Converting People-Meter Data From Per-Minute to Per-Second Analysis : A Statistical Model Offers a Closer Look At TV Ad Avoidance and Effectiveness
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 53-72 |
Journal / Publication | Journal of Advertising Research |
Volume | 59 |
Issue number | 1 |
Online published | 5 Mar 2019 |
Publication status | Published - Mar 2019 |
Link(s)
Abstract
Advertisers prefer second-by-second measurements of advertisements over program ratings, but collecting individual viewing data that are accurate to the unit of one second is very difficult and expensive. Under the condition of no additional cost or effort investment, the authors developed a methodology for converting minute-by-minute people-meter data into second-by-second audience ratings. This methodology is based on the successful modeling of television viewers' tuning-in behavior by a uniform distribution and tuning-out behavior during commercials by a beta distribution. The methodology could be applied to measure advertising effectiveness, assess advertising strategies, and aid in future media purchasing and pricing.
Research Area(s)
- TELEVISION, BEHAVIOR, EXPOSURE, PROGRAM
Citation Format(s)
Converting People-Meter Data From Per-Minute to Per-Second Analysis: A Statistical Model Offers a Closer Look At TV Ad Avoidance and Effectiveness. / Song, Lianlian; Zhou, Peng; Tso, Geoffrey et al.
In: Journal of Advertising Research, Vol. 59, No. 1, 03.2019, p. 53-72.
In: Journal of Advertising Research, Vol. 59, No. 1, 03.2019, p. 53-72.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review