Influence Measurement Optimization™

There’s lot’s of discussion – pro and con – about trying to measure influence, particularly in social media. The ability to accurately capture, analyze and rank influence is extraordinarily valuable. The key word is “accurately.” HiRes

There are many vendors (Klout, Peerindex, et al) trying to figure this out. Recently Klout came up with a +K button, an interesting invention. It’s like a more focused #ff (Follow Friday), for those familiar with it.  But it got me to thinking about the nature of influence in general and where this could be leading. I’ve discussed influence in marketing before (see Dark Matter and Invisible Thought Leaders) but I feel like we are moving towards a new era in “influence awareness.”

Heisenberg Social Media Uncertainty Principle

Sean McGinnis’ recent post The Problem With Klout discussed some of the challenges with one influence measurement vendor: Klout. He writes:

The minute you pay attention to your Klout score is the instant your Klout score stops being accurate.

I got flashbacks to physics and the Heisenberg Uncertainty Principle. But more relevant is the Observer Effect, wherein the mere act of observation makes changes to what it is we are observing. To look at this from a sociological perspective, in his 1976 paper “Assessing the Impact of Planned Social Change” social scientist Donald T. Campbell wrote:

The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.

Arms Race

For years there has been an arms race on the Internet: Search Engines vs. Search Engine Optimization (SEO). The search engines are trying hard to return accurately relevant search results. The SEO practitioners are trying hard to “game” the system, attempting to raise the rankings of particular content. This can be done because search engines have rules and algorithms that can be cracked or inferred.

So where does that leave influence measurement? Well move over SEO. It’s Time For IMO™! Influence Measurement Optimization™.  (Hey, Disney trademarked “Seal Team 6”!)

Maybe I should hang out my shingle?

Be sure to check out Part 2: Influence Measurement Optimization™ 2 – Rise of the Mathematicians

6 Thoughts on “Influence Measurement Optimization™

  1. Nice! Love the analogy between SEO and influence measurement, between the rules committee (Google and Klout) and the players (the rest of us). I’ve been making the exact same comparison.

    My issue with Klout and other who are “measuring” (isn’t calculating a much better word for what Klout is doing?) online influence is that there really isn’t a need for an algorithm to do what they are trying to do. One can easily get a grasp of the influencers within a specific target market just by looking at the raw data – not necessarily so in the case of Google.

    • Hey Sean,
      I think online influence has some low hanging fruit, but there’s some tough areas that represent large gaps. Suppose you tweet a link, I read it and then forward the link to my boss. You’ve influenced me (and by extension, my boss) but there is sketchy digital record of that relationship.

      Can you expand on “easily get a grasp of the influencers” and what you mean by “raw data?”

      Thanks!
      Alan

  2. Pingback: Influence Measurement Optimization™ 2 – Rise of the Mathematicians | The Intelligent Catalyst

  3. Pingback: What You Get When You Follow Me On Twitter » Musings of a Recovering Technologist

  4. This conversation always degrades into noise. You cannot measure it so I don’t know why people keep trying. You can tell who an influencer is, but you cannot apply a number to their “score” as an influencer. I don’t know how you can look at the raw data and grasp anything. You are talking about how words and images impact the human mind, and what the person does with that. It is like trying to measure sentiment. It is just not possible.

    • Thanks, Patrick. I agree. It was written with a bit of tongue-in-cheek. If you read the follow-up, Influence Measurement Optimization™ 2 – Rise of the Mathematicians, I pretty much say what you said.

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