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Privacy Enhancing Technologies (or PETs) are foundational to modern data monetization.

In this episode, we break down how PETs work in practice, including clean rooms, hashed ID matching, secure overlap analysis and privacy safe marketing and measurement. We explain how enterprises collaborate on data, run audience overlap and campaign analytics and unlock new revenue opportunities without sharing raw data or exposing identities.

This is for teams looking to move from fear based data protection to value based data collaboration for shared value.

AI models increasingly depend on real world, proprietary data, but monetising that data raises questions around privacy, consent and trust.

In this episode, we unpack how enterprises can monetise data for AI training safely and ethically. We cover why demand for AI training data is exploding, what types of data are most valuable and the governance principles that protect both organisations and customers.

A practical guide for organisations exploring AI driven data monetisation.

Data monetisation doesn't fail because of technology, but rather because of operating models.

In this episode, we go inside a Data Monetisation Unit and unpack how it actually works within a large enterprise. We cover the critical roles, governance structures, how the unit works and operates and the characteristics that separate high performing DMUs from stalled initiatives.

This is your guide to build repeatable data revenue.

Most organisations don't struggle with a lack of data, but rather with knowing where to start. In this episode, we unpack how to identify the first high value, high-margin data products your organisation can monetise.

We cover why datasets aren't products, what buyers actually pay for, the three tests every data product must pass and the red flags to avoid.

When it comes to data monetisation, most companies have the data, have the customers, and even have clear demand, but the revenue still doesn't flow.

In this episode, we break down the six barriers that stop enterprises from monetising their data, and what companies can about each one.

In this debut episode, Matthew Bernath breaks down the five biggest myths holding organisations back from unlocking the true value of their data. From the misconception that monetisation means "selling data" to the belief that it requires perfect datasets or complex technology, Matthew separates fact from fiction.

Learn how leading companies are safely generating new revenue streams, building internal data products, and embedding value based thinking into their data strategy.

Key Takeaways:

1. Why data monetisation isn't about selling data, it's about creating value.

2. The difference between internal and external monetisation.

3. Why perfection isn't required, progress is.

4. The role of privacy and compliance as enablers, not barriers.

5. How to start small, prove value, and scale sustainably.