Social media has become an indispensable part of day-to-day life for almost every person and an important marketing tool for most of the companies. One of the effective ways to reach a wider audience on social media is to benefit from other users sharing your content. Thus, there is a great number of articles on Internet advising on not only how to create the content people would love to share, but also what, when and how often one should or should not share.
The dimensions of the posts which are likely to be shared have been studied in academia as well. The researchers highlight such characteristics as emotional component (Heath et al., 2001) and relation to environmental cues (Berger, Schwartz, 2011) as well as popularity or being consistent with the image the target audience is developing (Toubia, Stephen, 2013). Additionally, social contagion and influence can significantly affect the diffusion process (Van den Bulte, Joshi, 2007). However, most papers focus on one dimension only and do not take into account how it is connected to the others.
By contrast, Zhang et al. (2017) introduce a model of social media rebroadcasting behaviour that integrates the various factors shown to influence the likelihood of sharing some content. Their research provides evidence that the fit between the message content and the audience’s interest is a significant driver of rebroadcasting behaviour and proves that shares by influentials affect the behaviour of other users who are susceptible to influence. However, there is considerable variation across users both in terms of their ability to influence other users and their susceptibility to the influence of others’ rebroadcasting.
Importantly for SMM specialists, the tailored messages designed to match the preferences and interests of the audience were found out to be most effective when there is less heterogeneity in the audience’s interests. Modelling content-user fit is crucial for user’s rebroadcasting decisions and consequently in a firm’s social media marketing strategies (Zhang et al.,2017).
Overall, the results of the study suggest that targeting influentials to encourage their rebroadcasting of our message can potentially lead to greater rebroadcasting activity than investing in message content. However, the analysis also provides evidence that, under certain circumstances, tailoring message content to the interests of the influentials can generate even greater rebroadcasting activity. Also, concerning the impact of content-user fit in social media rebroadcasting, while academical literature has suggested that certain types of content are on average more viral, it may be critical for managers to ensure that this content fits the preferences of their audience base. Content-user fit can possibly be especially impactful for homogenous followers, for which managers could tailor content to the followers’ preferences rather than simply disseminate viral content.
To conclude, although brands spend significant resources on social media to connect with their customers, there is limited understanding on how consumers engage with brands on social media and how it influences their purchase process. Therefore a further research may also look at influence in terms of one’s impact on brand health measures, the purchasing behaviour of others or context-specific decisions. Nowadays, practitioners are transforming the way to communicate with their target audiences and social media as new marketing channel allow them to engage with influencers one on one. A strategy is critical to the success of almost immediate continuing consumer conversations about the brands. With the immense growth of bloggers and their increasing power as influencers for media and consumers, analysing and evaluating the most influential for the targeted audience is a vital part of any social media campaign. Identifying the tiers of influencers and how they fit into a brand’s social media strategy will ensure a social media engagement that produces measurable results and a positive contribution to brand equity (Booth et al., 2011)
References:
Berger, J., Schwartz, E.M. (2011) ‘What drives immediate and ongoing word of mouth?’, Journal of Marketing Research, Vol 48, Issue 5, pp.869-880.
Booth, N., Matic, J.A. (2011) ‘Mapping and leveraging influencers in social media to shape corporate brand perceptions’, Corporate Communications: An International Journal, Vol 16 Issue 3, pp.184-191.
Heath, C., Bell, C., Sternberg, E. (2001) ‘Emotional selection in memes: the case of urban legends’, Journal of personality and social psychology, Vol 81, Issue 6, pp.1028-1041.
Toubia, O., Stephen, A.T. (2013) ‘Intrinsic vs. image-related utility in social media: Why do people contribute content to twitter?’, Marketing Science, Vol 32, Issue 3, pp.368-392.
Van den Bulte, C., Joshi, Y.V. (2007) ‘New product diffusion with influentials and imitators’, Marketing Science, Vol 26, Issue 3, pp.400-421.
Zhang, Y., Moe, W.W., Schweidel, D.A. (2017) ‘Modeling the role of message content and influencers in social media rebroadcasting’, International Journal of Research in Marketing, Vol 34, Issue 1, pp.100-119.
