Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments January 6, 2023 erstellt
Beschreibung:
Brands increasingly seek to leverage influencer marketing as part of their communication campaigns. However, brands’ influencer selection problem is difficult because influencers are large in number and highly heterogeneous. Moreover, industry practices provide rules of thumb that may not fully account for possible interdependencies among influencers. We propose two theoretically-motivated dimensions of influencer interdependence: audience overlap and content similarity. We then show how accounting for these two measures can impact follower engagement with influencers’ posts. We further contextualize our findings by partnering with a marketing agency and use our model to predict the engagement level with a campaign. Our analysis reveals that the agency would have mischaracterized engagement by as much as 27% had it used a model that did not account for interdependencies, and that the rank-ordering of candidate influencer sets based on expected performance could substantially differ. To our knowledge, this is the first empirical attempt to study interdependency dynamics among influencers. We discuss the managerial implications of our findings for brands planning influencer campaigns, and offer guidance on how to evaluate an influencer set