Using a music-sharing platform, the authors investigate how unknown music creators expand their follower base by directing outbound activities to other users (that is, seeding). They find that the responsiveness of seeding targets strongly declines with status difference; thus, unknown music creators (the majority) do not generally benefit at all from seeding influencers. Rather, “climbing,” or moving up the ladder slowly by gaining followers who are closer in status, is more effective than “jumping,” or attempting to influence much-higher-status influencers.
This strategy translates well to other industries. For example, for small and medium-sized businesses, seeding influencers may not be cost-effective; the expected return on influencers is actually lower than that on ordinary individuals.
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What You Need to Know
- The music industry can provide insights into seeding strategies.
- Though it might seem intuitive, seeding high-profile influencers is not in everyone’s best interest.
- For small and midsize operations, focusing on gaining followers who are closer in status tends to reap larger rewards.
This article addresses seeding policies in user-generated content networks by challenging the role of influencers in a setting of unpaid endorsements. On such platforms, the content is generated by individuals and firms interested in self-promotion. The authors use data from a worldwide leading music platform to study unknown music creators who aim to increase exposure of their content by expanding their follower base through directing outbound activities to other users. The authors find that the responsiveness of seeding targets strongly declines with status difference; thus, unknown music creators (the majority) do not generally benefit at all from seeding influencers. Instead, they should gradually build their status by targeting low-status users rather than attempt to “jump” by targeting high-status ones. This research extends the seeding literature by introducing the concept of risk to dissemination dynamics in online communications, showing that unknown music creators do not seed specific status levels but rather choose a portfolio of seeding targets while solving a risk versus return trade-off. The authors discuss various managerial implications for optimal seeding in user-generated content networks
Andreas Lanz, Jacob Goldenberg, Daniel Shapira, Florian Stahl (2019), “Climb or Jump: Status-Based Seeding in User-Generated Content Networks,” Journal of Marketing Research, 56 (June), 361–78.