Ad blindness, also called banner blindness, is the phenomenon of web visitors not seeing colorful banner-like information posted on a web page. This poses a big issue for advertisers, affiliate marketers and bloggers who want eyeballs and clicks going to AdWords ads, affiliate product links, sales pages, and call-to-action buttons.

Indeed, the issue is so big that many such publishers have moved to a different and more native form of advertising, which is content marketing through content-based recommendation engines. Taking advantage of these different search engines, many publishers produce high quality online content and use that as a major marketing channel.

What is a content-based recommendation engine?

At its most basic level, a content-based recommendation engine is an algorithm-based search engine that presents related content based on visitor browsing history, demographics, personal preferences, currently viewed content, etc. The relatedness of that content might be determined by matching keywords or keyword phrases, user votes, shares or recommendations, or paid placement by advertisers.

Thus, the content-based recommendation engine functions somewhat like Google AdWords or Facebook Ads, enticing visitors to click on and learn more about a related person, place or thing on a third party or advertiser site. The recommendation is often presented with the wording, “If you like X, you may also like Y.” Alternately, a recommended item might be presented as such: “Viewers who bought X also bought Y.” Amazon and Netflix are just two online retailers that make good use of recommendation engines to encourage the purchasing or viewing of related products.

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There are several advantages to content-based recommendation engines that are not evidenced in classic search engine marketing (SEM). To begin with, recommended content is typically not enclosed in a colorful banner or box ad, and thus is less likely to be ignored. For example, shown below is a content recommendation ad format that you may not have even suspected was an ad:

recommended content


Because recommended content doesn’t take the form of traditional advertising, it often blends into the web page background in the guise of native advertising.

Another major advantage of content recommendation engines is that they integrate quite well with today’s increasingly mobile device-focused environment. Whereas a desktop/laptop computer user might easily open up additional tabs to search on and view related content, the mobile device user is typically stuck navigating the Web one page at a time. A content-based recommendation engine, therefore, can easily feed into that user’s desire to click on and view related content.

Available content-based recommendation engines

There are many different forms of content-based recommendation engines. The first few are paid engines and work much like the Google AdWords platform.


This “content amplification” engine owns virtual real estate on CNN, Slate, ESPN, etc. websites and offers marketers and publishers the chance to display their content via these networks on a pay-per-click (PPC) basis. Just like with AdWords or Facebook Ads, you can set a maximum daily budget for clicks. Unlike AdWords or Facebook Ads, however, the content must be of informational or entertainment value, and not pure advertising.




This “content discovery platform” is another major player in content recommendation and owns virtual real estate on Time, TMZ, Fox Sports and USA Today publishing sites, among others. Content recommendations via Taboola appear in the form of “Related Content” or, on occasion, “Sponsored Content.” As with Outbrain, publishers are charged for this native advertising using a PPC format.


There are also the recommendation engines ContextlyGravityYARPP and the recently launched Yahoo! Recommends, most of which operate through a PPC portal. However, what if you’d rather not pay for such native advertising because you already have your own audience and just want extra page views?

To this end, you can install content recommendation widgets on your website and use them instead. Of course, this means that your audience will see your content recommended only on your own website, not national news sites like Time or Hearst. Even so, such widgets do help bring more eyeballs to your other web pages. The best ones currently out there include the following:


The Cross-Promotion Content Recommendations by Engageya plugin uses Natural Language Processing (NLP) algorithms to semantically match your new and older content. The plugin also profiles site visitors based on their search behavior and delivers personalized recommendations. You can also choose to have the Engageya widget link to related websites containing similar content; when users click on those particular content links, you make money.


Using “patent-pending technology,” this widget continuously analyzes the content on your website and matches it to your articles or blog posts. You can also choose to showcase content from other websites and make money from those clicks.


This widget enables you to place share buttons on your pages and posts, create a related content configuration panel, and perform analytics within your share area to find out who is clicking on your content and referring it to others.

Yet Another Related Posts Plugin

With YARPP, you can showcase related posts and pages below your content and in RSS feeds. You can also display sponsored content and make extra money. The plugin’s analytics help you determine which content is getting the most traffic and the demographics of your audience.

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