First, Go Big or Go Small?
Analysis of Sequential Social Advertisement

30 Pages Posted: 5 Aug 2017  

Parshuram Hotkar

University of Texas at Austin, Red McCombs School of Business

Rajiv Garg

University of Texas at Austin - Department of Information, Risk and Operations Management

Date Written: June 16, 2018

Abstract

Social media platforms like Twitter and Facebook have emerged as new channels for advertising that enable customer targeting based on demographics, interests, and user behavior. Spillover through word of mouth (WOM) and user engagement plays a crucial role in social media marketing. Since individuals are part of multiple groups (based on their diversified interests) on social media, strategically sequencing ad campaigns across asymmetric groups can potentially increase sales. In this paper, we present a theoretical model for information retention and show that sequence order of ads across different target groups may have asymmetric outcomes. We then estimate the effect of sequence order (targeting users in a small group followed by users in a large group, and vice versa) on sales through randomized field experiments on two dominant social media platforms (Facebook and Twitter). While advertising on small groups provides better returns on Twitter and ads on large group perform better on Facebook, we find that sequentially advertising initially to a small group followed by large group performs better on both platforms. The managerial insight behind our findings can help practitioners in strategically sequences ad campaigns across the different group and optimize the returns from social media.

Keywords: Social Media, Advertising, Social Media Marketing, Strategic Sequencing, Spillover.

JEL Classification: M00, M30, M31, M37

Suggested Citation

Hotkar, Parshuram and Garg, Rajiv, First, Go Big or Go Small? Analysis of Sequential Social Advertisement (June 16, 2018). Available at SSRN: https://ssrn.com/abstract=3007806 or http://dx.doi.org/10.2139/ssrn.3007806

Parshuram Hotkar

University of Texas at Austin, Red McCombs School of Business ( email )

CBA 5.202
Austin, TX 78712
United States
512-888-1994 (Phone)

Rajiv Garg (Contact Author)

University of Texas at Austin - Department of Information, Risk and Operations Management ( email )

CBA 5.202
Austin, TX 78712
United States

HOME PAGE: http://www.RajivGarg.org

Register to save articles to
your library

Register

Paper statistics

Downloads
99
Abstract Views
384
PlumX