Using our recently released influence algorithm (the post by the way describes our definition of social influence ;-)), we’re able to share some empirical data on a year old question: What’s the distribution of influence within a niche community?
Picking the following two examples, social media marketing (900) and computer security (750) blogs, we observe a pattern that looks a lot like a long tail.
If, rough approximation, we decide that the top 25 blogs form the head, 26-100 the magic middle and 100-last the long tail, the % of the total inbound links within those communities looks like:
Social Media Marketing
The ‘computer security’ community has a shorter head than the ‘social media marketing’ community but, roughly 1/3 of the inbound links are going to the ‘head’ (top 25), 1/3 to the magic middle (75 blogs from 26-100) and 1/3 to the long tail (101-last which is about 700 for computer security and 900 for social media marketing).
What’s the take out from a business standpoint?
Well, if you’re a marketer(s) and you think you should target only about the top25 bloggers in a community and forget about all the others (I hear that a lot, most of the time not even for niche communities, and I’m not the only one), you may :
miss out on a big chunk of the ‘influence dynamic’ going on within a niche community.
go the difficult way : The top influencers receive lots of requests and you’re less likely to be noticed..
forget about the trust factor: Studies have shown that trust is higher with friends/people you know and B-Z bloggers may have a tighter trust relationship with their audience which is smaller.