Measuring Influence: Klout’s Got its Work Kut out.
In case you do not know Klout, they are a company trying to measure influence on the web. However, I do not think that is really possible. At least yet.
What got me thinking about writing this was that for the second time in as many weeks, my man Kehers (Ope) influenced my downloading an app. He tweeted this below and I went to download the app. The previous one was an Android game called Mayhem.
Loving the new hotot interface twitter.com/kehers/status/…
— Opeyemi Obembe (@kehers) September 13, 2012
Now how on earth is Klout to know that Ope influenced my decision when Ope himself had no idea (well, now he does :P).
Direct Influence is rather really complicated because it depends on so many factors many of which are very subtle (proximity, timing, mood etc) . Most times, only the influenced will know about what influenced him or her.
Indirect influence is more on the subconscious level and that is where the manipulation of advertising comes into play. At that level, even the influenced will have no idea about it. So how does Klout expect to know what even I do not know what influence my action?
Not to confuse referral with influence, I take influence as a subset of referral. Referral is more like “how did you get here?”, Influence is more like “why did you get here? or, choose this?”. Google for instance is by far the most important referrer on the web. Facebook, Pinterest, Twitter are important referrers too.
As for influence, that is still down to humans. It is known that the reviews on Amazon influence purchases but whose review influenced which buyer? And why?
That’s a really tough one.
Anyone that can crack it would open a Diamond mine. I doubt that Klout and its peer, PeerIndex (great pun huh?) can, especially with the approach I am seeing. Influence much more than measuring likes, retweets and comments.