Optimal selection of media vehicles using customer databases

This paper investigates the problem where an organization must select among multiple media vehicles for a marketing campaign, and determine how many names from each vehicle to impress (the contact depth). The organization can estimate the return from contacting each prospective customer, and this return decreases as depth increases. Different vehicles have different marginal costs per impression, and may have minimum-spend requirements or activation costs to use the vehicle. Decisions are to be made to maximize profit subject to a constraint on the total amount spent. We proposed an optimization model and two computationally efficient methods that often lead to global optimal solutions under practical assumptions. The model is illustrated with two data sets.