“How Much Does Ad Sequence Matter? Economic Implications of Consumer Zapping and the Zapping-Induced Externality in the Television Advertising Market”, 2022-04-05 (; backlinks):
It is well documented that TV viewers avoid advertisements by switching channels during commercial breaks (“zapping”). Ads with lower audience retention ability lead to more consumer zapping.
Given that several ads are sequentially broadcast during a commercial break, an ad with a low retention rate will negatively affect the viewership of subsequent ads by decreasing their opportunities to be exposed to viewers. In this case, the ad imposes a negative externality on subsequent ads in the same commercial break. This externality is typically not priced in the TV advertising market; however, it may substantially affect the TV network’s profit.
Based on a large and rich data set on TV viewing and advertising, we build a comprehensive model of consumer zapping and conduct various simulation studies to quantify the impact of the zapping-induced externality on the network’s revenue.
Results: show that our focal network may increase gross revenue up to 19.38% by reordering ads during a commercial break so that the negative impact of this externality is minimized.
…We note that the average viewer outflow rate (ie. zap rate) and its variance are highest in the first minute, drop sharply in the second minute, and remain relatively stable thereafter. In summary, the net outflow rate is subject to a high degree of variation across minutes, and an average advertisement loses about 7% of the initial audience size at the start of the commercial break.
…For each ad A in break H, based on the estimated coefficients, we calculate the probability of each individual viewer watching ad A (unconditional on the viewing decision of the previous ad) in the current ad sequence in the data. We then average the viewing probabilities across all viewers in the break to get ad A’s average retention rate in break H. To eliminate the possible impact of slot position on ads’ capability to retain viewers, we set the slot position to be the first slot for all ads when calculating the retention rate. Figure 3 shows the distribution of retention rates across ads and breaks. Of the 4,893 combinations of ad and break, the estimated retention rate ranges 0.709–0.986, with a mean (SD) of 0.923 (0.046).
See Also:
“Online viewers’ choices over advertisement number and duration”
“Advertising and Content Differentiation: Evidence from YouTube”
“A New Benchmark for Mechanical Avoidance of Radio Advertising”
“Measuring Consumer Sensitivity to Audio Advertising: A Field Experiment on Pandora Internet Radio”
“Do not allow pop-up ads to appear too early: Internet users’ browsing behavior to pop-up ads”