in The Dynamics of Viral Marketing (.pdf) beschreibt Prof. Jure Leskovex, Carnegie Mellon University & Bernardo Buderman/HP:
We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of recommendations and the cascade sizes, which we explain by a simple stochastic model. We analyze how user behavior varies within user communities de¯ned by a recommendation network. Product purchases follow a ‚long tail‘ where a signi¯cant share of purchases belongs to rarely sold items. We establish how the recommendation network grows over time and how effective it is from the viewpoint of the sender and receiver of the recommendations. While on average recommendations are not very effective at inducing purchases and do not spread very far, we present a model that successfully identities communities, product and pricing categories for which viral marketing seems to be very effective.
Eric Kintz fasst die Ergebnisse der Arbeit zusammen:
#1 – Viral marketing does not spread well. In epidemics, high connectors are very critical nodes of the network and allow the virus to spread. In recommendations networks, a few very large cascades exist but most recommendation chains terminate after just a few steps.
#2 – The probability of viral infection decreases with repeated interaction. Providing excessive incentives for customers to recommend actually weakens the credibility of those links. The probability of purchasing a product increases with the number of recommendations received, but quickly saturates to a constant and relatively low probability.
#3 – Viral effectiveness varies depending on price and category. Social context has a high influence on the potency of viral infection. Technical or religious books for example had more successful recommendations than general interest topics. Smaller and more tightly knit groups tend to be more conducive to viral marketing
siehe auch Academic research on the Long Tail
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