In an age when everyone with a keyboard can be an influencer and the media continues to fragment like the Long Tail, it’s difficult for marketers to determine how and where to spend their marketing communications budget.
In our third post on the Waggener Edstrom Worldwide (WE) Influence Toolkit, we outline our methodology behind an increasingly popular software tool called Influence Ranking. Influence Ranking was created by our R&D superstars Samara Omundson and Emily Wheeler (bloggers behind Contrarian Librarian). The ranking algorithm is intended to rate and rank influential content creators and influence at the media outlet level.
The primary benefit of Influence Ranking is a rank order of influencers across media types — both traditional and social media — that highlights media “stars” who demonstrate consistent, sustained influence in a particular category.
While there are other influence authority measures (Technorati, Radian6, Sysomos), we consider these automated tools to be somewhat “lite” in their metrics. Why? Because most tools available usually only consider reach, or popularity, to be the key indicator of influence. WE’s Influence Ranking methodology crosses media platforms and accounts for nearly 30 discrete measures of influence that go beyond mere reach and popularity metrics.
There are currently five buckets of influence metrics in our algorithm:
- Buzz. Measures of sharing behaviors. Examples might include inbound links, popularity measures such as Digg or Reddit, social bookmarking presence, or retweets.
- Reach. Traditional PR measure of direct readership. Examples might be circulation, unique visitors, Facebook Friends or Twitter followers.
- Engagement. Measures of reader interaction with content. Comments and number of @replies are a good example of engagement.
- Content. Measures related to the relevance of content. Includes the frequency and depth of coverage of a client’s brand or industry.
- Audiences. Measures of the audiences reached or targeted. Preferably based on primary or demographic research, but this could also be extrapolated from reviewing the content.
Example of an influence ranking: