This value is the average over the potential customers and is usually determined by looking at characteristics of existing customers in the historical dataset. For each customer the offer with the highest expected economic return is highlighted. In some cases, it might be possible to use data mining technology to model the value directly, skipping the response probability stage. Assuming that the models are reliable, this would increase the accuracy of the optimization process. Before the optimization process can go any further, any constraints that the optimization process must handle need to be specified.
Constraints put limits on the marketing campaign based on external factors.
For example, there could be a budget limitation for the campaign, which limits the number of offers that could be made. This would result in more inexpensive offers than would otherwise be made. Examples include maximum campaign budget, maximum number of offers, maximum number of responses, and minimum number of responses. Per-offer Constraints . Examples of per-offer constraints include minimum number of offers, maximum number of offers, minimum number of response, maximum number of responses, maximum total offer cost, and minimum offer net response value.