Marketing measurement has gone through three distinct phases: 1. Legacy MMM Era (pre-2010s) 2. Attribution Boom (2010s) 3. MMM Rebirth (2020s) This isn’t a story about preference. It’s a story about adaptation to thrive in the everchanging business world.

Data Detail is Crucial: To perform causal analytics like Marketing Mix Modeling, you must preserve raw, event-level data (joint distributions). Summary reports (marginals) discard the necessary context to attribute success to specific combinations of customer traits. Avoid the "Average" Trap: Aggregated data can hide the true story. Two completely different customer behaviors can look identical in summary reports, making accurate attribution impossible without the raw source

Marketers have more performance data than ever, yet trust in that data isn’t really improving. The fix lies in performance measurement using Marketing Mix Modeling.

Authors: Drs. Hung-Ken Chien and Yu-Feng Wei, Co-Founders of Vizuro Introduction In the ever-evolving pursuit to measure promotional effectiveness, marketing mix modeling (MMM) has long been the norm to assess campaign lifts and help allocate their spending. However, the emergence of omnichannel marketing in recent years has imposed a great challenge to the conventional MMM methodology, due to its requirements for high tactic mix and segment granularity. Coincidentally, both