Alex Murrell wrote an excellent article titled Big Questions for Big Data regarding limitations of data in marketing.
“Some things are important but immeasurable. In fact, I’d argue that the vast majority of human behaviour falls into this group. Pride, passion, anger, anticipation, sadness, surprise. These are among the messy motivations of our actions. They are hard for us to recognise, difficult for us to process, and almost impossible for us to measure.”
“Big data will always be incomplete. It will always be restricted by the method of its collection, by the context of the culture and by the degree to which the meaningful can be measured. The danger of data is that it provides the perception of completeness whilst never actually achieving it.”
“The incompleteness of data is a problem. But the opposite is also true. Too much information can create just as many concerns as too little.”
“To truly understand a system, you need to understand more than just the variables that have been measured. You need to understand the relationship between them. You need to understand how they interact. How cause leads to effect. How action leads to reaction. And it is within this arena that errors begin to occur.”
“Those versed in organisational theory will be familiar with the DIKW model. The acronym stands for data, information, knowledge and wisdom. As you move up through the model’s hierarchy, each layer becomes increasingly difficult but increasingly valuable.”
“In marketing we often consider data to be the answer. The end, rather than the means. We think that if we have the right data, we will make the right decisions. But this simply isn’t the case. All data must be interpreted… The right numbers lead to the wrong conclusions. Because, to paraphrase John Hegarty, data gives us information, but it doesn’t give us understanding.”
“So, there you have it. Big data faces big questions. Questions of collection, claims, correlations, completeness and comprehension. The tools we use affect the data we collect. Consumer responses don’t represent reality. What matters cannot be measured. The noise grows faster than the signal. And perfect data rarely results in perfect decisions. One thing is clear. Big data is not perfect. It will never be totally correct or totally complete. It will never be faultless. It will never be foolproof.”
“We must stop treating our audiences as empty averages. We must stop passing people off as percentages. We must stop trying to quantify humanity and start trying to embrace it. Let’s get out from our offices and meet people. Talk to people. Understand what moves and motivates them. What drives their decisions. What alters their actions and affects their attitudes. Let’s go beyond the surface and search for the substantial. Let’s not stop at the measurable in pursuit of the meaningful.”
“So let’s stop trying to remove all risks. Let’s stop trying to reduce all waste. Let’s stop our obsession with quantifying culture and start our obsession with impacting it.”
This well-researched article cites eight books:
- Head In The Cloud by William Poundstone
- Truth, Lies and Advertising by Jon Steel
- Consumerology by Philip Graves
- Where Did It All Go Wrong by Eaon Pritchard
- The Signal and the Noise by Nate Silver
- Buyology by Martin Lindstrom
- The Black Swan by Nicholas Nassim Taleb
- The Choice Factory by Richard Shotton
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