Marketing Science

MIP for Marketing Budget Allocation: A Complete Guide

Learn how Mixed Integer Programming (MIP) with discretized response curves solves marketing budget allocation problems using branch-and-bound methods.

Analytics TeamSeptember 9, 20255 min read

Analytics Team

Analytics consultant specializing in marketing science, forecasting, and strategic data solutions.

Marketing Science

Part 3 | Hands-On Implementation: Building a Causal MMM from Scratch

A practical tutorial implementing causal marketing mix modeling with DoWhy, including code examples and a complete toy dataset

Aug 281 min

Marketing Science

Practical optimizer scenarios in MMM: A step-by-step guide

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.

Aug 2116 min

Marketing Science

Part 2 | Beyond Attribution: How Causal Inference complements Modern MMM

Exploring structural causal models using DAGs, counterfactual reasoning, and frameworks like DoWhy and PyMC-Marketing

Aug 208 min

Analytics Team

Related Articles

Part 3 | Hands-On Implementation: Building a Causal MMM from Scratch

Practical optimizer scenarios in MMM: A step-by-step guide

Part 2 | Beyond Attribution: How Causal Inference complements Modern MMM