Causal effects of dynamic direct mail campaigns on customer product portfollos

Statistical methods currently employed for marketing are based on strong parametric assumptions to correct for endogeneity. These assumptions may com- promise the results when applied to data in which the research expects endogeneity, but this is not the case. By considering the recent advances in the literature of causal models for panel data we propose to employ a latent Markov model which is tailored to estimate causal effects of a marketing campaign and to deal dynamically with endogeneity. Our proposal does not require the strong assumption of strictly absence of unmeasured confounders. The endogeneity correction imposes no restrictions on the data and it does not bias results when the endogeneity is not in. We assess the effects of multiple mail campaigns conducted by a large European bank with the purpose of predicting customer acquisitions of financial products.