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“You May Like…” Exploring Content Recommendation Platforms

We have recently discussed the basic mechanics of the Google and Facebook pay-per-click marketing platforms and the auction methods they use to determine ad prices and placement. Each platform enables advertisers to target viewers in a similar way and to provide relevant content to users at the true price of the ad-buyer. When the right ads show up to the right people, both sides win and this forms the basis for the entire PPC marketing industry.

However, these are now not the only platforms available for content marketers to use in order to drive traffic, engagement and conversions. “Content recommendation platforms” are now an alternative way to consistently match ad-buyers and content consumers.

The two leading players in this relatively new advertising sector are Outbrain and Taboola. You may have never heard of them, but you have certainly seen their ads before. The genius of their advertising platform is that it almost appears as native content in the site that you visit. These companies place articles and videos below existing content on online newspapers, blogs or magazines. Every time you see a header that says, “Recommended for you”, or “You May Like”, it is probably generated by the algorithm Outbrain or Taboola uses to predict what the next most interesting article or video for you is.

This is similar to the way Google AdWords displays ads based on your keyword. However, it is better for ad purchasers that are looking to expand the visibility of content such as videos and articles, rather than pure sellers who are driving traffic to landing pages. Many publishers use this to increase engagement and view time of their own content, while others use it monetize their traffic by displaying other publisher’s content. This is a very relevant and interesting way to compare the methods and techniques learned in this class about the strength and weakness of ties, which applies just as equally to the relevance between certain news stories and other relevant content.


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October 2015