I wrapped my brain around this question and after noodling it for some time I’ve come to believe you can take most paid tools out there and throw them into 3 essential categories:

1. Basic adhoc tools: These tools are quick and simple. The output is predictable almost to a default; what you put in controls ( and in someways limits) what you get out. These tools rely on very specific searches and the best types of these tools are Boolean based.

Pros: Cheap, quick and nimble, any one can use it, web-based (no installation)
Cons: Difficult to drill down, no data warehouse capabilities, limited data display options ( charts, graphs, etc), poor sentiment, limited historical data, user must know what to search for, lots of spam results

2. Database/ CRM Tools: These tools are for your number crunchers; they integrate easily with an external database ( sometimes yours/ sometimes the tool’s). Usually they also allow you to append additional data to you  searches, like web traffic. These tools are fundamental for a long-term social data storage and provide a central data source to query using internal systems.

Pros: Strong analysis capabilities, integration with internal databases, more robust data
Con: Expensive, high learning curve to adoption, must be embraced by non-social teams, poor sentiment, user must know what to search for, lots of spam results

3. Text Analytics/ Ontological tools: These tools answer the magical questions “What are people saying about my brand that I don’t know about.” Instead of being key word based ( like 1 & 2) these tools are either algorithmically [stats] or  ontologically [natural language] based. Rather than filtering content in or out, like a keyword tool does, they group content into hot topic sections. Essentially they find your everyday topics as well as topics you didn’t even know to look for. They are also great for answering ” what topics are people talking about most?”, ” what are unforeseen potential issues”, “how do people group our products together in discussion?”

Pros: Strong analysis capabilities, unearths hidden hot topics, auto generates categories, superb sentiment results, less spam content
Con: Expensive, high learning curve to adoption, must be embraced by non-social teams, not a solely social media tool & is best deployed in conjunction with other customer facing channels ( service, emails, etc), long  set up process, does not provided base level brand metrics, analysis in not immediate, not a long term data storage solution

In a perfect measurement world a company would have tool from each category type. But, for most companies that isn’t an option. The bigger questions becomes, which of these three type of tools does your company really need? [Read: Which of these tools can I persuade finance to give me budget for]. I wish there was an easy way to preemptively know which you need and which you don’t. There’s not.   Excellence in Social Media measurement like many things in the Social Media space is, well, difficult.

Way back when(March 2009) , Mashable gave us this theoretical equation: Influence = (Personal Brand * Knowledge * Trust2).

While it’s a good thinking theoretically, practically- it’s stupid. Trust makes a massive part of this equation and  is generally immeasurable. You can “approximate” trust through other metrics, but then are you really measuring trust or something else such as mass appeal or return visits? I visit Perez Hilton’s site often, but it’s definitely not because I trust him.  Just like Mr. Perez, quasi-related metrics are ALWAYS biased.   Plus most of the metrics proposed in this article are more measurements of a brand value than anything else. Likely because trust and knowledge are nearly impossible to measure since they are entirely relative. This is a theoretical equation, but not one that actually works in practice. It’s excellent example of the biggest flaw in the space currently- too much thinking in ideals, too little thinking about how to make  practical  application feasible. I could argue this further, but that’s NOT the point of this post.

The point is, people are confused. They’re baffled by how they match up everything. They know that in a world of millions of messages they have to pick and choose who they respond to- simply because it’s impossible to address every piece of online content.  Thus was born the term “ influencers” which became a proxy for pretty much every possible engagement population in social media. “Make sure we alert influencers of our campaign. Take care to address influencers needs.  What are influencers saying about our brand?” The list goes one and one with one common theme, the word “influencers”. Barf. Double barf.

Here’s the thing,  when you see some one’s social media profile and activity where available; you’re missing one thing. Context. All you can see is who they are online and whom they digitally interact with on a single social site. The full picture of online social activity is not currently measurable. That activity on one site is  a very small part of the picture. I am sure many of us have singel site relationships that are further supported by other online & even offline  engagement.  For example,  say I have a friend Alice, who I see quite often. We may share messages occasionally online, but it’s far less then I share online with other people. However, I would consider Alice one of my best friends even though it may not be discernible on open access social sites ( twitter, blogs, etc). However,  I am pretty certain if I ever needed some one to go to bat for me, Alice would be there regardless of how strong our “public” online relationship is.

Now lets pretend I am a nobody on social media (that’s not hard to pretend -I kind of am ) and Alice is a uber elite social media guru. And to drive this story forward let’s say I am refused service at McDonald’s because I want to order a happy meal & I am not a child. Remember this is all hypothetical. If I get pissed off and write a blog post on my experience and & it’s valid issue, Alice might go to bat for me and spread the message. So while up until this point  I am not measurably “influential”- all the sudden, without warning, the story spreads.  Why? Because there was no way to predict digitally I was connected to Alice or further more that she would go to bat for me.  Proof that, in general, online conversation is not predictable (yet).

So here’s my take on influencers. The concept is a load of rubbish- at least in the way people currently think about it. I think the term generally leads us to black and white perceptions of customers and friends and so forth. You’re either  and influencer and valuable to my [insert marketing terminology such as campaign, brand awareness, promotion] or you’re not. And lets be honest the world (and the internet) is rarely black and white. Instead I think the question we should be asking  instead of “how do I isolate influencers?” is  “how do we monitor what conversations matter & which are just noise? “

My thoughts:

1. Know your community

Learn who the biggest voices are in your target areas. Explore the landscape and understand the strengths and weaknesses in how conversations travel within your niche. Don’t just learn about it, be an expert.

2. Keep your ear to the ground

Simple street smarts-watch your back. It’s not a novel concept, but one many companies large and small forget to do it. Who can blame them? It’s easy to get caught up in reporting  and forget that one of listening’s biggest strengths is the ability to spot a storm before it forms.

3. Adapt, grow, & learn the hard way

Brands are going to make mistakes, and the first reaction is always going to be to freak out, As result, especially after a crisis, companies try to monitor every single brand mention. That’s not sustainable. The fact is, and I say this all the time, monitoring has and element of trial and error to it. The idea is to focus on growth and admit up front that there will bumps along the way. Key phrase here- you marketers will love this- hockey stick approach.

I’ll be the first to admit that there is more to this story than is in this blog post. The space, in general, is not evolved.   And yes, there is that tricky feat of operationalizing this thinking to work for thousands, perhaps millions of conversations. I’ve got some good ideas on how to do this, but I’m keeping my mouth shut. Let’s call it “competitive advantage”.

Watch this video. Ignore everything except the equations and how they progress. Yes, some of the metrics are complete nonsense. Yes, subscribers are just like followers. Yes, the video transition effects were nifty. I am asking you look past all of this.  Focus solely on the thought progression to the final equation.

You likely didn’t take notes while you watched that, did you?  If you didn’t, you missed all the messy bits. But, have no fear, because I am going to take you though the proposed equation step by step so you can see it for what it is- (mess x epicfail)/lack-o-judgment.

First, the host introduced you to three major metric categories (volume, engagement, & conversions). Under those three categories she listed several proposed metrics. Do you remember this? Or were you to focused on the super hero t-shirt? I know; it was a great t-shirt.

Now to make following the progression of this proposed equation easier, I broke each of those metrics into two groups. For example, I split the proposed Volume metrics into those that represent Reach & those that show Frequency. For Engagement I parsed the metrics into Time and Content engagement types. Lastly, I broke the metrics mentioned in the Conversion category into Responses & Revenue related metrics.  If you’re reading all this and are confused, the picture below should clear everything up.

In the next section the presenter outlined how you should divide these metrics, regardless of which category they were in within the previous section, into two groups: Hot & Cold metrics. Try to ignore that these groups make about as much sense as splitting the metrics by what which letter of the alphabet they start with. I know it’s hard, but just try.

The metrics the video host allocated to the Cold side are those that fall into the standard media buyers equation (reach x frequency) / timespent.  Additionally, revenue & responses are also fall under  Cold metrics. NOTE: it is not specified where in the equation these metrics belong, just that they belong there. Somewhere. The Warm side contains “harder to measure” Content Engagement metrics such as Sentiment & Ecosystem.  See below for the picture-fun version.

Now does anyone see some major possible issues yet? You should. If not, I am more than happy to point them out.

1. The actual metrics in the previous sections are replaced with less specific category titles. This begs the question why were those category groups originally defined? 
2. Responses & Revenue aren’t included in the Cold metrics equation & seem to be mentioned as an after thought?
3. Many of the data rich metrics in Content category of Engagement  are completely ignored, instead favoring to rely solely on Sentiment analysis
4. The host has introduced a new metric to the equation which was not included in the previous metric categorization: Ecosystem

So after all few more sultry glances and mirage of smoke, mirrors, and excessive metric organization, the video host presented the final equation:

You’ll likely note I added a little color to the above graphic. Here’s why. The yellow represents those metrics the host mentioned previously in each part of the discussion leading up to the grand reveal of the master equation. The plum section signifies metrics that were introduced in the second part of equation definition. Those red highlights those metrics which may have been alluded to, but were not brought out specifically during the previous discussions.

So now let’s play point out the possible problem points again (it’s a fun game isn’t it?).

1.  What are the Page Views & Visits in the Social Media world? Up until this point we have not see anything in this video that mentions these metrics or what defines what metrics would represent them.
2. Where did Frequency & Reach go? Are they supposed to be represented by Page Views & Visits? Are those two things really the same thing in social media measurement?
3. Why did the equation change from Timespent being in the denominator of the Cold metrics portion of the equation, to being an additive?
4. Why are Responses and Revenue removed, especially since they’re the only metrics which track possible financial return?
5. What exactly is the resulting metric meauring?

Now let’s combine everything together into a pretty picture. It’s a beautiful disaster.