When businesses conduct market research, the participants will typically answer
a variety of questions which will provide the business with a wide range of data.
This data can be categorised as either qualitative or quantitative data.
This video provides you with a comparison of the key characteristics of qualitative data
versus quantitative data, alongside an overview of the benefits and drawbacks
of each, finishing with examples of both in action at fast food chain Five Guys.
First of all, let’s have a look at qualitative data.
Qualitative data is usually expressed in words and is used to understand something
through the collection of participant’s opinions, thoughts and perspective,
providing the business with a description and reason behind the way they feel.
It is crucial for businesses to gain qualitative data as it often provides meaning and context
behind a participant’s answer which supports the business to understand customers wants and needs.
Qualitative data is often gained through asking open ended questions which ask participants ‘how’
and ‘why’ for example: ‘why’ did you purchase this product? or, if you could improve one thing
about this product, ‘how’ would you do it? These ‘how’ and ‘why’ open ended questions
require participants to expand on their answers, providing businesses with more quality data
which helps them to understand the views, needs and wants of their customers due to the amount
of information each answer contains. Which, in turn helps the business
when it comes to decision making on the back of the research findings.
However, it’s very important to be aware that the collection of qualitative data is based on
a much smaller sample size but typically takes much longer to conduct and process,
which ultimately costs more money that standalone quantitative research methods.
This is mainly due to the research methods used to collate qualitative data initially but more so,
the amount of time it takes to analyse qualitative research findings once it has been conducted.
Qualitative research methods used to collate qualitative data are often broad in their
focus and are often designed to get much more than a yes or no answer form participants.
When designing and conducting qualitive research methods,
the business really wants to know more than just the number of people who say yes
or the percentage of people who already purchase a specific product.
They want to know the real opinions of their customers and the reasons why.
Common qualitative research methods include: surveys and questionnaires
with open-ended questions which require participants to explain their answers,
focus groups and interviews where the interviewer can probe participants to
find out the reasons behind their answers. or observations which are often focused on
watching customers and observing their behaviour in store such as how they react to a change in
the store layout or a new product or service being launched, however this requires the
researcher to provide the logic or reason behind the behaviour rather than the customer themselves.
We will have a look at some of these examples in action towards the end of this video, but first
let’s have a look at how quantitative data compares.
Quantitative data is structured and statistical, with a much narrower
focus in comparison to qualitative data, often asking participants closed-ended questions
which contain terms such as ‘who’, ‘what’, or ‘when’.
In its purest form, quantitative research is used to confirm or test something for example,
a theory or assumption, you could consider it to
be the collection of cold hard facts which are typically expressed in a graph or chart.
Quantitative data is often collected through research methods
which use closed-ended questions such as ‘yes’ or ‘no’ answers
but multiple-choice options and rating systems are also commonly used and effective methods.
The main benefit to a business is the speed at which quantitative data can be collected
due to the simplistic nature of the research methods used,
which often leads to more responses being received.
Alongside this, quantitative data is also much easier and quicker to
analyse than qualitative data, providing the business with easy-to-understand results.
which are usually presented numerically as they are based solely on numbers and facts,
for example: ‘60% of participants would pay £20 or more for the product’ or ‘9 in 10
participants would recommend the product’. However, it’s important to be aware that
quantitative data often lacks depth due to its simplistic nature and can make it difficult for
businesses to make decisions on the back of the research findings as it doesn’t provide them with
context or insights into the motivations, thinking or attitudes of the participants who take part.
A business has many choices in relation to the design of its market research.
As we’ve already discussed, it could choose to just focus on quantitative data
if it wants to collect a vast amount of responses and a wealth of statistics in
a relatively short period of time which could provide a strong foundation to base decisions on.
Alternatively, it may choose to focus purely on qualitative data if it has the time to
wait to investigate not only the thoughts of customers but the reasons behind those thoughts,
which helps bring meaning to the numbers. Whilst both methods provide unique
benefits and approaches, it’s not really a question of quantitative vs qualitative,
more so, how can a business use these in combination to increase the effectiveness of the
research as they are often best used collectively. Let’s have a look at how a business such as Five
Guys could utilise a combination of quantitative and qualitative research to provide them with a
detailed understanding of their customer’s views in relation to visiting a restaurant.
The first question could be: Would you visit Five Guys again?
Yes or No? This would provide Five Guys with
quantitative data and a quick overview of how many customers would return to a Five Guys restaurant,
let’s say in this example, 90% of participants said yes.
So that’s 90% of those asked suggested that they would return, which sounds great, but
Five Guys don’t know why or how often they plan to return, or even how eager they are to return,
so we need more information. Therefore, we are going to ask another
quantitative question, this time. The second question is:
How likely are you to visit five guys again? With answers ranging from Extremely likely
to Not at all likely Asking this question
will provide Five Guys with an indication of the customer’s attitude to returning, if a customer
has answered yes to question 1 and extremely likely to this then we know they are very
eager to return and are likely to return soon. However, if they answered yes to question 1 and
somewhat likely to question 2 then although they are indicating they would return,
this might not be for quite some time. It could even be years before they return again.
At this point, we now know if a customer plans to return and how likely they are to return,
but it would also be great if we knew how often they plan to return. Therefore, we are now going
to ask another quantitative question. The third question is:
If you plan on returning, how often do you plan on visiting a Five Guys restaurant?
Ranging from More than once a week to Once every year.
Although this is another quantitative question, it provides us with a wealth of information
about the customer’s intentions, especially when it’s used alongside the initial two questions.
Even if the customer would return and was eager to do so, this may
have still been only once every six months. however, after answering this question, Five Guys
would then know how eager they are to return and how often they plan to visit a Five Guys store,
which I’m sure they would hope is closer to once a week than once a year.
Now a profile has started to be built for this customer, it would be useful to know
what has formed their thoughts and attitudes about visiting a Five Guys store, is it the burgers,
is it the milkshakes, the experience or the price? We will never truly know until we ask.
So, let’s introduce some qualitative questions. Question 4 is:
If you plan to return, please explain why? This question is very open ended and will
provide Five Guys with qualitative data, which helps them to truly understand the reasons behind
the customers thought process. For example, if this was me,
I might reply something along the lines of, the burgers are unbelievable, they have so much taste,
the best quality burger I’ve tried. I can choose my own toppings which is great,
and I get loads of chips. I always walk out full. By the way, I have not been paid to say this,
it’s what I’d genuinely say, I love a good Five Guys burger and chips.
Anyway, based on the questions so far, we now know why I and other participants would be eager
to return to Five Guys, but we do not know what might put us off and influence us not to return
which is just as important to understand. If Five Guys are aware of the reasons,
they could look to develop solutions and make improvements to increase the percentage of
customers returning and how often they return. So, the final question is:
What would potentially put you off returning? This question will again, provide Five Guys
with qualitative data and alongside question 4 will help the business to fully understand
the significance behind the quantitative data gained in the first three questions,
providing meaning to them by identifying the motivations and perceptions of the participants.
I’m sure you are all wondering what I’d put to this question and with me being a stereotypical
Yorkshireman, we are known for being tight, so I’m going to go for the price is too expensive
to go on a regular basis. Final slide
So that’s it, qualitative and quantitative data explained. Hopefully, you’ve found the
video useful, if you have, we’d appreciate it if you could hit the like button and remember
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