Content Recommendation Engines are all the rage today. Anytime you reach the end of an article, chances are you see a widget offering you ‘related articles’ or a ‘you might also like’ suggestion. These suggestions are great when they are done right. They give you different perspectives or a more in depth look at the subjects and keep you engaged.
When Content Recommendations Engines go Wrong
Unfortunately, not every content recommendation engine works the right way. Some engines blindly suggest content to you based on your geography, or something vague that you can’t quite relate to. This is why you may often finish reading an article that you found interesting, only to be suggested ‘related content’ comprising of pieces like ‘how to lose 8 inches in 2 days’ or ‘this mans secret to making $1000 a day at home.’ These recommendations are the kind that give the world of content recommendation engines a bad reputation. They are off putting, they insult your intelligence, they often contain spammy content, and are tacky to look at.
Image: Peter Sweeney / Medium
When online publishers begin to use a good content recommendation engine, the results are apparent. Related content is more customized, they can add dynamic content in their emails that are more personalized, and engagement automatically increases. Yet, investing in a solution like a recommendation engine can be a difficult sell for a marketing team to justify in terms of financial and budget constraints. So what do Online Publishers need to look for in a Content Recommendation Engine to guarantee that it will be worth the investment?
Does it Automate Manual Efforts?
A content recommendation engine should make a publisher’s and a publishing marketers life easier. Recommendation engines offered by companies like Boomtrain are sold as a service, where publishers don’t just get access to a recommendation engine but also to a support team and a solutions engineer who will make note of their current metrics and pain points, and focus on implementing the engine to fix these.
Does it Balance out the effects of Banner Ads and Content?
Banner Ads give online publishers revenue, but nobody likes them. According to Hubspot, “The average person sees more than 1,700 banner ads every month, and is more likely become a Navy SEAL than they are to click on one.” One company that ran sponsored content posts even used a US senator’s picture and damaged her reputation with clickbait titles this way.
Image: NY Daily News
What content recommendation engines do is offer relief to readers from the obtrusive effects of these ads. They let readers know that the publisher isn’t just out to bombard them with clickbait – but have their interests in mind, even if the ads continue to exist. It shows that publishers genuinely value the intelligence and interests of every reader – which is extremely important.
Does it Give Older Content a New Lease of Life?
As an online publisher, chances are your website has a lot of content. Especially when it comes to online news and websites with user generated content, not every piece of content needs to be current and timely. There are times when having older content can make you a genuine authority on a subject.
Using Older Content With the Right Context: Forbes
Say a reader finds a current story about a big trade agreement signed between two countries that had previously closed trade ties with each other. The reader may want to know about this trade related cold war. When did it begin? What set it off? Did it affect any other countries? With the right content recommendation engine, you can suggest articles that answer exactly these questions.
Does it increases time spent on a website for your readers?
The goal of creating content is to create engaged users, not readers who visit your website once, take a cursory glance, get annoyed and leave. That is a bad website experience and publishers needs to focus on increasing the time a reader spends on a website, the number of pages or articles they visit and read, the ads they click on, the comments they leave and a whole lot more.
A longer time spent on a site is an indication of a more enjoyable user experience. In the case of social media, users spend hours in a day on a website. This is an essential measurement for anyone who implements a content recommendation engine as it goes beyond the standard measurements of ‘likes’ ‘shares’ and ‘retweets’ and gives you real, usable information.