ISSN 2394-5125
 

Research Article 


DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz.

Abstract
With rapid increase of competition in business, there is a vital need of analyzing strategies continuously. The client is the focal point of every business. So, itís compulsory to monitor clientís demands, to make your business profitable and even to retain the client. This study uses logistics regression model to forecast clients loyalty, that whether the client will continue to subscribe the service or will stop. Four imputation techniques were compared to tackle the missing data, which own its own is a big issue. Upon getting the best performing imputation method, two feature reduction techniques were analyzed upon its outcome, to reduce the aspect of variance in the data. Finally, with the high performing imputation method and feature reduction technique, Logistic Regression model was developed, and validated using validation data. After that, predictions were made on test data.

Key words: Data Analytics, Customer Retention, Machine Learning, Feature Reduction


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Zunair Mahmood
Articles by Daniel Mago Vistro
Articles by Waleed Iftikhar
Articles by Usman Ashfaq
Articles by Hafiz Ilyas Tariq Aziz
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. JCR. 2020; 7(9): 1636-1643. doi:10.31838/jcr.07.09.300


Web Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. http://www.jcreview.com/?mno=100017 [Access: May 30, 2021]. doi:10.31838/jcr.07.09.300


AMA (American Medical Association) Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. JCR. 2020; 7(9): 1636-1643. doi:10.31838/jcr.07.09.300



Vancouver/ICMJE Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. JCR. (2020), [cited May 30, 2021]; 7(9): 1636-1643. doi:10.31838/jcr.07.09.300



Harvard Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz (2020) DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. JCR, 7 (9), 1636-1643. doi:10.31838/jcr.07.09.300



Turabian Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. 2020. DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. Journal of Critical Reviews, 7 (9), 1636-1643. doi:10.31838/jcr.07.09.300



Chicago Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. "DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES." Journal of Critical Reviews 7 (2020), 1636-1643. doi:10.31838/jcr.07.09.300



MLA (The Modern Language Association) Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz. "DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES." Journal of Critical Reviews 7.9 (2020), 1636-1643. Print. doi:10.31838/jcr.07.09.300



APA (American Psychological Association) Style

Zunair Mahmood, Daniel Mago Vistro, Waleed Iftikhar, Usman Ashfaq, Hafiz Ilyas Tariq Aziz (2020) DATA ANALYTICS FOR CUSTOMER RETENTION USING MACHINE LEARNING TECHNIQUES. Journal of Critical Reviews, 7 (9), 1636-1643. doi:10.31838/jcr.07.09.300