TURNING ARTIFICIAL NEURAL NETWORKS INTO A MARKETING SCIENCE TOOL - Modelling and Forecasting the Impact of Sales Promotions

Ibrahim Zafar Qureshi, Marwan Khammash, Konstantinos Nikolopoulos

Abstract

In this study we model the effect of promotions in time-series data and we consequently forecast that extraordinary effect via Artificial Neural Networks (ANN) as implemented from the Expert Method of a popular Artificial Intelligence software. We simulate data considering five factors as to determine the actual impact of each individual promotion. We consider additive and multiplicative models, with the later presenting both linear and non-linear relationships between those five factors; in addition, we superimpose either low or high levels of noise. Our empirical findings suggest that, for nonlinear models with high level of noise, ANN outperform all benchmarks. Standard ANN topologies work well for models with up to two factors while the Expert method provided by the software works well for higher number of factors.

References

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Paper Citation


in Harvard Style

Qureshi I., Khammash M. and Nikolopoulos K. (2011). TURNING ARTIFICIAL NEURAL NETWORKS INTO A MARKETING SCIENCE TOOL - Modelling and Forecasting the Impact of Sales Promotions . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 698-702. DOI: 10.5220/0003292306980702


in Bibtex Style

@conference{icaart11,
author={Ibrahim Zafar Qureshi and Marwan Khammash and Konstantinos Nikolopoulos},
title={TURNING ARTIFICIAL NEURAL NETWORKS INTO A MARKETING SCIENCE TOOL - Modelling and Forecasting the Impact of Sales Promotions},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={698-702},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003292306980702},
isbn={978-989-8425-40-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - TURNING ARTIFICIAL NEURAL NETWORKS INTO A MARKETING SCIENCE TOOL - Modelling and Forecasting the Impact of Sales Promotions
SN - 978-989-8425-40-9
AU - Qureshi I.
AU - Khammash M.
AU - Nikolopoulos K.
PY - 2011
SP - 698
EP - 702
DO - 10.5220/0003292306980702