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Analysis of predicting the success of the banking telemarketing campaigns by using machine learning techniques

Vongchalerm, Laksana (2022) Analysis of predicting the success of the banking telemarketing campaigns by using machine learning techniques. Masters thesis, Dublin, National College of Ireland.

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This research project is related to predicting the success of the banking telemarketing campaigns by using machine learning techniques. Machine learning techniques are playing an important role in improving marketing campaigns and providing timely information to management for effective decision-making. The banking institutions are using machine learning techniques for increasing their market share by reaching the target customers. There is a need to optimize the uses of available resources and attract potential customers for increasing the overall revenue of the banks. Some Portuguese are using advanced technologies and machine learning techniques for the marketing of products and services for increasing the market share. Customer behavior plays an important role in the decision-making process and Portuguese banks are using machine learning techniques for analyzing the behavior of customers. The banking system of the Portuguese is advanced and linked with the national multibanco system. This system is facilitating the financial institutions in running their business operations and providing opportunities to customers for opening their accounts. More than 150 banks are connected and interrelated through multibanco and banks are using telemarketing for their promotions in the target markets. The Portuguese financial institutions and banks are using different telemarketing methods including television, radio, telephone, and cells for promoting the services and reaching potential customers. Banks are using financial telemarketing services for increasing their sales and gaining a sustainable competitive advantage over competitors. These services are playing important roles in reaching the target audience and sparking sales by getting the word out through telemarketing calls. The researcher of this project used secondary data from May 2008 to November 2010 about the direct marketing dataset based on 41,188 records. The researcher collected the data through phone call interviews that are also considered half meeting. The researcher used logistic regression and decision trees for analyzing the performance of banking telemarketing campaigns.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
H Social Sciences > HG Finance > Banking
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
H Social Sciences > HF Commerce > Marketing
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 14 Mar 2023 14:18
Last Modified: 14 Mar 2023 14:18

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