A Fuzzy Logic Approach for the Assessment of Online Customers

Author(s):  
Nicolas Werro ◽  
Henrik Stormer

A key challenge for companies in the e-business era is to manage customer relationships as an asset. In today’s global economy this task is becoming simultaneously more difficult and more important. In order to retain the potentially good customers and to improve their buying attitude, this chapter proposes a hierarchical fuzzy classification of online customers. A fuzzy classification, which is a combination of relational databases and fuzzy logic, allows customers to be classified into several classes at the same time and can therefore precisely determine the customers’ value for an enterprise. This approach allows companies to improve the customer equity, to launch loyalty programs, to automate mass customization, and to refine marketing campaigns in order to maximize the customers’ value and, this way, the companies’ profit.

E-Marketing ◽  
2012 ◽  
pp. 350-367
Author(s):  
Nicolas Werro ◽  
Henrik Stormer

A key challenge for companies in the e-business era is to manage customer relationships as an asset. In today’s global economy this task is becoming simultaneously more difficult and more important. In order to retain the potentially good customers and to improve their buying attitude, this chapter proposes a hierarchical fuzzy classification of online customers. A fuzzy classification, which is a combination of relational databases and fuzzy logic, allows customers to be classified into several classes at the same time and can therefore precisely determine the customers’ value for an enterprise. This approach allows companies to improve the customer equity, to launch loyalty programs, to automate mass customization, and to refine marketing campaigns in order to maximize the customers’ value and, this way, the companies’ profit.


2002 ◽  
Vol 26 (3) ◽  
pp. 429-438 ◽  
Author(s):  
George Tsekouras ◽  
Haralambos Sarimveis ◽  
Costas Raptis ◽  
George Bafas

1997 ◽  
Vol 36 (11) ◽  
pp. 1519-1540 ◽  
Author(s):  
Bryan A. Baum ◽  
Vasanth Tovinkere ◽  
Jay Titlow ◽  
Ronald M. Welch

2016 ◽  
Vol 39 (2) ◽  
pp. 501-515 ◽  
Author(s):  
Evren Arslan ◽  
Sedat Yildiz ◽  
Yalcin Albayrak ◽  
Etem Koklukaya

Author(s):  
T. K. K. R. Mediliyegedara ◽  
A. K. M. De Silva ◽  
D. K. Harrison ◽  
J. A. McGeough

Author(s):  
A S Pyataev ◽  
A Y Redkin ◽  
A V Pyataeva

Tree state category identification allows forecasting forest development in the surveyed area. Tree state category determination process based on global features is subjective and uses concepts such as the degree of density of the crown, the degree of drying of branches, the fall of the bark, the color of the needles, etc. For global features estimation, fuzzy logic is used. To formalize these subjective concepts, linguistic variables and their terms were extracted. The characteristic functions describing the terms were piecewise linear and in this work were approximated by Gaussian functions. Such an approach in conjunction with image processing algorithms that allows to search objects on images or correct images obtained for example from unmanned aerial vehicles could be the basis of a system for automatically determining the forest plantations health state and improve the inspection quality. The study was conducted for coniferous species of the boreal zone. The mathematical model built in this work allows reducing the cost of automation of calculations related to the processing of the data obtained by forest pathological surveys, despite the fact that the accuracy value of fuzzy classification after the approximation of the membership functions remained at the same level.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 95197-95207
Author(s):  
Adebamigbe Fasanmade ◽  
Ying He ◽  
Ali H. Al-Bayatti ◽  
Jarrad Neil Morden ◽  
Suleiman Onimisi Aliyu ◽  
...  

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