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Welcome to my new newsletter – the darive Inspiration Pulse. I'm starting to write on a regular basis NOW. So here we go, here's the first one. THUS, It would be great to hear your opinion about it. Just reply to this mail. Having this said, I am wishing you a a great read – let's go :)

There's a pattern I see so many times: Tracking fires on every click. Dashboards and reports are polished. Yet six months later, CMO and marketing team still can't give sharp and precise answers to the most important questions about what's really moving the needle.

This isn't a data problem. It's a problem of not asking the right questions. And I see it too often. It is: 

Data without direction

Picture this: you find a chainsaw in the shed. Powerful tool. You walk into the woods and start cutting. Trees fall left and right. Sawdust everywhere. Feels productive.

After a full day: what have you actually achieved? A clearing nobody needed. Timber nobody can use. A forest that's worse off than before.

Playing around with a chainsaw? Actually fine for a while. You learn how the tool works. You get a feel for the material. But it becomes a totally different thing once you have a goal. And goals are what's missing so often. "We've got a tracking tool – let's track something." That's the level it starts at. And too often, the level it stays at.

I've worked with 100+ mid-sized organizations, and this pattern shows up so often: Teams invest in tracking, dashboards, BI tools. They integrate data sources. They build beautiful visualizations. And when someone in the leadership meeting asks: "So what should we change?" The room goes quiet.

That's not a tech failure. Instead, it is:

A questions and focus failure

The thing is: this isn't about finding an easier approach. It's about not letting the technology rule – but letting consciousness rule. Data is one of the most powerful tools we have. But it's a tool that helps you gain clarity and set direction. Not direction anywhere. Direction into the right place.

The chainsaw is the same chainsaw. But in the hands of someone who knows which trees need to come down and why – it helps the forest heal. It keeps people's houses warm. Same tool, same woods. Completely different outcome. Because the goal came first.

Example: How one of my clients improved

One of my clients built an app with dozens of features – and tracking to match. Every click, every scroll, every micro-interaction was captured. The dashboards looked impressive. The data volume was massive.

And yet – the team couldn't figure out what to build next.

Until we sat down and formulated sharp, specific questions. About the real usage goals – not the feature list. What are the core things a user needs to accomplish? What does success look like from their perspective? Which data points, connected together, would tell that story?

Et voilà – the entire tracking concept changed. Not because we added more data points, but because we finally knew which ones mattered. We could surface signals buried under noise. Connect measurements into one coherent story. Define what "good" actually looks like – with data that could confirm or challenge it.

Better questions gave them better data definitions. Better definitions gave them data they could actually trust. And trusted data? That's the muscle that moves the whole business forward.

And the best: This compounds

One sharp question today improves the data you collect tomorrow. That better data reveals a pattern next month. That pattern informs the next experiment. And suddenly, you're not reacting to dashboards – you're driving decisions with rhythm and momentum. A shipping muscle that gets stronger with every cycle.

But nobody stumbles into this by accident.

Most organizations sit on mountains of data – and still make their biggest calls on gut feeling. Not because the data is bad. But because it doesn't connect to anything meaningful. And no – AI doesn't fix this. More data processed, more patterns surfaced, more reports generated. But garbage questions in, garbage insights out. Faster, sure. But faster garbage is still garbage. AI slop isn't just a content issue – it's an analytics issue too.

Getting this right is like finding the needle in the haystack. You gotta be tough. You gotta be intentional. The organizations that pull ahead are the ones who learned to ask first and measure second. Who push into directions that are clearly identified and – this is the hard part – validated. Not assumed. Not hoped.

That's the difference between having data and actually using it.

What are your struggles right now towards using data in order to make a real impact? Hit reply – I'd genuinely love to hear it. Let's discuss.

Looking forward to reading from you.

Thomas

P.S. What about thinking through together, how a clearer good-questions-based approach could support also your data and decisions setup? I do have some 20-minute Clarity Sessions open this month. Let's just exchange based on a sharp outside perspective. Book a Clarity Session now.