IS2000: Blog Post 1 (9/16/2018)
Ethnography, or the science of describing a group of people, is something I have found surprisingly interesting. Marketing plays an enormous role in our lives today, but I never really thought about how this offshoot anthropology can be used to make something like certain advertisements stand out. Because advertisements are everywhere we go, most people have started to just block them out, meaning businesses have to find new ways of making their products visible to their intended audience. Ethnography helps businesses to more effectively stand out because it is a field focused on qualitative data instead of quantitative data. Quantitative data is still very important but in many cases, qualitative data can give researchers more useful information because it gives consumers the opportunity to communicate what they are looking for in a product. This allows companies to make long term bets on future products or services. Quantitative data might help companies figure out what their consumers like right now, qualitative data can help them figure out a long term strategy.
There are however, a number of difficulties that come with ethnography. Because it relies entirely on qualitative data, researchers need to spend a lot of time with focus groups or interviewing individuals. Simply finding suitable candidates can take a long time, meaning researchers need to consider their schedule, budget and what sort of personnel they will need to carry out the interviews or focus groups. They also need to make sure this is all carried out ethically and likely need to compensate those who participate. Just considering the methodology takes up a lot of time. On top of that you need people to analyze the responses and consider a large strategy.
There is an emerging variant of ethnography known as “computational ethnography.” Rather than have a researcher observe a group, computational ethnography uses computers and sensors to record a group’s behavior. These systems generally more objective than a human researcher, allowing for a lower chance that the data will be skewed by a human researcher. Computational ethnography is also much more scalable. The “Search Won’t Improve Until We Understand Why People Search, Not Just How” article says that an office may be an example of this, because the computers would be able to monitor everyone at once. It also points out that many of these system use key and monitor logging software. Honestly, I am not sure that this example would be considered ethically sound, as the employees may feel coerced into participating in a study where they are essentially spied on during work. Aside from that, there is the issue of interpreting the results, which still has to be done by a human researcher as the computational systems are still unable to say why groups act the way they do.
Citations:
Ken Anderson. 2009. Ethnographic Research: A Key to Strategy. (March 2009). Retrieved September 16, 2018 from https://hbr.org/2009/03/ethnographic-research-a-key-to-strategy
Martin White. 2018. Search Won’t Improve Until We Understand Why People Search, Not Just How. (September 2018). Retrieved September 16, 2018 from https://www.cmswire.com/information-management/search-wont-improve-until-we-understand-why-people-search-not-just-how/