Big data is generated by the millions of touch-points companies have with their customers across platforms and devices. Thick data is derived from observing human behavior and its underlying motivations. Thick data has been utilized by companies interested in the social sciences while big data has been used by people with an analytics bent and there has been very little dialogue between the two.


Big data relies on machine learning, reveals insights with a particular range of data points, identifies patterns by isolating variables and loses resolution.  On the other hand, thick data relies on human learning, reveals the social context of connections, accepts irreducible complexity and loses scales.

Companies that rely too much on numbers, graphs, and factoids of Big Data risk insulating themselves from the rich, qualitative reality of their customers’ everyday lives.  By outsourcing thinking to Big Data, our ability to make sense of the world by careful observation begins to wither, just as you miss the feel and texture of a new city by navigating it only with the help of a GPS.

Thick Data is the best method for mapping unknown territory. When organizations want to know what they do not already know, they need Thick Data because the act of collecting and analyzing stories produces insights. Stories can inspire organizations to figure out different ways to get to the destination. Thick Data often reveals the unexpected. It will frustrate. It will surprise. But no matter what, it will inspire. Innovation needs to be in the company of imagination. Many companies are shifting their perspective from a data-centric one to a human-centered one.

Thick Data fills the gap between what organizations have, and what they need to be more instinctive and understand how people feel and their emotions that underpin the customer experience. Now is the time for marketers to be more people focused, more emotional and empathetic in their approach. Engaging with Thick Data enables organizations to develop real, positive relationships with the people they are  targeting and stop thinking about them as numbers. It brings in the context of their complex lives which plays a significant role in what they do and why.

Melding big and thick data together requires changing practices, hiring new people, and allocating funds away from familiar ways of doing things. But once you’ve seen the power of real data, you’ll question the millions of dollars wasted on surveys and focus groups.  Big data is a powerful, and helpful tool companies should invest in. However, companies should also invest in gathering and analyzing thick data to uncover the deeper, more human meaning of big data. Together, thick data and big data give you an incredibly insightful advantage.

When organizations want to build stronger ties with stakeholders, they need stories. Stories contain emotions, something that no scrubbed and normalized dataset can ever deliver. Numbers alone do not respond to the emotions of everyday life: trust, vulnerability, fear, greed, lust, security, love, and intimacy. It’s hard to algorithmically represent the strength of an individual’s service/product affiliation and how the meaning of the affiliation changes over time. Thick Data approaches reach deep into people’s hearts. Ultimately, a relationship between a stakeholder and an organization/brand is emotional, not rational.

Big Data and Thick Data complement each other. This is a great opportunity for qualitative researchers to position the context of Big Data’s quantitative results.

Old big data analysts don’t die – they just get broken down by age and sex

Written by Bob Pritchard


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