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  • July 19, 2019

Unmetric Launches Outlier Detection for Branded Social Content

Unmetric, providers of branded content analysis and discovery solutions, has introduced outlier detection capabilities that enable digital marketers to identify and mine insights from social content that generates significantly higher than average audience interactions across Facebook, Instagram and Twitter. The new Outliers feature is available to all users of Unmetric Analyze.

"Marketers today are data-rich but insight poor, and social media plays a significant part in the ongoing data deluge," said Lux Narayan, CEO of Unmetric, in a statement. "Unmetric's mission has always been to help brands cut through the noise in the battle for mind share and get straight to the insights that matter most about their competitors' content. The outliers feature refines this further by taking that universe of social posts from competing brands and spotlighting the most attention-worthy content in its own visual feed that's easy to follow and react to."

Unmetric Analyze already allows marketers to select visual streams of content from some competitors. The outliers feature eliminates the need to manually sort or monitor content based on engagement by automatically detecting variances in publishing cadence or surges in audience interactions that fall outside norms (likes, comments, shares, retweets) or proportion of metrics to each other. Unmetric identifies outliers using a proprietary algorithm based on content published over the past 12 weeks.

Key Outliers insights include the following:

  • Post or Tweet Storm: Flags posting multiple times to Facebook, Instagram, or Twitter in a short period of time.
  • Post or Tweet Surprise: Flags publishing content on Facebook, Instagram, or Twitter after a significant amount of silence.
  • Engagement Surge: Flags content that receives a massive increase in likes, comments, shares, or retweets compared to all posts published in the past 12 weeks.
  • Engagement Proportion: Flags content that receives a disproportionate number of any engagement metric (likes, comments, shares, retweets) compared to any other engagement metric (e.g. a post got 17 times more shares than likes).

Armed with this information, users can do the following:

  • Accelerate content and campaign ideation based on strategies and tactics that drive massive audience interaction;
  • Uncover visual or topical trends per industry vertical that are garnering significant engagement compared to normal; and;
  • Detect and investigate a possible unfolding social media crisis through outliers such as a comment surge.

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