I’m not vain, honest – Just evaluating my online presence

Data within newsrooms is only partly about using statistics to find stories and presenting them in a visual and engaging way.

Data analysing the reach, popularity, type of engagement and how people found a particular piece of content are paramount for not only news organisations – but for companies, brands or individuals to evaluate their online presence and its effectiveness.

From WordPress analytics available to those running a blog or website on that platform, to Google Analytics, Chartbeat, Facebook insights and tools looking at twitter engagement such as Hootsuite, bit.ly and Buffer, there is no shortage of options.

I’m not self-absorbed, I promise

What these tools do is provide an insight into how others came across your content and how they engage with it. As you can imagine, this is essential to all media organisations – what is the point of producing content if, for whatever reason, people can either not find it, or don’t want to see it?

The assumption that analytics and measuring user engagement is a thing for “geeks”, or those with excessive amount of vanity, no longer holds true. Finding tangible ways to evaluate one’s output is the best way of working to improve it, both for yourself and your audience.

With digital journalism and specifically the rise of social media analytics (interesting infographic on that here) journalists can have instant access to in-depth analysis of how well their own article is doing online and what sort of reach it is getting. An example is the public viral dashboard that Buzzfeed US has for its articles.

Buzzfeed viral dashboard 2Buzzfeed viral dashboard

These two examples are very interesting in themselves, as they show very different patterns when it comes to origin of views, ie. where the readers came from. The first one large percentage of links originating from social networks, with the second one has considerably fewer ‘social shares’. Suffice to say that the one with five times the  number of views was the one which was predominantly shared through social media.

So, on a very (and I do mean very) micro level, I thought I would try this for myself, using my own personal twitter account.

I have used Google analytics in a previous job, producing weekly analytics reports for a website, but under very different circumstances and with considerable restrictions, however I have never really thought about how and what I share online via social media, take Twitter for example.

Last week, in a bid to for a more strategic online presence and intelligently experimenting with as many different social network tools as possible – I began evaluating my activity and what I can only describe as scattergun sharing techniques on Twitter.

Posting and scheduling links via bit.ly and buffer have given me some interesting results.

Lessons learnt

As I mentioned, this was done at a very micro level and drawing real conclusions from this is probably ill-judged. However, I have – for now – made one observation.

First of all, one of the most depressing (but not completely unexpected) things I realised was how few people interacted with the links that accompanied my tweets – for which interaction can be measured. This may be somewhat normal, or it may be (probably is) due to poor strategy on my part, anyway it is worth some analysis.

Most of the links attached to my tweets got 0-3 clicks – from a base potential of around 500. The potential did remain at a constant value, as none of the tweets I looked at were shared or retweeted.

Buffer tweet analytics

There are so many parameters when it comes to analysing this figure – people on/offline, time of tweets, type of followers I have, the content of the tweet, tone etc etc (I could really go on and on here).

I will analyse this further as I continue this strategic process but overall, my first and very basic impression is that within social media, you (or at least I) need to think and work hard to get people to click and engage with the content you are sharing with them. This is even when these people have some sort of interest in what you are tweeting, as they would presumably not be following you otherwise.

Interestingly, the tweet that did (marginally) better from this tiny sample was a more cryptic,  ‘mysterious’ tweet linking to a beta full screen online version of Super Mario – without explicitly mentioning it and warning my followers not to click because of the potential of procrastination.

In fact, maybe that’s the answer and I’ve cracked this. Telling people not to click. That’s guaranteed to get them interested.

Some further reading:


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