Sales and marketing alignment, and why RevOps is always hired too late: Brad Rosen of Sales Assembly

Sales and marketing alignment sounds, in Michael's words, like unicorns and rainbows and apple pie. Brad Rosen's answer to how it actually happens starts with an admission: a lot of the time, it does not.

Rosen is president at Sales Assembly, and was employee number three at G2, where he spent seven years scaling go-to-market functions before being asked to run revenue operations. This is the first episode of this show to cover the function.

How he ended up in RevOps

The origin story is funnier than most. Rosen started in finance at large banks, went to business school, decided against the cubicle, and moved to startups.

At G2, the CEO came to him and suggested he run RevOps. Rosen's response was that he did not know what that was. This was eight or ten years ago, when the function was only starting to form. The second time he was asked, he still did not know what it was. By the third time he took the hint.

It turned out to be a good intersection: a financial data and analytics background combined with go-to-market commercial strategy.

Why nobody can define it

Rosen's first substantive point is that the definitional confusion is itself the problem. Is it RevOps, sales ops, marketing ops? It means something different at every company.

His distinction on what people are actually hiring for matters. Some say RevOps and mean a sales operations person, effectively a Salesforce administrator. Others want a strategic partner. And the trouble arrives when you want both: the strategic partner who can also administer the system, build go-to-market strategy, and step into enablement when needed. That person is hard to find and expensive.

So the first question he asks anyone who tells him they want to hire for this is what exactly they are expecting, because only then can you discuss what that costs.

The ratio nobody hits

The most quotable data point in the episode is the recommended staffing ratio Rosen cites from Andreessen Horowitz, which he suspects would shock most listeners.

Roughly one RevOps person once you have ten go-to-market people. Two by the time you have twenty-five. Three by around fifty. And scaling from there.

Almost everybody is well behind that curve, and his explanation is the honest business case problem. There is no linear relationship between hiring a RevOps person and revenue produced. Faced with the choice, companies hire another account executive or sales development rep instead.

His counterargument is the one to make internally: done properly, the return is exponential rather than linear, because one RevOps person makes the entire go-to-market team meaningfully more effective.

What good foundations prevent

Asked what RevOps should solve early, Rosen frames it as setting the right foundation, and describes the failure mode in detail.

Without it you get poor data hygiene and poor systems and processes, which makes scaling harder. You cannot ramp people quickly. You cannot reliably identify high performers versus low performers. You have no consistent sales process. Leads fall through the funnel. Customers slip who should have been served better.

Later the work becomes data analysis, systems and tooling. And at real scale it bifurcates, with separate RevOps functions serving enterprise, small business and customer success.

Michael proposes a two-part summary, analytical and execution. Rosen adds a third, and it is the hardest.

The strategic function means melding data with feedback from the field and the organization's strategy, which he describes as a triangle. You go to the field and ask what is challenging them, and you cannot say yes to everything. So you prioritize the feedback, then check it against the data: is this a real problem or a squeaky wheel, how big is it, what would fixing it cost, and what would the impact be. Then back to the business and its goals.

His warning about the role: it is not for the faint of heart, because you have to be able to say no not only to an account executive but to the chief revenue officer and the CEO, with a coherent argument and data behind it.

Culture before tooling

On what a good foundation looks like from day one, Rosen's answer puts culture ahead of systems.

You could set up perfect tooling, and if the company does not believe in it and it is not part of the culture, it will not work. People have to understand that entering this data and following these processes is part of what they do, and that has to come from the top, from the CEO and the chief revenue officer down. It cannot rest on reps knowing how and wanting to.

The reason to get it right early is that a messy system is very hard to unwind, though he acknowledges the tooling and API landscape has made data migration easier than it was. What has not changed is the change management required at a legacy company to get people doing things a new way.

What AI actually changes

Rosen's assessment is measured. He does not think AI can yet transform a whole organization and all of its data in a meaningful way.

What he can see clearly is the conversion of unstructured data into structured data. A call gets recorded, summarized, and the takeaways land in the right fields in the system.

His extrapolation from there: all calls, emails and unstructured data being structured not just for record-keeping but for forecasting, with some understanding of intent to buy derived from what was actually said. Tools are already working on this and he expects them to get considerably better.

The interesting implication is that you may not need to make the data better than it already is, because the model can assemble and summarize it correctly regardless.

Why RevOps outlasted the buzzword phase

Rosen ties it directly to the end of the zero interest rate era, and the shift away from growth at all costs.

When the requirement becomes efficiency, and companies are trying to reach profitability or at least slow their burn, you need every rep to be effective and you cannot carry slack. Which means somebody has to be the partner asking whether you have the right systems, processes and people to execute on it. Plus the financial work: what is the burn, where can costs be cut, what do the unit economics look like.

How alignment actually gets built

Rosen's honest opening is that it often does not happen, because it requires people to lower their guard and their ego enough to do what is right for the business rather than for their own team.

Where it does work, he identifies two components.

Everyone speaking the same language and looking at the same data. His illustration of the failure is exact. Marketing is looking at qualified leads delivered. Sales is looking at closed business. Customer success is pointing out that the business closed is not renewing, so the top of the funnel needs to change to produce customers with proper lifetime value. Three functions, three scoreboards.

Compensation and visibility. He thinks marketing should almost certainly carry some component tied to sales, and possibly to retention. But he rates visibility above compensation: looking at all the data across the whole funnel through retention, and then actually acting on it.

His diagnosis of the underlying cause is structural rather than personal. Software companies were built so everybody does their own job extremely well and nothing outside it. Master marketing, then master the sales development role, then the account executive role, then customer success. The current pressure is forcing that to blend, with account executives doing more prospecting, and a visible trend toward customer success managers carrying quota, because it is hard to justify roles doing good work with no commercial component attached.

Alignment starts at hiring, and runs on self-interest

Asked how a leader creates alignment, Rosen starts at hiring. Does the marketing leader believe they are responsible for sales? Does the sales leader believe they are responsible in some capacity for retention? Does the customer success leader believe they owe feedback back to both, so the first call targets the right customer profile?

Then culture: visibility and transparency, showing the metrics in every team meeting, and bringing the relevant people into the problem. His example is a retention problem where the answer is not to send the customer success team on an offsite to fix retention alone. People feel ownership when they have visibility and a hand in crafting the solution.

And when Michael pushes on how you get people to put down sharp elbows, Rosen's answer is refreshingly unsentimental.

Everybody is looking out for themselves. Everybody wants to do better in their career, to succeed financially, to feel they accomplished something, to build their resume. And he noticed something specific while building RevOps at G2: money matters, and so does hitting quota, because people want to tell their family and put it on a resume.

So the way to get buy-in is to tie the metric back to what the person actually wants. Show the marketing team how solving retention helps marketing specifically.

Metrics that are not vanity

Sales Assembly distils to a few core company metrics, with departmental metrics tying into them.

Rosen's test is whether something ties back to revenue or retention or the actual goals. His example is instructive precisely because it is a metric they care about and deliberately exclude.

They sell training and development, and they track customer satisfaction with the programming religiously. It is not one of the company's core metrics, because they consider it a means to an end rather than something that drives business results. It is a precursor that indicates whether a customer is happy, which may in turn drive retention. There are steps in between.

The three requirements he names: clear, definable, and actionable, meaning you can take action on it and change something within your job.

Happy does not mean renewed

Michael asks for the single metric that captures customer happiness and business health, and Rosen questions the premise.

He does not think people renew on happiness anymore. During the money-is-free era you might buy a tool because you knew somebody, it sounded interesting, and it might give a small boost. That has changed, and ripping out a tool is easier now, because many tools overlap enough that you can find the capability elsewhere and migrate the data.

His observation about how budgets now work is worth noting for anyone selling into these companies. Budgeting is done on a prioritization basis rather than by departmental allocation. Sales may lose $25,000 to fund a finance tool the company has prioritized. From a sustainability standpoint he thinks that is the correct way to do it, and it is not how the model was built.

His summary: you need to be happy to renew, but you will not renew just because you are happy.

The AI sales development rep

Michael's story is a good one. He picked up an unknown number expecting his kid's school and found an AI agent prospecting him. It identified itself as an agent, and he found the conversation surprisingly useful. He asked hard questions and got direct answers rather than fluff or a pitch.

Rosen's assessment has two halves.

On volume, he is skeptical. The precedent is what happened when sales engagement platforms made it possible to send thousands of emails a day and inboxes became a graveyard. Personalization at the time meant using someone's first name. Now data enrichment tools can reference where you went to university, which demonstrates a good scraping job rather than that you are in the market for anything. If every company runs an AI caller that can dial as fast as it likes, the result is noise.

On speed, he finds the buyer's side genuinely interesting. Sellers typically slow the process down to qualify you. As a RevOps buyer, you often already know what you want, understand the integrations and the data requirements, and want to get to the substance. A bot might let you.

Michael's follow-up is the sharpest moment. At the end of the call the agent offered to book time with an account executive, and his reaction was to wonder why he needed to, and whether they could just complete it there.

And Rosen names the underlying dynamic: with a bot you do not feel obliged to let someone down gently, and you do not feel you are being pulled into a process, because hanging up costs nothing emotionally.

RevOps or sales ops

Rosen's answer is that the label does not matter much and depends on the organization.

Sales ops in theory covers sales, and you could equally have customer success ops, marketing ops, business ops, all potentially under RevOps. Someone might call themselves sales ops and be doing RevOps, or the reverse.

Reporting lines often decide it. Sales ops usually reports up through the chief revenue officer, and if that person also owns customer success, then customer success ops joins and you have RevOps.

His substantive point: the more bifurcated these roles are, the harder it gets, because you now have people with competing priorities negotiating with each other. A single operational foundation for the go-to-market team can see around corners, knows what is happening across departments, and can act as the tiebreaker when projects or budgets compete.

How to actually justify the budget

Rosen is honest that advocating for RevOps is hard, because you cannot draw a direct line from an enabling role to revenue, and getting budget for strategy is not intuitive. He likens it to enablement and partnerships, where leadership has to understand the inherent value and grant autonomy.

But he gives a concrete method.

Measure yourself against go-to-market outcomes. Are you getting better at forecasting? Is the sales team more efficient? Can you reduce team size, or hold it flat and grow revenue? Can you reduce burn? RevOps should be tied to organizational growth the way marketing is tied to revenue, and if you are not, you are probably working on the wrong priorities.

Then the time management discipline that makes it visible. RevOps easily degenerates into a support desk where everything is broken and you fight fires all day. His allocation: fires are 20% of the time, and the other 80% goes to strategic projects. Checking those off is what makes the work legible to the CEO and the board.

His examples of what a legible claim sounds like: we put in this tool and reps ramped a month faster than before, we changed the sales process and forecast 3% more accurately.

The spreadsheet is just a sheet

Asked what he wishes he had known earlier, Rosen gives the best line in the episode.

The spreadsheet is just a sheet. People do not operate out of spreadsheets. They operate from emotions and feelings, and they do not have the information you have.

His description of how the mistake happens is precise. You are in the room with the CEO, the chief revenue officer and the board. You have the data, the capacity plan, sensitive information about compensation and quota attainment. You make sound judgments, leadership agrees, you roll it out, and the sales team asks what on earth is going on.

And you may not be able to fully explain why it is the way it is, at which point emotions get involved, as he says they should, because everyone deserves to understand how decisions were made that affect their earnings.

He is candid that he rolled out territories and compensation plans believing the teams understood them, and they did not, and that this was on him.

His answer for what he would do differently is a good checklist. Be genuinely in tune with the field: on sales calls, meeting actual reps rather than only leaders, understanding what they care about. Much more documentation and training. And better timing, rolling things out sooner so there is time to digest, give feedback and share ideas.

With a warning worth keeping: people nodding their heads looks like agreement, and often is not.

The 5 things I took away from this conversation

1. One RevOps person per ten go-to-market people. Almost nobody is at that ratio, and Brad's explanation is why: there is no linear revenue attribution, so the account executive wins the headcount argument every time. The counterargument is that the return is exponential, and somebody has to make it out loud.

2. Three functions, three scoreboards. Marketing counting qualified leads, sales counting closed business, customer success watching renewals fail. That is not a people problem, it is a measurement problem, and it is why alignment initiatives that start with a workshop do not survive the quarter.

3. Tie the metric to what the person actually wants. Brad's version of alignment is unsentimental and therefore workable. Everyone wants to hit their number and say so. If you can show marketing how solving retention helps marketing specifically, you get buy-in that a values conversation will not produce.

4. Fires are 20%, strategic work is 80%. RevOps degrades into a help desk by default. The allocation is what makes the function legible to a board, because ramping reps a month faster is a claim you can make and defend.

5. The spreadsheet is just a sheet. I have made this mistake. You spend weeks inside the data, reach a sound conclusion, and roll it out to people who have none of the context and every reason to feel something about it. The fix is time and documentation, not a better spreadsheet.

FAQ

What is sales and marketing alignment? Getting the go-to-market functions working from the same data, the same definitions and compatible incentives. Rosen's test is whether marketing, sales and customer success are all looking at the full funnel through retention, rather than each optimizing their own handoff metric.

How do you align sales and marketing teams? Start at hiring, by selecting leaders who accept responsibility beyond their function. Then make the metrics visible to everyone and bring the relevant teams into each problem rather than assigning it to whoever owns the symptom. Compensation can help, but Rosen rates visibility higher.

What is RevOps and how is it different from sales ops? RevOps covers operations across the whole revenue organization, typically sales, marketing and customer success, while sales ops covers sales alone. Rosen notes the labels are used interchangeably and often determined by reporting lines, and that more fragmentation means more competing priorities.

When should a company hire its first RevOps person? Earlier than most do. Rosen cites a recommended ratio of roughly one RevOps person per ten go-to-market people, scaling to two at twenty-five and three at fifty, and observes that companies are usually well behind it because the business case is hard to make.

How does a RevOps team prove its value? By measuring against go-to-market outcomes rather than activity: forecast accuracy, ramp time, revenue per head, burn reduction. Rosen's supporting discipline is capping firefighting at around 20% of the team's time so the strategic work is visible enough to point at.

Also mentioned

• Sales Assembly, and its origins as an in-person networking group in Chicago
• G2, where Rosen was employee number three and later ran revenue operations
• The Andreessen Horowitz staffing ratio for revenue operations
• The zero interest rate era, and what changed when growth at all costs ended
• AI sales development representatives, and the volume problem they inherit from email automation

Listen to the full episode

Brad Rosen on Between Two COO's

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