Development and demonstration of a customer super-profiling tool to enable efficient targeting in marketing campaigns

Walters, Marisa ; Bekker, James (2018)

CITATION: Walters, M. & Bekker, J. 2018. Development and demonstration of a customer super-profiling tool to enable efficient targeting in marketing campaigns. In SAIIE29 Proceedings, 24-26 October 2018, Spier, Stellenbosch, South Africa.

The original publication is available at https://conferences.sun.ac.za/index.php/saiie29/saiie29/schedConf/presentations

Conference Paper

ENGLISH ABSTRACT: Being part of a competitive generation demands having good marketing policies to attract new customers as well as to retain existing customers. This research outlines a general methodology for segmentation of customers by using the model of Recency, Frequency and Monetary (RFM) to identify types of customers, and then predict their customer profiles, based on demographic and behavioural features. A few previous studies dealt with the question using non-aggregate customer data. We, however, also address the problem by using decision trees, something which has rarely been done before. We applied and demonstrated this tool on a large customer dataset and found useful results.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/107564
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