TY - CHAP
T1 - Pricing Strategies for Viral Marketing on Social Networks
AU - Arthur, David
AU - Motwani, Rajeev
AU - Sharma, Aneesh
AU - Xu, Ying
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research has been supported in part by NSF Grant ITR-0331640, TRUST(NSF award number CCF-0424422), and grants from Cisco, Google, KAUST,Lightspeed, and Microsoft. The third author is grateful to Jason Hartline andMukund Sundararajan for useful discussions.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2009
Y1 - 2009
N2 - We study the use of viral marketing strategies on social networks that seek to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. This choice of prices for the buyers is termed as the seller's strategy. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optimal strategy in a wide variety of models. The strategy is based on an influence-and-exploit idea, and it consists of finding the right trade-off at each time step between: generating revenue from the current user versus offering the product for free and using the influence generated from this sale later in the process. © 2009 Springer-Verlag Berlin Heidelberg.
AB - We study the use of viral marketing strategies on social networks that seek to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. This choice of prices for the buyers is termed as the seller's strategy. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optimal strategy in a wide variety of models. The strategy is based on an influence-and-exploit idea, and it consists of finding the right trade-off at each time step between: generating revenue from the current user versus offering the product for free and using the influence generated from this sale later in the process. © 2009 Springer-Verlag Berlin Heidelberg.
UR - http://hdl.handle.net/10754/599399
UR - http://link.springer.com/10.1007/978-3-642-10841-9_11
UR - http://www.scopus.com/inward/record.url?scp=76649093924&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10841-9_11
DO - 10.1007/978-3-642-10841-9_11
M3 - Chapter
SN - 9783642108402
SP - 101
EP - 112
BT - Lecture Notes in Computer Science
PB - Springer Nature
ER -