You are building a predictive model for customer behavior in a digital marketing product. The marketing team wants to predict which customers are most likely to respond to an upcoming campaign so they can target outreach more effectively and improve conversion efficiency.
How would you approach building this model, from defining the prediction target through selecting features, training a model, and deciding whether it is good enough to use in production? What tradeoffs would you consider when balancing model performance, interpretability, and operational use by a marketing team?