Year: 2025
Type: article
Abstract: The work presented in this paper is focused on customer segmentation based on the electricity demand by clustering methods.The main goal was to cluster the customers of a local electrical energy distribution company into groups with similar characteristics of electricity consumption based on annual data from smart metering systems.Such customer groups can be used to ease the understanding of the differences in behaviour of individual customers, and further can be used in targeted marketing or other machine learning tasks, such as consumption prediction for specific groups.The work followed the CRISP-DM process model, a commonly used methodology for the application of data analytics in businesses.In the paper, we briefly describe each phase of the methodology and present the most important outputs.The resulting customer segments are described and interpreted, and visualizations of clusters were provided, which help to better understand the behavior of customers.
Source: Acta Polytechnica Hungarica
Authors: Martin Sarnovsky, Peter Bednar
Institution: Technical University of Košice
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4412946103