At heart, I define myself as a qualitative researcher. However, over time, I believe this was primarily a philosophical perspective as I typically trade in stories collecting what happens and trying to make sense of it.

In my eyes, this would make me more of a qualitative researcher. Yet even if I take a simplistic approach, quantitative researchers care about numbers and causation and qualitative about the properties and descriptions of a thing, I believe I am somewhere in the middle. 

Qualitative and quantitative researchers both work with empirical (direct observation) data, quantitative focusing on perceived quantities (using techniques as usage analytics and NPS), and qualitative on qualities (using techniques as stories and descriptions).  

I believe that reality is constructed; it’s subjective, based on everyday interpretations. So, I am more of an inductive researcher, rooted in constructivism and trying to catch the richness of context and be emphatic with participants. Scale and causation are relevant but not my holy grail, as ambiguity is part of what I like about user research.

For me, It’s fascinating to understand how people think without the narrow focus of testing or proving a variable. I am always stunned by how great detailed stories centered on customers are great stakeholder and team engagers. This is where I excel and what I really love to do, probably the root for my passion for product\service continuous discovery.

At the end of the line, the value of a User Researcher is his expertise in research methodology. A researcher asks and answers questions, and most times, helps stakeholders understand the trade-offs of asking deductive or inductive questions and some strategies to overcome each route.

The choice paradox

When organizations and teams fall in love with their customers, their pains, and how they can improve their lives, a new mindset flourishes supported by an open and exploratory attitude.

We do not have to choose between participant focus and scale and causation — the dilemma between techniques and training of qual. and quant. researchers. Instead, we need to be conscious of the several methods we can apply, our personal preferences and biases.

Mixing research methods allows us to get a deeper and broader understanding of the challenges we are facing, and this provides valuable insights on the short and long run.