“…Influence is defined as ‘implicit or explicit effect of one thing (or person) on another,’ which online can be further simplified to ‘can someone’s words (and/or video) make you think or do something?’…
It becomes easier to understand influence when it’s broken down into its core components: Brand, Expertise and Trust. While there is much debate around online branding, it is clear that personal branding is important to online influence…
Personal brand is truly an aggregated representation of online activity. Can you build a personal brand by interacting on only one social service? Sort of, but it’s incomplete. It’s impossible to gain a true picture of who you are simply by looking at your photos on Flickr, or just reading your blog. Trust grows by being able to view a person’s social content in aggregate. This is why life streaming applications like FriendFeed have grown so rapidly.
In terms of measuring online influence, the stronger the personal brand, the more influence one wields online. The most important component of online influence is trust. Trust is defined as creating a consistent expectation that a person will always act in your best interest when given information.
Expertise is another core component of influence. One can gain knowledge on a specific topic, but expertise is a title that can only be given…
How does one get the title of expert? In the simplest terms, other people trust the knowledge you have accumulated. It’s why self-proclaimed expertise is not respected.
Personal Brand, Trust and Expertise. Understanding each is imperative to measuring influence, which can be expressed as:
Influence = (Personal Brand * Trust * Expertise)
Of course, since Expertise = (Knowledge * Trust), we can further refine the equation to:
Influence = (Personal Brand * Knowledge * Trust2)
Which shows the increased importance of trust. You could refine it more and extract trust from Personal Brand, but that begins to complicate things…
Now that we have defined Influence mathematically, how do we measure it? Well, it is difficult to apply direct numerical measures to each component, but here is a starting point:
Incoming Traffic - Pageviews, Incoming traffic from search engines, rss subscribers
Incoming Links - Primarily manual links such as blogrolls, in-post deep links
Reader Engagement - Internal searches, time on site
Recommendations - Retweets, share stats
Connections - Number of mutual connections, number of mutual connections on multiple sites
Track Record - Age of domain, number of blog posts, length of engagement
Engagement - How often and long a person has engaged with a service online…”