Personalized Interpolation: An Efficient Method to Tame Flexible Optimization Window Estimation
Journal:
arXiv
Published Date:
Jan 23, 2025
Abstract
In the realm of online advertising, optimizing conversions is crucial for
delivering relevant products to users and enhancing business outcomes.
Predicting conversion events is challenging due to variable delays between user
interactions, such as impressions or clicks, and the actual conversions. These
delays differ significantly across various advertisers and products,
necessitating distinct optimization time windows for targeted conversions. To
address this, we introduce a novel approach named the \textit{Personalized
Interpolation} method, which innovatively builds upon existing fixed conversion
window models to estimate flexible conversion windows. This method allows for
the accurate estimation of conversions across a variety of delay ranges, thus
meeting the diverse needs of advertisers without increasing system complexity.
To validate the efficacy of our proposed method, we conducted comprehensive
experiments using ads conversion model. Our experiments demonstrate that this
method not only achieves high prediction accuracy but also does so more
efficiently than other existing solutions. This validation underscores the
potential of our Personalized Interpolation method to significantly enhance
conversion optimization in real-world online advertising systems, promising
improved targeting and effectiveness in advertising strategies.
