The mathematical engines that power modern incrementality. Understand the "Why" and "How" behind every decision.
Measure true causal impact when experiments aren’t possible.
Understand how marketing impact differs across regions, segments, and business units—without losing statistical rigor.
Understand when marketing creates revenue—not just whether it does.
See exactly where spend stops working—and where it still does.
Know which phase of growth you’re in—before your dashboards make it obvious.
What part of revenue is real trend—and what part is just noise?
Understand best-case, worst-case, and typical outcomes—not just the average.
Understand how long outcomes take—not just whether they happen.
Which metrics move together long-term?
How channels influence each other over time.
How do we forecast with uncertainty, not false precision?
Identify exactly when something changed—before narratives form and mistakes compound.
Who should we market to—and who we shouldn’t.
Answer “what would have happened otherwise” when real experiments aren’t possible.
What is the maximum possible efficiency?
Model relationships that change over time—not ones frozen in the past.
Which model should we trust?
Understand how things break together—not just how they behave on average.
How behavior evolves across entities over time.
How should budgets adapt continuously?