🤔DO ADS ACTUALLY WORK?🤔
🧵We tackle this question using a large collection of display ad field experiments in a working paper with @EconInformatics & @enub
"The Online Display Ad Effectiveness Funnel & Carryover: Lessons from 432 Field Experiments” ssrn.com/abstract=27015… 1/8
Recently, the effectiveness of advertising has been called into question. Some of this skepticism is healthy. Measuring the effect of advertising properly is *really* difficult, as I detail here:
On average, our ad experiments run for 20 days & contain 4M users: 1.6B user-campaign observations in all! Our data come from the 1st months of Google’s Conversion Lift & Brand Lift products, which are powered by our (predicted) ghost ads methodology: doi.org/10.1509/jmr.15… 3/
We measure ad effects on user visits to the advertiser’s website & user conversions: e.g. purchase, sign-up, or download. Our lift estimates compare experimental Treatment users who can see the focal ad & Control users who can not.
% Lift = (Treatment - Control) / Control
4/
We show our site visit estimates (dots) ordered by lift with 95% confidence intervals (whiskers). The median lift is 16.6%. The estimates are noisy, but 85% are positive. Note: we rarely see negative lifts due to industry & academic publication bias. 5/
195 of our 347 site visit estimates are positive & statistically significant (5%, two-sided).
What is the chance that advertising does not work, but we observe 195 of 347 significant estimates? 7.4 * 10^-213. In other words… 6/
We next look at the lift estimates for conversions, which we observe for 184 campaigns. The median lift is 8.1% with 10th & 90th quantiles of -8.9% and 83.4%.
52 of 184 are statistically significant, yielding collective significance of p= 2.9 * 10^-40. 7/
In sum, we contribute some of the strongest evidence that ads actually work. We add to a literature in marketing that seeks to answer this question with multi-advertiser collections of field experiments in various media. FIN
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🇮🇹Journeyed to Milan for a marketing conference hosted by @Unibocconi 🇮🇹
A 🧵…
First up, Sonja Gensler documents welfare harms of German regulations capping days for AirBnB hosts. This restricts supply, but the good news 😂 is that non-compliance blunts the welfare harm. Marginal effect on long-term rental prices: the intended benefit of the policy…
@michielvancromb introduces a new research agenda on the “Spotify-ification” of the video game industry: consumers increasingly subscribe to a bundle of games, with profound consequences for the market. (And 3 papers!!!)
What is the impact of strict #privacy regulation on content supply and demand?
In Sept 2019, YouTube paid a record $170M to settle charges it violated children’s privacy law (#COPPA). We use this to study the "privacy-for-content" tradeoff. 1/11
Beginning Jan 2020, YouTube identified kids content and eliminated all related personalization including: personalized ads, search, content recommendations, & commenting.
This matches FTC's proposed rules to strengthen COPPA announced yesterday: 2/ bit.ly/3RMARdf
YouTube creators worried these changes amounted to the "COPPAcalypse."
We study 5,066 top U.S. YouTube channels by comparing child-directed content creators to their non-child-directed counterparts using a difference-in-differences design. 3/
We study the "privacy-for-content" tradeoff using the 2019 YouTube COPPA settlement.
"COPPAcalypse? The YouTube settlement’s impact on kids content” w/ @TesaryLin, James Cooper, & Liang Zhong
➡️ ssrn.com/abstract=44303… 1/9
Data sharing increases ad revenue, which pays for free content, & helps personalize websites to better find the content we want. On the other hand, people want more privacy online: especially for kids.
The YouTube settlement shows the consequences of strict privacy regulation. 2/
In Sept. 2019, YouTube paid a record $170M to settle charges it violated children’s privacy law (COPPA). Beginning Jan. 2020, YouTube identified kids content and eliminated all related personalization including: personalized ads, search, content recommendations, & commenting. 3/
Regulators & researchers seek to balance privacy & the data economy. The EU’s #GDPR is a landmark & influential regulation that defines personal data expansively. GDPR establishes:
-rules for data processing,
-rights for EU residents,
-responsibilities for firms, &
-BIG fines. 2/
#GDPR is hard to study:
A) Finding a suitable control group is hard because the GDPR had global spillovers. E.g., it affects EU firms & non-EU firms serving EU residents.
B) GDPR can screw with personal data: e.g., you may only see data from consenting users. 3/
🧵Explainer for the Topics API 🧵
Google announced the Topics API for Privacy Sandbox🏖️. Topics is basically FLoC v2.0. Google is deftly replacing FLoC v1 with a more anodyne technology and name...
Details: developer.chrome.com/docs/privacy-s… 1/8
Topics allows for interest-based ads without 3rd party cookies. Most research, including our own, shows ad prices are 2-3X higher with cookies.
Put concretely: Interest-based ads help fund content that is socially valuable, but uninteresting to advertisers. 2/
In Topics, the browser classifies begins by classifying the sites that users visit into topics from a list of ~350 readable & benign topics like cats🐈 or hockey🏒.
To do so, sites must opt in and users can opt out. 3/
Thread explaining FLEDGE (formerly TURTLEDOVE).
Online advertising generates value for publishers, advertisers, & users. Now, Google & others are proposing alternatives that preserve this value while better protecting user privacy under the "Privacy Sandbox" proposals. 1/12
The public discussion of #PrivacySandbox is dominated by #FLoC, but many tech solutions are required to satisfy advertising use cases while protecting privacy. In particular, #FLEDGE propose more fundamental & interesting changes to the status quo. 2/
The key to FLEDGE is to move user targeting information onto the *browser*, rather than broadcasting a cookie ID to the adtech ecosystem so advertisers can bid on ad opportunities based on what they know about that cookie ID. The prototypical FLEDGE use-case is retargeting. 3/