![](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjZUEiF803qnR3NltQiYqJ-WNlqHwPB_9YtaVYb_M-qWGYsXg-O3JYoq6stoOGfNO8JxKrH5le8E_cMbadEjRvfA99WLQ8RJqFVrmDwe8zrTDfXM7tWHgy3-mvFRZPrJR79ayUULzmesT8/s320/frombloggertoinfluencer.jpg)
With that in mind, my job is to find these people and clearly demonstrate their value to brand X. Klout is a great tool for this, and one that I have used a lot; but there were strong limits to what it could report, especially because it was pulling data from Twitter and Facebook exclusively. Just yesterday, however, they released a tool to measure social influence by topic - they call it +K.
According to the most recent articles I have read, topics are created by an algorithm, but the plan is for users to create topics on their own. Users get five +K's every day they can give to any user on any topic. As this data continues to grow, the ability to find the right "Influencer" on the right topic will become easier and easier. This was a fantastic move on Klout's part because it will put the controls in the hands of the users, and combine that data from what Klout is already pulling.
There is still the other major piece that isn't being combined with social media stats, and that's the stats of Influencer X's blog or site. Aside from Pageviews or Monthly Unique visitors, what else should be pulled to determine an influencer? Average number of comments per post? Average number of shares? Video views? Clicks from exposed links? This is obviously a serious work-in-progress. A concept that will need to be re-tooled many times over until it offers a seamless approach to this process. My goal is to find a way to combine all streams of data into one place, aggregate it, and end end up with the right result. Time will tell.
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