From Data to Dollars: 6 Webinar Takeaways

Data monetization is one of the most significant opportunities for software companies today, yet many projects never make it past the initial stages. In this webinar, experts Jan Kadlecek (CEO of Datalook) and Karel Callens (CEO of Luzmo) shared why these projects often fail and how to build a successful data product.

Watch the webinar replay here:

Or read our six essential takeaways to guide your strategy:

1. Monetization fails in the boardroom

The technology required to build data products is complex but solvable; the real reason most projects fail is that they are treated as technical exercises rather than new business models.  Success requires a strategic business decision and total alignment across four key "pillars" or departments: Technical, Product, Sales, and Marketing. If these four teams do not work together, the project is likely to collapse regardless of how good the data is.

2. Start with the customer, not your data catalog

A common mistake is performing a "data catalog" exercise to see what data is available to sell. Instead, you must reverse-engineer the process by starting with customer friction points The goal is to identify the outcomes your customers are afte; how can your data help them make faster, better decisions or save them money?

3. Evaluate value using the "four signals"

When determining what parts of your data are actually worth charging for, look for these four specific signals:

• Frequency: How often do they check the data? (Daily vs. monthly),.
• Dependency: How much would it hurt the customer if the data was taken away?,.
• Differentiation: Does this data make you stand out from your competitors?,.
• Customer specificity: Does the data serve a specific segment that might justify an add-on or a premium tier?,,.

4. Avoid the "free" trap

Giving away analytics for free is a "silent problem" that compounds over time. It trains customers to expect the service for free, making it nearly impossible to implement a paywall later without significant pushback. Furthermore, if there is no price attached to a product, internal teams (like engineering and product management) often stop prioritizing its quality and development, leading to a legacy solution that eventually loses customers.

5. Sell value instead of raw datasets

Avoid selling raw data exports like CSV or Excel files. When you sell raw data, you lose visibility into how the customer uses it and what business value they derive from it. It is more effective to start with standardized reports or templates that solve problems for 80% of your customers and then move toward advanced features like conversational agents and automated insights.

6. Governance is about trust and cost

Data governance is more than just GDPR compliance; it is the foundational step that determines if you are even ready for monetization. Beyond data quality, you must have complete visibility into infrastructure costs (ETL, warehouse, visualization) to understand your margins and how they will scale. Without understanding these costs and ensuring data consistency across all dashboards, you cannot build a sustainable, high-quality product.

If you want to start today, don't wait for a perfect slide deck. Pick three to five customers, put a price in front of them for a proposed data value, and start the conversation.

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