Ethnographic Methods in Practice at DreamHack
- FanAI’s work with DreamHack North America made use of both Big Data Analytics and Ethnography
- By further refining our research questions between ethnographic data collections we can provide actionable and relevant insights to clients
- Ethnographic insights armed DreamHack with the knowledge to better engage their fans
- Ethnography bolsters Big Data Insights with context that humanizes the data
The study of DreamHack’s events and community began as an exploratory study to aid the organization in creating better North American events and understand their North American audience. It was DreamHack’s second year putting on North American festivals and with events planned around the US, it was a perfect opportunity to examine how events in different parts of the country may differ.
Ethnographic Methods Overview
The investigation began with analyses of ticketing and attendee data of the DreamHack audience for the Austin 2017 event, the first of three mainline DreamHack events for the year in the US. This also involved deploying an ethnographer (yours truly) into the Austin event to experience, observe, and interview attendees, crew and staff. As the ethnographer on site, I went in with a notebook, audio recorder, credentials, and a bag of merch supplied by DreamHack to compensate participants for intercept interviews. This pilot study of sorts laid the foundation for a longitudinal study of the audience over the course of the year.
Most of the ethnographic methods we’ve discussed involve being present in the cultures and communities we study, that is one of the biggest advantages and hallmarks of ethnography. Through immersion in the data, an ethnographer gains a more nuanced understanding of the community at hand and can better position data within the context of the experience being studied. In the case of the DreamHack work, we relied on a combination of semi-structured interviews and participant observation.
To avoid any misconception, interviews in this case do not just refer to surveys, or running through a set number of questions with a participant and looking for set responses — ethnographic interviews rely on unstructured and semistructured methods and take the form of a conversation rather than an inquisition. By leaving questions open and engaging in an open dialogue with participants, we can gain greater understanding of the underlying themes and factors contributing to their response. Rather than simply accepting a response at face value and moving down a list of questions we have an interview guide from which we can pull topics and guide conversation, but the response is ultimately led by the participant.
In ethnographic data collection, our goal isn’t always to get defined answers to the questions we have, but to be guided in understanding the nature of cultures and communities.
Into the Breach: DreamHack Austin
While at the Austin event, I observed crew patterns, from setup to tear down of the event. I interviewed attendees, from those locals who were just there to see what it was all about to veteran LAN attendees and people who only had interest in one of the games on offer at the festival. I participated in freeplay events, watched the way that crowds moved through the venue, and took notes about everything from how the event changed depending on time of day, to conversations with just about anyone at the event.
Core to some of this investigation was the relationship between attendees and sponsors in an event context. The investigations at Austin, paired with the spend data analysis revealed a few areas of interest where DreamHack fans tended to spend more. For instance, the spend data indicated the audience spent higher than the national average on auto parts and accessories. Initially this seems like an outlier, until you add context.
DreamHack has always been first and foremost a LAN event, as such the audience contains a good amount of people who build their own gaming PCs. It stands to reason that someone with enough general know-how to handcraft a liquid cooling system for their PC likely has the technical prowess needed to do most of the routine maintenance on a car. In the ethnographic interviews with participants we found that PC building wasn’t the only hands-on work DreamHack audience members did. From home improvement to auto repair, cosplay to prop making, our ethnography revealed an audience rife with tinkerers, crafters, and hobbyists. With that information in mind we set out to further investigate additional non-endemic sponsorship opportunities and festival concepts while still bolstering our understanding of the overall culture of the DreamHack audience at both the Denver and Atlanta events.
The Research Continues: Denver and Atlanta
The data collection at Denver and Atlanta were much the same with the exception of the interview model switching from shorter intercept interviews, wherein an ethnographer may talk to someone for five to ten minutes with little to no structure, to longer semi-structured interviews that had more direct structure but were still open ended in nature.
Over the course of the next two events we worked and reworked the interview and research questions, framing them within the context of what we were seeing in the larger ticketing data sets. As the Big Data sets continued to give us everything from where participants were from, to their spending and social media habits, the ethnographic data helped us define personas around how attendees felt about sponsors and sponsorship not just at events but in the esports space in general. Ultimately we defined a set of 4 proto-personas to describe some of the attitudes toward sponsorship and esports communities present in the DreamHack audience.These personas were not the typical marketing materials, they did not segment the audience by demographics or produce a “market segment” DreamHack could target. These personas were meant to arm DreamHack with knowledge in how their audience thinks about and understands sponsorship within their community, with that knowledge they can communicate more effectively to their community and make activations work better for sponsors.
At the Intersection of Qualitative and Quantitative
In the above case, the interplay between ethnographic insight and Big Data flowed in both directions, with Big Data insights influencing ethnographic research questions and the ethnographic work providing context to what we saw in the data. This powerful combination allows FanAI to humanize the numbers and make them more approachable because they make sense within a context of reality. What’s more, rather than bolstering these insights on either side with assumptions based models, or self fulfilling survey data we continually challenge the data laid forth by either methodology.
People cannot be wholly defined by numbers, while advanced models of social physics can give us a generalized understanding, they can’t substitute for an ecological approach or experiential data. Research at its heart is meant to make salient the truth or at the very least the reality of experience. We make a commitment to rigorous research that gets at that truth rather than constructing narratives based around what people want to hear or around preconceived notions about the nature of the space. This commitment positions FanAI as a firm uniquely in the market of analytics we not only commit to the best practices in both data science and research, but we use the result to help sustainable growth of the esports space.