Users' engagement on Facebook: a cluster analysis
by Rania S. Hussein; Abeer A. Mahrous
International Journal of Business and Emerging Markets (IJBEM), Vol. 8, No. 4, 2016

Abstract: Social media platforms have shown dramatic growth in the past few years. Social media presents a wealth of marketing opportunities for companies. Companies can use these platforms to do tailored marketing, to build more effective customer relationship management programs and to engage their customers, just to name a few. Understanding social media users' characteristics and behaviour on social media is critical. This paper delineates an exploratory study to understand users' engagement on social media by attempting to segment and classify Facebook users, being the most popular social media platform, segmenting Facebook users will be based on users' motives to log on to Facebook, usage patterns, lifestyle, attitudes towards Facebook and demographic variables. A sample of 290 users was drawn from the Facebook users in Egypt. Data was analysed using two stages cluster analysis technique. Three different clusters were obtained namely; socialisers, laggards and information seekers, each with different characteristics and Facebook usage patterns. Socialisers and information seekers are the most frequent users of Facebook, while the laggards are the least frequent users of Facebook with an intention of discontinuation. This study provides useful marketing insights and implications to companies in developing their marketing strategies.

Online publication date: Thu, 13-Oct-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business and Emerging Markets (IJBEM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com