The problem with MMx was never the math, it was the calendar.
Reimagining Marketing Mix (MMx) Optimization With Process Agentification
Situation Context
For decades, MMx has been treated as a once-a-year, backward-looking exercise - technically elegant, but structurally disconnected from how fast commercial teams actually need to move. By the time the model output lands, the market has moved on and the business has already lost the window to act on it.
A panel of senior commercial analytics leaders sat down at Ignite 2026 to settle a harder question: how much of that process can agentic AI actually take over - and where does handing it off start costing you more than it saves?
"The other 30% is where I think that you have the greatest value to business."
- Panelist, Senior Decision Science Leader
What This Report Will Show You
- The real reason MMx outputs arrive too late - and why it has nothing to do with the model
- One company's build-vs-buy decision, and the skill sets it didn't see coming
- The exact split between what AI should own and what it never should
- Why "success" in 24 months looks nothing like faster reporting
- The one barrier every panelist agreed on - and it isn't the technology
"By the time I get your output, I've already moved on... I need them sooner."
- Panelist, Commercial Brand Analytics
Built For
- Commercial analytics leaders
- Marketing Mix Modeling teams
- Brand analytics teams
- Executives evaluating agentic AI's role in modernizing MMx
FAQs
