Commercial audience retention of television programs: measurement and prediction

Abstract

Program audience ratings are typically used as a reference in placing and pricing television advertisements. However, the discrepancy in audience size between a program and its commercials impairs the reliability of the program ratings. This study proposes a new metric, commercial audience retention (CAR), to measure a program’s capability of retaining its audience when a commercial break occurs and develops a model to predict a program’s CAR. The CAR metric and prediction model are tested and validated using a sufficient dataset with consumer TV viewing and program broadcast records for 1 year. We find that some factors that influence program ratings or commercial avoidance have no significant effect or have different effects on CAR. Our empirical results may be of value for advertisers and TV stations in purchasing and pricing of commercial airtime. A real-world application of the CAR metric for an advertising company is offered as an illustration.

Supplemental data for this article is available online at https://doi.org/10.1080/02650487.2021.1906541 .

Keywords:

• Commercial audience retention
• commercial avoidance
• regression model
• media planning

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding details

This work was supported by the [National Natural Science Foundation of China] under Grant [Nos. 71602089 and 71702201], [NSF of Jiangsu Province] under Grant [No. BK20160785], and [The Strategic Research Grant of Hong Kong] under Grant [Nos. 7005294 and 7005430].

Additional information

Notes on contributors

Lianlian Song

Lianlian Song, an Associate Professor of Nanjing University of Aeronautics and Astronautics. Her research focuses on advertising, statistical modelling, information systems and business economics. The research topics she has conducted include traditional and online advertising, consumer response to different advertising strategies, website design according to visitor click behaviour, and etc. Her work has appeared in Journal of Advertising Research, Energy Economics, JASIST and etc. Postal address: office 0926, College of Economics and Management, Jiangjun Road 29, Jiangning District, Nanjing. Postcode: 210000. Tel: [phone]. E-mail address: [email protected].

Yang Shi

Yang Shi is an Assistant Professor at Shenzhen Audencia Business School, WeBank Institute of Fintech and Guangdong Laboraty of Artificial Intelligence and Digital Economy (SZ), Shenzhen University. She focuses on academic research of marketing in statistical modelling. The research topics she has conducted include modelling consumer purchase decisions, consumers’ responses to TV advertisements, bidding and etc. Her papers have appeared in Journal of Interactive Marketing, International Journal of Forecasting and etc. Post address: office 367, Shenzhen Audencia Business School, 3688 Nanhai Road, Nanshan District, Shenzhen, China. Postcode: 518060. Tel: [phone]. Fax: [phone]. Email address: [email protected].

Geoffrey Kwok Fai Tso

Geoffrey Kwok Fai Tso is an Associate Professor of City University of Hong Kong. His research areas include information systems, business economics, and marketing research. He is the leader of two regular research projects for the production of the HK Consumer Satisfaction Index and HK Consumer Confidence Index. His articles have appeared in European Journal of Marketing, JASIST, Journal of Advertising Research and etc. Postal address: Office P7515, Academic 1, Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong. Tel: [phone]. E-mail address: [email protected].