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A process model for identifying online customer engagement patterns on Facebook brand pages

Purpose 
 
 
 
 
The purpose of this paper is to develop and empirically test a process model (comprising of seven dimensions), for identifying online customer engagement patterns leading to recommendation. These seven dimensions are communication, interaction, experience, satisfaction, continued involvement, bonding, and recommendation. 
 
 
 
 
Design/methodology/approach 
 
 
 
 
The authors used a non-participant form of netnography for analyzing 849 comments from Australian banks Facebook pages. High levels of inter-coder reliability strengthen the study’s empirical validity and ensure minimum researcher bias and maximum reliability and replicability. 
 
 
 
 
Findings 
 
 
 
 
The authors identified 22 unique pattern of customer engagement, out of which nine patterns resulted in recommendation/advocacy. Engagement pattern communication-interaction-recommendation was the fastest route to recommendation, observed in nine instances (or 2 percent). In comparison, C-I-E-S-CI-B-R was the longest route to recommendation observed in ninety-six instances (or 18 percent). Of the eight patterns that resulted in recommendation, five patterns (or 62.5 percent) showed bonding happening before recommendation. 
 
 
 
 
Research limitations/implications 
 
 
 
 
The authors limited the data collection to Facebook pages of major banks in Australia. The authors did not assess customer demography and did not share the findings with the banks. 
 
 
 
 
Practical implications 
 
 
 
 
The findings will guide e-marketers on how to best engage with customers to enhance brand loyalty and continuously be in touch with their clients. 
 
 
 
 
Originality/value 
 
 
 
 
Most models are conceptual and assume that customers typically journey through all the stages in the model. The work is interesting because the empirical study found that customers travel in multiple different ways through this process. It is significant because it changes the way the authors understand patterns of online customer engagement.