Choosing quantitative vs. qualitative market research

- [Instructor] When you're planning a research study, you probably start by considering, should we run a survey or set up interviews? What type of research do we need? These are questions even the most experienced researchers ask at the very start of a project, and the answer, well, that depends on what kind of data you're looking for. In this video, we'll explore when to use quantitative research and when to use qualitative research, and how to decide based on your research objectives. Let's start with quantitative research, quant for short. This type of research is all about numbers. Quant is your go-to when you need data that you can generalize across a larger population. For example, if you're looking to measure customer satisfaction at scale, say across a national audience, a survey is going to give you those hard numbers, like what percentage of customers are satisfied or how many are likely to recommend your product. Numbers like these help you track trends, identify patterns, and make decisions about where to take your business. Quant research is also perfect for understanding market demand. Let's say you're launching a new product and you need to know how many people are likely to buy it or which features they care most about. A survey will give you the scale you need to make statistically reliable decisions. Now, let's talk about when to use qualitative research. Qual is about depth. It's understanding the why behind customer behavior. Imagine you've seen survey data showing that customers are frustrated with a feature of your product, but you're not totally sure why. That's where qualitative comes in. Through interviews, focus groups or diaries, you can dive into those frustrations, uncover key motivations and barriers, and explore the emotions behind their feedback. Qualitative research is also useful when you're in the exploratory phase of a project. Let's say you're brainstorming new product ideas or testing creative concepts. Instead of sending out a survey, you might want to sit down when just a few customers, hear their thoughts, and explore their pain points in detail. These kinds of conversations give nuanced insights you probably can't get from a survey. Here's the thing: you don't always have to choose one over the other. In many cases, it's best to combine quant and qual methods in what we call a mixed methods approach, or what I call a sandwich method. For example, you might want to start with 10 interviews to start forming hypotheses. Then you say, "Okay, do these hypotheses scale across a larger population?" So you'll use a survey with, I don't know, 300 people or something like that to ensure that they do scale across a larger population. After that, inevitably find insights you want to ask specifically about, so we just plan in another round of qual at the end so that you can talk to people about those specific nuances and details. Bottom line, let your research objectives guide your approach. If you need numbers and scale, go with quant, if you need depth and understanding, go with qual, and if you want the best of both worlds, don't hesitate to combine both.