Sequential Social Media Advertising: An Empirical Evidence

42 Pages Posted: 12 Dec 2018

See all articles by Parshuram Hotkar

Parshuram Hotkar

University of Texas at Austin - McCombs School of Business

Rajiv Garg

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

Date Written: November 19, 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. Because 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 the sequence order of ads across different target groups may have asymmetric outcomes. We then estimate the effect of the 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 in small groups provides better returns on Twitter and ads in large groups perform better on Facebook, we find that sequentially advertising initially to a small group followed by a large group performs better on both platforms. The managerial insight behind our findings can help practitioners to strategically sequence ad campaigns across the different groups and optimize the returns from social media.

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

Suggested Citation

Hotkar, Parshuram and Garg, Rajiv, Sequential Social Media Advertising: An Empirical Evidence (November 19, 2018). Available at SSRN: https://ssrn.com/abstract=3287476 or http://dx.doi.org/10.2139/ssrn.3287476

Parshuram Hotkar (Contact Author)

University of Texas at Austin - McCombs School of Business ( email )

Austin, TX 78712
United States

Rajiv Garg

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

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