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Use of Lifestyle Segmentation for Assessing Consumers’ Attitudes and Behavioral Outcomes towards Mobile Advertising

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  • Nauman Zaheer

    (University of Ljubljana Faculty of Social Sciences)

  • Mihael Kline

    (University of Ljubljana Faculty of Social Sciences)

Abstract

Purpose – Mobile communication has become an integral part of people’s lives in recent times. Consumers’ purchasing behaviors have been found to be influenced by their attitudes towards mobile advertising. This study explored the usability of lifestyle segmentation to find differences among consumers and assessed the relationship between consumers’ attitudes toward mobile advertising. Design/Methodology/Approach – The study is based on primary data collected through a survey questionnaire on a consumer sample in Pakistan. The study surveyed 166 respondents and categorized them into three different lifestyle groups: self-indulgents, experiencers, and traditionalists. Factor analysis and cluster analysis techniques were applied on the data to identify lifestyle segments, whereas a one-way ANOVA test was used to find significant lifestyle differences among mobile device users as regards their attitudes and behaviors towards mobile advertising. Findings and implications – Significant statistical differences were found among lifestyle segments in terms of attitudes and behavioral outcomes towards mobile advertising. The demographic variables were found to be insignificant for finding attitudinal and behavioral differences among consumers. The relationship between attitudes and behaviors was also found to be positive. Marketers can design their promotional campaigns more effectively by using a lifestyle segmentation approach. Limitations – The scope of the study is limited, as it is a single-market investigation, and its explanatory power is low because of the sample size. Originality – The applicability of lifestyle segmentation in comparison to demographic variables to find attitudinal and behavioral differences towards mobile advertising had not been done before.

Suggested Citation

  • Nauman Zaheer & Mihael Kline, 2018. "Use of Lifestyle Segmentation for Assessing Consumers’ Attitudes and Behavioral Outcomes towards Mobile Advertising," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 30(2), pages 213-229.
    • Handle: RePEc:zag:market:v:30:y:2018:i:2:p:213-229
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    References listed on IDEAS

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    1. Justin P. Johnson, 2013. "Targeted advertising and advertising avoidance," RAND Journal of Economics, RAND Corporation, vol. 44(1), pages 128-144, March.
    2. Kim, Ki Youn & Lee, Bong Gyou, 2015. "Marketing insights for mobile advertising and consumer segmentation in the cloud era: A Q–R hybrid methodology and practices," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 78-92.
    3. Wang, Ying & Sun, Shaojing, 2010. "Assessing beliefs, attitudes, and behavioral responses toward online advertising in three countries," International Business Review, Elsevier, vol. 19(4), pages 333-344, August.
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    Cited by:

    1. Danijel Bratina & Armand Faganel, 2023. "Using Supervised Machine Learning Methods for RFM Segmentation: A Casino Direct Marketing Communication Case," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 35(1), pages 7-22.
    2. Jerónimo García-Fernández & Pablo Gálvez-Ruiz & Moisés Grimaldi-Puyana & Salvador Angosto & Jesús Fernández-Gavira & M. Rocío Bohórquez, 2020. "The Promotion of Physical Activity from Digital Services: Influence of E-Lifestyles on Intention to Use Fitness Apps," IJERPH, MDPI, vol. 17(18), pages 1-15, September.

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