Advertisement Ranking and Campaign Effects
https://www.nytimes.com/2019/10/20/us/elections/trump-campaign-ads-democrats.html
The article, “Trump Campaign Floods Web With Ads, Raking in Cash as Democrats Struggle” was published recently in the New York Times. The article explores Facebook advertising and engagement rate ranking of each ad, and the role that this plays in campaigns.
Facebook is a major focus for many companies and campaigns in terms of digital spending. It favors “emotionally charged content,” and this happens to be something in which the Trump Campaign takes advantage.
Campaigns are able to buy Facebook ads through an automated auction system that ranks advertisements on the predicted likelihood of the ad being clicked, liked, commented, and shared with other users. It is in this aspect that the Trump campaign manages to separate itself from Democratic policy-focused appeals. The often divisive themes perpetrated by the Trump campaign garner more engagement. In this way, Facebook often favors provocative and sometimes inflammatory messages.
According to Shomik Dutta, digital strategist and founder of a Democratic incubator, there exists a bias in the algorithm that Facebook uses to rank advertisements, and this bias pushes for controversial topics. In response, Facebook denies this, claiming that users are able to flag any negative content.
Another role that Facebook plays in Trump’s campaign includes Facebook’s “fact-checking rules”, which do not apply to political ads, allowing Trump to spread false information about other political candidates.
Looking back on the 2016 election, Facebook notes that Trump’s advertisements were more targeted to specific audiences than that of Clinton’s. The Trump administration made more unique ads, 5.9 million to Clinton’s 66,000, and a single message targeted a narrower audience of 2.5 million versus 8 million for a Clinton advertisement.
The topics that we learn in class such as keyword based advertising and prices of ads play major roles in the digital marketing of political campaigns. The engagement rate ranking used by Facebook to rate advertisements is similar to the concept of page ranking that we learned in lecture. There is a score for each node that is updated regularly depending on the engagement it receives.
Advertisements are ranked based on a “pay-per-click” basis, where click indicates engagement and can be referenced as a like, comment, or sharing of an advertisement on Facebook. The Trump campaign is also a good example of how targeted ads are worth more than ads that charge for impressions, and it shows how such ads are often much more effective than simple banner ads shown to everyone. This is a real-world example of how advertising and auctioning plays a role in our day to day lives.