Webinar Recap: From Guesswork to Growth—How to Build a Data-Informed Business

When I joined Hostinger, we had a clear goal: to build a product-oriented, data-informed culture. But here’s the thing about data: it only matters if people actually use it. That’s why my mission isn’t just about dashboards and metrics—it’s about making data meaningful for every team member.

I sat down recently with Amplitude’s Przemek Misior to discuss all things data: its evolving role, how to make it more accessible, and why training others to use it is key. Read on for a few takeaways from our conversation—and be sure to watch the on-demand webinar here.

Building bridges, not battles

Building a data-informed culture starts with understanding your internal stakeholders. Who will actually use the insights you produce? Is it the product team, marketing, or revenue? Each group has unique pain points, priorities, and definitions of success. The first step is to identify these stakeholders and map out their biggest challenges. This isn’t just about creating dashboards—it’s about making data meaningful, accessible, and actionable. You need to find your “first buyer”—that person or team with the most immediate, high-impact problems to solve.

But don’t approach it like a head-on collision. Experienced managers can be resistant to change, especially if they feel their instincts are being challenged by raw data (and analysts, in turn, often feel data is the one and only source of truth). Instead of trying to tear down their belief systems, engage them in discussions. Understand their perspective, ask smart questions, and show how data can support their goals. The goal isn’t to replace intuition but to enhance it, turning their gut instincts into informed decision-making. Once you’ve proven this with a quick win, it becomes much easier to scale this mindset across the company.

Explain it to me like I’m 5

As the Product Analytics Lead at Hostinger, my role is to bridge the gap between complex datasets and the people who use them. But if you can’t explain your insights without jargon to a busy product manager, it’s unlikely those insights will lead to action. Data without context or clear takeaways is just noise.

A great way to overcome this is to create a common “language” with the teams you’re working with. If you have multiple product teams, this language might vary, so it’s crucial to have clearly defined terminology. A good data “dictionary” ensures everyone on both sides is aligned, clear, and informed.

Anyone who’s worked in product or data will tell you that understanding one another is critical. But speaking the same language is only one part of the equation—we must also empower others to succeed.

Empowering self-service

If you’re a data analyst, you’re used to being the go-to SME. Chances are, you’ve built dashboards, deciphered insights, and are generally inundated with requests.

No problem, right? I mean, that is your job. But empowering your teams to understand and use data is one of the best uses of your time. In fact, teaching self-service while being available in a consultancy role not only helps your colleagues understand how to use data—it also helps your company scale. When receiving a request to build a dashboard, for example, I’ll fulfill the request with the requester watching. The next time they request a dashboard, I’ll watch them follow the steps I’ve already laid out for them. Moving forward, they’ll feel empowered to create their own dashboards, and I’ll remain available to guide them while tackling other high-priority requests.

So, fellow analysts, here’s my big takeaway for you: Build cultures, not bottlenecks.

Learning from every test

Speaking of culture, at Hostinger we’ve embraced a culture of experimentation. One of our early experimentation wins was a painted, or fake, door test to validate (or invalidate) user interest in proposed features without investing in full development. We launched a dummy button to see if users clicked on it, indicating interest. It was a cost- and time-effective way of testing ideas with the potential for major impact. (Spoiler: we were shocked at the number of clicks, leading us to build it out permanently.)

Final thoughts

At the tail end of our conversation, Przemek asked what advice I would give to my younger self. After thinking it through, I said, “Data isn’t the single source of truth.” It should inform—not dictate—business decisions. It’s a tool, not a crutch. And it should be something that every member on every team knows how to use effectively. As the old saying goes, “Give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime.”