Research Article
Customer Segmentation and Personalized Marketing Using K-Means and APRIORI Algorithm
@INPROCEEDINGS{10.4108/eai.7-12-2021.2314561, author={Gayathri K and Arunodhaya R}, title={Customer Segmentation and Personalized Marketing Using K-Means and APRIORI Algorithm}, proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India}, publisher={EAI}, proceedings_a={ICCAP}, year={2021}, month={12}, keywords={segmentation marketing offer recommendation rfm clustering k-means apriori eclat}, doi={10.4108/eai.7-12-2021.2314561} }- Gayathri K
Arunodhaya R
Year: 2021
Customer Segmentation and Personalized Marketing Using K-Means and APRIORI Algorithm
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314561
Abstract
In today’s business environment regardless of what type of industry we are in or what kinds of products and services that is sold, customers are the most important part of a business. Without the customer, sales doesn’t happen. If the customers’ views are not taken into an account, then it’s likely the campaigns will not be successful. Hence classifying the right customers also matters a lot to make the products to be bought frequently. Companies follow different strategies to segment the customers. In this paper, RFM and K-means clustering is used to segment the customers. It also provides a combo offer recommendation feature which can be implemented in any commercial websites using ECLAT and Apriori algorithm. This helps in analyzing the performance of the products and also about the customers whom can be focused more for selling the products.
