Why Big Data Will Never Replace Creativity

Data scientists work their magic to help marketers with everything from customer relations to pricing. But they have their limits

Written by Alicia Androich for Marketing

Much more than just a URL-shortener, Bitly keeps close tabs on what people all over the world are reading and sharing in the social sphere. Its chief scientist, Hilary Mason, is a self-professed data nerd who was named one of Fast Company‘s “100 Most Creative People in Business” this year. Mason went to Brown University and Grinnell College for computer science, and spent part of her early career as a software engineer. She spoke with Marketing Magazine to explain Bitly’s appeal to brands and why big data will never replace creativity.


There are a couple of reasons big data is popping up on most conference agendas these days, says Mason. While the work data scientists do with large data sets has been possible for ages, there’s been a massive reduction in the cost and an increase in the usability of the tools. The engineering aspect or analytics side of making data useful used to be professions in themselves (and in some cases still are) because that work was so complex, but Mason says it’s now become so much easier and more affordable that a data scientist can do the engineering, analytics and mathematics. Data scientists also do what Mason says is the most important part, which is either have the domain knowledge to make a good decision or the communication ability to sit down with their clients “and help them make better decisions based on data.”


Mason joined Bitly in 2009 in the days when its whole team fit in one elevator. In her first year with the New York-based company her title was “engineer,” but she insisted they put “scientist” on her business card. “I thought it sounded cooler,” she says. As the company has grown—there are now roughly 55 people there, including interns—so has Mason’s job. She’s progressed from being a hands-on coder to her present post, which sees her leading a team of six data scientists and working closely with the CEO and the board “to try and make decisions about where the business and products can actually use the data most effectively.”


“Bitly is the set of links people are sharing with each other on social networks, so it’s basically a huge database of gossip,” says Mason. She jokes that people joining her team of data scientists go through an emotional cycle that starts with excitement about how cool the data is, “then you just get really depressed because you realize that so much human attention is going to Kim Kardashian and Justin Bieber and some sports guy who scored a point.” Next, though, comes the pivotal a-ha moment when Mason says the data scientists “realize that for the first time, we’re able to actually study human communication at the scale at which that communication is happening.” The Bitly team sees data from hundreds of millions of people every day and Mason says, “I still find that completely amazing.”


Out-of-the-box sentiment analysis software or survey research counts the data and can provide numbers or graphs, but Mason says that data only represents a portion of the real world—not the whole thing. A data scientist’s job, she says, is to take the data that’s been counted then contextualize it, come up with a theory about why it appears to be the way it is, test that theory, and try to make better decisions.

“There is a lot of hype around how big data will replace creativity and, I know this isn’t the technical term, but I think it’s bullshit.” Although she hears lots of fear from people that data “is either going to replace them or somehow prove that they’re not actually good at their job,” she doesn’t think it’s justified. “The data should be a tool to empower people to be better at what they’re doing professionally, and I can tell you as someone who looks at data all the time that it is not going to replace creativity; it’s not going to replace a human connection.” As Mason sums up: “Data can tell you whether A or B is a better choice, but it can never tell you what A or B should have been in the first place.”

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