Analytics & Metrics Galore Oh My!!

One Million Tweet Map

Lately, I have seen analytics & metrics showing up all over the place & I am sure you have seen them as well: on Twitter streams, WordPress blog sidebars, Tumblr footers.

I like to espouse using the right tool for the right job. If the tool is not right for the activity at hand, find the one that is and use it. I simply don not understand the latest trend in analytic use in social media – or at least a part of its use. Let me explain…

I don’t actually have an issue with analytics or metrics as they can be instrumental in helping a user in supplying their viewers or clients with the content they require. But there is some work involved. There’s a lot of data that is collected that needs to be carefully considered & analysed. Unfortunately, this is where the users usually stop thinking and over rely on the powerful metric software tool they have selected.

The Net is filled with sites & services that promise to serve up numbers and copious amounts of all kinds of data: total tweets, total unique visits, country of origin and much more. Some of the ones I’ve seen in use are (not the best – Google being the exception):

By their nature these services are rather hands off, giving users auto-posting and autoupdating options that take one out of the ‘thinking’ & analyzing equation. Three of the services post maplets showing where in the world people are posting from and one other posts stats about new #s of new followers, mentions and the like to a public timeline. Interesting some say – but completely pointless from an analytics standpoint.

Analytics is the discovery and communication of meaningful patterns in data. Especially >valuable in areas rich with recorded information, analytics relies on the simultaneous >application of statistics, computer programming and operations research to quantify >performance. Analytics often favours data visualization to communicate insight.
Firms may commonly apply analytics to data, to describe, predict, and improve >performance. Specifically, areas within analytics include predictive analytics,
decision management, web analytics, predictive science, etc…(

Analytics or metrics are data collected to help inform decisions about what’s happening with sites, etc. that are under a user’s control. The key phrase here is ‘inform a user’s decisions’. Looking at the numbers or a pretty map without any analysis of what that data means is fruitless!

It might be like having someone else put a letter grade on your student’s assignments, handing them back to you and then having you continue teaching them. You have no idea where students went wrong on their assignments because you haven’t done any analysis of either the results or the trends or the particulars of the assignments. The number on the assignment itself isn’t all that useful. It doesn’t inform your instruction in the least and therefore the grade or number itself has no benefit to you at all without the analysis piece!

However, analytics tools can be potentially useful, even one of the ones listed above:

Maplet Example
Maplet Example

For example, if you must post a maplet, and the map indicates a dearth of activity in say Australia, what might you learn from this? I might have tweeted something like this: “This is interesting. I have good coverage in North America. I wonder how I could make better connections in Australia? Thoughts?” Not maybe the best tweet, but at least an attempt to use the tool as a conversation starter to broadened my reach. Perhaps a better use would be to not post the maplet at all and do this thinking, make my decisions and plan of attack offline.

What’s the difference you may be asking? I have a few reasons why posting analytics without thought is a practice that you may want to reconsider:

  • This is the same with ANY kind of analytics or metric. Without looking at the data and actually spending sometime THINKING about what they mean, they aren’t really interesting to anyone, they’re pointless and can only really serve one simple purpose especially if they raw numbers are just posted to a twitter stream or blog post: that of being potentially boastful.
  • Social Media Etiquette suggests that you shouldn’t humblebrag. In addition to your bio basics and account stats, most people will read your last two tweets when they are checking out your Twitter profile. One of the things that come up in research was hatred of the “humblebrag,” and self-aggrandizement in general. Posting material like the image below or maplets amount to nothing more than humblebrags in the absence of thinking and analysis.

    Humblebrag: Nothing Humble about it
    Humblebrag: Nothing Humble about it
  • Social Media Etiquette also suggests that you shouldn’t allow Robots to craft your tweets. If your recent tweets look like they were automatically generated, people may see you as disingenuous. Generally they are frowned upon. What people want on Twitter is to hear your genuine voice, in real time. They don’t want lofty quotes that you’ve scheduled to go live at strategic periods, stats from your latest workout or what your “top stories” are via a third-party curation service. Twitter is about engagement, not just broadcasting meaningless words.
  • In my opinion, here is the biggest issue with analytics and why they cause issues. Most people start with data instead of a question they are wanting to answer. The most common misunderstanding about analytics is that if you look at data hard enough, you will find insights. Staring at daily dashboards in the hope that insights will miraculously reveal themselves is often overwhelming, confusing and unsuccessful. Successful analytics start by identifying the question you’re trying to answer from the data.

I was scrounging the Net trying make sense of this and stumbled upon some resources that might assist in sorting through how to successfully get started using analytics with social media platforms, at least as a starting point:

To download the above PDF simply click the link below:

Hopefully, this post has helped to make clear the function of Metrics & Analytics and the useful but silent function they serve in assisting a user think about reaching clients and broadening their social media reach.

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