Category Archives: Metrics

A CEO’s High-Level Guide to GTM Troubleshooting

Posted on May 10, 2025 | 2 comments

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.

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Posted in CAC, Culture, Demandgen, Forecasting, Marketing, Pipeline, Sales, Sales Model, Salesops

How to Calculate Cost Per Opportunity

Posted on March 1, 2025 | Leave a comment

My marketing professor once said, The answer to every marketing question is, “It depends.” Thus, the important part is knowing on what.

So, how do you calculate the cost/opportunity? Well, it depends! On what? On the specific question you’re trying to answer. When people ask about cost/opportunity, they usually have one of two things in mind:

An efficiency question — e.g., how efficiently does marketing spend convert into sales opportunities (oppties)?
A cost question — e.g., how much it would cost to get 50 more oppties if we needed them

Knowing which question you’re being asked has a big impact on how to calculate the answer. Let’s illustrate this by looking at this typical marketing budget, which is allocated roughly 45/45/10 across people, programs, and technology:

If this marketing team generated 1,000 oppties, then the average total marketing cost/oppty is $9,000 = $9M/1K oppties. You might argue that’s a good overall marketing efficiency metric and try to benchmark it. But those benchmarks will be hard to find.

Why?

Because there’s a better overall marketing efficiency metric: the marketing customer acquisition cost (CAC) ratio = (last-quarter marketing expense)/(this-quarter new ARR). Why is the marketing CAC a better marketing efficiency metric than average total marketing cost/oppty?

It’s more standard. While relatively few startups break their CAC ratio in two parts, virtually every startup already calculates CAC ratio or CAC payback period (CPP). People are familiar with the concept and the math mostly already done — just back out the sales expense.
There is less room for calculation debates. While neither total cost/oppty or marketing CAC is hard to calculate, because marketing CAC is a derivative of CAC, some nagging questions are already answered for you – e.g., Is it all marketing or just a part? Is it GAAP expense or cash expense? Answers: look at how you calculate your CAC ratio for guidance.
The phase shift. The CAC ratio compares last quarter’s expense to this quarter’s new ARR in an attempt to better match expenses and results.
There are more benchmark data sets. I can think of about ten sources for CAC ratio data (not all of which make the sales/marketing split). I can think of approximately zero for average total marketing cost/oppty. You can’t benchmark a metric without good data sets to compare against.

So if someone’s asking you about marketing efficiency by looking at average total marketing cost/oppty, I’d politely redirect them to the marketing CAC ratio.

But say they’re looking at cost. Specifically, that the company is forecasting a pipeline generation shortfall of about 50 oppties and the CEO asks marketing: How much money will it take for you to generate 50 more?

Is $9,000 * 50 = $450,000 even correct?

The answer is no. To get 50 more oppties, you don’t need to hire 5% more marketers, boost the CMO’s salary by 5%, up the PR agency retainer by 5%, increase the userconf budget by 5%, spend 5% more on billboards, or increase tech infra spending by 5%. Thus, you should not multiply the average total marketing cost of an oppty by the number of oppties. You should multiply the incremental cost of an oppty by 50.

And the best answer we have here, at our fingertips, for the incremental cost of an oppty is the average demandgen programs cost/oppty. In our example, that’s $3,250. So, to generate 50 more oppties would cost $162,500. That’s good news because it’s a whole lot less than $450,000 and because it’s correct.

In short, cost/oppty = total demandgen cost / number of oppties.

This begs a potential rathole question which I call the low-hanging fruit problem. Most demandgen marketers argue that picking oppties out of the market is like picking apples out of a tree. First, you pick the easy ones, which doesn’t cost much. But the more apples you need, the higher up the tree you have to go. That is, the cost of picking the 1,000th apple is a lot higher than the cost of picking the first one. That is, the average cost of picking 1,000 apples is less than the incremental cost of getting one more.

While I think there’s some truth to this argument — and a lot of truth when it comes to paid search — you can’t let yourself slide into an analytical rathole. As CMO, a key part of your job is to always know the incremental cost of generating 50 more opportunities. Because — as veteran CMOs know well — either or both of these things happen with some frequency:

There is an oppty shortfall and someone asks how much money you need to fill it. You should answer instantly.
There is a money surplus and on day 62 of the quarter the CFO approaches you, asking if you can productively spend $100K this quarter. The answer should always be, “yes” and you should start deploying the money the next day.

That’s what you might call “agile marketing.” And you get agile by doing the math in advance and having the incremental spending plan in your pocket, waiting for the day when someone asks.

To make things easy, unless and until you have a spending plan that answers the cost of getting 50 more oppties, just use your average demandgen cost/oppty and uplift it by 25% to adjust for the low-hanging fruit problem. That way you can answer the boss quickly and you’ve left yourself some room.

Let’s close this out by raising a common objection to using demandgen costs only. It sounds something like this:

If I use demandgen cost only, someone might say that I’m understating the true cost of a marketing-generated opportunity and I’m going to get in trouble.

Well, that certainly can happen. People can accuse you of anything. There are two ways to avoid this.

Speak precisely. If asked, say “the average demandgen cost of an oppty is $3,250.” And, “the incremental cost of getting 50 more will be around $4,050.” (An approximately 25% uplift.)
Use footnotes. If making slides, always put definitions in the footer. So, if a row is labeled “cost/oppty” then make a footnote that explains that it’s demandgen cost only. Better yet, label the row “demandgen cost/oppty” and use the footnote to explain why that’s a better proxy for an incremental cost — which is the thing most people are worried about.

And finally, remind them if they want to discuss overall marketing efficiency, they should change slides and look at the marketing CAC ratio, which does proudly include every penny of marketing expense. And if you’re really, really good, ask them to skip to the slide that shows the sales/marketing expense ratio and discuss that.

Board-Level Questions On The Marketing Budget

Posted on December 2, 2024 | 2 comments

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:

Current-year marketing performance. Metrics on the left, OKRs on the right.
Next-year proposed OKRs.
Next-year proposed organization chart.
Top-down S&M analysis, e.g., CAC, CPP, sales/marketing expense ratio, history, benchmarks.
Top-down marketing budget analysis, e.g., spend by people/programs/infra, headcount, total cost/oppty.
Overall pipegen and coverage model, e.g., targets by horseman, how pipegen ensures coverage
Demandgen budget analysis, e.g., spend by channel, pipe/spend, DG cost/oppty, coverage.
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.)

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Posted in Boards, CAC, Marketing, Metrics, Pipeline, Silicon Valley, Startups

Tagged Marketing Budget

The Impact of AI on SaaS Metrics: Video Now Available

Posted on October 24, 2024 | 1 comment

Just a quick post to highlight that the good people of Benchmarkit, host of SaaS Metrics Palooza 24, have posted the video of my presentation, The Impact of AI on SaaS metrics. The slides are here.

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Posted in AI, Metrics, SaaS, Startups, VC

Slides from SaaS Metrics Palooza 2024: The Impact of AI on SaaS Metrics

Posted on October 8, 2024 | 1 comment

Just a quick post to share my slides from today’s presentation at SaaS Metrics Palooza 2024, entitled The Impact of AI on SaaS Metrics.

The short summary is:

The concept of ARR is already challenged by monthly-varying pricing, e.g., usage-based pricing.
AI will exacerbate that problem, bringing new forms of value-based pricing, e.g, unit-of-work or outcome-based pricing.
There are two schools of thought on dealing with this: (1) split the ARR baby into baseline and variable, then analyze the baseline as if nothing has changed, and (2) spend is truth, where we substitute trailing spend for ARR. I’m in the second camp.
AI will, gasp, require us to think about cost, something we don’t really like to do in the software business and something we’ve historically been able to kind of ignore.
All the heavy lifting is going to move to the pricing model.

In short, to know ARR we used to read contracts. In the future, we’re going to read invoices, instead.

Yes, for internal reporting we will do a lot of pricing model analysis and examination of the base/variable split. But for external reporting, the big six SaaS metrics all depend on ARR and going forward that won’t change. We’ll just use some proxy for ARR, as many quietly do already today.

Like a duck, nothing will change much on the surface, but they’ll be a lot of activity underneath. And the metrics won’t mean quite the same thing as they once did. For example, ARR and NRR will become less forward looking and work less well as leading indicators.