Article

Rosie Copland Mann
Rosie Copland Mann 27 June 2019

In This AI World, Don’t Forget We’re Marketing to Real People

If you’re in marketing, you’ve probably watched Mad Men. Last week I eventually sat down to see what the fuss was about. A couple of episodes in, the Creative Director walked into a room and sold an idea based solely on two things: brilliant creative and a gut feeling.

I paused the show. Where was the data that “proved” the idea would work?

It was difficult to comprehend a world where “just trust me on this one” was enough. In 2019, we live in a digital world of big data, analytics, and metrics, and we use them to justify all our business decisions.

But our ability and inclination to quantify everything is creating a problem. We’re drowning in data. Retargeting, psychometrics, real-time analysis… We spend so much of our time sitting behind screens, monitoring numbers and making “data-driven” decisions that we’re in real danger of forgetting who we’re designing for - humans.

Human insight makes sense of big data

Big data is a tool. Think of this tool like a metal detector. It exposes areas of interest; it surfaces conclusions and it highlights an area of opportunity. But you need to use another tool - human insight - to find the gold.

For research and strategy teams, especially in agencies, time is of the essence. Big data is quick, feels reliable and we know clients trust it. People are desperate to feel safe and search for a score that supports their thinking. This regularly results in strategists taking data at face value, without deep reflection and interrogation. The problem lies in the name, Big Data is just too big. It often produces so much information that if we rely on it completely, we develop a very forensic and clinical understanding of people. And this is where we miss the most meaningful insights.

I recently worked on a project for a baby brand. My quantitative survey provided me with some great facts and conclusions. I knew what was happening. I knew how long their babies slept, I knew what their babies ate, I knew which baby brands they purchased, I knew who they turned to for support.

It wasn’t until I interviewed the mothers that I understood their emotions. They were overwhelmed by responsibility and overpowered by information, opinions and judgement. They felt helpless and alone at 2 am when no one was around and were terrified of getting it wrong. Despite commonalities, every single experience was unique. There was no ‘baby bible’ or method that worked for everyone. It was trial and error, the mothers were literally learning as they went.

What they needed was a non-judgmental, supportive, hyper-personalised experience for when they needed a little extra help. I would never have been able to build that strategy from Big Data alone.

The first step is to understand what is happening, using Big Data. The second step is to speak to real people and uncover human insights to understand why it’s happening.

Steve Jobs said: ‘market research can tell you what your customers think of something you show them, or what they want as an incremental improvement of what you have, but very rarely can your customers predict something that they don’t even know they want yet’.

Jobs is right - consumers can rarely predict, but they can tell you about their beliefs, routines, habits, pain points and unmet needs...and as a researcher, you can listen, question and observe. These nuggets of human truth and behavioural nuances are things that big data does not provide, but they are crucial when we’re designing and creating products and experiences for real people.

It’s our job as creators to uncover these insights then use them to look to the future, hypothesise, innovate, create, experiment, test and learn - until we find better solutions to a shared customer need.

Taking a holistic approach to research

Researchers have always stressed the value of both qual and quantitative, and the same value applies equally to newer technologies like big data and machine learning.

So, step away from data-driven decisions, and make data-informed decisions. Use data to find opportunity spaces and to draw conclusions, then go and speak to the people you’re designing for. Understand what motivates them, what drives them, their problems and their needs.

We have the most incredible tools, so let’s use them properly, intelligently and meaningfully.

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