happen.  Small and medium businesses were having a tough time in 2012 and many customers who’d historically renewed on one-year payment cycles started asking for bi-annual payments.  Lacking enough controls around a rarely-used payment option, a small wave of customers asked for and got these terms.  They were happy customers.  They were renewing their contracts, but from a deferred revenue perspective, suddenly someone who looked like 100 units of deferred revenue for an end-of-quarter renewal suddenly looked 50.  When Wall St. saw the resultant less-than-expected deferred revenue (and ergo less-than-expected billings), they assumed it meant slower new sales.  In fact, it meant easier payment terms on renewals – a misread on the business situation made possible by the limitations of the metric.

This issue only gets more complex when a company is enabling some varying mix of one through five year deals combined with partial up-front payments (e.g., a five-year contract with years 1-3 paid up front, but years 4 and 5 paid annually).  This starts to make it really hard to know what’s in deferred revenue and to try and use billings as a metric.

Let’s close with an excerpt from the Zuora S-1 on billings that echoes many of the points I’ve made above.

saas3

Notes

[1] Source:  William Blair, Inc., Zendesk Strong Start to 2018 by Bhavan Suri.

[2] Even though it’s not labelled as a driver and will break the renewals calculations, implicitly assuming all of it renews one year later (and is not spread over quarters in anyway).

[3] I’m not a financial analyst so I’m not the best person to declare which metrics are most typically released by public companies, so my data is somewhat anecdotal.  Since I do try to read interesting S-1s as they go by, I’m probably biased towards companies that have recently filed to go public.

[4] As distinct from services revenues.

[5] Sometimes, however, those rates are survivor biased.

[6] And it worked to the extent that from a valuation perspective, a dollar of SaaS revenue is equivalent to $2 to $4 of on-premises revenue.  Because it’s less volatile, SaaS revenue is more valuable than on-premises revenue.

[7] Provided no customers expire before the last day of the quarter

[8] Now imagine that order happens on some day other than the last day of the quarter.  Some piece, X, will be taken as revenue during the quarter and 50 – X will show up in deferred revenue.  So revenue plus change in deferred revenue = it’s baseline + X + 50 – X = baseline + 50.

[9] Though not with the same clarity VCs can see it — VCs can see composition of new ARR (upsell vs. new business) and sales customers (new customer acquisition vs. customer success) and thus can create more precise metrics.  For example, a company that has a solid overall CAC ratio may be revealed to have expensive new business acquisition costs offset by high, low-cost upsell.

[10] You can see subscription revenue growth, but that is smoothed/damped, and we want a faster way to get the equivalent of New ARR growth – what has sales done for us lately?

[11] It is useful from a cash forecasting perspective because all those subscription billings should be collectible within 30-60 days.

[12] Moving the deferred revenue impact of one or more orders from Q(n) to Q(n+1) in what we might have called “backlogging” back in the day.  While revenue is unaffected in the SaaS case, the DR picture looks different as a backlogged order won’t appear in DR until the end of Q(n+1) and then at 75, not 100, units.

[13] Normally, in real life, they would ask a small discount in return for the prepay, e.g., offer 190 for two years or 270 for three years.  I’ll ignore that for now to keep it simple.