An Efficient Digital Marketing Data Mining Framework to Predict Customer Performance

Mansoureh Zare¹ Hassan Shakeri² Roya Mahmoudi³

1) Ph.D student, Department of Information Technology and Computer Engineering, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran
2) Assistant Professor, Department of Information Technology and Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
3) . Ph.D student, Department of Information Technology and Computer Engineering, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran

Publication : 2nd. International Congress on science & Engineering - paris(parisconf.com)
Abstract :
The connection of people s lives with digital space has created a new and attractive concept in marketing called digital marketing . Data is one of the most important parts of any organization. The framework of data extraction establishes close relationships with the customer and Manages the relationships between organizations. Data mining has become very popular in various digital marketing applications in recent years, and the classification model is an important data mining technique, This model is used to predict customer behavior to enhance digital marketing decision-making processes to retain valuable customers. This article provides an effective framework for exploring and classifying the Na Bayve Bayes classification model.
Keywords : Data mining Digital marketing Classification