Measure the causal impact of a marketing campaign, promo, or intervention on a business metric (revenue, conversions, transactions) using Bayesian structural time series. Use this skill whenever the user mentions "causal impact", "campaign uplift", "promo effect", "incrementality", "did the campaign work", "revenue lift from campaign", "measure uplift", "what was the true effect", "counterfactual
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Causal Impact Campaign Analysis
This skill guides the analyst through measuring the causal effect of a marketing campaign or business intervention on a target metric using Bayesian structural time series methods. The skill encodes hard-won lessons from real client engagements — particularly around short-lived campaigns, retail seasonality, and honest statistical communication.
The approach runs two independent Bayesian methods (tfcausalimpact and CausalPy) for robustness, includes a rigorous
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