Advertising Age features Exponential’s own Senior Director of Insight Services, Bryan Melmed, where he presents his ‘Six Ways to Make Your Data More Human’

  • June 3, 2014

Check out the Advertising Age article.

Big Data Is Great, But Marketing Still Needs the Human Touch

There is no doubt that data has fundamentally changed the nature of marketing. Not only are we able to target audiences with increasing precision, but the shift to data-driven methods has transformed our ability to understand consumers. We can deliver more, and are expected to deliver more, making work in this industry both exciting and daunting at the same time.

Sadly, this data revolution has been so hyped that we risk thinking it is the answer to everything. Data has been hailed as a way to predict terrorist strikes, cure cancer, or even solve the age-old problem of knowing which half of your marketing budget is wasted. But data is neither omnipotent nor infallible.

For a start, it takes people to design the systems that collect and organize data. It takes people to understand the limitations and biases of these systems; and it takes people to focus data on the right questions that can lead to meaningful and actionable insight.

Ultimately, data that comes from people has a human quality of its own. Insights driven by people, not machines, are essential to making data actionable. But as marketing becomes more reliant on automation, and programmatic responses are increasingly easily to implement, so is the temptation to write off that human touch. With this in mind, here are six ways to keep your data “human.”

1. Use human insight to frame the problem.

Data doesn’t ask questions. In many ways, the first few steps of any inquiry are the most challenging. The wrong choice of variables, poor instrumentation and measurement, or an imprecise question come with a high cost. No amount of automation can correct these missteps.

2. Remember that bigger is not always better.

Massive amounts of data defy the limits of human analysis, which is why machines are essential to understanding large amounts of information. But increasing the volume of data is only useful if it serves to improve the ratio of signal to noise. More data also means a greater risk of finding false correlation, or conclusions that aren’t relevant or actionable. A machine can find any number of answers, but it takes a human to discern treasure from trash.

3. Know that everyone is lying.

To put it more gently, people are masters of self-deception. Unlike weather patterns or traffic data, information that people volunteer is always biased in some way. People distort the truth about all kinds of things — sometimes directionally, as in how much they earn, and sometimes in unpredictable ways, such as how they feel about a product they know others like. This is yet another problem a machine can’t solve, but experience and human judgment can. It is also why passive observation is often the best way to gather data.

4. Understand that context is everything.

The events that are captured and recorded in our data are almost impossible to understand without knowing the context in which they were collected. The same action, even by the same person, can mean wildly different things. Purchase of a children’s toy at a supermarket or drugstore often indicates a child is present — unless it is December, when the holidays play havoc with shopping patterns. The same product purchased online is usually bought by an adult without children. And if the toy is purchased in a store outside a consumer’s home area, there is likely to be a guilty parent traveling alone at the register.

5. Embrace the idea that data forces us to abandon stereotypes.

This one almost works backwards. Robots struggle to recognize patterns, while the human brain revels in the process. That’s not always a good thing. Our minds adapt to poor or incomplete data by filling in the blanks with shortcuts and assumptions. With better data, the machines are practically begging us to abandon stereotypes like “soccer mom” and respect that each person has a unique cross-section of interests and characteristics.

6. Realize that a robot never told a great story.

In reducing people to what data can measure, we leave out that most human of attributes — emotion. Emotions are marketing’s primary currency. People literally make decisions from the emotional center of their brain, which is why smart marketers use narrative, context and feelings to tell stories that resonate. A story created by a robot is a story devoid of human emotion, which is one more reason why effective marketing, even in the data-driven era, will always need the human touch.