Gradient Boosting Application in Forecasting of Performance Indicators Values for Measuring the Efficiency of Promotions in FMCG Retail
This work addresses forecasting promotion efficiency for FMCG retailers, but it appears incremental as it applies an existing method to a specific domain without broad novelty.
The authors tackled the problem of forecasting promotion efficiency in FMCG retail by applying gradient boosting to predict six performance indicators, achieving results for three product groups from a large grocery company.
In the paper, a problem of forecasting promotion efficiency is raised. The authors propose a new approach, using the gradient boosting method for this task. Six performance indicators are introduced to capture the promotion effect. For each of them, within predefined groups of products, a model was trained. A description of using these models for forecasting and optimising promotion efficiency is provided. Data preparation and hyperparameters tuning processes are also described. The experiments were performed for three groups of products from a large grocery company.