| January 02, 2019
In this video, Keith Reinhard, Chairman Emeritus, DDB, states, “We over-appreciate data and under-appreciate data”, and he is right. We tend to over-appreciate the data which tells us what people do, and under-appreciate the data that tells us why they do it.
In these digital days, automated systems separate us from needing to actually think about what data actually means. When it comes to digital advertising convenience metrics like clicks, views, and shares enable automated systems which decide who gets targeted with what and when. This is hugely beneficial, but only if the content delivered has the power to engage people and move them to action.
The problem is that as Reinhard points out,
“There is still a difference between an algorithm and a true insight into human nature.”
The algorithms that power our targeting systems are no more insightful than their programming, which is to say, not a lot. Instead of insight they are largely driven by assumption. If you want to change human behaviour – the real job of marketing – then you need to know what will motivate people to make the desired change. And that requires understanding human drives and motivations not just what they clicked on.
In a fascinating critique of what is wrong with advertising these days Martin Weigel takes the ad industry to task for losing touch will real human beings. And I cannot help but believe that our use of data plays a part in that disconnect.
Weigel talks about how the use of labels allows us to describe something without understanding it. He states,
“Labels give the illusion that you mean something specific but in fact you don’t at all.”
“Worse, labels dehumanise. And in so doing they too easily undermine empathy.”
In the same way, I would contend that a lot of data dehumanises, it gives us the illusion that we understand what is going on even when we do not, and it stops us from seeing the essential motivations behind people’s behaviour. As a result, we often fail to identify any real insight into how we might change that behaviour or, if we do, it becomes an uphill battle to convince anyone to act on the insight without proof that it will pay off.
Maybe it is time to remind ourselves that real insights come from understanding people not data. And that understanding starts by having an empathy for people and their diverse needs, drives, and emotions. But what do you think? Please share your thoughts.