Optimal Delivery with Budget Constraint in E-Commerce Advertising

Chao Wei, Weiru Zhang, Shengjie Sun, Fei Li, Xiaonan Meng, Yi Hu, Kuang-chih Lee, Hao Wang
Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling, PMLR 109:46-58, 2019.

Abstract

Online advertising in E-commerce platforms provides sellers an opportunity to achieve potential audiences with different target goals. Ad serving systems (like display and search advertising systems) that assign ads to pages should satisfy objectives such as plenty of audience for branding advertisers, clicks or conversions for performance-based advertisers, at the same time try to maximize overall revenue of the platform. In this paper, we propose an approach based on linear programming subjects to constraints in order to optimize the revenue and improve different performance goals simultaneously. We have validated our algorithm by implementing an offline simulation system in Alibaba E-commerce platform and running the auctions from online requests which takes system performance, ranking and pricing schemas into account. We have also compared our algorithm with related work, and the results show that our algorithm can effectively improve campaign performance and revenue of the platform.

Cite this Paper

BibTeX
@InProceedings{pmlr-v109-wei19a, title = {Optimal Delivery with Budget Constraint in E-Commerce Advertising}, author = {Wei, Chao and Zhang, Weiru and Sun, Shengjie and Li, Fei and Meng, Xiaonan and Hu, Yi and Lee, Kuang-chih and Wang, Hao}, booktitle = {Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling}, pages = {46--58}, year = {2019}, editor = {Vinagre, João and Jorge, Alípio Mário and Bifet, Albert and Al-Ghossein, Marie}, volume = {109}, series = {Proceedings of Machine Learning Research}, month = {19 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v109/wei19a/wei19a.pdf}, url = {https://proceedings.mlr.press/v109/wei19a.html}, abstract = {Online advertising in E-commerce platforms provides sellers an opportunity to achieve potential audiences with different target goals. Ad serving systems (like display and search advertising systems) that assign ads to pages should satisfy objectives such as plenty of audience for branding advertisers, clicks or conversions for performance-based advertisers, at the same time try to maximize overall revenue of the platform. In this paper, we propose an approach based on linear programming subjects to constraints in order to optimize the revenue and improve different performance goals simultaneously. We have validated our algorithm by implementing an offline simulation system in Alibaba E-commerce platform and running the auctions from online requests which takes system performance, ranking and pricing schemas into account. We have also compared our algorithm with related work, and the results show that our algorithm can effectively improve campaign performance and revenue of the platform.} }
Endnote
%0 Conference Paper %T Optimal Delivery with Budget Constraint in E-Commerce Advertising %A Chao Wei %A Weiru Zhang %A Shengjie Sun %A Fei Li %A Xiaonan Meng %A Yi Hu %A Kuang-chih Lee %A Hao Wang %B Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling %C Proceedings of Machine Learning Research %D 2019 %E João Vinagre %E Alípio Mário Jorge %E Albert Bifet %E Marie Al-Ghossein %F pmlr-v109-wei19a %I PMLR %P 46--58 %U https://proceedings.mlr.press/v109/wei19a.html %V 109 %X Online advertising in E-commerce platforms provides sellers an opportunity to achieve potential audiences with different target goals. Ad serving systems (like display and search advertising systems) that assign ads to pages should satisfy objectives such as plenty of audience for branding advertisers, clicks or conversions for performance-based advertisers, at the same time try to maximize overall revenue of the platform. In this paper, we propose an approach based on linear programming subjects to constraints in order to optimize the revenue and improve different performance goals simultaneously. We have validated our algorithm by implementing an offline simulation system in Alibaba E-commerce platform and running the auctions from online requests which takes system performance, ranking and pricing schemas into account. We have also compared our algorithm with related work, and the results show that our algorithm can effectively improve campaign performance and revenue of the platform.
APA
Wei, C., Zhang, W., Sun, S., Li, F., Meng, X., Hu, Y., Lee, K. & Wang, H.. (2019). Optimal Delivery with Budget Constraint in E-Commerce Advertising. Proceedings of the 2nd Workshop on Online Recommder Systems and User Modeling, in Proceedings of Machine Learning Research 109:46-58 Available from https://proceedings.mlr.press/v109/wei19a.html.

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