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What is good data made of?

There are many different types of data. You can categorise most data into two kinds: qualitative and quantitative. Find out what those are here.
A satellite image of the United States taken at night. Yellow lights speckle the otherwise dark landscape.

As we saw from the Pepsi commercial, much of our culturally insensitive material comes from poorly interpreted data and lazy cynicism.

The best way to combat that is through high-quality research and good data gathering practice.

Rather than checking what’s trending right now, we need to get deeper into our customers’ psyches. We must understand what they want and how they wish to be portrayed and treated.

But, how can we collect that data and ensure its quality?

From a high level, there are two main kinds of data: Qualitative and Quantitative. Both are relevant to research – and not just in the scientific sense. We should consult both types of data in our creative work too, or, like Pepsi, we risk completely missing the mark with our customers.

Quantitative data

Quantitative data is measurable. For example, data that explain how many customers go on holiday with a particular airline every year are quantitative.

Qualitative data

Qualitative data help us to explain the why behind the quantitative data. For example, why do those customers choose that particular airline every year? This is much harder to measure in terms of numbers.

When we expand our understanding of what data mean and how they can be applied, it becomes clear that we use some form of data in every aspect of our lives.

Even something as simple as what kind of takeaway you prefer is based on years of data you have collected through your experiences of ordering various takeaways.

Quantitative: The number of takeaways you’ve had of each variety, when you ordered, frequency, etc.

Qualitative: How you felt about each takeaway, and your opinions of each cuisine, etc.

From these data, we can begin to understand our customers better. The data themselves don’t do the heavy lifting – that’s on us. To ensure we use data the right way, we need to ensure that diverse people interpret it.

‘Diverse’ is not a byword for ethnic minorities. It just means a multitude of people from various backgrounds.

If we simply decide that ‘people are into X and X this month’ based on streams of online data, our creative work will fail miserably. Especially today, people can smell an advertiser from miles away.

Appropriating a cultural phenomenon and spuriously linking it to your product, work or influences isn’t just lazy. It exposes the cynicism of profit-driven business and makes your company look stupid to the very customers you’re trying to capture.

This doesn’t just ring true for maligned or discriminated cultures; it goes for every culture.

Imagine if your shoe company wanted to capture the adult marbles enthusiast market. The dullest approach would be to create media in which random people play marbles while wearing your shoes. That achieves nothing and creates a spurious, inauthentic link between marbles and shoes.

Worse still would be an attempt to define the culture of the adult marbles enthusiast market in terms of your initial, unresearched understanding.

It may turn out that adult marbles enthusiast culture involves much deeper meaning than you initially thought. What if the marbles represent chaos? What if that chaos is a spiritual reference to the natural entropy of the universe?

A much more interesting commercial or piece of media would seek to connect those core beliefs of the marble enthusiasts to the core beliefs of the product.

Perhaps your company could sponsor the next marbles world cup, or even just some local games, making it easier for people to play marbles.

But, you say, we can’t do that because my shoes have nothing to do with marbles enthusiasts.

This is true. The marbles enthusiasts will laugh at you, and they still won’t buy your shoes.

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Cultural Appropriation vs Cultural Appreciation

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