Articles on how big data can increase sales and customer connection are all over the internet. “Big data” refers to data sets that require new processing and storage methods due to size and complexity. People are buzzing about it, but big data is often discussed in isolation, and this makes it seem like a catch-all-solution.
Academic research & big data
Coming from an academic background, I see big data’s potential differently. For me, its true potential lies in an opportunity to examine how theories developed in lab studies play out on a larger scale across different contexts. It’s a chance to understand the exceptions, small populations, and the concepts that truly are universal.
In his book Dataclysm, Christian Rudder, describes one of the first attempts to connect big data to academic research. Because of its ”bigness,” these datasets allow for a more complete description of some populations than ever before. Through multiple sources, we can understand the shared features of specific groups by combining what people write across various public forums.
Study social issues with big data
Big data also allows researchers to study the things that people don’t say, out of concern for social conventions. For instance, search history reveals racial biases that people don’t vocalize. This is a similar concept to what psychologists refer to as implicit prejudice; a gut feeling of aversion toward someone who’s not part of their group, which negatively affects everything from social interactions to hiring decisions.
There are differences between search history and implicit prejudice in that the former can reveal what people don’t want to say, whereas implicit prejudice measures can reveal what people don’t know they feel. Additionally, whereas laboratory studies tell us how hidden prejudice influences social interactions, big data tells us that unvoiced prejudice influences election results. Together, these sources deepen our understanding of a complicated social issue.
Improve retail with big data
By now, you might be wondering how this applies to retail. At CTi this is a question that we’re beginning to answer. For instance, we’re fusing big data with findings from group psychology to study how to best personalize customer experiences across digital and physical platforms. This combined research will allow us to understand features that are similar and different across platforms and will help us create the same positive experiences no matter how a customer is interacting with us.
But this is just the beginning. We want to be more than retail to our customers, and with connected research we can determine how to meet and support the broader needs of Canadians as they grow.