Quantitative study of selected Facebook marketing communication engagement factors in the optics of different post types

  • Received June 17, 2019;
    Accepted July 22, 2019;
    Published July 31, 2019
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.15(3).2019.02
  • Article Info
    Volume 15 2019, Issue #3, pp. 16-25
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The objective of the research was to identify statistically significant differences in selected engagement indicators on Facebook – likes and shares in relation to the different types of content that brands on this platform add to. The analysis was performed on a sample of three global companies from the top 25 most valuable brands in the world and their posts. Using quantitative statistical methods – MANOVA (Multivariate analysis of variance) and Gammes-Howell post hoc test, a total of 1,280 brand posts were analyzed in order to differentiate the liking and sharing of content types. Data collection was carried out in the first half of 2018. The findings pointed to two statistically significant differences that were also interpreted in the discussion of the research. The findings have shown that in case of liking, in two cases out of three, there is a statistically significant difference in terms of the type of content added, when photos came out as those with the greatest potential to get like from Facebook users and fans. At the same time, the same finding appeared in the case of sharing, which is an even stronger form of engagement. Likewise, photos were shown to be the most promising in terms of potential content sharing by Facebook users and fans. The study provided some clues as to where this research should go further and explore the relationship more deeply in view of the more extensive quantitative research, and also the potential qualitative approach. The future research directions include analyzing companies of different types and sizes and also taking into account the contribution from other social networks with the same or similar engagement indicators.

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    • Table 1. Description of variables
    • Table 2. Normality test
    • Table 3. Multicollinearity test
    • Table 4. Homogeneity of covariance matrices. Box’s test of equality of covariance matrices
    • Table 5. Levene’s test. Levene’s test of equality of error variances
    • Table 6. Multivariate tests
    • Table 7. Statistical significance of differences
    • Table 8. Paired comparison of post types