Predicting Customer Engagement through Social Media Platform Technical Features: Evidence from Food and Beverage Establishments in Tangub City

Abstract

The study utilized a descriptive-correlational and predictive quantitative research methodology to identify whether the degree to which customers perceive that various technical characteristic of social media platforms (i.e., the social media platform itself) will influence how engaged those same customers will be with regard to a particular food and beverage establishment's use of that social media platform. A total of 299 responses from the sample of 300 participants who had viewed or used Facebook pages of food and beverage establishments prior to or in conjunction with making a decision regarding where they would dine were collected via an on-line survey. The researchers investigated four different technical feature categories for social media platforms; completeness, flexibility, evolvability and integration. The researchers assessed customer engagement across five distinct categories: enthusiasm, attention, absorption, interaction and identification. Descriptive statistics (means), Cronbach’s Alpha, and multiple linear regression analyses were applied to investigate the results obtained from the data. Overall, the results indicated that the technical features of the Facebook pages surveyed by the participants were highly influential to them, but their levels of engagement varied greatly. The reliability of the survey instrument was found to be extremely reliable based upon Cronbach’s Alpha (α = .964). Additionally, the regression analysis suggested that there is a statistical relationship between the technical features of Facebook pages (e.g., completeness, flexibility, evolvability, etc.) and customer engagement (F[4, 294] = 218.14; p < .001; R = .865; R2 = .748; adj R2 = .745). These findings indicate that approximately 74.8% of the variability in customer engagement can be accounted for by the technical features of the Facebook pages. Of the technical features identified in this study, three (completeness, evolvability and integration) were shown to be statistically significant and thus likely to predict customer engagement. Flexibility was not found to be statistically significant. It was also noted that integration was the most influential factor when predicting customer engagement. Thus, it appears that customers are more likely to engage with a food and beverage establishment if its Facebook page has functional uses and connections that allow customers to obtain information about the organization and assist customers in connecting with one another. Because the study utilized a cross-sectional survey methodology, caution should be taken when interpreting these results as indicative of causal relationships between the technical features examined and customer engagement.