Data Insights: Significance of Quantitative and Qualitative Research in Marketing

This presentation discusses the significance of quantitative and qualitative research in modern marketing, including correlation and regression analysis, time series, and issues affecting analysis procedures with specific reference to Big Data and its use in current business decision-making. It also provides examples and assessments of the problems affecting the measuring process and how data can be effectively collected and used to make business decisions.

MG 314 Data
insights

CONTENT
 INTRODUCTION
 Discuss the significance of quantitative research in contemporary marketing
 Explain the importance of qualitative research in the context of discussion guide design.
 Using examples, explain what correlation and regression are and how they are used.
 With an example, explain about time series and how it is useful.
 Give an assessment of the issues affecting the analysis procedures in 3 and 4, with specific
reference to Big Data and its use in current business decision – making.
 How data could be more effectively collected and used to make business decisions
 CONCLUSION


INTRODUCTION
The important goal of this presentation is to
understand some kinds of purposes which are
directly related to the modern business practices of
research methodologies. It also show the concept
and analyse the objectives of quantitative research
which mainly depends upon the modern marketing
techniques and analysis of data.

Discuss the significance of quantitative
research in contemporary marketing
It can be define as a systematic way of inquiry with the main objective to
collecting quality of information and executing mathematical, statistical and
calculated method. Generally, The research of quantitative method gathered the
data from available and highly potential clients by utilizing sampling techniques
and delivered in online data survey, questionnaires and online place, etc. The
outcomes of it can be represented in a form of numerical term. Afterwards, the
cautious knowing of these numerical data to forecast the future of goods and
service and create variations on that basis.

Continue…
Role of quantitative research in modern marketing research and data analysis:
It is one of the most strong equipment which mainly used for asking the questions to the targeted consumer in a
effective way with the assistance of surveys and questionnaires. This type of data is usually measured to create
decision for advanced goods and services. This data is very helpful in modifying sells along with the purchases.
Example of quantitative research
The monthly expenditures of house maximized by how much proportion?
a) 15%
b) 15% - 25%
c) 25% - 35%
d) 35% and above

Purpose of qualitative research in modern
marketing research and analysis of data
 It is define as market research technique that mainly concentrated on acquiring
information with the help of conversation and open-ended conveying. The research
is mainly depend upon the elements of social science such as sociology,
psychology and anthropology. On the other side, this research techniques permit
in-depth and future searching and questioning of respondents in relation to their
consequence, where the interviewer also tries to know their motivation and
feelings.

Continue…
Role of qualitative research in modern marketing research and data analysis:
This technique give deep and adequate qualitative data to the market researchers. Which is useful in
expanding new and innovative goods or idea. It mainly includes in the identification of the strong, weak
and buying nature of the customer. This technique give different kind of data based on the demographics
market, segments and teams of customer.
Examples of qualitative research.
Consumer' attitudes toward commodity which are as follows:
a) Good
b) Moderate
c) Bad

Using illustrations, Describe what correlation
and regression are and how they are useful
Correlation: It is used to measure the relation among the two components which
includes the dependent and independent variable or two independent factors.
Regression: It measure to identifying the relation between the outputs variable and
only one factor. The outputs indicates the reaction of autonomous variable but on
the other side, the risk factors indicates the parasitic variables. The dependent
variable is denoted by 'y' and independent variable is denoted by 'x' in analysis of
regression.

Continue…
Correlation is method that comes to analyse the possible direct relation between the two
average variables. It's not usually settled and easier to calculate just like an incorporate.
It is helpful to describing, summarizing the strong relation among the two or more
mathematics variables. This theory is used to construct the data in respect to improve
the relationship knowing.
A B C
0 2 2
14 6 11
1 8 3
10 5 13
5 6 4
A B C
A 1 - -
B
0.1915
16 1 -
C
0.9092
68
0.1088
93 1

Describe the concept of time series and its
uses along with the example.
It is gathering and representing a well- explaining data items acquire due to the
continuous evaluations for a particular period of time. For example: it is used to
evaluate the worth of retail deals in each and every month of the annual year. This
happen because income of company is apparent and continuously evaluated at same
individual elastic. Data collected very few or only one time is not a time order. It's
not a basic and highest analyses of time that should be incorporated.

Continue…
Uses of time series:
• It is helpful to calculate the decisions based policy and future tasks.
• To interact the variations in the amount of different prospects of time order.
Year Quarter Period Sales
2013 1 1 $ 986.2
2014 2 2 $ 595.8
2015 3 3 $ 865.9
2016 4 4 $ 1296.89
2017 1 5 $ 989.54
2018 2 6 $ 1482.00
2019 3 7 $ 992.8
2020 4 8 $ 695.4

Provide an assessment of the problems which create an impact on the measuring
process in 3 and 4, with particular reference to Big Data and its used in present
business decision – making.
On the basis of the above measurement of of correlation, regression and time
series, big data plan are helpful in creating the critical decisions. It catch all word
for the various of data affiliated that are so big and modern that its tough to deal
with using standardised information analysing schemes also the information
planning. It assists in measuring and modifying in creation with a biggest data
volume.

How data effectively collected and used to make
business decisions.
The information can be gathered and useful for forecasting
the company decisions must accomplish the following:
• Collect survey reaction to determine categories,
services and principles that their customers might desire.
• Organize user checking to see how clients are
teach to use their goods and services and to determine
tough problems that should be set on before the complete
supply.
• Launching a new and innovative goods for testing

CONCLUSION
As it is concluded from the above report the knowing of data insights is the data
that company earn for estimating the set of details and information which relates to
the particular theme or situation. It is communication in context to the work of
quantitative and theoretical in modern marketing study. Apart from this, in context
of correlation and regression it should be considered in particular duration of time.
It also provide justification in regards of the problems arising during the regression
that helps in creating business decisions. At last it indicates how data can be
collected appropriately to make decisions.

REFERENCES
 Aswani, R., Kar, A.K. and Ilavarasan, P.V., 2019. Experience: managing misinformation in social
media—insights for policymakers from Twitter analytics. Journal of Data and Information Quality
(JDIQ). 12(1). pp.1-18.
 Berliner, R.M., Hardman, S. and Tal, G., 2019. Uncovering early adopter’s perceptions and purchase
intentions of automated vehicles: Insights from early adopters of electric vehicles in
California. Transportation research part F: traffic psychology and behaviour. 60. pp.712-722.
 Cepeda-Plaza, M. and Peracchi, A., 2020. Insights into DNA catalysis from structural and functional
studies of the 8-17 DNAzyme. Organic & Biomolecular Chemistry.18(9). pp.1697-1709.