Keyword Optimization in Sponsored Search Advertising: A Multi-Level Computational Framework

Yang, Y., Jansen, B. J., Yang, Y. C., Guo, X., & Zeng, D., (2019). Keyword Optimization in Sponsored Search Advertising: A Multi-Level Computational Framework. IEEE Intelligent Systems, 34(1), 32 - 42.

11 Pages Posted: 10 Jun 2019 Last revised: 16 Feb 2022

See all articles by Yanwu Yang

Yanwu Yang

School of Management, Huazhong University of Science and Technology

Bernard Jansen

Pennsylvania State University

Yinghui (Catherine) Yang

Graduate School of Management, UC Davis

Xunhua Guo

Tsinghua University - School of Economics & Management

Daniel Dajun Zeng

University of Arizona - Department of Management Information Systems

Date Written: May 24, 2018

Abstract

In sponsored search advertising, keywords serve as an essential bridge linking advertisers, search users and search engines. Advertisers have to deal with a series of keyword decisions throughout the entire lifecycle of search advertising campaigns. This paper proposes a multi-level and closed-form computational framework for keyword optimization (MKOF) to support various keyword decisions. Based on this framework, we develop corresponding optimization strategies for keyword targeting, keyword assignment and keyword grouping at different levels (e.g., market, campaign and adgroup). With two real-world datasets obtained from past search advertising campaigns, we conduct computational experiments to evaluate our keyword optimization framework and instantiated strategies. Experimental results show that our method can approach the optimal solution in a steady way, and it outperforms two baseline keyword strategies commonly used in practice. The proposed MKOF framework also provides a valid experimental environment to implement and assess various keyword strategies in sponsored search advertising.

Keywords: keyword strategy; keyword optimization; advertising strategy; search advertising

JEL Classification: M3

Suggested Citation

Yang, Yanwu and Jansen, Bernard and Yang, Yinghui (Catherine) and Guo, Xunhua and Zeng, Daniel Dajun, Keyword Optimization in Sponsored Search Advertising: A Multi-Level Computational Framework (May 24, 2018). Yang, Y., Jansen, B. J., Yang, Y. C., Guo, X., & Zeng, D., (2019). Keyword Optimization in Sponsored Search Advertising: A Multi-Level Computational Framework. IEEE Intelligent Systems, 34(1), 32 - 42., Available at SSRN: https://ssrn.com/abstract=3393235 or http://dx.doi.org/10.2139/ssrn.3393235

Yanwu Yang (Contact Author)

School of Management, Huazhong University of Science and Technology ( email )

1037 Luoyu Road
Hubei 430074
China

Bernard Jansen

Pennsylvania State University ( email )

University Park, PA 16802
United States

Yinghui (Catherine) Yang

Graduate School of Management, UC Davis ( email )

One Shields Avenue
Apt 153
Davis, CA 95616

Xunhua Guo

Tsinghua University - School of Economics & Management ( email )

Beijing, 100084
China

Daniel Dajun Zeng

University of Arizona - Department of Management Information Systems ( email )

AZ
United States

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