“Show Me the Data”: What Great Product Teams Do Differently

Data As a Common Language

In many companies, product teams and business stakeholders are deeply disconnected, often struggling to find common ground. Business leaders are dissatisfied with product performance and worry about the money spent on development. Meanwhile, product managers feel overwhelmed by a never-ending queue of ad hoc requests. I often hear that Product and Business "speak different languages."

But there’s one language everyone in the company should learn to speak: Data.

What Does It Really Mean to Be a Data-Driven Product Organization?

In a data-driven product organization, data is expected and respected at every level. Whether it’s a strategic decision or a tactical one, it must be backed by data. This mindset dramatically improves organizational efficiency, reducing time spent on alignment and increasing the return on investment in product development.

Here’s a quick checklist to assess where your organization stands:

✅ Data is easily accessible

✅ Data is reliable and trustworthy

✅ Teams know how to interpret data and draw insights

✅ Strategy and roadmaps are informed by data

✅ Product teams are accountable for measurable outcomes

✅ Data resolves disagreements and wins over opinions

"Data isn’t just a reporting tool. It’s how your team learns, aligns, and earns trust."

Polina Oparina, Director of Product Career.io

How many boxes did you tick? And why?

The most common excuse I hear from PMs is:
 “We don’t really use data with stakeholders because they only trust their gut and so-called experience.”

Wrong. In my experience, most people like data, because it makes decision-making easier. CEOs and business leaders are no exception. Not everyone is data-fluent, but when presented with a clear, well-structured report based on a trustworthy data source, they get it. They follow your logic, absorb your story, and sometimes even see insights you missed.

Building a Data-Driven Culture: Our Story at Career.io

I’m proud of the strong data culture we built at Career.io, and I want to share how the transformation unfolded. It wasn’t a one-person job. There was a small team driving the change, and I was fortunate to be part of it. It started in one business unit with three product managers (myself included) and a data analyst. Later, we gained a crucial ally: our new Chief Product Officer, who joined six months after we did to run the whole product org and provided the executive support we needed.

Laying the Foundation: Tools, Talent, and Trust in Data

The first essential ingredient in our transformation was the right people. We had team members who not only understood the value of data but were energized to champion its use across the organization.

Our initial challenge was clear: data was difficult to access and often unreliable. We had multiple data sources that were technically complex and, worse, often produced conflicting results. It was nearly impossible to make confident decisions. What we needed was a solid foundation—a single, reliable source of truth and tools that made insights easily accessible.

With strong support from our CPO, we decided to invest in Mixpanel. It was a significant cost, but in hindsight, one of the best investments we made. It completely changed the game. Today, product managers can find answers to their questions within 5 to 30 minutes, rather than spending hours writing SQL or waiting days (sometimes weeks) for an analyst to deliver results.

We also implemented HotJar for session recordings, heatmaps, and in-app surveys. While this data is more qualitative and sometimes seen as anecdotal, it complements the quantitative insights from Mixpanel beautifully.

These tools cover about 90% of our day-to-day product questions. However, we still rely on a separate data source for financial reporting. Mixpanel, being event-based, has limitations. For example, it can’t track the current status of a transaction if there was a chargeback. To address this, we invested into enhancing our data warehouse, enabling us to generate highly accurate financial reports.

Giving everyone access to reliable insights empowered us to have stronger, data-backed conversations with leadership and cross-functional teams like Marketing. Data gave us a voice, and people listened. Of course, the transition wasn’t seamless. In the beginning, we faced lots of questions about our methods, our A/B test setups, and our KPI choices. But as the organization became more data-informed, the conversations became smoother, more efficient, and more impactful.

Scaling the Culture

As the company grew, three of us from the original team (myself included) were promoted to leadership roles. Scaling the team while preserving our data culture became the next challenge. It meant training our direct reports, hiring new team members, reorganizing our structure, and ensuring every team had clear, measurable outcomes.

A few highlights:

• Training – We reviewed each team member’s work and provided coaching through 1:1s and workshops. Some of the coaching topics we covered included A/B testing, cohort analysis, product metrics, and integrating quantitative with qualitative insights in the product development lifecycle.
• Hiring – Data fluency became a must-have, not a nice-to-have. We looked for skills in product analytics tools, a strong understanding of product metrics, and the ability to use data to inform roadmapping and strategy. The interview process was intentionally rigorous, leaving no room for compromise in assessing candidates.
• Team Structure – This was essentially a “metrics tree” exercise. We began with the company’s strategic goals, identified the key drivers, and structured teams around them. In practice, it's more complex—you have to minimize cross-team dependencies and aim for a structure that is mutually exclusive and collectively exhaustive. But the core principle remains: every team should own a metric that directly maps to a company-level KPI.
• Processes – This could be an article on its own. The key point: we require every initiative to have defined expected outcomes before the work starts, we use this data in the prioritization process, and analyze actual results afterward. Our PRD template includes sections for background data, expected impact, and final outcomes—no PM can skip them.
• Performance reviews – Data provides clarity on which teams are driving business outcomes and which aren’t. While I don’t rely solely on business results for performance reviews, and I don’t set quarterly KPIs for PMs, data still plays an important role. It informs my conversations with direct reports. If a certain area isn’t showing tangible outcomes, it signals the need to dig deeper, realign priorities, or adjust the approach. On the positive side, data is also incredibly helpful when it comes to recognizing and justifying promotions.

The Broader Impact Across the Organization

The ripple effects of our data-driven culture reached far beyond the product team. Adjacent teams, Marketing, Design, and even Engineering, began relying on data more frequently in their decision-making. Few things are as rewarding as seeing an engineer reference user data when proposing a solution to a corner case.

As a Director of Product, I participate in many cross-BU initiatives, which gives me a chance to extend this approach beyond our business unit. Promoting a shared data mindset across business units has significantly improved alignment and made prioritization far more objective and effective.

Final Advice

Data isn’t just a reporting tool. It’s how your team learns, aligns, and earns trust.

If you’re an executive wondering where to start, my advice is simple: hire a strong data-driven product leader who can define the strategy and lead the transformation.

If you’re a product leader unsure whether senior leadership truly values data, trust me  — they do. They might not realize it yet, but it’s your responsibility to show them the value and make it impossible to ignore.

And if you’re a product manager looking to become truly data-fluent, the best thing you can do is join a strong, data-driven team. No book or course can match the impact of being coached by a product leader who lives and breathes data.