Citation

Ting, Choo Yee and Ho, Chiung Ching and Yee, Hui Jia (2018) Optimal geospatial features for sales analytics. In: AIP Conference Proceedings 2016, 2016.

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Abstract

Location analytics has been employed to capture insights about business, retail, disaster planning, public safety, conservation of energy, and many more. Despite the success of location analytics in various domains, obtaining a set of optimal features or criteria for analysis purposes remained a challenge. Hence, feature selection plays an important role in obtaining the optimal features as it determines the valuable and significant factors to be included in the final analytical dataset. In this light, feature selection was proposed to optimize the geospatial features to predict sales as well as recommendation for locations when establishing new outlets. In this study, sales data for a certain telecommunication company was used. This paper ends with the results of empirical experiments and recommendation of location characteristics that optimize yearly sales.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	sales
Subjects:	H Social Sciences > HF Commerce > HF5001-6182 Business > HF5410-5417.5 Marketing. Distribution of products
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	10 Mar 2021 19:56
Last Modified:	10 Mar 2021 19:56
URII:	http://shdl.mmu.edu.my/id/eprint/7450

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