Synthetic data is everywhere in marketing, but students need an evaluative lens. Teach when it’s useful (privacy, imbalance, simulation) and when it creates false confidence (distribution shift, missing causal structure). End with a simple validation workflow: compare summary stats, train on synthetic test on real
