Editor’s note: John Dick is CEO of CivicScience, a Pittsburgh-based research firm.
A couple of years ago, our office used an imaginary swear jar to collect a fine when anyone uttered the term big data. At the time, most self-respecting statisticians and database engineers would scoff at the term, along with other buzzwords like data scientist.
Eventually we succumbed. Engineers changed their job titles to data scientist – which, by the way, instantly increased their salary requirements. No roles or skills changed in any meaningful way. The hard-core Carnegie Mellon computer science grads around the industry had been working with large data sets and tools like Hadoop for a long time. (Note: Saying big data will still elicit an eye-roll or two around the office.)
There is no denying that the pace and scale of data being generated today is unprecedented. It’s an exciting and promising development, for the most part, with the potential to fundamentally alter everything from health care and energy to politics … and even marketing research.
The proliferation of data
Many in the marketing research industry view the proliferation of data and analytics as a scary frontier (at best) or a threat to their job security (at worst). Who needs people to administer 20-person focus groups and 800-person survey samples when consumer information is flooding in by the terabyte while you sleep? Looking for a great answer to that question? Important things like forward-looking intent and in-the-moment perception are best ascertained by asking people things. While consumer data sets are inherently backward-looking, the best predictive analytics will never be as reliable as asking someone, “Are you planning to switch your wireless carrier this month?”
I’m not here to defend the sustaining virtues of analog marketing research techniques. I’ll be happy to do that another day. The truth is that large-scale data and analytics are here to stay and will continue to grab a larger budget. If you don’t figure out how to make yourself relevant in this new world, you better start driving for Uber.
But don’t dismay. You see, the data themselves are not the endgame. Go to any marketing research conference if you want to hear about the difference between data and insight. Big data is not the enemy. Think of it as fuel. As data sets get larger and larger, they will fuel the development of more powerful technology. This is how the proliferation of data will change marketing research – and the roles of its practitioners – most profoundly.
Driving technical innovation
When marketing researchers are playing with modestly-sized piles of data, the tools required to manipulate them are pretty simple. Maybe an Excel spreadsheet or CSV file here, SPSS or an R package there. But, as the size of these data sets continue to grow, they are driving technical innovation that was incomprehensible just a few years ago. The field of predictive analytics is a big leap, but projects still require a lot of customization, supervision and translation before outputs can be useful to the C-suite. There’s still a lot of work to be done – but it’s happening.
Look at work by non-marketing research companies like Narrative Science and Automated Intelligence. These businesses are pioneering the fields of natural language computation. Narrative Science, for example, can crawl the box score of a recently-completed baseball game and a write a fully-formed news article, with personality and tone that is virtually indistinguishable from a human-written piece. Why can’t that same capability be applied to a marketing research data set?
Now, take that a step further and think about the role artificial intelligence or machine learning can play. The same machines that turn data files into prose can teach themselves to discern valuable or unexpected insight from obvious or uninteresting ones. They can learn what kind of information you or your executives find most useful and focus only on those in their analysis. No doubt, leading marketing researchers (and aspiring garage start-ups) are thinking about these things or have already begun developing and using them. And the capabilities will only get smarter as more and more data run through the pipes.
Future of MR
Data are the textbooks that are enabling other technologies – namely automation and artificial intelligence – to learn. Before you begin to fear your role in the future of MR and automation, you should look at the value you bring to your organization. A quality marketing researcher should not be at risk of being replaced by a robot.
Researchers have the context and conviction no one else has. Imagine how much different your work would be if you didn’t have to spend so much time synthesizing data, drafting reports and creating PowerPoints – or even writing e-mails. As marketing researchers respond to business needs faster, having time to take their place in the boardroom becomes more of a reality.
The robots of the future will work for you and that will make you indispensable. All because of big data (puts dollar in swear jar).