Jeremiah Owyang (@jowyang) demonstrated yet again why he is at the top of his game when it comes to social strategy with his post on “Klout for Business: A Useful Metrics but Incomplete View of your Customer” published earlier today. Jeremiah is well known to me, having interviewed me back in the day and, more recently, for having worked with John Lovett and I on our Social Media Measurement Framework over at Web Analytics Demystified. If Jeremiah is not on your “must read” list … shame, shame on you!

As I read his most recent piece on measuring social media I was pleasantly reminded of how much Jeremiah’s thinking has influenced our work here at Twitalyzer. His point that special treatment for select customers isn’t anything new at all, and that relying on a single metric for “influence” is dangerous, is absolutely spot on. If you haven’t already, be sure to give the post a read.

Jeremiah offers up a handful of cautions worth mentioning here since they are relevant to our work on Twitalyzer and the value we believe we provide for the social business:

Don’t alienate mainstream customers to serve “influentials.” The reason we provide such a broad set of metrics in Twitalyzer (link to @Jowyang’s metrics) is that web firmly believe that there is goodness in nearly every social relationship and every customer or prospect. They may not have “Klout” but everyone talking to, with, and about your brand in Twitter is worthy of your attention. With Twitalyzer we help you easily discern the characteristics of those individuals without simply assigning them a single, crappy score.

Consumers will game the system, without a doubt. It’s already happening … so much so that the attention our niche has attracted from major media is increasingly turning to efforts to “cheat” influence scores. Cheaters never win, but they will also never stop trying, and the more cheaters there are, the more suspect easily gamed systems become.

At Twitalyzer we don’t think social media is a game and have removed nearly all of the major incentives individuals have to “cheat” our scoring algorithms. We are transparent, easy to understand, and “cheating us” doesn’t get you airline tickets, into bars, or job interviews … it just highlights that you are willing to cheat to win, which is #fail.

These measures are not representative of real influence. What our system, Klout, PeerIndex, and others measure is activity and behavior in Twitter and other “social media” channels, not “influence.” Sure, we use that word — and we do, although we have a very transparent and very conservative definition of the term — but don’t fool yourself, it doesn’t translate to the real world. Worse, if you try and make that leap, you could end up making a horrible decision.

Take, for instance, the fine folks at Klout’s translation of their measure of influence as a basis for Grammy Awards predictions. By my measure they only got 40% of their predictions correct, which suggests a very poor correlation between “social influence” and “influence over people voting for Grammy awards.” To be fair, I wouldn’t have picked Esperanza Spalding over Justin Bieber either, but the magnitude of the miss on these predictions should give anyone trying to make a decision with ANY single score pause.

Without sentiment the gauge is incomplete. Sentiment is hard as hell, trust me, and we barely scratch the surface with what we are able to do. But I will take this point a step further and argue that “without context the gauge is incomplete.” This is why, again, we provide a diverse set of metrics INCLUDING Klout, PeerIndex, and others, as well as a complete archive of the user’s recent Tweets. Consider the whole individual, including their Tweets, and you get a better picture of who you are dealing with.

This is especially useful if you harbor particular social biases … say, against Nicole Polizzi (aka Snooki aka @sn00ki) as our friend Chase Adams (and others) do.

Relying on a single metric alone is dangerous. Agree. Fully. So much so that I penned a little piece that got a lot of attention a few weeks back. Shel Israel pointed out one danger of this, Jeremiah does another … and the list will keep on coming until businesses wake up and realize the danger of taking Twitter and these “silver bullet” metrics out of context.

Influence is not a gauge of true buying potential. Leave it to the social strategies to tie this back to the one number that makes a difference — revenue. A “high Impact” Twitter user might say nice things about you … but if they don’t drive traffic and revenue, how influential are they really? We have had some amazing folks drive huge volumes of traffic to us … Robert Scoble, Guy Kawasaki, Pete Cashmore, Shel Israel, and yes, even Jeremiah Owyang … but I can assure you, they don’t all drive revenue the same way.

We believe revenue is important, so much so that we have the industry leading integration with Google Analytics (the most popular analytics platform in the world) to help our customers tie Twitter users and Twitalyzer data back to cold, hard cash.

When brands are considering relative influence (Jeremiah’s words) we think you need to be considering the circle you work in. I personally have a lot of love for the web analytics (#measure) community and so spend a lot of time thinking about Twitalyzer’s “Communities” report. The Communities report takes any hashtag and breaks the group of people using that report down into participants, influencers, and contributors while detailing all of their key metrics in our system.

Customers find this useful as an input into their own formulas. Perhaps you would too.

Anyway, I apologize for fawning somewhat over Jeremiah’s post but it seems like every time I turn around someone else is cheering for the “single score” crowd. Like Jeremiah, we at Twitalyzer think this is wrong, dangerous, and disrespectful of Twitter users around the world.

I welcome your comments.