Who to target? Low- versus high-status seeding in user-generated content networks

Beichert, Maximilian ; Bayerl, Andreas ; Goldenberg, Jacob ; Lanz, Andreas U.

Document Type: Conference presentation
Year of publication: 2021
Conference title: European Marketing Academy Conference (EMAC)
Location of the conference venue: Madrid, Spain
Date of the conference: 26.05.2021
Related URLs:
Publication language: English
Institution: Business School > ABWL, Quantitatives Marketing (Stahl 2013-)
Subject: 330 Economics
Abstract: The battle for consumers’ attention is constantly on the rise. Hence, marketers are looking for alternative, more efficient ways – such as influencer marketing –to reach out to their audiences. Recently, there have been more and more industry articles pointing out the value of low-status influencers (e.g., Haenlein et al. 2020). This goes against seeding literature in marketing, which almost unanimously recommends targeting high-status influencers, i.e., hubs with a large following (e.g., Goldenberg et al. 2009; Hinz et al. 2011). Since the common (mostly implicit) assumption in this literature is that high-status influencers generate a high return, our goal is to fill this research gap and consider the whole influencer marketing funnel, i.e., conversions from followers (e.g., on Instagram) to views (on the sponsored post), to engagement (with the sponsored post), to landingpage views (on the firm’s website), to sales. Given the accumulating empirical evidence that optimal seeding policies may very well be reversed (e.g., Lanz et al. 2019; Watts & Dodds 2007), does it really pay off to engage high-status influencers as opposed to low-status influencers when considering the whole influencer marketing funnel? To shed light on this question, we conducted two (supply-side) field experiments. For these experiments, we collaborated with a large influencer marketing platform to recruit low-status (N=68; N=60) and high-status (N=70; N=54) influencers. Both groups were given the task to promote an e-commerce store’s sneaker offering by posting a well-specified “Instagram Story,” which included a coupon code. Such codes are typically used to achieve full attribution between an influencer’s post and eventual sales within the e-commerce store’s sneaker offering. We find supportive evidence that high-status influencers may indeed not be as effective (as mostly implicitly assumed). Although they perform better regarding views––a view from them costs about a third––in the subsequent stages of the funnel they seem to underperform: They are less effective in terms of engagement as well as concerning sales. More specifically, an engagement from low-status influencers costs about half and regarding sales a conversion costs about a tenth. Surprisingly, for sales the difference in effectiveness holds not only in relative but even in absolute terms: High-status influencers generated a third of the conversions compared to low-status influencers. However, both groups disappoint when considering the return on spending (ROS), where return is the revenue after spending: Both feature negative ROS, however, with low-status influencers the manager loses only about 50% (-.4; -.65) compared to well over 90% (-.97; -.94) on the Euro.

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