Customer profiling, segmentation, and sales prediction using AI in direct marketing

Kasem M.S. Hamada M. Taj-Eddin I.
March 2024 Springer Science and Business Media Deutschland GmbH

Neural Computing and Applications
2024 #36 Issue 9 4995 - 5005 pp.

In the current business environment, where the customer is the primary focus, effective communication between marketing and senior management is vital for success. Effective customer profiling is a cornerstone of strategic decision-making for digital start-ups seeking sustainable growth and customer satisfaction. This research investigates the clustering of customers based on recency, frequency, and monetary (RFM) analysis and employs validation metrics to derive optimal clusters. The K-means clustering algorithm, coupled with the Elbow method, Silhouette coefficient, and Gap Statistics method, facilitates the identification of distinct customer segments. The study unveils three primary clusters with unique characteristics: new customers (Cluster A), best customers (Cluster B), and intermittent customers (Cluster C). For platform-based Edutech start-ups, Cluster A underscores the importance of tailored learning content and support, Cluster B emphasizes personalized incentives, and Cluster C suggests re-engagement strategies. By understanding and addressing the diverse needs of these clusters, digital start-ups can forge enduring connections, optimize customer engagement, and fuel sustainable business growth.

Boosting tree , Data mining , Deep learning , RFM analysis methodology , SVM

Text of the article Перейти на текст статьи

Department of Multimedia Systems, Assiut University, Asyut, Egypt
Department of Computer Science, International IT University, Almaty, Kazakhstan
Department of Information Technology, Assiut University, Asyut, Egypt

Department of Multimedia Systems
Department of Computer Science
Department of Information Technology

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026