Digital Ethnography for PR, Part 2: Ethnography Explained

Digital ethnography is a relatively new field of study which promises, when done well, to deepen the relationship between communicators and their audiences by developing and understanding context. In this series, we’ll examine digital ethnography – a field of study pioneered by our colleagues at NATIONAL Public Relations. We’ll explore why it’s important, what it is, major frameworks and limitations, and how digital ethnography will be practiced by PR practitioners.

Why is digital ethnography important?

We are overwhelmed by data. We have so much of it, and yet we rarely use more than a fraction of it. We have so much of the what in marketing analytics, and so little of the why. The promise of ethnography is to uncover the why, the story behind the data.

If we know the why, why people make the decisions they do, we are able to better interpret the what, the decisions recorded in our data. When we understand the why and the what, our marketing and communications improve. The results we generate by aligning our communications to our audiences improves.

Before we delve into digital ethnography, we need to explore the what more: what is this practice?

What is digital ethnography?

The definition of classical ethnography is the scientific description of the customers of individual peoples and cultures. Ethnography specifically refers to a method of study, a way of collecting data by trained observers, about people and their behaviors.

Ethnography originated in 1834 as a practice in the field of anthropology, and is keyed especially to the usage of language, of how people use language to communicate with each other. An anthropologist uses ethnography to learn and describe a culture. Classical ethnography often involves an anthropologist embedding themselves in a foreign culture and observing it for significant periods of time, to better understand the culture and how it functions.

Digital ethnography follows similar practices, but uses digital media and communication as the primary means of obtaining information. Documents such as websites, digital news media, blogs, forums, and social media provide passive data collection for digital ethnographers. Surveys, interviews, usability studies, and analytics tools provide more active data collection to supplement or inform the passive data collection.

Limitations of digital ethnography

By definition, digital ethnography willfully ignores the offline, non-digital portion of peoples’ lives. Prior to the mobile revolution, this exclusion represented a serious gap in the practice, significantly diminishing its credibility. However, with audiences now integrating the smartphone and other mobile devices into every aspect of their lives, digital ethnography’s data collection is far more representative.

Digital ethnography still partially suffers from classical ethnography’s main design flaw: the Hawthorne effect, or observer effect. When we watch others, their behavior may change as a function of being observed. In digital ethnography, the Hawthorne effect is not only triggered by researchers, but by our online community. We are aware as audience members, as participants in digital and social media that we’re always being observed by others.

The Hawthorne effect is accompanied in digital ethnography’s known limitations by an additional form of distortion, a variation of cheerleader effect. Cheerleader effect is a cognitive bias in which individuals believe they are more attractive in a group and thus behave differently; in social and digital media, this leads to people publishing only the “greatest hits” of their lives, rather than a balanced, representative view of their lives. For every amazing meal someone photographs on Instagram, they may eat dozens or hundreds of meals they never feature. This combination of the Hawthorne effect and cheerleader effect must be accounted for and built into any digital ethnographic study.

Advantages of digital ethnography

The primary advantage of digital ethnography is scale. In an analog, offline study, we require significant resources just to observe and study a small population for years; if chosen poorly, any bias will invalidate the study and destroy years of effort and resources.

In digital ethnography, we have a large body of data to pull from without requiring real-time observation. Using social and digital search tools, we’re able to extract years of historical data from participant pools numbering from dozens to thousands of people, limited only by our data processing and interpretation capabilities. We’re also able to run multiple variations of experiments and studies with historical data. If we find that our original data collection parameters had an unforeseen bias, we can restart without needing additional years of observation time.

Next: ethnographic frameworks

In the next post in this series, we’ll explore six major ethnographic frameworks and how we apply these frameworks to digital ethnography for public relations and marketing communications.

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