Title :
Neural networks and customer grouping in e-commerce: a framework using fuzzy ART
Author_Institution :
Sch. of Manage., State Univ. of New York, Buffalo, NY, USA
Abstract :
This paper introduces a proposed neural network-based data mining method that utilizes a company´s internal data about customers for the purpose of marketing strategies such as target marketing and direct marketing. Unlike past data mining approaches that put market survey or customer feedback data into input values, the fuzzy ART neural network proposed in this paper takes a customer´s purchasing history as input values and clusters similar customers into groups. Step by step procedures of how to implement the fuzzy ART algorithm are provided and practical considerations for it to be used in marketing management in the context of electronic commerce are discussed
Keywords :
ART neural nets; data mining; electronic commerce; fuzzy neural nets; marketing data processing; company internal data; customer grouping; customer purchasing history; data mining; direct marketing; e-commerce; fuzzy ART neural network; marketing management; target marketing; Data mining; Economic forecasting; Electronic commerce; Fuzzy neural networks; Intelligent networks; Marketing and sales; Marketing management; Neural networks; Statistical analysis; Subspace constraints;
Conference_Titel :
Research Challenges, 2000. Proceedings. Academia/Industry Working Conference on
Conference_Location :
Buffalo, NY
Print_ISBN :
0-7695-0628-3
DOI :
10.1109/AIWORC.2000.843312