Unmetric integrates Promoted Post Detection with Analyze
Unmetric, providers of a social media intelligence platform, has integrated its Promoted Post Detection feature to its Analyze product.
Unmetric's Promoted Post Detection uses machine learning algorithms to identify and sort paid and organic Facebook posts with up to 95 percent accuracy. It also provides insights that help social media analysts compare internal paid and organic content, as well as benchmark performance against competitors.
Previously, Promoted Post Detection was available only for clients as a separate add-on feature and only tracked a limited number of brands. Now, social media analysts using Unmetric Analyze can see what posts are promoted and organic for more than 40,000 brands across multiple industries. Paid posts will be tagged as promoted and organic ones tagged as organic. Because the Promoted Post Detection feature needs five days of engagement data to make a prediction, posts not yet five days old will be flagged as new. Each tag will include a probability value, an indication of how confident Unmetric is about the prediction. Users can set threshold values (instead of the default 50 percent) to identify promoted posts.
"Since launching Promoted Post Detection last year, we've fine-tuned the detection algorithms, and with the improved model and larger available data set, we're able to provide probability values along with predictions," said Aswani Yeraguntla, director of predictive and business analytics at Unmetric, in a statement. "These updates provide our clients with additional tips and insights into the paid strategies of thousands of brands and have made it simple for social media analysts to automatically generate and download their own reports on demand, saving additional time and resources."
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