Industry leaders have been successfully using qualitative research for decades. But for many years, we didn’t really understand why it worked. Now we know, and understanding these dynamics can supercharge your research.
Self-driving cars, drone delivery, augmented reality. The world is changing, and companies need to innovate to stay relevant. Most companies turn to quantitative data for answers, and the rise of big data is the natural outcome of that trend. Quantitative data is great, but without the unique insights that only qualitative research provides, the most valuable opportunities remain hidden.
A large consumer packaged goods company faced just this challenge. For years, they worked to make incrementally better multi-blade razors: sharper razors, safer razors, faster razors. And yet, growth had started to plateau.
Seeking an answer, the company launched a global shaving survey. What they found was unsurprising: people want a clean, close shave. This was the same old playbook they had been operating from for decades. On the face of it, there were no new opportunities for growth.
The team decided to take a step back and reframe the study. Working with Jump, they conducted qualitative research designed to uncover the social and psychological needs that men have around hair removal. The team shadowed men in the morning and conducted in-depth interviews with participants.
The team found that using razors wasn’t just about getting a clean, close shave. Men actually care about shaping and styling their facial hair. And furthermore, the presence of facial hair, not just the act of shaving it off, is an important signifier of adulthood for boys. Shaving is how you create a look.
Company executives were surprised by the results. After all, weren’t most men clean-shaven? The team went back to the global shaving survey. This time, they mined the database for one question: how many people have facial hair? The answer was over 50%. The data was there all along. No one had thought to ask the question.
Analyzing data in a vacuum, without understanding the underlying experiences and motivations of customers, obscures critical insights. It’s difficult to know how to cut the data, and how to make sense of what might surface. But interviewing just a handful of people can provide groundbreaking insights and bring that data to life.
Ethnography shouldn’t work. But it does.
Ethnography was originally developed in the social sciences to understand people and cultures. Conventional wisdom, rooted in statistics, would suggest that studying just a handful of people could never produce valid conclusions. However, companies have been able to produce meaningful insights from studying less than twenty people. As with the shaving study, these insights have then been validated by larger quantitative surveys.
Back in the late eighties, Abbie Griffin at MIT wanted to know how many people she would need to interview to gather a comprehensive set of needs on a given topic. Analyzing the results revealed that the bulk of needs are identified within a dozen interviews.
Griffin’s work demonstrated that qualitative research was effective at revealing a large amount of information with just a handful of participants. But why does this methodology work so well?
The magic of ethnography lies in cultural consensus.
When running qualitative studies about a specific subject, it’s important to choose highly experienced subject experts. Within a group of these subject experts, cultural consensus is the degree to which everyone in the group agrees with each other about the given subject. Achieving cultural consensus increases the accuracy of the responses and reduces the number of people required for us to learn about the subject.
Here’s a simple example that illustrates this point:
Let’s say you want to learn the rules of baseball just by talking to people. First, you ask random passersby on the street in Mumbai, but many have never watched a baseball game before. Eventually, you end up with most of the rules of baseball, along with some erroneous rules, but it takes hundreds of conversations to get there.
The question was clear (what are the rules of baseball?), but cultural competence wasn’t high (the people you spoke with didn’t know a lot about the game).
When Qualitative Research Works
You decide to try this experiment again, instead with little league baseball players in Chicago. You ask each player to tell you the rules of baseball. The first player covers most of the rules. The second player repeats many and adds some new ones. After just a handful of conversations, you’ve learned the rules of baseball.
When you defined the subject area (the game of baseball), located subject experts (little league baseball players), and targeted just this group, you were able to learn about the subject quickly and accurately.
That’s the real reason why qualitative research works. People are, by definition, subject matter experts in their own lives. And so, as you speak with people who have similar lives (similar ages, geographies, or cultural backgrounds, for example), you don’t need to talk to many of them to get to the right answers.
Harness cultural consensus by properly defining your study, choosing participants, and analyzing your findings.
Watch out! The temptation to expand the impact of a study by covering a larger breadth of customers instead breaks down cultural consensus and thus the accuracy of the research.
Cultural competence and cultural consensus work together to make qualitative research work. Define the subject area, find people that know a lot about that subject, and study just a handful of those people.
Still, at different stages in the process, teams can make critical missteps, often unsuspectingly, that can derail the study. Knowing where you can bend, and where you need to stand your ground, is crucial.
Here’s what to do:
This could include basic demographics like gender and age, activities like shopping tendencies and pastimes, or mindsets such as religious beliefs and political leanings.
Be wary of trying to slip in other customer segments to seem inclusive or to appease a stakeholder. If they don’t fit the group, it’s better to run two separate studies, rather than sacrificing the credibility of the research.
This is the sweet spot, creating a sample that is large enough to capture a range of needs, and reveal meaningful patterns, but small enough to be feasible.
Participants often struggle to directly communicate their underlying motivations and feelings. It’s important to devote ample time to analyzing the results to uncover a greater understanding of what’s going on. Be wary of taking soundbites at face value.
If validity is critical, such as in building support for large-scale changes, follow up with quantitative samples. This “qual then quant” approach lets you figure out what the most important insights are before seeking further validation.
The best way to learn these principles is to go out and run a study. Structure your plan and rally your team. Then find those subject experts, get out of the office, and chat with them. Walk in their shoes. See what their life is like. Doing so will shed light on your data, add strength to your business decisions, and position your company for future resilience.
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