Development of an identification system for customer journey in a mobile company (Case study: Mobilis).
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Date
2024-06
Journal Title
Journal ISSN
Volume Title
Publisher
Mohamed Boudiaf University of M'sila
Abstract
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.
Description
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