Digital Ethnography for PR, Part 4: Example Study

digital ethnography

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.

From Concept to Reality

Up until now, our exploration of digital ethnography has been largely theoretical. What do we need to do to transform it from intellectual curiosity to practical application?

Begin with Spradley

Recall from our previous post that Dr. James Spradley’s 9 dimensions of ethnography forms the master foundation of most ethnographic studies.

The 9 Dimensions in Spradley’s foundation are:

  • Space: the physical setting, such as rooms, places, locations, etc.
  • Actors: the people involved in the study.
  • Activities: the activities conducted by the actors.
  • Objects: the physical elements involved in the activities and space, used by the actors.
  • Acts: the individual actions taken by actors.
  • Events: context of the acts, actors, and space, such as a meeting or a dinner.
  • Time: the sequence of events from beginning to end.
  • Goals: what the actors seek to accomplish in their acts.
  • Feelings: what emotions the actors express in the events.

To begin, we must define what we are looking for, and digital or not, ethnography is intricately tied to the places and spaces people live, work, and play. Suppose we sell coffee. We want to understand the coffee drinker better. How might we go about investigating the ways in which people consume coffee?

Translating Spradley’s 9 Dimensions to Digital

Let’s start with an obvious context: the point of purchase of coffee. Using geographically-based social media monitoring tools, let’s start with Spradley’s framework, one dimension at a time.

Space: a competing coffee shop. Here’s one near the SHIFT Boston office.

map-geo.png

Actors: who are the people in this space? We dig into the biographies of their social media profiles.

collage-geo.png

We have a startup founder who visits frequently, as well as students, remote workers, home designers, and more.

Activities: what are the people doing?

As we scroll through the various photos and text updates, people are obviously drinking coffee, but what else are they doing? A key activity is study; they post photos of their notes, notebooks, and work materials.

Objects: what are the items in photos?

We see notebooks. We also see tables, pens and pencils, food and drink (logically), laptop computers, reading materials.

Acts: what do the actors say they’re doing?

Studying. Working remotely. Enjoying seasonal drinks.

Events: what events are occurring?

On the premises, we see comparatively few people talking about local occurrences, other than local bands and festivals.

Time: timeframes are automatically provided by the software; we need only note them.

Goals: this is one of the parts of Spradley’s framework which are impossible to divine solely from data diving. We don’t know why people are doing what they do, beyond the act of obtaining food and drink, and the overt items they publish. We know, for example, that they are there to work remotely or study, but we don’t know whether or not they successfully did so.

Feelings: this is another part of Spradley’s framework which is difficult to identify. One interesting artifact is that, despite the selfie culture, there are almost no selfies taken at this location.

Ethnographic Analysis

What do we conclude about the way people consume coffee, based on this location? Just from a cursory look, we see that the coffee shop is not just a place for the consumption of drinks. It’s a place of work and study as well. It’s a place where people go to do things they can’t accomplish in another context.

What we don’t see is equally telling: we don’t see large social gatherings, group photos, or even selfies. We instead see the product featured prominently.

The next step, after a qualitative study of any kind, is to gather quantitative data. How many people come to our coffee shop to work? Are they profitable visitors? How many people in the general population/addressable market would consider a coffee shop a good location for work and study?

Qualitative data like ethnography informs the questions we should ask in quantitative studies like surveys.

Insights and Actions

Based on the coffee shops we’ve been in, they’re not always conducive to study. After our ethnographic study and quantitative research, we could make decisions about how to favor work and study in our shop:

  • We could change the music to be instrumental (less distracting).
  • If our shop had televisions, we could ensure they were tuned to a less distracting channel, such as the weather.
  • We could ensure fast Wi-Fi and abundant electrical outlets to encourage people to spend time.
  • We might even go so far as to change the seating to accommodate study.

After study and implementation, we must next measure to see if our changes create the desired result: more, better customers.

Next: Other Frameworks

Spradley’s framework, as shown above, has limitations when it comes to digital ethnography. In the next post in this series, we’ll examine other ethnographic frameworks and whether they’re suited better to digital ethnography.

Christopher S. Penn
Vice President, Marketing Technology

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Posted on September 26, 2016 in Ethnography, Public Relations, Qualitative, Research

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About the Author

Christopher S. Penn is an authority on digital marketing and marketing technology. A recognized thought leader, author, and speaker, he has shaped three key fields in the marketing industry: Google Analytics adoption, data-driven marketing and PR, and email marketing. Known for his high-octane, here’s how to get it done approach, his expertise benefits companies such as Citrix Systems, McDonald’s, GoDaddy, McKesson, and many others. His latest work, Leading Innovation, teaches organizations how to implement and scale innovative practices to direct change. Christopher is a highly-sought keynote speaker thanks to his energetic, informative talks. In 2015, he delivered insightful, innovative talks on all aspects of marketing and analytics at over 30 events to critical acclaim. He is a founding member of IBM’s Watson Analytics Predictioneers, co-founder of the groundbreaking PodCamp Conference, and co-host of the Marketing Over Coffee marketing podcast. Christopher is a Google Analytics Certified Professional and a Google AdWords Certified Professional. He is the author of over two dozen marketing books including bestsellers such as Marketing White Belt: Basics for the Digital Marketer, Marketing Red Belt: Connecting With Your Creative Mind, and Marketing Blue Belt: From Data Zero to Marketing Hero.
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