Skip to main content

Identifying latently dissatisfied customers and measures for dissatisfaction management

Buy Article:

$54.08 plus tax (Refund Policy)


Customer satisfaction continues to be an important topic in the financial services industry. However, there is an increasing awareness that customer satisfaction as such is not enough. Distinguishes between overall satisfied customers and latently dissatisfied customers; the latter being those customers who, although reporting satisfaction in a survey, have other characteristics (i.e. satisfaction with specific service items and/or socio-demographic characteristics) that resemble dissatisfied customers. The identification of these latently dissatisfied customers may function as an early warning signal. Indeed, their probability to defect is relatively high and can be compared to that of dissatisfied customers. Proposes a data mining technique called "characteristic rules" to identify latently dissatisfied customers of a Belgian bank. Appropriate marketing actions (dissatisfaction management) may help to avoid these customers leaving. Therefore, the objective of this study is to provide scholars and business managers with theoretical, methodological and managerial insights into identifying latently dissatisfied customers.

Keywords: Banking; Customer orientation; Customer satisfaction; Data mining

Document Type: Research Article


Publication date: February 1, 2002


Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more