Behavioural segmentation analysis of online consumer audience in Turkey by using real e-commerce transaction data. (2017)

• Record Type: Journal Article
• Authors: Huseynov, Farid; Yıldırım, Sevgi Á-zkan
• Is Part Of: International journal of economics and business research. Volume 14:Number 1(2017)
• Page Start: 12
• Page End: 28
• Publication Date: 2017
• Subjects: online consumer behaviour -- market segmentation -- segmentation analysis -- two step cluster analysis -- behavioural segmentation analysis -- B2C e-commerce -- online shopping -- Turkey; Economics -- Periodicals; Business -- Periodicals; 330.05
• Languages: English
• ISSNs: 1756-9850

Abstract

This study is about determining the different consumer segments in online shopping platforms. Consumer segmentation is a marketing strategy which involves firstly dividing customers into groups based on their underlying characteristics, needs and interests, and then designing and implementing strategies to target them. One of the most common types of segmentation approaches is behavioural segmentation analysis in which consumers are grouped based on their certain behavioural characteristics such as decision making, spending, usage, etc. This study carried out behavioural segmentation analysis based on real e-commerce transaction records of 10, 000 online customers and found five different types of online consumer segments which are opportunist customers, transient customers, need-based shoppers, skeptical newcomers and repetitive purchasers. Behavioural characteristics of each segment were discussed in detail and recommendations were made about how to approach to each segment in order to increase their online shopping rates. Understanding the behavioural characteristics of each segment will enable the selling companies to develop marketing strategies accordingly.