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Creative Data Science: How to keep your creative agency relevant

The past decade in the creative industry has been quite disruptive, to say the least. Digital departments that used to take up a corner in the agency have now overtaken their progenitors in both size and revenue and are getting most of the attention from both clients and investors.

To make matters worse, the data department, which often was left to languish in the basement, is starting to overtake even the digital marketing team in relevance.

So, how do you keep your creative agency relevant when the client is focused on data over creativity? Here are a few key points for brevity:

Understand the mind of the AI beast

Knowing what you are up against is the first part of the battle. If you and your team are not up to speed with what is happening in the world of data science there is no way for you to add value to the conversation, or to know that the conversation is actually happening.

You do not need to swap #adobe for #python but it is key that you know how data science is being positioned to your customers and where you can pitch in. A company that would be worthwhile taking a look at is Dataiku, they have marvellous examples and are making waves in the #enterpriseAI space.

Understanding the changing business and consumer environment

If you think you have it bad, imagine the challenges your clients are facing in the post-Covid world. Customers are changing attitudes and long-held beliefs faster than you can say LGBTQIA+, resulting in communication and product usage patterns being upended.

A renewed focus on sustainability in all its forms means more nuanced communication to diverse stakeholders is also required. With these changes come opportunities and new ways to look at people and the world, this is where agencies can support their clients, by bridging existing data with real-world empathetic creativity.

Release the creative data scientist in you

I believe creative agencies have always been data scientists (or alchemists) in that we are required to take masses of data from various disparate sources, filter out the good from the bad and extract the essence of a problem to deliver an output, in this case, a creative concept that will deliver results.

In my experience, the ability of creatives to make connections between seemingly unrelated ideas (nodes) and leaps in logic is analogous to being a biological machine learning engine.

No to ad infinitum

I believe there is a nexus between creativity and data science where creative teams can frame and ask questions in a different way to the very analytical minds building today’s algorithms. Challenging the initial questions we want answered is where creative data science comes alive. All the computing power in the world is pointless if it is not guided in a way that will solve a relevant and compelling need.

If we are simply solving today’s problems with today’s logic we are missing the opportunity to move past entrenched thinking and formulaic processes. Both the way we frame challenges and deliver the result requires creative expression.

Find the right balance and you will solve more than you can even imagine.

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