Social Media Analytics – Fish or Fowl, Quali or Quanti, Believable or Just Jargon!

2 Jan

A few days ago, while having one on ones with some business analysts, i was flummoxed – nay dismayed, by a bright young man telling me – “so, i thought when i joined this company, that i would be working in analytics. All we do now is social media.”

It took me the better part of an hour to explain to him why what he did was truly analytics – even though it was social media analytics!

It did set me thinking though – a look at wiki definitions showed me – “Analytics is the discovery and communication of meaningful patterns in data”.

Now this was the gist of what i had told that young analyst. The fact that you are observing patterns and deriving key takeaways from a vast quantity of data means you are ANALYSING it, and therefore working on analytics. After all, while in social media, a lot of the challenge has to do with just the extraction and aggregation of data – comprehensively i might add, and this is where all tools like Radian6, Sysomos etc concentrate, a big part of the challenge is also what you do with this data – how do you then process (ANALYSE) it to derive the “so what”. Hence all the dashboards/ the buzz on “measurement” etc.

I think where the confusion lay in my young friend’s mind, and actually also lies at the heart of why purist market research people continue to scoff at Social Media analytics as a reasonable source of consumer insights, is highlighted when you read the next part of wiki’s definition: “Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statisticscomputer programming and operations research to quantify performance”. THIS was what my friend was talking about – most folks in social media analytics do NOT use advanced statistical models to derive the insights – they mainly use plain sums/ or averages – ie simple/ intuitive tools to do it. Having said that, THIS is also what we were trying to do – inject classical MR techniques in the analytics of unstructured data ie Social Media data.

Think about it – given technology’s weaknesses, we actually used a combination of people and tools – what we called a “bytes and brains” methodology  to derive the appropriate insights and nuances. (As a fallout, SocialMedia analytics actually combined the best of quantitative techniques and the qualitative insights as seen in focus groups and depth interviews). But the way to do it was via classical sampling techniques – and that which worked best was Stratified random sampling! Additionally, we used cluster analysis, factor analysis, multi dimensional scaling..what have u — to show patterns – and ofcourse to do this we used spss and sas — now, the problem was, that given the state of evolution of the medium and its apprecaition by the larger world, folks weren’t ready for it! Hence the regression (yess, pun intended!) to sums and means!

The point here is, therefore, Social Media analytics IS TRUE analytics – it definitely gives businesses an opportunity to mine and process data to answer critical business problems, it even has the ability to use the standard statistical models and methodologies to do so, it combines the best of quali and quant research…its just that the world is not ready for the full leveraging of this. It needs folks like us to educate and demonstrate to the world, the art of the possible.

Evangelists anyone????


4 Responses to “Social Media Analytics – Fish or Fowl, Quali or Quanti, Believable or Just Jargon!”

  1. Avinash January 7, 2013 at 9:04 am #

    Interesting. So you are saying that it is the medium of data collection through Online SM channels that is different in SM as compared to traditional data collection routes like F2F, telephonic or online surveys that are used to generate data in MR.

    Beyond that SM analytics should be no different from traditional MR since the analysis is performed with the same statistical and OR tools.

    A couple of my thoughts – Data collection in traditional MR is probably more structured and machine independent. In SM how data is collected that becomes crucial and is that where the value lies – A tool that can collect and analyze data through SM channels with the human layer providing data/ analysis integrity?

    The second is eliminating biases that could creep into SM data collection – For e.g. geographical bias, dissatisfaction and hence online venting bias etc.


    • joshsang January 8, 2013 at 9:07 am #

      bang on, avinash. agree with both yr points – but, the points here apply to both trad / primary research as they do to social media research – the difference is only one of degrees…


  1. Analytics, Big Data, Crosswords and Agatha Christie « joshsang - January 28, 2013

    […] do in analytics is exactly this – connect dots, draw parallels and then solve problems. (see my earlier blog on […]

  2. Social Media: More a Research/ Analytics than a Marketing Tool? | joshsang - September 2, 2013

    […] It kind of points towards an old felt-but-not-quite-articulated hypothesis I had! At the time, I used to think that I felt this way because my business was more focussed on the use of social media for a “learning” experience, not so much an “outreach” one. And this despite the fact that marketers we spoke to almost always were interested in the lower hanging fruit, i.e., the marketing using SM. So, when we went in with a pitch that said – “hey, this is what social media can teach you about your consumer or your competitor or your brand”, they would say, “hey, can you help us make our facebook page better”! Maybe it was compounded by the fact that the consumer insights/ market research people, those that would truly benefit from this, turned up their noses at this “unconventional, unstructured, “qualitative”‘ data source and took whatever we said with a pinch of, no! scratch that – huge dollops of salt! (See my very first blog post on this question of whether social media research is fish or fowl! ) […]

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