Thick data and big data: why you need both to make user-conscious decisions

By Steven Carr | November 23, 2020
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thick data neural network

Making decisions can be difficult, especially when confronted with uncertainty. Nevertheless, business decision-makers are faced with making critical choices on a daily basis—some that can heavily impact their customers. So naturally, they want to make the right decisions. But doing so often requires them to predict the future, which is nearly impossible. By leveraging big data and thick data together, decision-makers may not be able to predict the future, but they just might be able to come close.

By now, you’ve heard of big data, but thick data might be a newer concept. In this post, we’ll walk you through thick data (originally termed by Tricia Wang, global tech ethnographer and recent presenter at UserTesting’s Human Insight Summit) and how, paired with big data, forms a more complete context of any given situation.

What is thick data?

At its core, thick data is qualitative data (like observations, feelings, reactions) that provides insights into consumers’ everyday emotional lives. Most often collected through ethnographic research methods, it can also be captured during remote usability testing when the mic and camera are turned on.

thick data definition

Because thick data aims to uncover people’s emotions, stories, and models of the world they live in, it can be difficult to quantify. It’s squishy and is collected in small sample sizes, but that doesn’t make it insignificant or unimportant. In fact, despite all of that, thick data provides never before seen perspective, depth of meaning, and emotionally-powered stories that can influence business decisions and build customer empathy

This is why, together with big data, it can paint a more holistic view of consumer wants, needs, and desires. But before we get into that, let’s take a moment to define big data.

What is big data?

Big data, for all intents and purposes, is the opposite of thick data. Most obviously because it’s quantitative in nature—meaning it deals with numbers and figures. What’s characteristic about big data is that it’s collected at such a large scale, and growing exponentially over time, that most processing powers aren’t even capable of capturing, storing, and analyzing it. Enter: a $138.9 billion market dedicated to just that.

big data definition

Because big data is captured at such a high volume, it becomes difficult to analyze—to do so, it needs to be normalized, standardized, defined, clustered, the list goes on. But once this is complete, data scientists can focus on certain elements in the mass of data to isolate trends and make predictions. This is amazing and valuable, but there’s only one problem: big data is largely void of context and emotion.

Thick data can fill the cracks in the trends that big data uncovers by providing the necessary context and emotion that is lost when making big data usable.

Why big data needs thick data

Only using big data or only using thick data is like opting out of one of your five senses. Alone, each of your senses is valuable and provides you information about the world around you, but together they form a more holistic view of any given situation. The same goes for data. By integrating big and thick data, organizations are able to depict customer needs more holistically.

That’s because big and thick data produce different types of insights that complement each other. Like we mentioned, big data takes massive amounts of data from millions (even billions) of customer data points to uncover patterns at scale, while thick data takes smaller customer samples to bring to light human-centered patterns in depth.

In other words, thick data aims to build empathy and understanding of humans between data points while big data uncovers insights by isolating variables to identify patterns. 

Thick data grounds our business questions in human questions. -Tricia Wang

Collect thick data with remote usability testing

You don’t need millions of customers to tell you the same story in order for thick data to be impactful. In fact, if you’re able to observe the same frustration, pleasure, or irritation with 3-5 people, you’ll probably take notice. That’s exactly why usability testing is so important. 

Whether you’re testing your marketing messagingcollecting feedback for product development, or simply discovering the needs of your customers, remote usability testing allows you to get the necessary information to ensure you’re meeting their needs and expectations. Ultimately, in order to understand (and sometimes predict) people’s actions and what drives them to your business (or not), you need to understand the humanistic context. Meet your customers exactly where they are and get a first-person understanding of whatever it is you need to test.

How to marry thick data and big data with UserTesing and Qualtrics

Late last year, UserTesting and Qualtrics formed a unique partnership to make it easy for customers to pair qualitative insights and quantitative data, so they can better understand why their customers do what they do, and want what they want.

The UserTesting Human Insight Platform empowers businesses to see, hear, and talk with consumers, customers, and a wide range of customizable panels to gather audio, video, and text responses that drive fast, informed decision-making. By giving organizations richer qualitative data that explains the ‘why’ more deeply than big data analytics alone possibly could, UserTesting and Qualtrics’ mutual customers can create deeper customer empathy. And those deeper insights translate directly into more user-centric action.

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About the author(s)
Steven Carr

Steven is a Marketing Content Strategist. When he’s not inserting oxford commas where they belong, you can find him shooting pool at a local dive or building killer playlists on Spotify.