Whether you've paid attention or not, content recommendation has taken ahold of many popular websites today.
From information publishers to ecommerce websites, many industries are taking advantage of the opportunities that content recommendation provides them, and consumers are loving it. For businesses, content recommendations are another way to keep customers on your website for longer as well as a bonus way to display your products. For customers, recommendations provide multiple advantages including seeing more items that might be of interest to them as well as seeing items they might not have known existed.
Here are examples of content recommendations from around the Web spanning different industries:
When reading the article, "Meet the Brothers Behind the Web's Most Controversial Social Network," Time offers recommendations on the right side of the page. The recommendations on Time's website are based off contextual relevance (in other words the article the user is currently viewing).
After selecting the article, "Uruguay's Suarez gets nine-match ban for biting", viewers are shown a variety of recommended articles that are contextually relevant to the Suarez article. After selecting multiple aritcles on the site, all recommendations seem to depend on the article the viewer is currently on with no recommendations based on previously viewed articles.
Sports Authority's website is unique in that it contiains two types of content recommendation. when a customer is on a products landing page and scrolls down there is a section that display items related to the item they are currently viewing. Every time the user selects an item and views its designated landing page Sports Authority logs the action. Whenever the user returns to Sports Authority's homepage, he or she will find a section labeled "Recommended for You" which is based off of their previous actions on the site.
TigerDirect is another unique case. Their company website has two different section located one on top of the other for product suggestion. The first section is labelled "People Who Viewed This Item Also Viewed" and the second is labelled "People With Similar Interests Also Viewed".
Twitter's recommendations are a little different. Under the "Who to follow" section users will see a short list of people based off the people of businesses that the user follow. For instance, if a user follows the NFL then they may see a recommendation for Roger Goodell (the commissioner). Another way Twitter makes recommendations is by listing people and businesses that are followed by those that the user follows.
Amazon's content recommendation style is similar to that of Sports Authority's. First, Amazon uses contextual relevance when users are on a products designated landing page and recommend other products that are similar to the one they are viewing. Amazon also makes recommendations on their homepage based on products that users have viewed in the past.
Macy's delivers recommendations to users using contextual relevance. Whatever item the user is viewing Macy's will display similar items at the bottom of the page.
A few companies that offer content recommendation platforms are Sailthru, Taboola and Outbrain, AddThis, RichRelevance and more.