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Using data mining for bank direct marketing: an application of the CRISP-DM methodology

Sérgio Moro · Raul Manuel da Silva Laureano · Paulo Cesar Cortez

208 citations0/0 files storedPortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)

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Customer churn and segmentation Big Data and Business Intelligence Data Mining and Machine Learning Applications

Abstract

The increasingly vast number of marketing campaigns over time has reduced its effect on the general public. Furthermore, economical pressures and competition has led marketing managers to invest on directed campaigns with a strict and rigorous selection of contacts. Such direct campaigns can be enhanced through the use of Business Intelligence (BI) and Data Mining (DM) techniques. This paper describes an implementation of a DM project based on the CRISP-DM methodology. Real-world data were collected from a Portuguese marketing campaign related with bank deposit subscription. The business goal is to find a model that can explain success of a contact, i.e. if the client subscribes the deposit. Such model can increase campaign efficiency by identifying the main characteristics that affect success, helping in a better management of the available resources (e.g. human effort, phone calls, time) and selection of a high quality and affordable set of potential buying customers.

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References

1998Data mining for direct marketing: problems and solutions 2006Decision Support and Business Intelligence Systems (8th Edition)

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