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Twitter Analytics

Ryan keeps statistics from his various Twitter posts. Documents are created via Google Drive and data is downloaded directly off of the Twitter analytics page. This data includes amount of retweets, likes, url link clicks, and other forms of engagement that each tweet receives. Here is an example of his past worksheet. This snippet categorizes the 4 most engaged tweets...

This is arguably the biggest asset to Ryan's presence on social media. What Ryan finds here, helps guide him for future posts. By analyzing the facts, Ryan has been able to develop a trend with his posts that can help maximize his engagement.

 

By reading two posts that analyze these numbers (here and here) one will notice that Ryan changed his strategy from sarcasm and comedy, to directly saying what his linked blog posts talk about. He also saw a difference timing made. At first, Ryan put out his tweets around 3-4 P.M. Ryan decided to change that up to post early in the morning (7-8 A.M.) and later at night (7-8 P.M.) in hopes of getting more interaction. That turned out to be a negative influence on his numbers. Thus spawning the set posts at his original timing.

Take a look at Ryan's recent Twitter Analytics

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