Abstract:
Customer satisfaction analyses often suffer from the fact that it is difficult to compress the large amount of gathered data material into relevant, concrete action recommendations for decision makers, whereby the practical significance and operative convertibility of the results is particularly disputed. The suggested solution basis describes how a model of factors influencing customer satisfaction, from which initial measures can be derived, can be produced using a special kind of neural network based on empirically gathered data. Relevant, precise action recommendations are derived by testing the measures using a neural network as a simulation tool. This reduces the volume of information in a customer satisfaction survey to a list of measures to be implemented by the decision maker.
Research Papers
Data mining VS. conventional analysis
Catalogue: ESOMAR Congress 1998: The Power Of Knowledge
Author: Luiz Sá Lucas
 
September 1, 1998
Research Papers
Modelling with neural nets
Catalogue: ESOMAR Congress 1998: The Power Of Knowledge
Authors: Pierre Marie Windal, Nathalie Gouenard, Christine Oneto
 
September 1, 1998
Research Papers
Free space
Catalogue: Congress 2014: What Inspires?
Author: Darren Fleetwood
 
September 10, 2014
