Follower Count: The New Hit Counter

We live in an age of data, in which statistical analysis has replaced theological discussion in the search for the truth, and where heightened probability is the closest we ever get to absolute reality.  Or it might be, it all depends on what the numbers say.

Evolving Metrics

When I first got involved in SEO, measuring success was easy:  Where did we rank?  If we were number 1, it was good, if our website was at 20, it was bad.  We knew that ranking at number 1 was good because we could see increases in our traffic, and we knew that the traffic was increasing because we had a hit counter:

A Hit Counter: Useful?

Every morning at precisely 9am I would add the current count into a spreadsheet and a “clever” formula would calculate how many visitors had been to the website over the past 24 hours.  This provided me with a fantastic level of insight into how many people were visiting the website, and allowed me to produce graphs.  Like this one:

A Graph: Old School

My boss liked graphs, but to be honest, even though this was better information than the hit counter, it wasn’t much better, because it was essentially the same information.  It was possible to get more information about visitors to the website by looking at log files, but this took a long time, and was incredibly inconvenient.

Thankfully, I discovered AWStat, which looked like this:

AWstat: Graphs + Keywords

AWStat was cool.  It let me know all of the information from my log files in a more easy to read way, and it was accurate.  It wasn’t dynamic, and I couldn’t do much with the data at the time (you can with the newer versions), but it had graphs, which my boss liked, it was free, which my boss liked even more, and more importantly it had keyword level data, which I liked, because it meant I could see what was working and what didn’t.

There were better solutions around, but they had a major disadvantage as far as my boss was concerned.  They cost money, but in 2005, the world changed forever, when Google bought out Urchin, and started to give away a free version called Google Analytics:

Google Analytics: Win!

Google Analytics was (and still is) great.  Sure, you give away a stack of “should be secret” information about your business to Google, which lets them get an idea for how much traffic is worth, and therefore how much they should charge for it, but in return, you get a tool that in the right hands can tell you pretty much anything you want to know about your traffic.

The Social Version

In my last post, I wrote about how you can use custom shortened URLs to improve your tracking of social media traffic, but the sad thing is, that for a lot of social media campaigns, the only metric for success is this:

How do you like this

Or This:

Are you following?

In a lot of ways, and for a lot of social media campaigns, it’s almost like the last ten years never happened.

The follower count is not a valid metric for success of any campaign.  It provides no insight into the type of person following you, how interested they are in your products or information, how relevant their interests are to yours, or what level of engagement they can have with you.  It includes bots, auto followers, and more.

Even a regular analytics solution is not enough, because it only gives you a small percentage of the information about a social media campaign.  And because of this, in a lot of cases, marketers have been sent back to an era where a lot of the data that you needed to manage the activity and calculate ROI needs to be sourced from a number of places, and then collated before it can be properly analysed and understood.

There are plenty of social media monitoring tools available, and plenty of campaign level data that can be captured, but overall success is difficult to measure with currently avaialable solutions, which underlines the need for a well structured and disciplined campaign management system to determine a valid ROI.