Understanding the key features and benefits of qualitative and quantitative data
In market research, a common early consideration is whether
to include a qualitative and/or a quantitative element in a study. In basic terms, looking at the difference
between qualitative and quantitative data, quantitative research will collect
numeric and easily quantifiable answers, such as the number of visits to the
cinema in the past month, age, height or weight of individuals or satisfaction
with a service on a scale of 1-10. Qualitative research on the other hand, is about feelings, or exploring
reasons and topics with no fixed questions or ridgid agenda.
Qualitative data can take many forms
and is often used at the start of a study, to help define the topics and
structure of the overall project. Forms of qualitative data include;
research usually takes place in-person or via video, either in small groups or
one-to-one. Because the conversation is
not structured, or semi-structured, it is not restricted to topics already
considered, enabling the exploration of new areas or thinking. Whilst there may
be an ‘interview guide’ with questions to be covered, if new themes emerge
they can be explored ‘off guide’.
research output is based on interpretation and is expressed in language,
images, or even sound bites and video.
Quantitative data, depending on the sample size, can be used
to make statistically significant statements about the general population. It is collected in large quantities,
typically thousands of respondents who are interviewed to represent different
demographic groups in the general population, with analysis conducted to
compare results among different groups (e.g. age groups, gender or region),
discovering trends and patterns.
The actual data collected can be;
Often, quantitative data is collected over time to track
changes in results, or could provide a benchmark before or after the launch of
a new product or service.
Quantitative research data can be collected via a survey,
online, in-person, mail or via telephone.
There will always be a balance between the comforting
statistical significance of quantitative conclusions and the feeling that you
may have missed a depth of insight or lost a nuance because of the quantitative
structure required. Achieving the right
balance depends on the specific business objectives – are you looking to fine
tune a new product or to get an understanding of the success of a product
launch? The former may benefit more from
the depth of qualitative while the latter will need the definitive conclusions
of quantitative data.
With quantitative research, specific and measurable findings
are possible – in the example below we can say that a third of respondents are
completely satisfied with the service provided by Acme.
Depending on the sample sizes, statistically significant
differences in the satisfaction of certain groups of respondents could also be
noted, such as between men and women, or older/younger service users. This would help guide the client company focus on groups where lower satisfaction levels are experienced.
Further, an attempt could be made to discover the reasons
for satisfaction or dissatisfaction, via a question such as ‘For which of the
following reasons did you give a score of 1 for satisfaction?’, listing areas
such as slow, poor staff knowledge, etc. However, this could never be a complete list as you cannot predict all
of the possible responses.You may also
not get to the root of the issue, ‘poor staff knowledge’ would not tell you the
specific things they could not help with.
Quantitative questions therefore need to be complimented by
qualitative insights to get the full picture, where possible. Asking the
open-ended question ‘Why did you give a score of 1 for satisfaction?’ will
get the real, unrestricted reason for their rating.
This article has already contrasted the two approaches to
research in depth, but let’s also consider the practical implications to help
weight up the advantages and disadvantages of qualitative and quantitative
Weighing up the cost of completing a qualitative vs.
quantitative project, the cost per interview will be significantly
different. With a small budget where you
may not be able ask a large enough sample size to make clear conclusions, you
may still be able to complete some individual depth interviews (IDIs) to get
greater depth of insights instead. On the other hand, asking 100 people ten questions, one of which is open-ended gives
you an element of each.
can take longer due to respondent recruitment, length of interview (typically
an hour or more for 1-2-1 interviews, or two hours for a group discussion (e.g. 6-8 people
discussing a topic) and more time-intensive analysis.
Quantitative research analysis is statistical, looking at
themes and trends in the data set, making comparisons between subsets of the
data to come up with robust conclusions that can predict the real world or
In a qualitative project, analysis involves reading
transcripts of interviews, watching videos, reviewing behaviour diaries, or
Qualitative reports will include individual quotes or video
voxpops to illustrate the themes emerging. Quantitative results will consist of charts and tables and strong
recommendations based on the statistical conclusions.
It is possible to get the best of both worlds with a hybrid
survey, containing both closed quantitative and open-ended questions, which
provide qualitative data within that quantitative survey structure.
Open-ended questions provide the best of both worlds because
not only can you read each one individually to get a sense of the data in depth, or to follow up on
specific customer issues, they can also be coded, using software
such as codeit, effectively converting qualitative data into quantitative data.
Coding is the systematic classification of open-ended
verbatim comments into themes or groups. It enables analysis of themes and topics as well as sentiment within
open-ended qualitative responses to give you a quantifiable or categorical set
of actionable answers alongside other quantitative results. Find out more about
the power of coding read the seven stages of analysing open-ended questions
and learn the practical steps of how to analyse open ended questions.
Based on the benefits and disadvantages of qualitative and
quantitative data, you will likely choose either one approach or a hybrid
model, either with a qualitative phase followed by a quantitative phase, or a
quantitative survey that enables you to capture qualitative insights in
open-ended questions. Either way, you
can use a dedicated coding platform such as codeit to further enhance the depth
and actionability of your research by classifying the open-ended qualitative
you’d like to give codeit a go, you can take up their 30 day free trial
to help you start coding and analysing your open-ended question data today.
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