The Product Marketing metrics that actually matter

Most AI can already build dashboards. Increasingly, AI can also explain what's happening in those dashboards. But it still can't tell you whether your growth problem is caused by poor positioning, the wrong ICP, weak sales enablement or a product that simply isn't solving an important enough problem.

That's why I think Product Marketing's value is shifting towards interpreting what those Product Marketing metrics are telling us about the business.

Shared metrics create shared ownership

One thing I've learned over the years is that metrics only change behaviour when someone feels responsible for them.

If Marketing is measured on MQLs, Sales is measured on revenue and Product is measured on feature delivery, everyone can hit their targets while the business still misses its growth goals.

That's why I prefer shared metrics.

When Marketing and Product Marketing both own MQL to SQL conversion, they naturally start discussing campaign quality and messaging. When Sales and Product Marketing both own SQL-to-Won conversion, they review objections, positioning and enablement together. And when Product shares responsibility for adoption and customer feedback, roadmap discussions become grounded in what customers actually need rather than internal assumptions.

The metric itself isn't the objective. Its real value is creating the conversations that help solve the business problem.

Metrics don't tell the whole story

One of the biggest mistakes I see is teams treating metrics as answers rather than clues.

I've been in plenty of meetings where someone points at a falling conversion rate and immediately starts proposing solutions. We should change the messaging. We should generate more leads. We should train Sales.

Maybe, but at that point nobody actually knows what's causing the problem.

A metric can tell you that something has changed, but it can't explain why it changed.

That's where Product Marketing should step in. The job isn't to add more metrics. It's to understand what's happening in the market and inside the business using the metrics we're already measuring. Are customers describing a different problem? Has Product moved in a new direction without the messaging evolving? Is Sales hearing new objections? Has Marketing started attracting a different audience?

Those conversations are far more valuable than another report.

AI will continue to get better at analysing data, spotting patterns and highlighting anomalies. But someone still needs to connect those insights, understand what they mean for the business and bring the right teams together to respond.

In my experience, that's where Product Marketing creates the most value.

AI is changing where Product Marketing adds value

When people ask whether AI will replace Product Marketing, I think they're asking the wrong question. The real question is: "What parts of Product Marketing should still require human judgement?"

AI is becoming incredibly good at analysing customer calls, summarising feedback, identifying trends and producing first drafts of almost any asset you can think of. It frees Product Marketing from spending hours collecting information and allows us to spend more time making sense of it.

The difficult part now is deciding what matters, helping the business make better decisions and keeping Product, Marketing and Sales aligned around those decisions.

If AI makes analysis faster, good judgement becomes even more valuable.

Leading indicators give you time to act

One lesson I've learned is that revenue is usually the last place a problem shows up.

By the time revenue starts falling, the real issue has often been building for months.

That's why I spend far more time looking at leading indicators than lagging ones.

If MQL to SQL conversion starts declining, sales cycles suddenly become longer or a product launch generates fewer opportunities than expected, those are all early signals that something in the go-to-market motion is starting to drift.

The goal isn't to obsess over those numbers.

The goal is to spot the problem early enough that you still have time to fix it.

The real job of Product Marketing

I don't see Product Marketing as the team that reports dashboards.

I see it as the team that helps explain why the numbers are moving and brings the right people together to solve the problem.

The first question shouldn't be, "How do we improve this metric?" It should be, "What is this metric telling us about how well Product, Marketing and Sales are working together?" That's usually where the real answer lies, because metrics rarely reveal an execution problem in isolation. More often, they reveal that the teams are no longer aligned on the customer, the value proposition or the go-to-market strategy.

Final thought

That's how I think about Product Marketing measurement.

The real problem isn't choosing the right metrics. The real problem is that Product, Marketing and Sales often interpret those metrics in isolation.

The best Product Marketing teams don't use metrics simply to measure performance. They use them to create better conversations, make better decisions and keep the entire go-to-market organisation aligned around the customer.

If you missed my previous article, Why product launches don't deliver the growth SaaS founders expect, it's a good companion piece. It explains why many of the problems these metrics reveal actually begin long before launch day.