How to Choose the Right Research Methodology: Quantitative vs. Qualitative

Alright, so you’ve all agreed you can’t make this next big decision for your business without talking to customers. But what’s the best way of getting their feedback? Can we just shoot a quick SurveyMonkey out to them? What about a focus group? Can I just ask my wife what she thinks?

Like many things, those options can all be useful tools, so long as we use them for the right job. For us big-word-using researchers we put research methodologies in two major buckets: quantitative (when you need to choose something) or qualitative (when you need to understand something). They serve very different purposes and which you’d choose depends on what types of questions you want to have answered. Let’s take a look at those two categories to learn when you might use one or the other.

Quantitative Research

When we already know the options and want lots of people to choose between them.

“Should we make this raspberry or mango flavored?”

Let’s say you’re trying to decide what flavor to make your new energy bar and your team has made 3 delicious options, but you have to choose one to bring to market. This is a great time to bring all 3 to a booth and get 100 people to tell you which one is their favorite.

Or maybe you’re trying to decide if you should include lunch for everyone coming to your next big conference, or just take $5 off the ticket price and make it BYO-Lunch. Sounds like a great job for a quick poll to put on the Facebook page.

Quantitative research works best when you need to get a sense of how a large group of people feel about a fairly binary question. Blue or Red? $10 or $15? Biking or Swimming? If you need to have hard numbers to make a decision or prove your case (e.g. “we surveyed 1000 residents and 84% of respondents said we’re not doing a good job of street cleaning.”) this type of research is a great tool to help make your case.

In short: use ‘quant’ when you need to get answers to a specific question from a lot of people without a lot of legwork on your end.

Qualitative Research:

When there are nuanced answers to complex questions with options we have yet to define.

“What new product might help a new mom?”

If you’re a company looking to make a product to help new moms of young children, while we could send a survey asking if they needed help with cleaning, feeding, or bathing, there’s a high chance that we’d be missing out on a whole assortment of potential challenges we might help them address. Instead, sitting down one-on-one would allow you to really understand them as people, the context in which they’re living and the nuances of the help they might need.

Let’s say you’re looking to create something to help wheelchair owners navigate the world more easily. You should probably follow them around for a few hours to see what they actually go through before you start sketching ideas.

Unfortunately for those of us trying to give people what they want, as humans we’re pretty terrible at:

1) Accurately self-reporting behavior

2) Predicting the future we’d actually want or use. (remember Henry Ford’s quote “if you’d ask customers what they would have wanted, they would have said a faster horse.”)

Therefore, qualitative research is great when dealing with the murky complexities of human beings. Use ‘qual’ when you need to deeply understand human behavior or when charged with generating solutions for people who might not even know what they need or want.

The right answer to the wrong question doesn’t help anyone.

Acknowledging we might not have all the answers is a great first step. Getting input from customers is a fantastic second step. But make sure to think carefully about the type of information you need and what it’s being used for before deciding how you’re going to get that feedback. As a general rule, Quantitative is good when you’re nearing the end of a process and need to fine tune your options. Qualitative is good when you’re at the beginning and unsure about how best to start.

Now get out there and start learning!