Exploring Editorial Content Optimization for Websites through a Statistical Ranking of Articles.

This study describes an online content optimization ranking system for editorial teams. Research on online content optimization has either focused on developing serving schemes for large online news and aggregation websites or complex algorithms for user generated content-based websites. An unexplored area in this domain was the development of a content optimization technique for smaller, editorially-focused sites that creates a long-term brand value that inspires visitors to engage with websites. The results of a study on 276 online articles and associated web metrics show that images within an article, the number of times visitors viewed an article and if they reached the article through a search engine were significant positive predictors of the time they spent with articles. However, the percentage of single-page visits to an article and the number of times visitors clicked a link outside of an article were significant negative predictors for the time they spent with articles. These factors were utilized to develop a statistical rank for content optimization, which shows some initial promising results.