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Unmetric Adds Facebook Reach and Impressions Data to Social Media Analytics Product
  • USA - English


News provided by

Indicate Media

Aug 02, 2016, 08:00 ET

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New York, NY (PRWEB) August 02, 2016 -- Unmetric, the leading brand-focused social media intelligence platform, today announced it added Facebook post reach (number of people who saw a post) and impressions (number of times a post is displayed) data to its Analyze product. Analyze for social media analysts is one of three core Unmetric products alongside Discover for brand content creators and Track for marketers.

Even with so much available data, reach metrics were one of the top two features our brand and agency clients requested, second only to the ability to detect competitors’ promoted posts, which we introduced earlier this year.

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This new feature is significant as Facebook currently only provides brands with reach and impressions data for pages the brand controls, which makes it a challenge for social media analysts to benchmark against competitors with these metrics. Unmetric Analyze now allows brands to view the estimated Facebook post reach and impressions of more than 55,000 brands. While social media engagement (likes, comments, shares) are important, these interactions highlight only a fraction of the people who actually see a post, which creates an incomplete picture of how purchasing decisions are really made.

“While reach and impression data could be viewed as a throwback to traditional mass media advertising, it’s often the first metric social media analysts bring up because it’s easy for everyone to understand the number of people who saw your content,” said Lux Narayan, CEO of Unmetric. “Even with so much available data, reach metrics were one of the top two features our brand and agency clients requested, second only to the ability to detect competitors’ promoted posts, which we introduced earlier this year.”

Based on Unmetric’s analysis, the 100 brands with the greatest reach on Facebook garner around 10 million unique views and 17 million impressions per day. Unmetric uses machine learning algorithms to estimate a brand’s Facebook post reach and impressions based on a number of factors including audience size, the time of day the content was posted, and the number and type of audience interactions (e.g. Shares affect reach more than Likes).

“To date, estimating reach and impressions has been a challenge due to the lack of data to build and apply a model. Existing solutions simply measure this based solely on the absolute number of audience interactions a post receives and number of followers for the brand page,” said Aswani Yeraguntla, Director, Predictive and Business Analytics for Unmetric. “However, this simplistic and grossly exaggerated method doesn’t account for differences based on audience size, sector or industry. Our approach addresses these issues and captures complex patterns in audience interactions and provides the most accurate estimate of reach and impressions.”

Unmetric Analyze clients can immediately gain access to reach and impressions data, which will automatically be displayed next to the engagement metrics of any brand Facebook post. For further details and to request a demo, visit https://unmetric.com/analyze/.

About Unmetric
Unmetric, the leading brand-focused social media intelligence platform focused on brands, helps digital marketers, social media analysts, and content creators harness social signals to track and analyze competitive content and campaigns, and to create better content and campaigns of their own. Unmetric is trusted by hundreds of global brands and digital agencies for real-time insights from the owned channels of over 55,000 brands across more than 30 sectors on all the major social networks including Twitter, Facebook, Pinterest, YouTube, Linkedin, and Instagram. The company was founded in 2011 and is headquartered in New York City with offices in Chennai, India and the U.S. For more information, visit http://www.unmetric.com.

Peter Moran, Indicate Media, +1 (347) 880-2895, [email protected]

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