Customer profiling using classification approach for bank telemarketing

Palaniappan, Shamala and Mustapha, Aida and Mohd Foozy, Cik Feresa and Atan, Rodziah (2017) Customer profiling using classification approach for bank telemarketing. International Journal On Informatics Visualization, 1 (4-2). pp. 214-217. ISSN 2549-9610

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Telemarketing is a type of direct marketing where a salesperson contacts the customers to sell products or services over the phone. The database of prospective customers comes from direct marketing database. It is important for the company to predict the set of customers with highest probability to accept the sales or offer based on their personal characteristics or behaviour during shopping. Recently, companies have started to resort to data mining approaches for customer profiling. This project focuses on helping banks to increase the accuracy of their customer profiling through classification as well as identifying a group of customers who have a high probability to subscribe to a long-term deposit. In the experiments, three classification algorithms are used, which are Naïve Bayes, Random Forest, and Decision Tree. The experiments measured accuracy percentage, precision and recall rates and showed that classification is useful for predicting customer profiles and increasing telemarketing sales.

Item Type: Article
Uncontrolled Keywords: Decision tree; Classification; Data mining; Customer profiling
Subjects: H Social Sciences > HF Commerce > HF5001-6182 Business > HF5410-5417.5 Marketing. Distribution of products
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Miss Nur Rasyidah Rosli
Date Deposited: 17 Nov 2021 06:17
Last Modified: 17 Nov 2021 06:17

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