Design your research to better research your design
In user experience design, it’s imperative to do user research before you start designing as well as during the design phase. Thus research plays an important role in shaping our designs. But for it to work best, it’s crucial that we follow it the other way around too, that is designing our research well.
Your research is what provides you with all the data, if research isn’t designed in a proper manner, you may end up with incomplete or useless data or at least feeling that you do so.
Thus designing your research is crucial process and the term used for it is ‘research design’.
If you google these two words, the first definition to pop up is this one:
The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data.
Thus basically it involves creating a plan for the three most important steps in research — data collection, measurement and analysis.
Data collection is the initial and the most important step. Without proper data collection, you won’t have anything substantial to measure or analyze. Thus you need to go about this task very carefully.
I recently took part in a qualitative research where we had to collect data regarding how people perform a particular task. So to do so, we first came up with an intro script, which helped those being interviewed understand the task and our research, thus helping them know what exactly we are looking to get from them. Then we prepared a questionnaire, in which we selected a bunch of questions according to the data we wanted to collect from the interviews.
This being a qualitative research, we could modify our questions on the go, depending on the flow of the interview, even going in the gray area every once in a while, something which is actually encouraged in this type of research. But if you’re doing a quantitative analysis, you need to form the questions with a lot more precision, since most of your interviews would be to the point, with gray area being completely avoided. Thus if the questions you ask aren’t concise, you might end up with a huge amount of useless data.
Coming to the second phase, that is data measurement. Measurement is a bit easier when you’re doing a quantitative research, but when it comes to qualitative research, it can be quite tricky. In quantitative research, in most cases the questions are pretty straightforward, yielding either binary or multiple choice answers, thus the data collected is really easy to measure. But in qualitative research, the data is more varied and thus a lot of thought must be put into coming up with the parameters to measure the data collected, which at times could be a really perplexing.
But coming up with the right framework is important, as without it, we would never be able to make sense of the collected data, which in most cases would seem quite overwhelming in it’s raw form. Thus without finding the right parameters which can encompass all the data, or at least the majority of it, a proper analysis of the data won’t be possible.
And last but not the least is the stage of analysis of the data. The stage which involves deriving inferences from the data which we’ve organized in a framework. Analysis is what provides us with answers to questions like ‘what’s wrong with the experience?’, ‘where do it’s shortcomings lie?’, ‘which area needs to targeted?’, etc. Analysis of data can again be either qualitative or quantitative or sometimes even a combination of them, depending upon the results from the earlier steps.
Without an appropriate analysis, we won’t be able to find the pain-points of the users, thus not getting to know the areas which are crucial or those which are in a need of redesigning.
Thus without a proper designing of all these steps of your research, researching your design would be a waste of your time and efforts, providing you with information of little or no use. Reaffirming the saying,
“Failing to plan is planning to fail”
