Quantitative and qualitative methods

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Author: M.Sc. Tyutkov V.
Quantitative and
qualitative methods

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Quantitative and qualitative analysis are
complementary methods that can be combined
in surveys to obtain comprehensive results.
Simply put, quantitative data gives you numbers
to confirm the general points of your research.
Qualitative data provides details for a deep
understanding of their full implications. To get
the best results from using these two methods in
your surveys, it is important that you understand
the differences between them. Let's look at this
question.

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Comparison of quantitative and qualitative studies
Definition of quantitative research Quantitative data are bare facts — figures. Quantitative data is
structured and statistically processed. They help to draw general conclusions from the study.

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Definition of qualitative research
Qualitative data provides descriptive information rather than measuring. These can be
impressions, opinions or views of people. A qualitative survey is less structured — it is aimed
at in-depth analysis of the topic under consideration in order to get information about people's
motivation, their views and attitudes. Such a survey, on the one hand, provides a deep
understanding of the research issues, and on the other hand, complicates the analysis of the
results.

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When should qualitative research be used, and
when quantitative
Quantitative data allows you to see the big picture. Qualitative data brings details and the
human factor to the survey results.Let's see how to use these methods in a research
project.Formulation of hypotheses: qualitative analysis helps to collect detailed information
on the topic. You can use it to start research by discovering problems or opportunities that
people are thinking about. These ideas can become hypotheses that will be proven
through quantitative research.

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Confirmation of hypotheses: quantitative research provides numerical data to which statistical
analysis can be applied to confirm hypotheses. Does the problem have a real background, or did it
arise as a result of someone's incorrect perception? The objective facts obtained will allow you to
make the right decision. Finding common answers: more respondents usually take part in a
quantitative study than in a qualitative one, since it is much easier to conduct multiple-choice
surveys than a series of interviews or focus groups. Thus, it can help to get certain answers to a
wide range of questions, for example: do customers prefer your company or competitors? What are
the most important services of your company? Which ad is the most attractive? Inclusion of the
human factor: qualitative research can also help in the final stages of your project. Comments
derived from open-ended questions can add a human voice to objective numbers and trends in your
results. In many cases, it helps to find out how customers describe your company in their own
words in order to identify hidden pain points. Qualitative data provide such an opportunity.

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How to balance qualitative and quantitative research
These two research methods do not contradict each other. In fact, they work much better together. In
the world of Big Data, there is a lot of statistical information and figures that form a solid basis for
your decisions. But the basic data will be incomplete without information received from real people
that gives meaning to the numbers.So how do we combine these two forms of research? Qualitative
research is almost always the starting point when you need to discover new problems and opportunities
for improvement — this will help to conduct more in-depth research later. Quantitative data allows you
to confirm and understand each problem or opportunity for improvement.

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How to get high-quality data
There are many ways that you can use to conduct qualitative research that will provide
detailed information on the topic you are interested in. Interview. One-on-one conversations
that allow you to work deeply on a topic of interest. Case studies. Collecting customer stories
from detailed interviews. Expert opinions. Valuable information from knowledgeable
sources. Focus groups. Face-to-face conversations or online meetings with small groups of
people to get acquainted with their opinions about a product or ideas on a specific topic.
Questions with an arbitrary answer option. A text field in the survey in which the respondent
can freely express their thoughts on the issue under consideration. An observational study.
For example, observing the behavior of people during their normal interaction with the
product.

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However, this method of research does not always allow
you to get accurate answers to important questions. In
addition, it makes it difficult to analyze the results,
because different people use different words and phrases
to express their point of view, they can even talk about
different things if they find a reason to deviate from the
topic in their answers.In some cases, using only
quantitative questions may be a more effective method.

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Why collect quantitative data?
Survey questions for qualitative research may be too vague In order not to confuse respondents, avoid such
questions as: "What do you think about our Internet service?". Instead, it is better to use a clear closed
question of quantitative research, as in the following example. Does the Internet service work reliably:
Always Most of the time About half the time Sometimes Never It takes more time to answer quality
questions Respondents do not always have the patience to think for a long time about what they are being
asked about and write long answers that accurately express their opinion. It is much faster to choose one of
several pre-loaded answer options in the questionnaire. Using quantitative questions allows you to include
more questions in the survey and get more answers to them.

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Quantitative questions are more amenable... quantitative
determination Even for verbal answers to closed
questionnaire questions, numerical values can be
assigned and then converted into indicators and charts.
This means that the overall data quality will be better.
Remember that only the most accurate data allows you to
make the best decisions.

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Thank you for your attention
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