TY - JOUR
T1 - Modeling the value of information granularity in targeted advertising
AU - Rallapalli, Swati
AU - Ma, Qiang
AU - Song, Han Hee
AU - Baldi, Mario
AU - Muthukrishnan, S.
AU - Qiu, Lili
PY - 2014/3
Y1 - 2014/3
N2 - Behavioral Targeting (BT) in the past few years has seen a great upsurge in commercial as well as research interest. To make advertising campaigns more effective, advertisers look to target more relevant users. Ad-networks and other data collectors, such as, Cellular Service Providers (CSPs), hold a treasure trove of user information that is extremely valuable to advertisers. Moreover, these players may have complimentary sets of data. Combining and using data from different collectors can be very useful for advertising. However, in the trade of data among the various players, it is currently unclear how a price can be attached to a certain piece of information. This work contributes (i) a MOdel of the Value of INformation Granularity (MoVInG) that captures the impact of additional information on the revenue from targeted ads in case of uniform bidding and (ii) an expression that is applicable in more general scenarios. We apply MoVInG to a user data-set from a large CSP to evaluate the financial benefit of precise user data.
AB - Behavioral Targeting (BT) in the past few years has seen a great upsurge in commercial as well as research interest. To make advertising campaigns more effective, advertisers look to target more relevant users. Ad-networks and other data collectors, such as, Cellular Service Providers (CSPs), hold a treasure trove of user information that is extremely valuable to advertisers. Moreover, these players may have complimentary sets of data. Combining and using data from different collectors can be very useful for advertising. However, in the trade of data among the various players, it is currently unclear how a price can be attached to a certain piece of information. This work contributes (i) a MOdel of the Value of INformation Granularity (MoVInG) that captures the impact of additional information on the revenue from targeted ads in case of uniform bidding and (ii) an expression that is applicable in more general scenarios. We apply MoVInG to a user data-set from a large CSP to evaluate the financial benefit of precise user data.
UR - http://www.scopus.com/inward/record.url?scp=84902459354&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902459354&partnerID=8YFLogxK
U2 - 10.1145/2627534.2627547
DO - 10.1145/2627534.2627547
M3 - Article
AN - SCOPUS:84902459354
SN - 0163-5999
VL - 41
SP - 42
EP - 45
JO - Performance Evaluation Review
JF - Performance Evaluation Review
IS - 4
ER -