Market Research Overview
22 August 2017

Data collection in quantitative research

When it comes to market research, we need to focus on two different ways of data collection. This can be done in two ways: qualitative and quantitative.

If you are reading this post, probably we are not revealing any secret, but it is good to make a small clarification on the difference between these two approaches.

Qualitative research is an unstructured research and it is based on a classification of non-numerically collected data. It is useful when you need to collect information about a certain behavior and you want to plumb qualities to classify them textually.

Quantitative research, is on the other hand, essential, as can be seen from its own nomenclature, when we need to collect numerical data to structure them in the form of structured and organized, numerical and numbered categories.

The CATI method, as we have already explained in our posts, is based on a kind of quantitative research, for this reason, in this post we will look more closely at the characteristics of quantitative research.

Let’s try to systematize them in a short list.

  • Quantitative research measures, quantifies and calculates data
  • Data is collected on very large samples of participants
  • Participants are interviewed by structured and checked questionnaires
  • Each questionnaire has specific questions and answers that should not be subject to any external interference or interpretation
  • Quantitative research is by its very nature replicable, since it’s structured in standardized psychometric questionnaires

What can be seen from all this? What kind of data collection can we hope to get from quantitative research? What kind of data will we collect and how?

Data collection in quantitative research

Certainly, the benefits of quantitative research are many, especially in terms of a marketing that never remains the same and which must necessarily follow trends and tastes. For this reason, quantitative research is often a confirmation of what researchers want to achieve. Its rigorous nature is also a great support to the reproducibility of the analysis.

The data we get will be clear and unambiguous even though they may demonstrate little humanity, but human variables can be often misleading, so they represent a qualitative flaw which can be easily resolved. We will find ourselves in front of tables, numbers, highly complex operations that enclose in a small space the meaning of a sought-after and multifaceted work, but that will provide us with immediate answers.

If the indisputability of data is something where we tend to, there is no other way except for quantitative research.

Can we combine the two research?

Of course, it will undoubtedly be the subject of our future thought.

If you need help, write me

Ennio Armato, Branch Manager Italy

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