Research Article
Customer Segmentation on Online Retail using RFM Analysis: Big Data Case of Bukku.id
@INPROCEEDINGS{10.4108/eai.1-4-2019.2287279, author={Mohamad Abdul Kadir and Adrian Achyar}, title={Customer Segmentation on Online Retail using RFM Analysis: Big Data Case of Bukku.id}, proceedings={International Conference on Environmental Awareness for Sustainable Development in conjunction with International Conference on Challenge and Opportunities Sustainable Environmental Development, ICEASD \& ICCOSED 2019, 1-2 April 2019, Kendari, Indonesia}, publisher={EAI}, proceedings_a={ICEASD\&ICCOSED}, year={2019}, month={9}, keywords={customer segmentation big data rfm clustering location}, doi={10.4108/eai.1-4-2019.2287279} }- Mohamad Abdul Kadir
Adrian Achyar
Year: 2019
Customer Segmentation on Online Retail using RFM Analysis: Big Data Case of Bukku.id
ICEASD&ICCOSED
EAI
DOI: 10.4108/eai.1-4-2019.2287279
Abstract
The purpose of this research is to identify customer purchase behavior, form customer segmentation, and identify customer address of Bukku.id. this research uses customer purchase data of Bukku.co.id in the period 1 September 2017 – 17 September 2018. RFM method and clustering are used to identify customer segmentation. Then, pareto analysis results which publishers and authors need to be concerned for prioritizing effort in order to gain maximum benefit. Customer address or location has been mapped based on priority authors to determine promotion and offline marketing strategy. The results of this research show three customer cluster based on RFM and clustering analysis. Each cluster has different characteristic and it can determine which strategy suit to approach their customers. Customer profile based on authors and publisher could also benefit the company to prioritize any treatments relate to them. Better offline marketing strategy can be developed by knowing location analysis.
