Humanizing Data – Words Can Hurt, But Data?

Humanizing Data – Words Can Hurt, But Data?
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In this guest post, B&T regular and ad veteran Robert Strohfeldt takes a look at the avalanche of data now available to marketers and offers top tips on how NOT to get overwhelmed…

A recent article titled “We need to humanise our approach to data management”, led me to the conclusion that if data was the currency of marketing in the 21st century, then there is a ton of counterfeiting happening.

Data is, well data. There are two approaches to data:

  • The right approach
  • The wrong approach.

In comparison to science, marketing has only just “discovered” data. I spoke to a couple of friends who work in scientific fields (Geology and Medical Research) and asked them “how would you feel about having your data humanised”? .

The Geologist, thinking I was talking about milk, said “Isn’t all bloody milk homogenised?” The medical researcher initially looked at me as if I had come from another planet and then said, “Surely you are not fucking serious”?

Science has “always” used data. It is the basis of science. Galileo concluded, much to the anger and threat of violence from the Catholic Church, the sun was the centre of the solar system, not earth. And the earth revolved around sun, as did the other planets known of at that time. And how did he come to this conclusion? Data!

Many marketers, in relation to data, are like kids with a new toy.

Next it will be “How do you want your data, rare, medium rare, medium or well done?” Or even worse, will data become Vegan?

It is easy to be critical, much harder to be positive (and make sense,). No one could deny the amount of data now collected is enormous and growing at an ever- increasing rate.

I have used the facts below several times, as it always adds perspective to the issue of data collection:

In 2017, IBM estimated: Every day, we create 2.5 quintillion bytes of data. (10 with 18 zeros) To put that into perspective, 90 percent of the data in the world today has been created in the last two years alone – and with new devices, sensors and technologies emerging, the data growth rate will likely accelerate even more.

That was four years ago. Stating the bleeding obvious, we are being inundated with data at an ever increasing rate. The old expression of “not seeing the wood for the trees” applies here.

Going back to basics, what is the role of data? Maybe I am wrong. I have always though the role was to provide insights into consumers  – be they customers, competitors’ customers or just the whole universe of consumers in general. And if the data does not provide relevant insights, then the data does not serve any useful purpose.

On first seeing “humanising data” , I thought it was a good move.  Very few people understand the complex statistical analysis behind the conclusions drawn from the data. For example:

“The data has shown that on average, 400 customers enter a store every Friday night.  What is the probability 600 customers will enter the store on any given Friday night”?

This makes sense, But, if the marketing department and their advertising agency were to be told. “Ok, to calculate this, we will need to use a Poisson Distribution”  (If you don’t believe, check it out. It is a simple and widely used  Stochastic Process to model when the times at which arrivals enter a system. Simple, not really. Stochastic processes are highly complex.)

The Poisson probability is: P(x; μ) = (e-μ) (μx) / x! where x is the actual number of successes that result from the experiment, μ is the average number of successes in a given region, x! is factorial x and e is approximately equal to 2,71828 (recuring) Make sense? No, and nor should it and that is not a criticism. (It’s been so many years since I did my maths degree, I would have to  look up how to do it as well.)

“Humanising data”, I first thought, was putting the outcome of data analyses into terms or outcomes so people who are not statisticians or mathematicians understand.  Dehumanising data is hitting them with gobbledygook (even though it is basically true, it is gobbledygook to the uninitiated.)

Having read the article on Humanising Data, it is full of complexities and buzz words/phrases, that if being honest, the average marketing manager would not have a clue about.

For example:

  • Does your infrastructure allow for the most optimal connections between marketing, AdTech, Martech? Do your marketing and tech teams ‘sit’ together? Is technology involved in solving traditional marketing challenges? Ad and Martech have the capability to enable marketers to do their jobs more effectively, efficiently and empower them to make more informed decisions.

(Seriously, can a well- trained and experience marketing  manager, who expertise is, well, marketing, know if their infrastructure allows for the most optimal connections between marketing, AdTech and Martech. Spell it out in simple English!)

  • Do you have the tech in place to really see and understand all the signals which your known and unknown audiences are sending you? If not, get it! Get it and future-proof it as much as possible.

(How would they know their tech allows them to “Really see and understand all the signals” – you don’t know, what you don’t know! And future proof it while you are at it!)

  • Does your infrastructure allow for the most optimal connections between marketing, AdTech, Martech? Do your marketing and tech teams ‘sit’ together? Is technology involved in solving traditional marketing challenges? Ad and Martech have the capability to enable marketers to do their jobs more effectively, efficiently and empower them to make more informed decisions.

(Many people forget, technology is a not an answer, it is only a tool.).

Over 20 years ago, a Professor of Market Research said to me too many researchers make the mistake of trying to give the impression of being clever by being complex.

But they failed to recognise the ability to make the complex simple and easy to understand, is in fact the realm of the very clever.

KISS. It stands the test of time.

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Robert Strohfeldt

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