Coming off the heels of two prototypes — one emphasizing commerce, and one emphasizing discovery — I realized that I lacked a finessed understanding of the needs and expectations of shoppers. To help clarify that, I developed a plan of attack for some agile UX research, in order to develop a baseline of shopping behavior — as well as a more targeted audience to design for.
My primary methodology was experience sampling. Experience sampling is a longitudinal research technique that’s very similar to a diary study, except that it’s designed to be more lightweight and in-the-moment. By sending short questions to participants and requesting that they respond in near-realtime, experience sampling allows researchers to dip into participants’ lives without as much filtering or forgetfulness. In my case, I recruited about twenty participants, and spent about two weeks asking them a daily question about their shopping behavior, in order to identify trends and opportunities. Since it’s important to optimize for realtime responses — and to minimize the burden on participants — I used SMS messaging as my medium, organizing my questions via a Google Sheet and then sending them out broadband via Google Voice. (Apps like Paco exist as a more formalized way to run this kind of study, but text messaging is far easier and more in-the-moment for participants.)
Google famously uses this methodology for an ongoing study about “daily information needs.” While Google asks participants questions about knowledge (i.e., “what did you want to know recently?”), my questions were, naturally, more targeted towards shopping. I asked about discovery of local stores, good and bad experiences shopping locally and online, and how mobile devices factor in. Then, I coded the open-ended answers to identify key themes. Finally, I folded these findings into further development of Nearbuy.