“Content discovery” refers to a rapidly-growing space in the world of digital media that involves the use of predictive algorithms to help people discover content they may like but never knew existed.
Social media platforms often have discovery-based features integrated into their sites, such as Facebook’s News Feed or YouTube’s “Recommended for You” section. Discovery platforms like TrendMD are built around a predictive engine that all kinds of publishers can integrate into their site, surfacing targeted recommendations for their readers.
Content recommendations are offered in a variety of ways on publisher websites and apps. Recommended stories can be placed within content streams/feeds on a publisher’s homepage or along the right side of an article. The most impactful placement often immediately follows the end of an article, though recommendations can also appear mid-article (especially on mobile).
These types of promoted recommendations are less intrusive than traditional online banner ads, and the best examples create real value for consumers by providing them with relevant and informative content. Story-driven content also enables marketers to create a stronger emotional connection with their target audiences in a way that direct advertisements cannot.
Content discovery can drive results for marketers across industries and in service of many different metrics or goals. While banners ads may only have been effective for high-level brand awareness, content can engage consumers at all stages of the “consideration journey”, driving a variety of goals, such as lead generation, email subscriptions, purchases, and more.
TrendMD is the world’s leading discovery platform, delivering over 1 billion recommendations to over 100 million unique users each month on 4,500 websites from over 300 scholarly publishers. As a content discovery platform, TrendMD surfaces promoted content alongside editorial content at a critical moment, when readers are steeped in “content consumption” mode. This moment is when readers are most open to discovering something new.
Despite our name, TrendMD is a content recommender system currently used across all academic disciplines.
Once our widget is installed, we begin distributing links to scholarly content from your journals and blogs in the widget results of our relevant partner sites. We send a large amount of new unique visitors from many of the largest publishers to come discover, read, and cite your articles. TrendMD looks beyond just related links to help people discover, read, and cite interesting scholarly content from your journals and websites through personalized recommendations. Our recommendation algorithms continuously optimize the placements of links to your content for the right audience while readers are actively looking for something interesting to discover.
TrendMD powers a recommendation widget, which is free for content providers (such as publishers) to install on their website(s). This widget generates recommendations for readers based on their reading habits, allowing for content providers to increase the discoverability of their content. Clicking on the link might take the reader to another article within the same publishers' website(s) - or to a third-party website owned by a different publisher altogether.
Each click on a link that directs a reader outside the host publishers’ website(s) earns the host publisher a new visitor back to their site in return.
TrendMD is the leading scholarly content discovery platform dedicated exclusively to the distribution of high-quality content across disciplines. With TrendMD, links to your content appear as recommendations on the web's largest scholarly content publishers and premium publisher sites.
We help publishers grow their readership and increase pageviews per reader.
TrendMD optimizes for engagement. The more interesting your content and the more traffic you drive, the more you will be recommended throughout our network. We use a complex set of algorithms to find the most interesting and relevant links for each individual reader on every page. TrendMD algorithms serve what readers want to read when they want to read it.
