• Ujwal Arkalgud

Insights and Innovation Professionals: Why you should care about big data ethnography

Symbolic capital, tension, and tempo — the three tenets of understanding the why behind human behavior.

Summary: There’s no other methodology that enables the identification symbolic capital (an intangible resource that grants one power, prestige, privilege etc.), the understanding of the tensions between different forms of symbolic capital, and the calculation of tempo (rate of change and exchange of capital).

We define symbolic capital as a resource that is acquired by exhibiting or drawing on particular forms of knowledge, competencies or skills and interpersonal relationships that, like money, provide access to things. These intangible forms of capital can be converted into other intangible but valuable assets, such as prestige, honor, privilege and acceptance into a particular community and beyond (which, in turn, can also translate into actual capital, that is, money). A university education is perhaps the most obvious manifestation of this. Irrespective of the fact that you might have spent your university years hungover and skipping class, the mere fact of having somehow attained a university degree — especially if it’s from an elite US institution — will open certain doors for you based simply on the value that has been assigned to the degree itself. In other words, the symbolic capital you acquire may have little to do with what you actually learned and more to do with the way “university education” is understood and valued by society at large.

The premise of the 2001 rom-com Legally Blonde is a good example of this. Rejected by her longtime boyfriend because he perceives her as not being serious or smart enough (due largely to her blond hair!), the film’s protagonist Elle Woods takes on the challenge of being accepted to Harvard Law School as a way of “proving” him wrong. Despite the plot twists in the rest of the movie (that confirm Elle’s actual intelligence), this framing of Harvard Law School as synonymous with intelligence and responsibility is what symbolic capital is all about: the meanings that society attaches to certain ideas, practices or beliefs that then become access points to honor, prestige or power.

Tension refers to the power struggle that inevitably exists between different forms of symbolic capital within the context of a culture or marketplace. For example, a Harvard education carries with it two opposing forms of symbolic capital. One that points to the idea of intelligence and responsibility in a positive sense and the other that points to the idea of elitism and exclusion. These are both forms of symbolic capital that provide people with opportunities to gain power, prestige, and acceptance, but obviously in different social and contextual settings. Understanding and quantifying this tension is critical to our understanding of culture and our ability to predict the future of a culture (as there will eventually be a winner or the creation of a new form of symbolic capital that will aim to revolve the existing tensions).

In our modern world of digital connectedness, information travels at breakneck speeds and people communicate with each other like never before in human history. As a result, the tempo of culture (of the nuances and meanings that people assign to the world around them) is highly variable. When transposed into the marketplace, this means that consumer trends are in a constant state of flux. One only has to think of the dramatic fluctuations in the “green” household cleaning industry, which was virtually unknown about a decade ago but then exploded on the market as sales of eco-friendly, natural and organic cleaning alternatives more than doubled from $303 million in 2007 to $640 million in 2011.50 This boom, however, was suddenly followed by a period of stagnation and even decline. In recent years, there has been another upward trend in green household cleaning products, primarily with mass-marketed brands such as Clorox Green Works or private label brands from giants such as Walmart, which introduced an all-natural line of affordable cleaning products in 2013 with huge success. Now, the global market for natural and plant-based household cleaners is projected to grow from $17.90 billion in 2017 to $27.83 billion by 2024.

What dominates the market today is thus no guarantee of popularity tomorrow. In the past, cataclysmic events such as war or epidemics influenced broad-sweeping changes across society. Today, everything simply moves faster, and because information is so easy to come by, meanings and opinions change at lightning speed. Measuring the tempo of cultures and the spread of symbolic capital is therefore critical to our ability to understand and predict the impact of trends on our business.

Big Data Ethnography is more important to innovation than you think.

It is here that we turn our attention to online ethnography, also known as virtual ethnography, cyber ethnography, netnography or social media netnography. Based on the principles of immersive observational ethnography discussed above, the online adaptation moves away from the traditional face-to-face model and focuses instead on close observation of everyday human activities as they take place online. The ability to capture people’s “natural” everyday behavior remains at the center of this modified methodology. A major difference between traditional and online ethnography is that the latter does not directly observe the research subject; thus, the “interaction” between researcher and subject remains mostly anonymous and/or noninvasive. There are several important implications of this, including a significant reduction — if not complete elimination — of interview bias (research subjects are just “being,” communicating online in natural and non-prompted ways rather than responding to and possibly altering their behavior in the presence of an interviewer/researcher). The anonymity of online ethnography also reduces instances of respondents lying in order to save face when it comes to sensitive topics. Taboo loses its power when you are protected by a pseudonym.

Let’s take menstruation as an example. We were commissioned by a Fortune 1000 company to help them understand the culture of managing menstrual pain. It is generally difficult to obtain rich, in-depth data on this topic because it is historically sensitive and culturally “taboo.” But online ethnography allowed us to be a fly on the wall, as large samples of women engaged online. We could overcome the traditional alibis that women would share in a focus group and eliminate the bias of the research to get to a deeper, rawer representation of women’s experience of living with and managing menstrual pain. What we found was that a significant portion of the core market around menstrual pain (it’s worth noting that this is a substantially sized market of more than ninety million consumers in the US) was concerned with pain acknowledgment: many women talked about the frustration of having their menstrual pains dismissed or minimized and tried to find ways of having their pain recognized. This concern manifested in frequent online conversations about kidney pain, which we then interpreted as a strategy that women employ to render their menstrual symptoms more universal (i.e., less woman-focused) in the hope of being taken more seriously. For our client, this was valuable information for product development and marketing, as they could now confidently engage in a business plan that legitimizes the pain experienced by its consumer base by communicating that “your pain is real” and that menstrual pain could possibly affect other areas of health.

A key element of the kind of online ethnography we are describing here is big data. Defined as “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions,” big data used in conjunction with the ethnographic method enables researchers to observe and interpret the billions of interactions taking place online, in detail, in depth and at any given point in time.

The intersection or mixed methodology of big data analysis and ethnography provides us with the social context and nuanced meanings that exist within cultures while also capturing the temporal scope or rate of change of these contexts and meanings over time. When applied to significantly sized samples, this mixed method enables the quantification of ethnographic insight. In turn, this allows us to identify the hidden meanings that consumers inadvertently create in each of their online interactions (as people do offline as well).

When we talk about big data ethnography, what we mean concretely is that we rely on the computational power of algorithms (i.e., machine learning) to identify meanings and then capture and “measure” the relative strength of each meaning that consumers associate with a particular topic over time (i.e., the search term under consideration). Context is key here, that is, the cultural context in which a particular topic or trend is placed. Without this context, you won’t be able to do much more than engage in basic pattern recognition.

Big data ethnography is really the only method today that allows us to decode the forms of symbolic capital that drive cultures while also opening the door into an understanding of tension and tempo — all critical ingredients in our ability to understanding the forces in the present that will shape the future of our business.

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