Budi Tanzi

AI has raised the bar for what qualifies as “good data.”

The conversation is no longer about how much data marketers can collect but how well that data reflects reality. In this new era, success depends on data that is accurate, fresh, consented and interoperable – principles that ensure AI models learn from accuracy.

When you lose something important, you want to get it back. That’s the human instinct driving the conversation around signal loss. Marketers rightly feel an urgency to get back to a higher level of confidence targeting, attribution and measurement – particularly with broader economic pressures squeezing budgets.