This paper is published in Volume 3, Issue 12, 2018
Area
Consumer Behaviour
Author
Ashwini Pradhan
Co-authors
Dr. U. Suma Rao
Org/Univ
Sri Sathya Sai Institute of Higher Learning, Anantapur, Andhra Pradesh, India
Pub. Date
27 December, 2018
Paper ID
V3I12-1160
Publisher
Keywords
Consumer Behaviour, Motorbike Owners, Perception, Profiling, Product Attributes

Citationsacebook

IEEE
Ashwini Pradhan, Dr. U. Suma Rao. Profiling motorbike owners on the basis of their perception, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARnD.com.

APA
Ashwini Pradhan, Dr. U. Suma Rao (2018). Profiling motorbike owners on the basis of their perception. International Journal of Advance Research, Ideas and Innovations in Technology, 3(12) www.IJARnD.com.

MLA
Ashwini Pradhan, Dr. U. Suma Rao. "Profiling motorbike owners on the basis of their perception." International Journal of Advance Research, Ideas and Innovations in Technology 3.12 (2018). www.IJARnD.com.

Abstract

In an environment where people are constantly looking for and finding smarter and more efficient ways to address their needs, understanding the customer; both existing and potential is of prime importance for a marketer. When it comes to marketing products that have a high involvement for the customers, like a motorbike, this understanding becomes even more crucial. There are several ways of classifying the unique needs people, profiling being a commonly used way. In this study, a very unconventional mode of profiling customers based on their own perception about the kind of relationship they share with their motorbike is used. A mixed methodology research approach is used in this study. The primary data is collected through a questionnaire, and semi-structured interviews, which were formulated after an extensive study of the existing literature. The survey sample size is 100 respondents who own a motorbike. The 14 motorbike owners who participated in the interview are a different sample from the survey sample. The primary data from the questionnaire is analyzed using the factor analysis, cluster analysis, discriminant analysis, and the KANO model. The semi-structured interviews were analyzed using the cluster analysis. The profiles or segments made in this study are based entirely on the findings and the analysis of primary data.
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