Estimating the Performance Indicators of Promotion Efficiency in FMCG Retail.

Forecasting promotion efficiency is an important issue in the fast-moving consumer goods sector. The objective of this paper is an analysis of the forecasting performance of two key performance indicators (KPI) used for the assessment of the sales process using machine learning methods. The authors present results of the experiments which were performed for 17 different products on real-life data from a large grocery company. In the paper feature extraction and construction methods are discussed also five different prediction algorithms are compared as well as the feature importance analyses are also provided. Out of the compared algorithms random forest leads and the feature importance are strongly related with the KPI.