Thick Data - Big Data's complimentary brother

Thick Data – Big Data’s complementary brother

Critical marketing decisions are often backed by customer research. But when it comes to data-driven decision making, quantitative/Big Data often does not give you all the answers you need. In “Big Data Is Only Half the Data Marketers Need“, a highly recommended article by Mikkel Rasmussen and Andreas Hansen published in Harvard Business Review in 2015, we learn that Big Data is best complemented by “Thick Data“ – insights gained through psychological, ethnographic and anthropological methods. These insights help you answer the “why“ and “how exactly“ of customer behavior, and thus give you an idea wether your actions will succeed or not.

Big Data: quantitative description of the entire sample 

Data is regarded as the gold of the digital age – as Big Data it is automatically generated in large quantities at interactions between companies and customers. The advantage of mass data is that it is generated by the entire customer population and not by a small sample. However, like all types of quantitative data, this data can only describe human behavior in terms of its frequency, but cannot explain it. For example, it provides information about which products were most frequently purchased, or which version of a newsletter was clicked more often, but it remains unclear why this is the case.

Thick Data + Big Data = Real Data 

Thick Data, insights gained through psychological, ethnographic and anthropological methods, are of help. Above all, they shed light on the motivation behind human behavior, the “why“ and the “how exactly“, the important details of something that distinguish between what works and what doesn’t. On the other hand, Thick Data cannot provide any information about the “how much“. Both approaches complement each other here: Thick Data enables genuine and deep insights into the consumer’s world and can offer great strategic added value. Big Data, on the other hand, serves as a crosscheck, validating hypotheses found through Thick Data. Or it can provide patterns that can then be explored further with Thick Data. 

So far, however, Big Data and Thick Data are mostly used by different groups and there is little communication between the two sides. Awareness and reconsideration are necessary here. Combining both perspectives pays off through more meaningful insights – resulting in an enlightening whole with real strategic added value. Together, Big and Thick Data can become Real Data.


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