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

Date

2017-01-01

Author

Huseynov, Farid
Özkan Yıldırım, Sevgi

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

URI

https://hdl.handle.net/11511/30374

Journal

International Journal of Economics and Business Research

DOI

https://doi.org/10.1504/ijebr.2017.085549

Collections

Graduate School of Informatics, Article

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Citation Formats

F. Huseynov and S. Özkan Yıldırım, “Behavioural segmentation analysis of online consumer audience in Turkey by using real e-commerce transaction data,” International Journal of Economics and Business Research, pp. 12–28, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30374.