Data Insights for Business Decisions

This report discusses the importance of quantitative and qualitative research in marketing research and data analytics, including tools and examples. It also covers correlation and regression analysis, time series, and the advantages and disadvantages of using them in big data analysis. Additionally, it explores how data can be collected and used effectively to make informed business decisions.

Data Insights for the
Business Decisions

Contents
INTRODUCTION.................................................................................................................................3
Main Body.............................................................................................................................................3
Role and importance of quantitative research in marketing research and data analytics and its tools
with examples....................................................................................................................................3
Define qualitative research and its role in modern marketing research and data analytics. Also
describe the important of discussion guide and its use.......................................................................4
Describe correlation and regression analysis with two examples of each explaining how they are
useful to an organisation....................................................................................................................5
Discussion the time series and two examples of how it is used in an organisation............................6
Elaborate the advantages and disadvantages of using correlation and regression in analysing big
data in modern business decision making..........................................................................................6
Describe how the data can be collected and used more effectively to make more informed business
decisions............................................................................................................................................7
CONCLUSION.....................................................................................................................................9
References...........................................................................................................................................10

INTRODUCTION
The upcoming report looks into the importance of quantitative and qualitative research in the
marketing research and data analysis. Additionally, it also looks into the role of correlation
and regression in the business firms with examples of each. Furthermore, it also contains the
statements on the advantages and disadvantages of correlation and regression analysis in the
business decision making. Moreover, it also comprises the data analysis method that a
business should adopt for the effective decision making.
Main Body
Role and importance of quantitative research in marketing research and data analytics and its
tools with examples
In marketing research
• Allows the businesses to perform research at scale.
• Helps business in providing insights about the large groups of customers or
population altogether.
• Assists the companies to make comparisons between the different groups by age,
gender, etc. to gain knowledge of the differences or resemblances.
• Helps the companies to recognize the dimensions of the new opportunities in the
market.
• Aids the business enterprise in solving the complex issues
In data analysis:
• It helps the business price to get the meaningful data from the raw numbers with
the applicability of rational and critical thinking.
• Quantitative research involves the evaluation of frequencies of variables and
distinction between the variables.
• It helps in finding out the patterns, averages, allows to make presumptions, helps
in assessing the casual relationships etc.
Tools of Quantitative research:
• Probability Sampling: It means that there are chances where every member of the
targeted population will be included in the sample. For example: If the population is

of 100 people, then every person will have odds of 1 in 100 for getting selected in that
sample.
• Interview: It is the mechanism for the data collection. It can be done through
telephonic, face-to- face interviews, computer assisted personal interviewing. For
example: From interviewing a candidate the data can be gathered in quantitative
manner such as; how frequently a person text while driving?
• Surveys/ Questionnaire: Creating surveys with the help of online software system
plays a great role in collecting the data through an online mode. It helps in the
simplification and knowing the attitude of the respondents. It can be done through two
ways: mail questionnaire and web -based questionnaire. Example: The quantitative
answers can be derived by yes/ no, or rating scale etc.
• Observations: It is the simplest method of collecting the data. It is conducted by the
researchers through systematic observation like counting the number of people that
are present at the particular place and specific time. Its examples are: age, weight,
height, length, population, size and other numerical figures.
Importance of relevance questionnaire design in the qualitative research:
• Practicality: The questionnaire helps the business to target the customers and
allow the researchers to manage strategically. It also helps in managing the
questions and format by collecting large data quantities.
• Cost- efficiency: The business owners can easily place the surveys on the
company’s website and avail the response from the customers. There are no
surveyors involved. So, no extra cost is charged.
• Comparability: The questionnaire can be compared yearly and the company can
get the knowledgeable insights and rectify and minimise the errors.
• Easy analysis: Questionnaires have the built- in the statistical tool and that
provides with the easy interpretation.
Define qualitative research and its role in modern marketing research and data analytics. Also
describe the important of discussion guide and its use.
Qualitative research is the method of inquiry that interprets the data conveyed via language
and behaviour in natural settings. It is the mechanism that provides the expressive
information which is not conveyed by the quantitative data. These expressive data can be
values, feelings, motivations and beliefs.

Role of Qualitative research in modern marketing research:
• Helps in understanding the behavioural pattern and wants of the customers.
• Assists in getting an understanding of what a consumer think about the product and
what is his perception towards it.
• Aid in getting knowledge on the business decisions and strategies that whether they
are successful or not.
• To estimate the demand for the product that a company is producing and what kind of
messages have a great influence on the customers.
• It helps in gathering detailed information and also assists in communicating the brand
proposition accurately and reducing the customer churn.
Role of quantitative data in data analysis is that it is used to gain the understanding of people
feelings and thoughts, and these insights delivers the ground for the future qualitative study.
It also helps the company to find out the survey instruments for conducting the quantitative
research.
Discussion Guide: It holds the set of topics and questions that a surveyor would like to talk
about to the customers in the interview. It comprises of an introduction, exploratory questions
and a debrief. Its importance is that it is used to make up or construct an interview.
Describe correlation and regression analysis with two examples of each explaining how they
are useful to an organisation.
Correlation is the statistical measure which describes the degree or extent to which two
variables can move together i.e., in coordination with each other. If the two variables tend to
move in the same direction, then it is considered as the positive correlation and if they do not
move together or if they move in an opposite direction then they have negative correlation.
Example for the positive and negative correlation in an organisation.
• If the company hire more people for sales, then the sales will also be increases.
• If the employment level in an economy will be high and inflation will rise because
there is an increased money in an economy.
• For instance, demand and price if the price of good rises, then the demand for that
commodity declines and if the price falls, then then quantity demanded increases this
is the negative correlation.

Regression analysis: It is the accurate mechanism to identify which variables influence the
topic of interest. It helps the business in identifying the components and elements that matters
the most, and which factors can be ignored and also how they impact each other. The
example is:
• The business can project the number of people who will buy a product and uses this
information to evaluate the amount of manpower or workforce and resources.
required to produce the product.
• Like the insurance companies uses regression analysis to compute the credit health of
policy holders and a possible amount of claims in the given time duration.
Discussion the time series and two examples of how it is used in an organisation.
A time series is the series of data points that are listed or graphed in a timely manner
or it can also be defined as the collection of observations of well -defined data items which is
obtained by repeated measurements over time. Time series is used to evaluate a model that
can be useful for projections of the business tools such as prices of the stock, sales, turnover,
profit, etc. It is used in an organisation for demand forecasting for retail, procurement and
dynamic pricing: To make predictions about the customer demand for a product is very
important because the procurement and supply of the goods depends on this factor only. It is
also used for making projections on pricing for the goods and services that forcibly adjust the
prices relying on the demand and revenue targets. Time series helps in analysing and
interpreting the past, which is useful to make the predictions or presumptions for the future.
This is really helpful for the business organisation as the forecast is grounded on the
historical pattern of data points that are collected over the period of time. The business can
make comparisons of the current trends with the past trends.
Elaborate the advantages and disadvantages of using correlation and regression in analysing
big data in modern business decision making.
Correlation is the term which is defined as the relationship between data in a business
and is most commonly use in the analysis of financial reports and it support decision making
of the business. Regression term used define the relationship between data which are
recorded in sets but also it used to define as that if one data set changes, it will make all
further causes to the corresponding change in the other data set. Regression is often used in
sales forecasting, product, and service development, predicting future market trends, and

other data causes. Correlation and regression analysis gives business leaders in making more
impactful predictions based on patterns of data used in the sets. This process can help to
guide business processes, direction, and performance accordingly, and as a result it will
improve in management, better customer experience strategies, and optimized operations.
Correlation and regression analysis combined together to the way for modern approach to the
business in succeeding by its increase in profitability, reducing the complexity and
uncertainty of decision making, and increases the business flexibility in ever-changing and
it’s involvement in the business environments. Correlation and Regression Analysis are used
in business to forecast its potential outcomes so that the businesses can make informed data-
driven decisions based on predicting the outcome of events. These both the variables may be
associated with each other; they may not necessarily be causing each other to change. There
is no cause and effect in the data sets. No inferences can be found by results. Possibility of
the third variable problem and factor.
Describe how the data can be collected and used more effectively to make more informed
business decisions.
Data driven decision are the decisions that are grounded on the data. In this method
the data is gathered and business decisions are framed from the procedure that are based on
the goals or KPIs. Interpreting and observing and also processing the data so that it gives the
good and reliable information. It is very essential for the business to collect the data which
will affect the company’s goals and objectives in a positive manner. The data collected shall
relate to the aim and goals of the business organization. For this purpose, the data
management, data governance and data visualization are very important that delivers the
procedure of informed data decisions and support the management in their operation. For
effective data collection the company must make the decisions that rely on the data quality
and insights. By this the company will be able to make the decisions that ensures the
continuity and profitability of the business organisation. Data is the asset for the company
that allows the business to make money by giving the valuable insights in the customers
needs and wants. It shall be treated as the lifeblood of the business so that the business can
attain the customer attraction. For any business enterprise it is very important to get the
feedback of the customers. Through the feedbacks the firm can gather quantitative as well as
qualitative data which will help the organization or a company to make improvement on
different fields. Along with this, after offering the products and services to the customers the
telephonic interview shall be conducted where the buyer shall be asked about whether the

company shall add more features or not. This will help the organization to grow in every
aspect.

CONCLUSION
From the above report it can be concluded that the quantitative and qualitative
research plays a crucial role in a business enterprise for gaining knowledge on the terms of
figures and emotions. Along with this, it is also clear that how the questionnaire and
telephonic interviews can help the business organizations in making informed decisions on
the basis of data. Furthermore, it also gives a clear representation that how discussion guide
helps in the structure of interview and it has its huge significance in the company.

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