Understanding the critical distinctions between causal identification, uplift, and contribution—and why conflating them leads to bad marketing decisions
No spam. Technical articles on forecasting, pricing, and decision systems.
Learn how Mixed Integer Programming (MIP) with discretized response curves solves marketing budget allocation problems using branch-and-bound methods.
A practical tutorial implementing causal marketing mix modeling with DoWhy, including code examples and a complete toy dataset
Walk through real-world MMM optimization scenarios using Mixed Integer Programming. See how to discretize response curves, formulate constraints, and solve practical reallocation problems with actual numbers.