• by Joanna Drews , 4 hours ago

Consumer behavior has changed dramatically. People move between streaming services, creator content, social platforms, connected TVs, and traditional television without thinking twice. Yet we're using technology that was built 30 or 40 years ago to measure entirely new viewing behaviors.

I hear big claims about how people watch all the time: broadcast is more fragmented, streaming is winning, audiences are shifting their attention elsewhere.

Each experience is being measured using different technologies and methodologies. Before we keep debating what is happening in media, we need to ask a more basic question: Do we actually know if those statements are true?

What we've created is a Frankenstein of data. Technology built for linear television is now being applied to streaming, and that’s where things start to break down.

Brands are allocating budgets and evaluating performance every day based on what they believe is driving results. The problem is they don't know what is actually working and what’s wasted. Yet they're still expected to make decisions with confidence.

For decades, media companies learned from audiences. What people watched influenced what got renewed. What resonated shaped what got created next.

If brands and media companies want a clearer picture of what's actually driving results, they need to start thinking differently about measurement. That starts with a few practical changes in how we evaluate and use audience data.

It starts with better questions. Find ways to trace performance more directly instead of relying on metrics brands may not fully trust. Ask where your data comes from. What is the baseline source? How was it created?

The shift toward outcome-based trading and automated systems is a step in the right direction. But even then, brands should ask what data is being compared, where it comes from, and whether it's measuring the right thing.

Better data leads to better decisions. Invest in proprietary data sets and alternative data sources. As measurement becomes more fragmented, competitive advantages will come from better data, better insights, and a clearer understanding of audiences than competitors have. AI is only as good as the information feeding the system. Bad data in, bad data out.

Ask harder questions about the data brands are using. If we don't understand how that measurement is being captured, what it is measuring, and what it might be missing, we're still making decisions with an incomplete picture.

The goal is understanding audiences. For brands and media companies to get back to learning from audiences, they need a trusted foundation for the data they're using. The goal isn't simply to produce more data. It's to understand what people actually watch, what they respond to, and what they want more of.

The conversations coming out of the ufronts were focused on the future: AI, automation, and new ways to buy and measure media. But what foundation will that ecosystem be built on? to make sure it reaches the right audience at the right time?

Before we can confidently predict where media is headed next, we should be able to answer a much simpler question: What are people actually watching today?