Siamack is the founder of mobile ethnography tool EthOS. In this video, he recommends using vertical analysis to understand who your participants are as individuals.
Video Transcription:
Most mobile ethnography projects if not all of them are based on a bunch of tasks that we give participants to complete and you can number them task 1, task 2, task 3. You can schedule them to appear one after the other. You can have things like, skip logic. So that when one task is completed, depending on how its completed, then another one pops up appropriate to the first one and so on and so forth. There’s a problem with this. And the problem is that in order to save time, we will go horizontally through the data by which, I mean, we’ll go to all the responses, to task or probe number one and go through them systematically. Sure, we can filter them by segment or what have you and trying to see what the differences are between the various segments and that’s all good and you will get some understanding of people’s sentiments or feelings or behaviors or whatever it is you’re trying to explore by task. But here’s what you don’t get. What you don’t get is who these people are, and mobile ethnography is still qualitative research. It’s not to be confused with quantitative research. And one of the really, most important things in my books is to go vertically through the data, by which, I mean, understand the individual actors and players by looking through their task systematically to see how they’ve responded to your questions and probes and activities that they were set. So, don’t forget if you miss out on that, you’ve missed out on a good 50% of the learnings and the understanding that will help you with your sense-making. And that sort of meanings that you add to this data. And don’t get stuck on the data. You’re not just doing analysis. Analysis is sorting through what you have and what people have said. Interpretation is adding meaning to it, making sense of it, and you can’t really do that bit of it unless you’ve gone through the data vertically. Thank you for watching.
