Antonio García Martínez's at Wired writes about the effects of scaled pricing based on algorithms in Faecebook's advertisement auction. Just buying advertisements in the auction does not guarantee that the ads get through to the target audience so the clickbaitiness of the ad is estimated by algortithms which adjust the price. Ads estimated to be clickbaity by the algorithm get lower prices so more can be purchased with the same money. The more problematic the ad, the more cost effect it is for the buyer
A canny marketer with really engaging (or outraging) content can goose their effective purchasing power at the ads auction, piggybacking on Facebook’s estimation of their clickbaitiness to win many more auctions (for the same or less money) than an unengaging competitor. That’s why, if you’ve noticed a News Feed ad that’s pulling out all the stops (via provocative stock photography or other gimcrackery) to get you to click on it, it’s partly because the advertiser is aiming to pump up their engagement levels and increase their exposure, all without paying any more money.
During the run-up to the election, the Trump and Clinton campaigns bid ruthlessly for the same online real estate in front of the same swing-state voters. But because Trump used provocative content to stoke social media buzz, and he was better able to drive likes, comments, and shares than Clinton, his bids received a boost from Facebook’s click model, effectively winning him more media for less money. In essence, Clinton was paying Manhattan prices for the square footage on your smartphone’s screen, while Trump was paying Detroit prices. Facebook users in swing states who felt Trump had taken over their news feeds may not have been hallucinating.
Thus the advertisement auction algorithms themselves were yet another major factor in the results of the 2016 US election.