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 observed the propagation of recommendations and the cascade sizes, which can be explained by a stochastic model. We then established 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, there are product and pricing categories for which viral marketing seems to be very effective.

This is a joint work with Lada Adamic and Bernardo Huberman from HP Labs.