Rethinking marketing's relationship with data | MarTech

"For most of my career, I believed marketing was a bridge between creativity and commerce - between what brands make and what people truly want. I held senior roles in digital marketing, leading campaigns that reached millions. I had every tool: dashboards, KPIs, analytics and insight engines. I believed that if we measured, optimized and personalized enough, we could make marketing scientific."

"But something was off. The dashboards looked impressive - full of graphs and metrics - but they were meaningless. We'd celebrate a 3% lift even when nothing really changed. The data didn't connect to revenue, loyalty or human connection. Multimillion-dollar command centers ran on unverified or fabricated data. Campaigns on platforms like Facebook and Google relied on metrics that barely reflected real outcomes. We were guessing rather than knowing, pretending instead of understanding."

"Over time, marketing shifted from asking why people feel something to how to make them feel something - usually urgency, envy or inadequacy. We called it engagement, but it was manipulation, systematized at scale. Inside the machine, departments competed for credit instead of alignment. Agencies chased awards instead of impact. We built campaigns to impress each other, not to serve the people we claimed to understand."

Marketing presented itself as a bridge between creativity and commerce, promising scientific precision through measurement, optimization and personalization. Dashboards and KPIs proliferated but often reflected unverified or fabricated data, producing cosmetic lifts that did not translate into revenue, loyalty or real human connection. Platforms and command centers amplified metrics that barely tracked outcomes, encouraging guessing rather than knowing. Marketing tactics shifted from understanding why people feel something to engineering feelings like urgency, envy and inadequacy. Organizational incentives rewarded short-term engagement, awards and internal credit over customer impact, driven by dirty data and corrupted incentives.

Read at MarTech