Development of an identification system for customer journey in a mobile company (Case study: Mobilis). - Djeblahi, Fatima Ez Zahra; Metarfi, Khawla; Tahar, Mehenni: Reporter (Mohamed Boudiaf University of M'sila, 2024)
Mobilis, the mobile phone company, faces significant challenges in retaining customers and attracting new ones due to intense competition. The company conducts a precise analysis of the customer journey, which starts from discovering the service and extends to developing loyalty. This analysis helps the company understand customer behavior and effectively customize services for each customer segment. Through this analysis, we can also predict potential customer churn. Our research involves collecting customer interaction data and analyzing it using statistical analysis and data mining techniques to understand customer behavior. We have developed a model based on machine learning and artificial intelligence to predict the customer journey, which has proven effective in forecasting customer behavior and providing recommendations to improve their interaction with the company. This enables Mobilis to enhance its marketing strategies and customer service, contributing to increased loyalty and sustainable growth.
Keywords: customer journey; data analysis; customer behavior prediction; customer satisfaction; mobile telecommunications company; artificial intelligence; statistical analysis; customer retention; Python; PyCharm; K-NN; Decision Tree; data mining