These are the issues presented in a new book by Colin Strong, a market researcher, speaker, and writer. His book, Humanizing Big Data, raises some interesting questions that anyone in marketing research – and indeed, anyone interested in big data analytics – should consider.
In short, Colin argues that standard big data is missing a vital ingredient in its search for data-fueled enlightenment: data points, are, after all, provided by people. And people are anything but simple data points.
Can Big Data Fall Short?
Another voice on this subject, Mindjet data scientist Anna Gordon, summed it up this way in a VentureBeat post: “Basically, what we’re seeing is that new elements of behavior are affecting data, such as politics, opinions, and agents interacting with and influencing each other. So, in addition to looking at data in the traditional way, we must now consider political and social structures, and how people learn from and influence each other; we must consider how ideas flow through social networks, what motivates people to contribute to discussions, and the consequences of engagement.”
In other words, you can’t isolate data from its sources and motivations. Strip away the human element, and even the most sophisticated big data machine can go wrong.
How Can Data Be Humanized?
The idea of humanizing data may seem counterintuitive on its face, but it’s really not. As our experts point out, data starts with humans. Therefore, at some point, humans must also be involved in the processing of data.
Humanizing Big Data argues that data isn’t really something that can be fully automated. Rather than handing the entire processing task over to super-smart machines, the author makes the case that the human element, so integral to understanding the results, can’t be removed from the analytics process.
This book ultimately raises valid points and interesting questions. What’s the best approach for the small business that wants to get into data analytics? Are we forgetting the customer while we embrace the soulless technology that delivers the data? And what about the future? Can we extend big data to do more than just improve marketing?
Big data has reached the point where it has to answer some equally big questions, and Humanizing Big Data asks quite a few of them. For most businesses, though, the question boils down to this:
What Does Humanized Big Data Mean for Me?
Is big data humanization a challenge or an opportunity? The goal is to shift the spotlight to the most important people in any business: customers and potential customers. But applying it can also mean having a rethink of how your data organization does its job.
It certainly is no fault of Colin’s that his book raises a lot of questions that don’t have clear answers (at least not at this point in time.) That’s what the book was designed to do. It has started a conversation that any market researcher, and really anyone in marketing, should be part of.