Online advertising amounts to an increasingly big share of all advertising. Along with that, more and more different platforms for the production of online advertising campaigns are being developed. Our goal is to find out, which attributes most affect the necessary production time of online advertising campaigns. We use the data about campaigns production provided by Celtra d.o.o. We evaluate attributes with the use of RReliefF and Boruta, then we build several different machine learning models for campaign production time prediction. With the use of Shapley additive explanations, we explain the most successful of our models. We find out that the number of components used, the number of users, and the percentage of production time done by graphic designers have the greatest impact on the production time.
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