Big Data is Still About People

The digital revolution has disrupted a century of economic, social and political norms bringing a variety of new opportunities as well as unfamiliar and complex problems. As a media psychologist and researcher, I am excited by the new approaches to audience analytics enabled by digital and social technologies that let us ‘listen’ unfiltered to the consumer’s voice. Buzz words such as ‘big data’ and ‘sentiment analysis’ reflect the eagerness to put large scale data gathering and sophisticated tools and algorithms to use in hopes of capturing the promised new insights and improved predictive capabilities. 

The avalanche of data techniques and allure of new insights–not to mention the cognitive bias that says ‘numbers must be true’– can distract us from remembering three key things:

1)    Data is about people. All those numbers represent individual customers who only perform “statistically significantly” with some probability (i.e. not all the time) in the aggregate, but respond to empathy all the time, individually.

2)    People’s behavior adapts to environmental change but core psychological drivers remain the same. (In other words, what we want is pretty much the same. How we can get it done changes with technology.)

3)    Data measures past activity–what customer did–in a specific context at a specific time within larger social conversations. Data does not tell you why they did something so you can figure out what they will do in the future.

That’s why I’m so big on integrating media psychology frameworks and qualitative methodological approaches such as narrative inquiry into data analysis. From the start, qualitative research has sought to provide a means for interpreting another’s experience. Qualitative researchers make two assumptions: 1) Competent observers can objectively and clearly report on observations in the social world and on the experiences of others; and 2)  The individual is the “expert” on his or her experiences and emotions.  Where researchers relied solely on data gathered from interviews of life stories and personal experiences and other documents such as letters and photographs, qualitative researchers are now able to use a myriad of social media sources to investigate the meaning their subjects make of their life experiences, such as consumption patterns or relational behaviors.

The methodological and theoretical approaches in qualitative research allow data and research teams to dig deeper and learn who their consumers really are and what they really want in human terms. Narrative patterns reveal the stories, cognitive frames and biases behind consumer behavior that form the consumer’s understanding of how the world works and how your product or service fits into it. This type of analysis forms a critical bridge between the human and empirical that not only improves confidence in predictive analytics but gives decisionmakers actionable insights to position products and services that can engage the consumers in what matters to them, speak in their voice and anticipate future.