A Comparative Study at UoB Confirms the Importance of Machine Learning in Decision-Making Through Extensive Data Analysis

Sakhir – University of Bahrain (Khadijah Abdusalem)

31 October 2023

A comparative study conducted at the University of Bahrain (UoB) confirmed the effectiveness of using machine learning algorithms to predict a company’s customer lifetime value, which is the amount of total value (in terms of revenue) it can expect from a customer throughout his life as a shopper.

This study was prepared by the student in the Master’s program in Big Data Science and Analysis, researcher Mohammed Khaled Al-Mearaj, and was titled: “A Comparative Study Using Machine Learning Algorithms to Predict Customers Lifetime Value.”

The researcher indicated that the mechanism for calculating a (customer lifetime value) is to know the time it takes the customer to shop from the online store, the average spending, and the rate of repeated purchases per year, in addition to identifying the phenomenon of (customer churn), which is when the customer stops using the products or services.

Al-Mearaj stressed the need for industries today to use machine learning algorithms in the decision-making process, to deal with a wide range of diverse data, saying: “Knowing the lifetime value of a customer is important because it determines the amount of money that the organization will spend on acquiring a new customer, in exchange for retaining the current customer.”.

The researcher aimed to compare the findings of studies that predict customer lifetime value, using machine learning algorithms, and examine the extent to which the findings of his study reflect the findings of other studies conducted in this field.

Al-Mearaj concluded that using the random forest regressor algorithm provides the best prediction of the customer’s lifetime. In addition, the researcher recommended that companies use segmentation to find out which age group contributes to achieving the greatest amount of income for the company, in order to provide more accurate results.

The study supervisor, Head of the Mathematics Department at the College of Science, Dr. Sawsan Juma Hilal, pointed out that the Master’s program in Big Data Science and Analysis invests in the skills that students acquire during thier studies, and which they employ in resolving various difficulties in several practical fields, as the students transform information into implementable decisions. She pointed out that this study emphasized the importance of data analysis and the use of machine learning algorithms in the field of marketing, which is expected to have a noticeable practical impact.

The discussion committee included Dr. Riadh Binmohammed Ksantini, associate professor at the Department of Computer Science at UoB, as an internal examiner, and Dr. Mohammed Abdulrahman Basool, professor at the Prince Hussein bin Abdullah II College of Information Technology in Jordan, as an external examiner. While the thesis was supervised by the head of the Mathematics Department at the College of Science, and the Master’s Program in Big Data Science and Analysis coordinator, Dr. Sawsan Juma Hilal.

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