Quantitative analysis is different from qualitative analysis in that quantitative analysis

In the field of public relations and communications, it is critical to use both quantitative and qualitative thinking. However, the two are often confused. As a result, PR and communications professionals sometimes attempt to assign arbitrary pseudo-measures to qualitative work (a process known as “making numbers up”), or attempt to influence quantitative analysis with qualitative perspectives.

Mixing up either one badly diminishes the credibility of the PR practitioner and diminishes the trust given to us by our stakeholders, executives and clients.

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 is 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 and surveys
  • 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:

  • Closed-ended questionnaires and surveys
  • Large-scale data sets
  • Analytics gathered by machines
  • 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 problem

Qualitative and quantitative analyses work best when blended together, a method appropriately called mixed method analysis.

It begins 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 them?
  • What kinds of flavors do they like?
  • 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 should be.

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 money.

Conclusion

Understanding the difference between qualitative and quantitative research helps PR practitioners to explain where they are in the research and analysis process.

Understanding why we cannot mingle qualitative and quantitative data all at once, or refer to one form of data in the language and context of another helps us to do our best work and preserve our credibility.

Understanding what to use and when helps us to do our very best work and go beyond simple public relations work to real, credible research that benefits our stakeholders and ourselves.

How is quantitative analysis different from qualitative analysis?

Generally speaking, quantitative analysis involves looking at the hard data, the actual numbers. Qualitative analysis is less tangible. It concerns subjective characteristics and opinions – things that cannot be expressed as a number.

What is the difference between qualitative and quantitative example?

Quantitative data is fixed and “universal,” while qualitative data is subjective and dynamic. For example, if something weighs 20 kilograms, that can be considered an objective fact. However, two people may have very different qualitative accounts of how they experience a particular event.

What is the main difference between qualitative and quantitative research?

In a nutshell, qualitative research generates “textual data” (non-numerical). Quantitative research, on the contrary, produces “numerical data” or information that can be converted into numbers.

Why is the analysis of quantitative data different from that of qualitative data?

Quantitative data are measures of values or counts and are expressed as numbers. Quantitative data are data about numeric variables (e.g. how many; how much; or how often). Qualitative data are measures of 'types' and may be represented by a name, symbol, or a number code.