Why Related Content Doesn’t Always Engage Readers
Here at TrendMD, we think the world of academia is brainwashed by relatedness (think of PubMed-related links). Scholarly recommendations have often been presented as ‘related links’ and have provided just that by relying primarily upon contextual relevancy. At TrendMD, we strive to find the most interesting content for each and every person through personalized recommendations that are interesting to that person but not necessarily related to what they were just reading.
TrendMD’s Data-Driven Insights on Content Recommendations
Recently, we dug into our data to see how this notion of ‘Most related ≠ Most interesting’ plays out in numbers:
We grouped the content in our index into 7 categories (eHealth, cardiology, nephrology, surgery, emergency medicine, internal medicine, endocrinology) and compared the average click-through rate on related content recommendations (from the same category as the current article) vs. unrelated content recommendations (from a different category from the current article).
We found that unrelated content recommendations generated a 24% higher CTR on average!
Enhancing Reader Engagement with Personalized Recommendations
With more and more data like this, perhaps the ‘relatedness brainwash’ will start to wear off, and it will become more apparent that the best way to engage audiences deeply is to tailor recommendations to each individual person.
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