Commercial Use of Upc Scanner Data: Industry and Academic Perspectives
Marketing Science
Promocast": a New Forecasting Method for Promotion Planning
Marketing Science
A tutorial on support vector regression
Statistics and Computing
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A hybrid sales forecasting system based on clustering and decision trees
Decision Support Systems
Improved supply chain management based on hybrid demand forecasts
Applied Soft Computing
Prediction in Marketing Using the Support Vector Machine
Marketing Science
Expert Systems with Applications: An International Journal
Forecasting model selection through out-of-sample rolling horizon weighted errors
Expert Systems with Applications: An International Journal
Applicability of ARIMA Models in Wholesale Vegetable Market: An Investigation
International Journal of Information Systems and Supply Chain Management
Hi-index | 12.05 |
Promotions and shorter life cycles make grocery sales forecasting more difficult, requiring more complicated models. We identify methods of increasing complexity and data preparation cost yielding increasing improvements in forecasting accuracy, by varying the forecasting technique, the input features and model scope on an extensive SKU-store level sales and promotion time series from a European grocery retailer. At the high end of data and technique complexity, we propose using regression trees with explicit features constructed from sales and promotion time series of the focal and related SKU-store combinations. We observe that data pooling almost always improves model performance. The results indicate that simple time series techniques perform very well for periods without promotions. However, for periods with promotions, regression trees with explicit features improve accuracy substantially. More sophisticated input is only beneficial when advanced techniques are used. We believe that our approach and findings shed light into certain questions that arise while building a grocery sales forecasting system.