With Data Artistry Comes Humanizing Context

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By Mick McCabe, Global CSO, Publicis Worldwide and Tim Rich, Director of Data Science, Publicis Worldwide

The obsession with data in the business and marketing worlds has reached frothy and frenzied levels. We brand it… big data, small data, smart data, dark data, responsive data. We embark on journeys with deep-sea data dives and we go swimming in data lakes. We treat it like a prized possession by capturing the data, getting granular with it, cleaning it before we finally put the data to work.

You can never go wrong by talking data in a meeting. But it also creates a deep sense of insecurity or inferiority that we are failing or are not doing enough with it. It may be that Dan Ariely has it right when he says “Big Data is like teenage sex, everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it”.

To give some clarification to data and the changing ways we are thinking about it, let’s first consider the shift in emphasis from structured to unstructured data. In the beginning, a mere 25 years ago, data was collated and analyzed in what is known as ‘structured data’. Imagine massive excel sheets with rows of characteristics and columns of observations, holding names, addresses, and other relational observations. Most companies’ data was of this structured type, regardless of business vertical or industry. This data had and has its limits.

Gartner cite that 80% of newly created data is of the unstructured kind.

More recently we have seen the exponential rise of ‘unstructured data’ (Gartner cite that 80% of newly created data is of the unstructured kind), typified by real-time flows of data like social posts or data aggregated from devices connected into the IoT. It is within this hidden world, where the break-neck speed of unstructured data travels, that the nuances of consumer behavior, emerging market trends, new experience opportunities and ultimately business growth lies a deep-water trove of value waiting to be discovered, waiting to be put to work across the creative, strategy, experience design and media ecosystem. This data is trying to tell us things.

This unstructured data is overwhelmingly behavioral data and signals human intention, motivation and action and gives a clear human context. It avoids stereotypes or superficiality based on demographics such as race, gender, and income. It is collected from cellphone movement, internet browsing or online searches, consumer reviews and expressions of dissatisfaction or love, and enables us to garner insights of consumer behavior without survey bias and without the human propensity to exaggerate, forget or misremember. Your search history knows you well, it doesn’t lie, and may indeed know more about you than many friends or family. It tells us about our humanity in a frank and honest way. And it allows the promise of hyper-personalized, hyper-relevant marketing to move out of the world of “I wish”, to “I can and I am”.

Behavioral data can help us answer big and small pressing questions. Help with how we find local insights efficiently, in far-flung markets at the scale and speed required in this competitive business landscape. It can help us utilize search, browsing behavior, unstructured data among other methods, to find out consumer preferences, questions, and concerns around products and services. It can help us with the timing of advertising delivery and optimal mediums for specific messages, and increasingly, how a client can optimize, change, reimagine and radically improve its customer service and its brand experience.

Even the best data needs a creative context.

Tapping into global flows of behavioral data, we are able to move from insights at a neighborhood level, up to country and continent levels of scale. So, when a global spirits brand wanted to put billboards in major cities, giving a nod to the neighborhood’s culture, we aggregated and analyzed data from sources like Yelp and local search patterns to reveal what local people actually care about. It took the guessing out of the equation.

Importantly, and perhaps an unacknowledged, but real point, is that even the best data needs a creative context, a narrative, a point of view, a human context for it to have the maximum impact. When it is placed in that context, it all of a sudden becomes different to human beings. Consider these pieces of data framed in an imaginative and human context, and how at once they feel different.

…There are millions of stars in the solar system vs. there are more stars in the solar system than there are grains of sands on the entire earth.

…Ikea is the biggest seller of beds in Europe vs. one in every 10 European children are conceived in an Ikea bed.

…Video games have no real value to society vs. surgeons who play video games three hours a week make 37% fewer errors.

We have a very different relationship with data when it gets revealed and framed in this way.

We are on our journey to reveal, understand and channel how big data can be used in new and inventive ways in the service of creating a consumer experience that is exciting, magical and mutually beneficial to customers and brands alike. And yes, we need better data to do that. The oceans of unstructured, behavioral data are that next frontier for us, and our Data Scientists resemble and act more like Data Artists in this world.

More like Jacques Cousteau exploring, discovering, unearthing data that lies unseen and untouched but holds incredible worth if we can find it.

When those Data Artists collide with creative, media and strategic people focused on making that data visceral and inspiring, imbuing it with human energy, placing it in the right contexts, and framing it in ways that recognize how people are moved by data, then magic consistently happens.

Make no mistake, the need for brilliant, intuitive, imaginative, creative people to do things with this data will never go out of fashion.

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1 Comment
  1. Excellent article you guys! Really enjoyed reading this. And I love your stance that creativity it still needed to interpret and relate the data. I spend a lot of time working with people on how to make meaning of the data in an organisational context (employee data). I wonder how you guys do the sense-making part of getting it all right?

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