In a previous post, I talked about what designers need to know about economic class. How did we learn that economic class can be “seen” in designs? How did we learn that “refined” taste is “upper” class?
In general, use qualitative research at the beginning of a design process to uncover innovations. Use quantitative research at the end of a design process to measure improvement.
It started with qualitative research, and became “refined” (no pun intended) with quantitative research. French sociology Pierre Bourdieu followed a typical arc to the narrative research by first investigating economic class in an open-ended fashion. Once he established what he thought was going on, he tested these ideas with large surveys.
If you know little about the topic, start with the qualitative. This means ethnographic observation and in-depth interviewing. Open ended questions are best. At this stage, you’re trying to find the lay of the land. If you’re designing a new car stereo for example, you may wish to start by watching people use their existing car stereos. Maybe drive around with them and ask them questions about what they like.
Once you’ve learned the basics of car stereo requirements, user needs and pain points, it’s time to test your assumptions. This is where the quantitative comes in. Close-ended questions are best here, including multiple choice, yes/no, or simply number of “successes.” Let’s say you’ve learned through your observations that people don’t like how their stereos require programming their radio stations. It’s too much bother, they told you. You think pre-programmed stations might be a good design improvement, so you create a new stereo with pre-programmed stations.
Did it work? Ask your stereo users how they like the new system after they have bought their new car. But the question is, compared to what? This is where quantitative research gets tricky. You can compare the new stereos on select models (58% of users of the new model are very satisfied, while only 32% of users of the old model are). Or you can compare before and after the improvement — the so-called “pre-and post test.” That requires time, foresight, and — you guessed it — budget.
Below is a diagram that summarizes the research “funnel” from exploration to validation.
