Data Insights for Business Decisions - Importance of Quantitative and Qualitative Research

This presentation discusses the importance of data insights for making informed business decisions. It covers the essence of quantitative research, the role of qualitative research in marketing research, uses of correlation and regression, time series, and how data is collected. The presentation also highlights the challenges faced while collecting and analyzing data and concludes with the benefits of data insights for future decision-making.

Data insight for Business Decisions

Cover Content
• Introduction
• The Essence of Quantitative research
• Role of qualitative research in marketing research
• What are the uses of correlation and regression?
• Discuss about the usage of time series
• Uses of Time Series
• Issues of analyses techniques of regression, Correlation and Time series
• How is Data collected?
• CONCLUSION
• REFERENCES

INTRODUCTION
Data insight refers to understanding that an
organisation germinates by examining
information for a selected scenario or situation.
By analysing this information, a business
frames their decision and tries to reduce risk
factor in a decision that arises due to usage of
trial and error method.

The Essence of Quantitative research
• It refers to the procedure of gathering and evaluating quantitative data by focuses
on factual, numeric content.
• It deals with data that can be presented in numbers. Under this research, data is
collected from existing users with the help of various sampling methods such as
online surveys, questionnaire but all in numeric data.

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• Quantitative data is used by researchers to present problems and issues in
numeric form so that it can be easily understood.
• It helps firms in collecting information about its firm through which marketing
strategies can be framed.

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• For instance,
• How much sales of firm has increased after the launch of new marketing
campaign.
• a) 0 - 10 %
• b) 10 – 20 %
• c )20 – 30 %
• d) More than 30 %

Role of qualitative research in marketing research
• It can be defined as collecting and
analysing non numerical data for
understanding the concepts, experiences
and opinions. It makes use of non numeric
data and factual assessment. Their are
different kinds of tools that can be used for
analysing this information.

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It is very beneficial in modern marketing research in following manner.
• It assists in conducting test for inventive thoughts like gathering information
about the way people reacted to particular item.
• It aids in understanding in relation to perspective and conviction of unique ideas
and evaluating them according to the circumstances and analysing their results.

What are the uses of correlation and regression?
Sales $ Advertisement $
650 24
760 25
880 30
1060 35
1230 42
A B
A 1 -
B 0.99 1

Discuss about the usage of time series
• Time series is a method that is used to record all the data at regular time period
and monitoring for using it for the purpose of making decisions of trends. This
data is collected at an equal time intervals.

Uses of Time Series
Example
Year Quarter Period Sales
2015 1 1 $ 980
2016 2 2 $ 600
2017 3 3 $ 850
2018 4 4 $ 1300
2019 1 5 $ 990
2020 2 6 $ 1200

Issues of analyses techniques of regression,
Correlation and Time series
• All the organisations faces challenges while collecting and analysing any data
whether it is government, any institution or researcher.
• While dealing with any big data, it is important to use proper strategies which is
challenging as it is not easy to sort the data containing large number of values.

How is Data collected?
• Manual data capture – In this process, the data is entered manually by the person
with the help of devices like keyboard, touch screen etc. the data is presented in
figures or text in a software like excel.
• Optical Character Recognition (OCR)- In this, the technology is used to convert
a machine printed document into image or Pdf file.

CONCLUSION
From the above analysis, it can be concluded that data insight is useful in making
decisions for future as it helps in analysing the trends and can be used for making
interpretation for coming time. This included both the quantitative as well as
qualitative data.

REFERENCES
• Akoum, M. and et.al., 2019, November. Big Data Insight towards Well planning, A
case study. In Abu Dhabi International Petroleum Exhibition & Conference. OnePetro.
• Hanafizadeh, P., Firouzabadi, M.B. and Vu, K.M., 2021. Insight monetization
intermediary platform using recommender systems. Electronic Markets, pp.1-25.
• Phillips-Wren, G., Daly, M. and Burstein, F., 2021. Reconciling business intelligence,
analytics and decision support systems: More data, deeper insight. Decision Support
Systems. 146. p.113560.