Display advertisements vary in the extent to which they annoy users. While publishers know the payment they receive to run annoying ads, little is known about the cost such ads incur due to user abandonment. We conducted a two-experiment investigation to analyze ad features that relate to annoyingness and to put a monetary value on the cost of annoying ads.
The first experiment asked users to rate and comment on a large number of ads taken from the Web. This allowed us to establish sets of annoying and innocuous ads for use in the second experiment, in which users were given the opportunity to categorize emails for a per-message wage and quit at any time.
Participants were randomly assigned to one of 3 different pay rates and also randomly assigned to categorize the emails in the presence of no ads, annoying ads, or innocuous ads. Since each email categorization constituted an impression, this design, inspired by et al 2011, allowed us to determine how much more one must pay a person to generate the same number of impressions in the presence of annoying ads compared to no ads or innocuous ads.
We conclude by proposing a theoretical model which relates ad quality to publisher market share, illustrating how our empirical findings could affect the economics of Internet advertising.
…We chose categorizing emails as the task to proxy for using a publisher’s site because users either implicitly or explicitly need to categorize their emails as spam or not spam in the presence of ads when using free web-based email services such as Yahoo! Mail, Gmail, and Outlook.com.
…Results: …Relative to a baseline of “bad ads”, both the “good ads” condition and the no ads condition led to substantially more impressions (19% and 25% more impressions, respectively).
The model expressed in Figure 1 can be used to estimate the compensating differential of annoying ads in this experiment. Since the curves are slightly non-linear, a range of compensating differentials could be calculated across the pay rate and ad conditions. To get a simple, single approximation we use the middle, “good ads” condition to estimate the effect of pay raises.
We take the average of the 0.2–0.4 and 0.4–0.6¢ differences, giving an estimated increase of 16.58 impressions resulting from a 0.2¢ per impression pay raise. When summarizing the effect of ad quality, we use the number of impressions at the 0.4¢ pay rate. Moving from “bad ads” to no ads, impressions increase by 12.68. The pay raise required to achieve a 12.68 impression increase is 0.153¢ per impression (= 0.2 × 12.68/16.58) or $2.07$1.532013 CPM (cost per thousand impressions).
That is, in this experiment, a participant in the “bad ads” condition would need to be paid an additional $2.07$1.532013 per thousand impressions to generate as many impressions as a person in the condition without ads. Similarly, moving from the “bad ads” condition to the “good ads” condition resulted in an additional 9.52 impressions per person. It would require a pay raise of 0.115¢ per impression (= 0.2×9.52/16.58) to generate 9.52 additional impressions, meaning that people in the “bad ads” condition would need to be paid an additional $1.56$1.152013 CPM to generate as many impressions as in the “good ads” condition.