If you cannot run an experiment, propose and justify at least three identification strategies to estimate the promotion’s causal effect, including assumptions, diagnostics, and failure modes: (1) Difference‑in‑Differences/event‑study with staggered rollout using modern estimators (avoid naive TWFE bias), parallel‑trends checks, and placebo tests; (2) Synthetic Control at the geo level with pre‑period fit metrics and sensitivity to donor pool/regularization; (3) Instrumental Variables exploiting exogenous variation (e.g., eligibility rules, random delivery outages), with relevance/exclusion checks and weak‑IV diagnostics; (4) Regression Discontinuity if eligibility thresholds exist (e.g., tenure ≥ 30 days), with bandwidth/functional‑form sensitivity and McCrary density tests; (5) Propensity‑score or doubly‑robust learners (IPW/AIPW, causal forests) with overlap checks and covariate balance. Explain how you would report ATE/ATT with uncertainty, account for interference/network effects, and control for seasonality and concurrent campaigns.