Which Methodology is Right for You? Qualitative? Quantitative? Or Both?
Best Practices | 4 minute read
As insights partners, we’re often asked about the differences between conducting qual vs. quant research and when to choose one over the other. At its most basic, qualitative can provide answers to questions that start with “what” and “why.” Quantitative insights can answer questions about “how many,” “how much,” and “how often.” While that distinction is helpful, it does not go far enough in describing the core benefits of each approach and determining which is right for your needs.
Marketers should begin by considering the following:
- What type of question do I need to answer?
- What type of data will I need to collect to answer those questions?
- Who are the internal stakeholders that need to use this information?
- How will the information be used?
Qualitative – Learning About Human Nature
Imagine you needed to learn about the reasons consumers use a product or service. You would be interested in knowing the various reasons why people make that choice, what competitive products or services they use instead, as well as what perceptions, attitudes, and beliefs lead to use or non-use of the product or service. These are open-ended questions and do not lend themselves to statistical analysis. Therefore, qualitative methods are the most appropriate.
Other uses of qualitative research include observing certain consumer behaviors, such as using a product in a natural setting or shopping at a retail location. A qualitative approach helps gather in-depth feedback to understand the reasoning and rationale motivating consumer behavior and brand preference. This makes qualitative an exceptional tool for a wide range of research needs including new product ideation, concept evaluation, brand positioning research, customer journey mapping, and communication checks.
Quantitative – Benchmarking and Tracking Progress
Quantitative research is best used when you need to answer questions that start with, “how many” or “how often” in order to validate or disprove assumptions. Whenever you need to understand the proportion of consumers who behave a certain way, or have certain attitudes or beliefs in common, you’ll need a quantitative measurement. The results will provide numerical data that can be analyzed statistically for patterns and possible correlations between different factors.
Some of the common applications for quantitative insights include brand awareness tracking, attitude and usage, purchase process, and customer experience studies.
Qualitative vs. Quantitative-At-A-Glance
The following summarizes the differences between qualitative and quantitative approaches:
Qualitative
Objective Purpose
- Exploratory research to establish a base of insights on a key topic area
- Understand underlying motivations, attitudes, and perceptions
- Provide insight into a problem definition, providing hypotheses and language for subsequent quantitative evaluation
Sample
- Small and narrow
- Not statistically projectable
Methodology
- Focus groups, in-depth interviews, ethnographics, etc.
Data Collection
- Semi-structured, using discussion guides
- Can evolve over the course of the study
Reporting Outcome
- Directional in nature
- Not projectable to the total target audience
- Often used to develop a sound understanding as a basis for future insights
Quantitative
Objective Purpose
- Quantify data and generalize results to the target audience
- Measure the incidence of motivations, attitudes, and perceptions
- Benchmark and track data over time
- Predict future behaviors (with caution)
- Understand differences between target audience segments
Sample
- Large and broad
- Usually statistically projectable
Methodology
- Surveys conducted by phone, online, or mail
Data Collection
- Highly structured questionnaires
- Few changes over the course of the study
- Wide variety of question types
Reporting Outcome
- Representative of the target audience
- Provides guidance for business decisions and course of action
Using a Hybrid Qual/Quant Approach
Qualitative and quantitative techniques are often
Objectives Drive Selection
The meaningful differences between qual and quant are far greater than the numeric difference in sample size. Ultimately, the choice between approaches always comes back to your core objectives and the specific business decisions you need to make, which will be guided by the intelligence you expect to gain.


