I'll be at SaaStr AI Annual this week (May 12–14, San Mateo). If you're going, let’s meet up! Grab 20 minutes with me here.

Now back to today’s post …

The sales and marketing alignment problem is one of the oldest conversations in B2B. And it keeps happening at company after company because almost everyone diagnoses it wrong.

The conventional diagnosis: it's a culture problem. Different incentives. Different timelines. Different definitions of success. Fix the culture, fix the relationship.

So companies run joint offsites. They create shared Slack channels. They talk about "one team" in all-hands presentations.

And six months later, the same arguments are happening in the same pipeline review meetings.

The real diagnosis: it's a data problem. And until you fix the data, the culture won't follow.

The same numbers mean different things to different people

Ask a marketing leader how the quarter is going and they'll tell you about pipeline generated. MQLs, SQLs, opportunities created, influenced revenue. The numbers look strong.

Ask the sales leader running the same quarter and you'll hear something different. Pipeline is there but it's not converting. The deals that are closing came from outbound or referrals. Marketing-sourced leads are taking longer and churning at a higher rate.

Both of them are right. And because they're both right, neither can hear the other.

This is the core of the alignment problem. It's not that sales and marketing disagree about what's happening. It's that they're measuring different things at different points in the funnel and calling both of them pipeline.

Three definitions that break down first

The first is lead quality. Marketing defines a qualified lead by behaviour — content downloaded, forms filled, score reached. Sales defines it by fit — does this person have the problem, the budget, and the authority?

These are not the same definition. When marketing hits their MQL target with volume of the first kind, and sales misses quota because the pipeline is full of the second kind masquerading as the first — the fight that follows is entirely predictable.

The second is pipeline itself. Marketing counts pipeline when an opportunity is created. Sales counts it when an opportunity is real. In enterprise sales, the gap between those two things can be enormous.

The third is attribution. Was that deal marketing-sourced or sales-sourced? Did the conference generate the relationship or did the SDR sequence? Attribution models answer these questions with false precision — and when budget decisions are tied to the model, both teams have an incentive to argue about the model rather than improve the outcome.

What a shared data model actually looks like

It starts with agreed definitions at every stage. Not a CRM picklist nobody fills in consistently. A written agreement — signed off by both leaders — on what it means to move from one stage to the next. Built from outcome data, not compromise.

It requires shared accountability for downstream metrics. Marketing should be measured on conversion rate from MQL to closed won. Average deal size of marketing-sourced opportunities. Retention rate of marketing-sourced customers.

These numbers force marketing to care about what happens after the handoff. They create an incentive to generate fewer, better leads. And they give sales a reason to take marketing-sourced pipeline seriously.

The most powerful structural change is also the simplest: put both teams in the same room, looking at the same dashboard, having the same conversation about the same numbers. Not a marketing review and a sales review that occasionally collide. A joint revenue review where the questions are about the whole funnel.

This sounds obvious. It happens almost nowhere.

The management problem underneath the data problem

Even when the data model is right, the alignment problem persists if the management structure works against it.

Marketing leaders are typically measured on a quarterly cycle tied to pipeline generation. Sales leaders are measured on closed revenue. The lag between those two things — especially in enterprise sales — means a marketing leader can hit their number in a quarter where the pipeline they generated three quarters ago isn't converting.

This is a structural incentive to optimise for your own metric and blame the other team when the overall number misses.

The companies that solve this permanently don't just fix the data. They align the incentive structures — giving both leaders skin in the same game, measured over a timeframe that reflects the actual sales cycle, with shared accountability for outcomes neither of them can produce alone.

That's a harder conversation than a shared Slack channel. It's also the only one that actually works.

One question worth asking this quarter

Pull the data on your last twelve months of closed deals and ask: where did the deals that closed actually come from — not by attribution model, but by honest reconstruction of the buying journey?

The answer will tell you more about your alignment problem than any survey or offsite. And it will give you something specific to fix.

The alignment problem is most visible at the top of the funnel — when outreach goes out that doesn't reflect what sales knows about the buyer, or when leads come in that don't reflect what marketing knows about the ICP.

Skyp sits at that junction. When your outbound motion is built on the same understanding of the buyer that informs the rest of your GTM — the same triggers, the same pain points, the same language — the handoff from first touch to sales conversation is a continuation, not a restart.

That's what alignment actually looks like in practice. Not a better relationship between two teams. A shared model of the buyer that both teams are working from.