MG413 Data Insights: Role of Quantitative Research in Marketing

This presentation provides a detailed analysis of quantitative research in modern marketing, emphasizing questionnaire design, correlation, regression, and time series analysis. It critiques issues surrounding these techniques with reference to big data and modern business decision-making. The presentation further discusses how data is collected and used effectively to make informed business decisions. Key areas covered include the role of quantitative research in evaluating performance and assessing financial instruments, with examples from customer and supplier satisfaction surveys. The analysis extends to structured interviews, customer behavior understanding, and the application of correlation and regression to predict future trends and brand image. The presentation concludes by addressing the importance of data collection methods and effective data management systems for ensuring the proper use of big data in business.

DIBD

INTRODUCTION
Quantitative marketing research is the technique to ask questions by using surveys, polls or
questionnaires (Baškarada and Koronios, 2018).
This is the group presentation by the four members who will analyse and identify the –
roles of quantitative market research in business, framing of questionnaire in business, role of research
which is undertaken qualitative in nature, setting out correlation and regression, setting out the time
series and how it will be used, providing the issues surrounding the analysis technique with reference
to big data.

MAIN BODY
1.Role of quantitative research in modern marketing research and data
analysis
There is application of modern marketing techniques in the market research and therefore, they are known as
quantitative marketing research. Quantitative research is done using the polls, questionnaires, surveys among many
of the techniques. There are various types of responses which are gained by the participants who are willingly taking
part in the research. The responses help in improving the products and services at large scale (Moisander, Närvänen
and Valtonen, 2020).

The major role of quantitative research is mentioned as –
 Being clear – Quantitative research is very clear in nature which helps in stating all the
information and details properly within the research being conducted. Use of simple and easy
understandable language makes the questionnaire clearer. The questions are to be framed in such
clear and understandable manner (Vrontis, Christofi and Katsikeas, 2020).
 Evaluating performance – This research helps in evaluating the performance appropriately and
helps in considering the concerns as to how effectively research is carried out. With the help of
gaining the responses of the respondents, there is improved and enhanced performance of the
participants taking part in the research.

 Assessing financial instruments – The financial information and data is analysed and addressed
which helps in indicating the concerns which are related to how effectively and appropriately the
solutions are analysed based on the financial criteria. The questionnaire consists of the financial
information which is to be answered by the respondents or participants.
There are examples which include customer satisfaction survey, supplier satisfaction survey etc. Thus,
the quantitative research is being analysed and is categorised as how effectively the participants are
taking part in the research.

2. Role of quantitative research with specific emphasis on discussion guide
design and use
There are also interviews which are conducted within the quantitative research and this helps in indicating the aspects as to how
effectively and in appropriate manner the interviews can be in the form of structured and unstructured form. In the structured
interview, there is data collection method which relies on asking questions in a set order to collect data on the topic of the
research being undertaken (Guetterman and Fetters, 2018).

There are certain examples which included in the interview and are addressed as important.
These are some of the examples which include customer discussion, understanding the customers’
behaviour (Rashid, Rashid Warraich and et.al., 2019). Interview method is being used when there are
complex ideas to be initiated and to gather in the discussion. There is also digital recording of the
interviews which helps in addressing and knowing that how the data can be made available.

3. Setting out what is correlation and regression and how it is
used with examples
In statistics, correlation is the statistical relationship between two random variables. There is liner
relation between two variables. It is used in the research which helps in indicating the aspects as to
how effectively the correlation is helping to predict that the data which is used for future and brand
image and sales. Further, partial correlation is also used for the analysis of two variables by controlling
the third variable. Regression is defined as the statistical method which is used in statistics which helps
in finding out relation between the independent and dependent variable (Kasuya, 2019).

This is helping the marketers in analysing that how the independent variable is affecting the
dependent variable and results at large scale. It is helping the companies to analyse and evaluate the
aspects as to how there are major concerns of analysing the relation between the variables of dependent
and independent. This helps in analysing and concerning the aspects as to how effectively and
appropriately there are advantages of using the correlation and regression for analysing the statistics
and data at large scale.

4. Understanding time series and its use
 The data and information that has been collected is mainly presented with the help of the index. This index is based on the time
series. The time series analysis has been considered as important element that has been used for marketing research. It has been
proven beneficial for marketing research as it helps in having effective understanding in relation of the trends that are related to
the product.
 Analysing the trend that are related to the product is highly important as it helps in taking the major decision. With the help of
time-series the current demand of the product in market can be analysed easily (Parmezan, Souza & Batista, (2019).

 For example: When there is the season of holiday which in generally in December and January the
demand for the gifts has been increases.
 During this time people like to celebrate the moments and they celebrate it within giving gifts to
each other.
 Therefore, the demand for gifts in this particular season has been increased. This information can
be easily analysis with the help of time series as it helps in identifying the particular period in
which the demand for the particular gift has been increased.

5. Critiquing the issues surrounded the analysis techniques in 3 and 4, with
reference to big data and modern business decision making
 Big data is defined as data sets that are too large and complex to be dealt with by the traditional
data processing application software.
 Correlation and regression are the big data analysis techniques which are to be chosen and
creating value for both small and large scale organization.
 There is one fundamental flaw which helps in realizing to analyse that whether there is casual
relationship between two variables.
 There is no value of data when it is known as that the data has correlation and not causation.
 This leads to mistakes by the organization which creates problems in the overall process of not
being creating value at large scale (Favaretto, De Clercq and et.al., 2020).