When asked, “how is it going?” many companies will respond with something akin to, “things are looking strong, the pipeline is up to $50M.”
Not a bad statement, but certainly an imprecise one. “Over what timeframe?” you might ask. To which you’ll typically hear one of two answers
“Uh, that’s the whole thing.” I don’t love this answer as many companies –particularly the ones who answer with all-quarter pipeline — let junk opportunities get parked in the 5Q+ pipeline. (You can fix this by including a timeframe as part of the definition of opportunity and ensuring you review the entire pipeline whenever you do a pipeline scrub.)
“That’s the rolling four-quarter (R4Q) pipeline.” I don’t love this answer either because, in my experience, companies who focus on R4Q pipeline as their top pipeline metric tend not to put enough emphasis on pipeline timing. It’s too easy to say in January, “this year’s number is $20M and we’ve got $50M in the pipeline already (2.5x pipeline coverage) so we are golden.” The problem, of course, is if 80% of that pipeline is backloaded into Q4, then while “the year may look great,” you’re going to need to survive three wasteland quarters to get there. Even if that $40M Q4 pipeline were real, which it usually isn’t, most sales VPs won’t be around in October to close it.
I never look at rolling-four-quarter pipeline for the simple reason that I’ve never had a rolling-four-quarter sales target. We have quarterly targets. Instead of looking at R4Q pipeline and hoping it’s well distributed (over time and across sellers), my philosophy is the opposite:
Once you accept this viewpoint, a few things happen:
Someone needs to start forecasting day-1 next-quarter pipeline coverage. What’s the point of focusing on next-quarter coverage if no one is tracking it and taking corrective actions as needed? As mentioned, I think that person should be the CMO.
We need to start tracking the progression of the pipeline over time. This quarter’s starting pipeline is largely composed of last-quarter’s next-quarter pipeline and so on. Since there are so many ebbs and flows in the pipeline the best way to track this is via periodic snapshots.
Towards that end, here’s a chart I find useful:
Let’s examine it.
Each row is a snapshot of the pipeline, broken down by quarter, taken on the first day of the quarter. (Some allow a week or two, for pipeline cleanup before snapshotting, which is fine.)
We’re tracking pipeline dollars, not opportunity count, which generally works better if you have a range of deal sizes and/or a multi-modal distribution of average sales prices. Doing so, however, can leave you overconfident if you create new opportunities with a high placeholder value. (See this post for what to do about that.)
We show pipeline coverage in the block on the right. Most people want this-quarter coverage of around 3.0. Targets for next-quarter and N+2 quarter are usually less well understood because many people don’t track them. Coverage needed in the out quarters is a function of your sales cycle length, but the easiest thing is to just start tracking it so you get a sense for what out-quarter coverage normally is. If you’re worried about that 1.6x next-quarter coverage shown on the 7/1 snapshot, read this post for ideas on how to generate pipeline in a hurry.
It’s good to carry at least one year’s prior snapshots so you can see historical progression. Even more is better.
I’m assuming bigger deals and longer sales cycles (e.g., 6 to 12 months) so you will actually have material pipeline in the out-quarters. For a velocity model with 25-day sales cycles, I’d take this template but just switch the whole things to months.
The most fun part of this chart is this you read it diagonally. The $7M in starting this-quarter pipeline at the 7/1/21 snapshot is largely composed of the $6.5M in next-quarter pipeline at the 4/1/21 snapshot and the $3M in pipeline at the 1/1/21 snapshot. You can kind of see the elephant go through the snake.
When you add this chart to your mix, you’re giving yourself an early warning system for pipeline shortages beyond simply forecasting starting next-quarter pipeline. You should do this, particularly with big deals and long sales cycles, because one quarter’s notice is usually not enough time to fix the problem. Yes, you can and should always try to mitigate problems (and never give-up saying, “looks like we’re going to hit the iceberg”), but if you give yourself more advance notice, you’ll give yourself more options and a better chance at reaching the goal: starting every quarter with 3.0x coverage.
Logo retention rate, why a count-based rate works best when your customers are more or less “all the same” on deal size, and that you should use a dollar-based rate when they’re not.
Available-to-renew (ATR) logo retention rate, which factors in only those customers who had a chance to renew or not. If you’re an ARR-based company but do multi-year contracts not every customer has the chance to get out every year.
Gross revenue retention rate, and why it’s gathering steam as an important metric. (Sometimes great expansion is hiding major churn and just looking at churn before expansion will reveal that.)
Net revenue retention (NRR), aka net dollar retention (NDR) for those who work only in dollars, which is probably the hottest SaaS metrics after ARR and ARR growth.
The risks of math and MBA types becoming over-reliant on numbers / models, and how to manage them. Remember the George Box quote: “all models are wrong, some are useful,” which I discussed in my SaaStr 2021 presentation.
Mitigating this problem by “just talking” and doing periodic win-touch analysis to keep you connected to reality.
The attribution problem and my new favorite mug. How to present attribution data to avoid problems and over-reactions (hint: put disclaimers up front).
In the land of disruption, there’s always something dying and something lining up to replace it, so we’re pretty used to hearing things like “on-premise is dead, long live SaaS.” Sometimes, they’re right. Despite the 2008-era views of our resident luddite below, SaaS really did kill on-premises.
Sometimes they’re wrong. Despite years of hearing, “the data warehouse is dead, long live the data lake,” the data warehouse is doing just fine, thanks. Snowflake can tell you 60 billion reasons why.
Sometimes, they’re both right and wrong. Data lakes are doing pretty well, too. Not everything is zero sum.
You don’t hear this just about technologies, but business models, too.
When the Internet eliminated sellers’ monopoly power over information, I heard, “traditional B2B sales is dead, long live facilitating buying processes.” This was right and wrong. B2B sales wasn’t dead, it just changed. When buyers can get more information themselves and advance further without needing sellers, reframing sales as facilitating buying is a good idea.
I think of PLG as embracing the continuation of a trend already started by the Internet. In phase one, buyers no longer needed sellers to get basic product information. (It’s almost hard to believe, but back in the day, if you wanted even a white paper let alone a demo, you had to talk to a seller.) In phase two, buyers no longer needed sellers to get hands-on product trial. It’s the same transformation, just applied to the next two phases down the funnel.
While some companies consider trials customers (and ergo need to count them in churn), I think most enterprise startups should consider trials leads, and the ones who do the right things with the product become leads worthy of passing to sales. Because they’re qualified by product usage and not marketing actions, they’re called PQLs instead of MQLs. (Ask my friends at Correlated, or any of the new PLG CRMs, to learn more.)
The other day an old friend of mine, now a highfalutin GM at a big-name software company, forwarded me this article, Traditional B2B Sales and Marketing are Becoming Obsolete. So, anticipating the content, I donned my “it’s PLG and enterprise, not PLG or enterprise,” gloves and got ready to fight.
But I was surprised. Instead of saying, “B2B sales is dead, long live PLG,” the article threw me a curveball:
“B2B sales is dead, long live the unified commercial engine (UCE).”
Huh. The what?
Who wrote this, I think? Ah, it’s some guy from Gartner. Before I can add, “and they should stick to IT prognostication,” I see that “some guy” is Brent Adamson, coauthor of The Challenger Sale, one of my top five favorite sales books.
The Article: Summary and Analysis
The article argues that it’s no longer enough to try and integrate (in the sense of align) sales and marketing, we should instead unify them. That’s because buyers have more access to information (including hands-on trials), buyers have access to that information via multiple channels (e.g., vendor websites, review sites), and buyers don’t want to interact with salespeople (which is not exactly new, though he argues that younger people want to interact with sellers even less than older ones).
Sales is thus fighting for relevancy in the buying process and seeking to regain customer access. The linear model is dead, long live the unified model. In short:
Helping today’s B2B buyers buy isn’t a sales challenge, nearly so much as an information challenge (or, alternatively, an information opportunity).
He begins with motherhood and apple pie:
The companies that best provide customers the information they most urgently seek, specifically through the channels they most clearly prefer, are in a far better position to drive commercial success in today’s rapidly evolving digital commercial landscape.
While once a relatively accurate proxy for the underlying buying behavior it was meant to approximate, the serial commercial engine is hopelessly out of date — and dangerously out of sync — with how today’s B2B buyers buy.
With a requisite Gartner dash of profundity:
Today’s buyers are not only channel agnostic in terms of behavior, they’re digitally dominant in terms of preference.
I think that means people like to research shit online before buying it. Got it. Stipulated.
I always say that any good sales pitch is 80% tee-up and 20% knockdown. Now, on the receiving end of such a pitch, I need to advise some caution in that approach. At some point people want to hear your solution; I’m on page 6 of what’s barely 8 pages and still waiting. It’s always easier to agree on the problem than the solution (e.g., child poverty, wealth inequality, climate change). It’s why the 80/20 formula works — you get people agreeing with you, sounding smart, heads nodding, and then you shift to a credible solution that drives your agenda.
But you can’t wait too long to shift to the solution (so I should probably revise my rule to 60/40). And you should introduce the solution from first principles, not via a case study (which you can always present later, as proof). And if you’re going to introduce the solution via a case study anyway, it shouldn’t be a 1300-person company based in Calgary that I’ve never heard of.
Yet, here I am, about to learn how SMART Technologies found the answer to this pervasive problem by “rebuilding it from the ground up.” But first, I need to learn about SMART Technologies. I am now at page 6.75 of an 8.25 page article and still not heard the solution.
The answer: completely dismantle traditional sales, marketing, success, and service altogether and reconfigure them into a unified commercial engine (UCE).
I’m now thinking:
Can you partially dismantle something?
Can you completely dismantle something without it being altogether?
Where did success and service sneak into things? While I’d certainly, almost definitionally, want to put all customer-facing teams into a unified engine, how is it that success and service are totally omitted from the argument’s tee-up?
You create a UCE by:
Careful mapping of customers’ buying journeys across a range of predictable “jobs to be done” as part of a typical educational technology purchase.
Never one to miss a gratuitous Clayton Christensen reference, I have to observe that while I am big believer in his work and the jobs-to-be-done framework, I think this is something of a misapplication. Christensen’s point was about innovation — if you think of products as hired instead of bought, and hired to do specific jobs, then you will anchor yourself in the customer’s point of view when contemplating new products and features. Think: not how can we make this milkshake tastier, but how can we make this milkshake more effective when it’s hired as a one-handed commuter breakfast. What we’re talking about at SMART is simply mapping customer journeys.
When you do that careful mapping, this happens (or, at least, this is what happened at SMART):
Through that initiative the team identified five common buying jobs (Learn, Buy, Order/Install, Adopt, Support) and established an internal team specifically deployed to support each one, reassigning nearly every member of legacy marketing, sales, service, and success staff as a result. In all, over 250 team members received new job designations as part of the process.
You can’t do a re-org these days without creating a center of excellence, so SMART created three:
SMART created three centers of excellence, where they consolidated otherwise duplicative efforts across traditional functional boundaries, one for data and analytics, and one for customer insights and positioning, and one for creative and digital experience.
Those, by the way, sound like a good idea. I like centralized, specialized support teams, particularly in areas where we’re trying to present one face to the customer.
And then, the re-organization:
Finally, the team then deployed their staff in geographically aligned “pods,” where each pod contains members supporting each of the respective five buying jobs. So, the pod for the southeast United States, for example, is made up of combination of individuals tasked with supporting the entire range of customer jobs from Learn to Support across all relevant digital and in-person channels (including third-party distribution).
In short, run your regions in the USA more like you run countries in Europe.
It’s neither a bad idea nor some insanely different approach. It does create the need, however, for sophisticated regional leaders who are capable of aligning on both dimensions of the matrix. Concretely: is the French country marketing manager part of the French team or the marketing team? Answer: it’s a trick question. The answer is both and they need to learn which way to look, when, as they face managerial decisions — e.g., look to the CMO for questions on messaging and positioning, look to the French country manager when prioritizing campaigns and investments.
I’m going to ignore the end of the article where the VPs of sales and marketing proudly introduce themselves “the former heads” of their respective departments, because they both seem to still work at the company and do something, though the article doesn’t say what their new titles and jobs are. I’ll assume, hype and semantics aside, that they’ve implemented some sort of functional vs. pod matrix. As one does with countries in Europe.
Before wrapping up, let me challenge some of the more detailed points in the tee-up.
Yes, the machine is by default linear. But that’s just the first pass.
Contacts that don’t make it MQL or SQL get put into nurture and nurture is not linear. Nurture is a popcorn machine where we dump kernels in, expose them to heat, and over time and in a pretty random order, the kernels pop into recycled MQLs. I’ve run companies where half of all MQLs are recycled.
There’s the question of whether we should nurture people or accounts, as we would in account-based marketing. Nurturing accounts is definitely not linear, it’s like having one popcorn machine per account.
There is no 11th Commandment where God said that nurture shalt be digital only. While a lot of nurture is automated digital, marketers should remember that a nurture track, broadly defined, can also involve live events (e.g., C-level dinners), dimensional marketing (e.g., mailing a coffee-table book or a Moleskine), and live interactions (e.g., SDR or AE outreach). Nurture doesn’t definitionally mean a sequence of emails, nor should it.
The part of the linear handoff I detest is when sales “waives off” marketing once an opportunity is in play. This happens less frequently than it used to, but it reveals a deep lack of trust that should be fixed by destroying walls, not erecting them.
I’ll conclude by saying I think the article misses the most important point in organizational design. When it comes down the game on the field, who calls the plays and the audibles? Sure, we have a playbook, and we all know the play we’re supposed to be running. But things have changed. There’s a new participant in the meeting. They mentioned a new competitor who we didn’t know was in the deal.
With a group of talented people, they’ll usually be several different and vocal opinions expressed on how to proceed. The AE may want to reschedule the meeting. The SC wants to proceed with the demo. The consultant thinks we shouldn’t be in the deal in the first place. The sales manager thinks we can win it because the champion has our back. What do we do? Who calls the plays and the audibles that modify them?
In my mind, the person with the quota wins. As the old joke goes about breakfast: the chicken is participating, but the pig is committed. In a world where accountability for results legitimizes decision-making authority, it’s not enough to have a pod/commune and say we can all work it out. Sometimes we can’t. And often we can’t fast enough.
Whether you call that person the regional pod leader or the country manager, the role needs to exist and they need to take lead on deal strategy. Everything else is a supporting resource. Which is why I think marketing alignment with sales is enough. Yes, we need to collaborate and yes we need smart managers to work in the functional/regional matrix. Yes, in the case of marketing, we need field marketing to ensure ground-level local alignment.
But do we need to reorganize everything into regional pods? No. We just need to work together and be aware that buyers have more information, options, and control than ever before.
# # #
The irony is I ran a company in a pod structure, MarkLogic, where we had vertical pods (aka, business units) where we didn’t have sellers, SCs, and consultants. We had Federal sellers, Federal SCs, and Federal consultants — all working for a VP/GM of Federal. Ditto for information & media. But we did it not in the name of “traditional B2B sales is dead because buyers have more information,” but in the name of a vertical go-to-market strategy where we wanted specialization and alignment. Pods can work. It’s all about strategy first and organizational design to support strategy.
A great revops or FP&A person will give the answer from multiple sources and explain the differences among them. Moreover, they’d observe that sales and marketing (S&M) expense really should vary with growth rate, and they’d know that KeyBanc tracks that:
So if that $15M SaaS company is growing at 25%, then median S&M spend is 20% of revenue, whereas if it’s growing at 70%, then median S&M spend bulks up to 46%.
But that’s all SaaS Metrics 101. Today, I’d like to hop to the 201 level by introducing a simple that metric that can reveal a lot and on which few people focus: the sales/marketing expense ratio, which just equals sales expense divided by marketing expense.
To introduce the idea — quick, tell me what’s happening at this company:
The company is high relative to the benchmark
The company is not making much progress towards the benchmark
Sales is getting less efficient while marketing is getting more efficient
This situation is very common. Sometimes, it’s justified bottom-up — e.g., we’re building a partners function in sales that is only slowly becoming productive and we’ve upgraded both marketing leadership and the martech stack to improve marketing efficiency.
Normally, it’s not. In fact, normally, there’s no justification whatsoever. When you ask, you get, “well, that’s just how the budget process worked out, the real focus was on improving S&M and we did. Next question, please.”
Yes, you did improve S&M, but you put the “S&M” improvement 100% on the back of marketing (in fact, 200%) and with no bottom-up justification for why sales needs to get more expensive while marketing is going to magically become more efficient. This is a mistake. The likely result is underfed sellers screaming for pipeline, forming an angry mob with dogs and torches headed to the CMO’s office.
Let me tell you what’s going on when this happens:
Your CRO is a better negotiator than your CMO. They better be. If they’re not, you have an additional problem.
Your CRO has more negotiating leverage than the CMO. They are negotiating the company number directly with the CEO and indirectly with the board. This is high-stakes, board-level poker.
There’s usually no broken-out benchmark, typically only a combined benchmark, and given the prior two points, the CRO is just fine with that.
It’s easy to think that hiring sellers “leads directly” to new ARR than investing in marketing. Why? Because in enterprise software the bookings capacity model is typically driven off the number of sellers. Yes, this is intellectually lazy and only works on the margin, but deep down, it’s what a lot of CEOs and CFOs feel.
So the CMO gets asked to suck it up, the board doesn’t notice the problem, the CFO notices but doesn’t want to rock the boat, and the CEO is just happy to get the plan approved.
Hopefully the CRO has the decency to attend the CMO’s going-away party in the fall. Because if this process repeats itself for even a few years, that’s how it’s going to end.
So how do we fix this?
1. Shine a light on the problem, by adding the sales/marketing ratio to the in-line metrics presented in the plan.
I prefer to show it this way, which makes it clear we used to spend $2 in sales for every $1 in marketing, but that has crept up to over $3. Showing the metric gives people the chance to ask the all-important question: why?
The other way to show this is via “sales composition,” i.e., sales as a percent of sales and marketing:
In this case, you can say that sales has risen from two-thirds to three-quarters of S&M expense, and again ask why. I think the former presentation is more intuitive, but the advantage of this presentation is that KeyBanc benchmarks it in this form:
2. Shine a light on your inverted funnel model. Sometimes you can squeeze marketing expense just on the people side, but the real way you usually cut to these targets is by making a series of seemingly innocuous assumptions in your funnel. Consider:
Saying, we need to take MQL to SQL from 10% to 12%, SQL to SAL up from 65% to 70%, and SAL to close up from 15% to 20% all sounds pretty reasonable. When you combine these effects, however, you’re saying that you’re going to cut the cost of generating an opportunity by more than a third, from $2700 to $1800. That should get some attention — without any explanation other than the compound effect of small tweaks, it sounds like an Excel-induced hallucination to me.
3. Get the CRO on your side. Make them understand that squeezing marketing too hard for purely top-down reasons increases their risk on the plan. Get them to go to bat for you saying, “we need to ensure we feed the sellers enough pipeline.” Most boards solve for growth with one eye on the CAC and not the opposite.
4. Get the CFO on your side. In my experience, the hardest person to convince in these debates is the CEO, not the CFO. Why? Because the CEO is the one and only person who must negotiate the plan target with the CRO and that’s always something of a painful process. So, if you get the CRO and CFO on your side, you will greatly increase your odds of getting the CEO to along with you. You win the CFO over by emphasizing risk. Think: “we’ve (finally) got the CRO signed up for the number, but we’ve squeezed marketing too hard and that’s adding risk to the plan” and then say the magic words, “we don’t want to miss plan — do we, CFO?” They never do.
In a world where sales has more political power, better negotiating skills, and more negotiating leverage than their marketing colleagues, the somewhat natural state of affairs is for this ratio to slowly increase over time. The question is: should it? Everyone on the e-team needs to take accountability for thinking about that and ensuring the company gets the right, not just the easy, answer. And the CMO has the unique responsibility of ensuring they do.
I’m Dave Kellogg, advisor, director, consultant, angel investor, and blogger focused on enterprise software startups. I am an executive-in-residence (EIR) at Balderton Capital and principal of my own eponymous consulting business.
I bring an uncommon perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud EPM vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of the $500M Service Cloud business at Salesforce; CEO of NoSQL database provider MarkLogic, which we grew from zero to $80M over 6 years; and CMO at Business Objects for nearly a decade as we grew from $30M to over $1B in revenues. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Bluecore, Cyral, FloQast, GainSight, MongoDB, Pigment, Recorded Future, and Tableau.