Part III
Quantifying Effects: Experiments, Causality, Regression, and Pricing
From what happened to what to do
This part is about acting on data by asking what would have happened otherwise. Every chapter chases the same object — the counterfactual — and the arc moves from naming it (Chapter 5 reframes any metric as a missing comparison) to identifying it (Chapter 6 makes regression earn the word "causal"), to recovering it from field data no one randomized (Chapter 7's difference-in-differences, synthetic control, and heterogeneous effects), to spending it on the firm's highest-leverage lever (Chapter 8 turns an elasticity into a price). A single thread of worked evidence — Progresso soup scanner data, a 1,700-store milk experiment, a Zillow-and-cannabis synthetic control — runs through all four, so the same number grows more trustworthy as the design tightens. The discipline it leaves behind is refusing to read a coefficient until you know which counterfactual produced it.
4 chapters · 14 articles
What you’ll learn
- Translate any business metric into a precise causal question — naming the lever, unit, horizon, comparison, and decision threshold before fitting a model
- Distinguish identification from estimation, and demand the identification memo and diagnostics that separate a causal coefficient from a precisely-wrong one
- Recover treatment effects from unrandomized field data using difference-in-differences, synthetic control, and panel fixed effects, and audit each with balance and placebo checks
- Surface heterogeneous effects so a single average lift no longer hides which segments actually pay
- Convert an own-price elasticity into an optimal markup via the Lerner rule, and see in dollars why a naive elasticity hands back the wrong price
Chapters in this part
Every metric worth acting on hides a counterfactual you must construct, not assume.
A regression number is only as trustworthy as the comparison it secretly makes.
Build the missing counterfactual — then trust the effect only as far as the design that produced it.
Turning an identified elasticity into a defensible price, then into a memo a committee can act on.