Co-Created Model Blueprint
Next, we sit down with your pricing, finance, and data teams to co-create a modeling blueprint. Together, we define the key questions each model needs to answer, like own-price, cross-price, or promo lift, broken down by segment and channel. We identify the confounders to control for, select the right variables, and choose the best-fit method for your data. Double Machine Learning is our go-to, but we use causal forests when elasticity varies by segment and hierarchical Bayesian pooling for thin data slices like new SKUs or small customers. This upfront alignment means you get no surprises at validation, just models that answer your real business questions.