  In online advertising (Ad), advertisers are always eager to know how to
globally optimize their budget allocation strategies across different channels
for more conversions such as orders, payments, etc. Ignoring competition among
different advertisers causes objective inconsistency, that is, a single
advertiser locally optimizes the conversions only based on its own historical
statistics, which is far behind the global conversions maximization. In this
paper, we present a cross-channel Advertising Coordinated budget allocation
framework (AdCob) to globally optimize the budget allocation strategy for
overall conversions maximization. We are the first to provide deep insight into
modeling the competition among different advertisers in cross-channel budget
allocation problems. The proposed iterative algorithm combined with entropy
constraint is fast to converge and easy to implement in large-scale online Ad
systems. Both results from offline experiments and online A/B budget bucketing
experiments demonstrate the effectiveness of AdCob.
