How does Shareaholic decide what to recommend?

A healthy mix of data inputs & data science drives Recommendations -- we tap into sharing, aggregate viewing habits, influence, intent, social profiles, topics of interest (based on proprietary NLP, semantic, etc analysis of content), etc to deliver the best recommended content that has proven to increase pageviews and engagement for websites at scale.

We don't just pay attention to what readers click on; we aim to ensure they love every page they find. What this means for you is more engaged readers that stick around longer and discover more of your great content.

Have more questions? Submit a request

Comments

Article is closed for comments.