Data Insights Presentation: Marketing Research Techniques and Analysis

This presentation delves into the realm of data insights within modern marketing research, focusing on both quantitative and qualitative approaches. It examines the roles of quantitative research, emphasizing questionnaire design and providing examples of best practices. The presentation also explores qualitative research, highlighting discussion guide design and its practical applications. Furthermore, it elucidates correlation, regression, and time series analysis, including their applications and limitations. The analysis extends to the use of Big Data in business decision-making, along with the importance of data collection and its effective utilization. The conclusion emphasizes the significance of data analysis using statistical tools, the relationship between variables, and the utility of time series data for forecasting. The limitations of each statistical tool, such as the time-consuming nature and the requirement of extensive knowledge, are also discussed.

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Introduction
• Roles of quantitative market research in business
• Importance of relevant questionnaire design
• Role of Qualitative research in Business
• Importance of discussion guide and use
• Correlation. Regression. And Time Series Analysis
• Limitations of Correlation, regression
• How to improve collecting Data (when the data is required to make
business decisions)

The role of quantitative research in modern
marketing research and data analysis

The role of quantitative research: Questionnaire design with
examples of good practice

The role of qualitative research in modern marketing research
and data analysis

The role of qualitative research. The Interview Discussion guide:
design & use (with examples)

Correlation & Regression:
How & why it is used - with examples
Correlation Regression

Time series:
What it is & how it is used - with examples
• The time series is being defined as the
observation which involves the discrete time
data in order to evaluate the data in better terms.
• This use of time series is being used as the
running charts which is being created in order to
evaluate the working of the company and to
decide for the future working as well.
• this includes the collection of the different
observation in order to identify the trends and
pattern within the past performance in order to
improve the future working.

Critique of issues surrounding the analysis techniques
Correlation
•The use of correlational study that is study based on
the correlation and the limitation is that it only
uncovers the relationship being present within the
variables.
•Under this method only the information being
gathered is connected with the phenomenon and this
result in developing the outcome.
Regression
•The drawback of using the regression analysis is that
it involves a lengthy and complicated process which
affects the calculation and output to a great extent.
•along with this another limitation of using regression
is that it is not applicable to qualitative elements and
phenomenon. this sometimes limits the use of
regression as in case of study based on qualitative
factor will not be evaluated in proper manner.

Critique of issues surrounding the analysis techniques
Time series focusing on Big Data & its use in business decision making (focusing on Big Data & its use in
business decision making)
•Along with this there are also many different limitations of using time series data. these limitation involves the
following-
•the major problem being attached with the use of time series is that it has the issue of generalisation from the
single study.
•This is because of the reason that many a times a single study is being generalised and the outcome is applied
to every situation and even in case where it is not applicable.

How data can be collected & used to make informed business
decisions.
• Along with this it can be stated that the data must be collected and used in better and effective manner.
• This is very necessary for the reason that in case data will not be used in proper manner then this will be
affecting the working efficiency to a great manner.
• For the better informed business decision, it is necessary that proper data is being collected in order to take
the decision. hence, for this the different sources of data can be used.
• These sources of data involve primary and secondary sources of data.

Conclusion
•In the end it is concluded that the data insight is being defined as the analysis of the data using different
statistical tools and techniques.
•This is very necessary for the reason that when the data will not be analysed in proper manner then the
objective of the study will be met.
•Along with this it was evaluated that correlation and regression is important to be analysed in order to
evaluate the relation between the variables.
•Moreover, the use of time series was also evaluated in order to evaluate the data from past and it can be
used for future prediction as well.
•Along with this the issues being identified in every statistical tool like all the tools are time consuming
and involves great knowledge.