We are interested in everything we lay our hands on – according to some estimates, even 90% of all the global data was developed over only the past few years. We take interest in many things – flows, clicks, duration of stay at the website. But we forget that the human factor is not always limited to figures. Figures may help choose direction, but so long as we are not turned into robots, the ability to make conclusions will add value.
According to the 2014 Social Media Marketing Industry Report, most of the marketers believe in the growing role of social media. It is a paradox that only more or less one third believe it is important for the business. Is it that in the we are looking in the world of figures only for a quick justification of our doings, not quite believing in them? This is a provocative thesis, but it is worth remembering such variables as quality of provided texts, their relation with context in which we function and sensitivity for the needs of the group of our listeners. To be clear, I am not writing it to counter the opportunities that have come with the era of Big Data, but simple conclusions often based on worthless statistics, which does take motivation into account. Does the growing role of social media mean the need for companies to increase outlays?
In general, we are facing 3 major challenges when thinking about communication management through data. Firstly, the volume of available data is growing like an avalanche and as a matter of fact it is not quite clear where to put the limits of their collection. Sine we collect, we want to collect more and more – because of activeness in social media, because of data from CRM, because of the flows at the website, because we have ambition to have knowledge, which we generate for ourselves. The next challenge is the structuring of data in the way permitting for fair conclusions. Since the multitude of data is often without a common denominator, then again we have to simplify gathered knowledge so as to be able to draw rational conclusions, acting counter to the huge mass of data, which was supposed to be the advantage at the outset. Thirdly, even if we find way to draw conclusions based on such data – which entails many costs at the operational and investment levels – time is still unknown that will be needed for the processing of data. The problems referred to do not classify me in the group of sceptics, but induce to take a greater distance to rationalisation of everything with figures.
Let me add yet another perspective – data tell us what was done in the past, and on the basis thereof we make conclusions for the future. The figures do not provide answer to the question what was the underlying idea and why it was done. By the same, it is hard to draw conclusions regarding new products or new technologies on the historical grounds, it is even hard to anticipate the trends. Neither do we know how events collected in the form of data were assessed, or what was their impact on the positions, which in turn will determine what we will be doing tomorrow.
With my say, I do not want to position myself in the group of data analysis sceptics – I just want to demonstrate that data have no soul and are not absolute, especially in relation to man. What creates attitudes and positions to the greatest extent, is the experience, recommendations and communication of the interested objects, and decision signifies faith in the correct interpretation of data.