important to understand the difference between qualitative and quantitative
research, especially if you’re new to the field. There’s a common misconception
that one is ‘better’ than the other, however qualitative and quantitative
research serve vastly different purposes. Read on to learn about what makes
them different, how you can turn one into the other, and when you might use
which method. Let’s differentiate between the two.
Qualitative analysis fundamentally means to measure something by its quality
rather than quantity. When we do qualitative analysis, we are exploring how we
describe something. Very often, we cannot use numbers or numerical expressions
to describe those things. When we do qualitative work, we work with
descriptions. We work with feelings, thoughts, perceptions. We attempt to
understand motivations and behaviors.
Quantitative analysis means the opposite, to measure by quantity rather than
quality. When we do quantitative analysis, we are exploring facts, measures,
numbers, and percentages. When we do quantitative work, we work with numbers,
statistics, formulae, and data.
Both qualitative and quantitative analysis are vitally important
to public relations.
EXAMPLES OF QUALITATIVE ANALYSIS
Qualitative analysis focuses on why.
Why do people behave in certain ways? Why do they make decisions? Qualitative
analysis and research methods often include:
- Focus groups
- Open-ended questionnaires
- Unstructured interviews
- Unstructured observations
(like reading social media posts)
- Case studies
Qualitative analysis tends to look very deeply at a few things
to understand the why.
EXAMPLES OF QUANTITATIVE ANALYSIS
Quantitative analysis focuses
on what. What happened? How many people bought this product? What
percentage of people considered this brand? Quantitative analysis and research
methods often include:
questionnaires and surveys
- Large-scale data sets
- Analytics gathered by
- Random sampling
- Structured data
- Tracking software such as
CRMs, marketing automation, advertising
Quantitative analysis tends to look very broadly at many things
to understand the what.
THE RIGHT METHOD FOR THE RIGHT
Qualitative and quantitative analyses work best when blended together, a method appropriately called mixed method analysis.
We begin with qualitative research and analysis to understand
the problem broadly, to define what language we should be using.
Suppose we sell coffee. We might start a research process by
asking people what they like about coffee in general.
- Why do they buy the
coffee they buy?
- Is cost most important to
- What kinds of flavors do
- What’s their favorite way
to drink coffee?
Once we know what questions to ask, we switch to quantitative
methods to help us understand how many people have answers to our questions and
what those answers are. Suppose, in our example, people said that the top
reason for why they made the coffee choices they made was because of price.
We’d run a survey asking people at what price they believe a good cup of coffee
Once we understand the numbers and math, we switch back to
qualitative to ask why. Why did we receive the results we did in the
quantitative research? Why did people make the choices they made? We would
survey or interview a representative, random sample of our
quantitatively-analyzed audience to understand why.
In our example, suppose we found out that a majority of people
chose coffee priced at $1 or less. Why? What did the people who answered this
have in common – were they in similar professions? Perhaps they shared a common
gender, geography, or ethnicity. We’d then look at that group and return to
qualitative research to ask more questions of them, about how coffee fits into
their personal budgets.
We’d then switch from qualitative to quantitative to gather more
data based on our refined understanding of our audience…
… and the cycle repeats until we either have solid, defensible
answers to our questions or we run into resource constraints such as time and
Here’s a helpful hint if you are ever stuck trying to remember the
of these words: quantitative and qualitative. After all, they are
identical. Remember that qualitative has an “l” just like
“letters” so that’s
the one that deals with categorical data (non-numerical). GoodLuck!
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