Using data mining for bank direct marketing: an application of the CRISP-DM methodology
Using data mining for bank direct marketing: an application of the CRISP-DM methodology
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发表时间：
2011-10
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通讯作者：
Sérgio Moro;Raul M. S. Laureano;P. Cortez
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作者：
Sérgio Moro;Raul M. S. Laureano;P. Cortez
随着时间的推移，越来越多的营销活动减少了对公众的影响。此外，经济压力和竞争导致营销经理投资于有针对性的活动，并严格选择联系人。这种直接营销活动可以通过使用商业智能（BI）和数据挖掘（DM）技术来增强。本文描述了一个基于CRISP-DM方法的DM项目的实现。真实世界的数据收集与银行存款订阅葡萄牙营销活动。业务目标是找到一个可以解释联系成功的模型，即客户是否订阅了存款。这种模式可以通过识别影响成功的主要特征来提高活动效率，帮助更好地管理可用资源（例如人力、电话、时间），并选择高质量和负担得起的潜在购买客户。
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.