I was disappointed to not be able to join Keith, Jason and Olivier on the first two Measure “Mobcasts” – those darn international flights sure do get in the way! However, that doesn’t mean I won’t take the opportunity to put in my $0.22. (It would be my $0.02, but I was in Australia, and their dollar is worth more, so I figure I’ve got the exchange rate working for me.)
I wanted to add what are just a few (minor) “parting thoughts” after having an opportunity to hear the guys so deftly discuss their opinions on measuring social media influence. So here are mine …
1. Measuring Social Media “Influence” is Necessary
The reality is, while companies (and even individuals) would love to have an opportunity to engage with every voice that reaches out to them via social media, that kind of engagement isn’t necessarily scalable or realistic, and even if it was, there would still be a need to prioritize the order in which a company reaches out to people.
While that doesn’t mean, to Jason’s point, that anyone should be ignored because their Twitalyzer scores aren’t high enough, some kind of measure of where to start is realistically necessary, especially for companies with a large number of social interactions.
2. Social Media Influence Measurement Isn’t Perfect
I feel like part of where we get hung up is in thinking that if a measure isn’t perfect, it’s not useful. I agree with the guys that a measure of “influence” should be considered in context of other data, and I also agree that it’s probably more realistic to call it “potential influence.” After all, you never know whether someone who is considered to have social media influence is actually going to influence behavior of fans/followers/friends.
As we love to say in the analytics industry – you can’t manage what you don’t measure. However, the unfortunate reality is that you can’t measure everything that you would like to manage. (And our attempts to do so often end with “KPI” Dashboards that show fifty metrics instead of the one thing that executives want, because that measure isn’t truly possible at this stage.)
How could we measure true influence? Maybe: Person A engages with Person B, or shares a positive experience with everyone. Person B then goes, “Huh – I hadn’t thought of going to Restaurant X for dinner” and heads on over. Well, sadly we don’t have that insight. (Yet, or maybe ever.)
So what do we have? We have measures that look at, in the example of Twitter, how many contacts someone has, how often their tweets are shared or responded to, as a proxy for influence. Does that mean that the person following will “monkey see monkey do?” No. Is the measure perfect? No. Is the measure useless? No. Understood for what it is, it can be helpful. Blown out of proportion, of course it’s not. However, I know one thing – digital measurement is a constantly evolving industry. We will get better at this. But that doesn’t mean that we can’t do something with our “first draft”.