Research Analysis: Data Insight in Modern Marketing and Business

This report provides a detailed analysis of data insight, focusing on the roles of quantitative and qualitative research in modern marketing research and data analysis. It covers key concepts such as correlation, regression, and time series, highlighting their applications in business. The report also critiques issues surrounding analysis techniques and examines how data is collected and utilized to make informed business decisions. Various data collection methods, including surveys, interviews, and document analysis, are explored, emphasizing their importance in gaining competitive advantages. The conclusion underscores the significance of qualitative and quantitative data in organizational decision-making, supported by a comprehensive list of references.

Data insight

Table of content
 Introduction
 Role of quantitative research in modern marketing research and data analysis
 Role of qualitative research in modern marketing research and data analysis
 Concept correlation and regression and its uses in business
 Concept of time series and its use
 Provide a critique of issues surrounding the analysis technique
 How data is collected and used to make business decisions
 CONCLUSION
 References

Introduction
Data insight is considered as the depth understanding of an
individual and business gains regarding specific issue. The
concept of data insight facilitates business through taking
more efficient decisions that enables organisation to attain
success in competitive business environment. It helps business
in conducting marketing campaigns, provide better services to
customers, conduct operations in efficient manner as well as
reduce risk from business.

Role of quantitative research in modern marketing
research and data analysis
 Quantitative research: Quantitative research is related to
gathering as well as analysing data in numerical term. This
research in implemented by organisations with the objective of
find out averages, patterns, and make predictions for future.
 Quantitative market research is used by organisation to gain
numerical data and information related to customers.

Continuous..
 Roles of quantitative research in business marketing research are mentioned below:
 Produce numerically rational theories
 Calculate and analyse data
 Enhance willingness of respondent

Role of qualitative research in modern marketing
research and data analysis
Qualitative market research: Quantitative market research consists
open-ended questions that enables business to gain depth
information and data. Organisation can conduct research through
using various methods such as observation, focus group, interview,
online forum and other research methods.
 Help to gather detailed information
 Helps to reduce customer churn
 Help to gain best method to collect market information

Concept correlation and regression and its uses in
business
Correlation: The concept of correlation is considered as the statistically term which reflects
the extent or degree to which two or more aspects and variables are coordinated with each
other.
 Correlation enables organisation to forecast future and develop planning accordingly.
Effective planning helps business to attain the objective of growth and development.

Continuous
Regression: Regression is referred as the set of statistical processes which is undertaken by
business to estimate interrelationship between a independent variable as well as dependent
variables.
 Regression facilitates organisation to understand and analyse relationship between various
aspects such as consumer income and market demand for goods. Business takes effective
decisions on the bases of these relationship.

Concept of time series and its use
Time series is considered as the concept which are related to observation
in sequential manner. It includes various discrete-time and various
succession intervals. It is also known as running chart and time is
independent in which all task needs to be performed.
 It is effective model that helps organisation to forecast various
business metrics such as organisational customer’s, sales, turnover
and other aspects.

Provide a critique of issues surrounding the analysis
technique
Business implements different analysis
techniques such as factor analysis, regression analysis,
decision-making, factors analysis, data-mining and system
analysis that facilitates organisation to analyse situations
in appropriate manner than create planning and strategies
accordingly.

Big data and its use in modern business decision-making
Big data is considered as the concept that is related to the collection of data which
is large in size as well as continuously growing with time. It is defined as the set of various
structured, semi-structured and unstructured data that enables organisation to maintain their
data and records systematic manner that can be used in decision-making and strategy
formulation. Use of big data are explained below:
 It enables organisation to find out various market opportunities through making efficient
and appropriate decisions on time.

How data is collected and used to make business
decisions
 Data collection is referred as the procedure that is consist the activity
of gathering as well as measuring data and information regarding
targeted variables in systematic manner. Organisation uses various
methods and ways to collect data and use this information in
decision-making that help business to take competitive advantages.
Some data collection methods are explained below:
 Survey
 Interview
 Documents and records

Conclusion
As per above presentation, it can be concluded that qualitative and quantitative helps
organisation to gain reliable and important information. This information are uses by
organisation in decision-making process. There are various data collection methods such
as interview, questionnaire, survey, records and other sources are used for data collection.

References
 Aparicio, G., 2017. Data-Insight-Driven Project Delivery: Approach to Accelerated Project
Delivery Using Data Analytics, Data Mining and Data Visualization.
 Schelp, K. and Zheng, D., 2017, July. Linear Sales Automation and Data Insight As a Step
Towards Programmatic TV. In SMPTE17: Embracing Connective Media (pp. 1-12). SMPTE
 Couper, M.P., 2017. New developments in survey data collection. Annual Review of
Sociology, 43, pp.121-145.
 Clark, K.R. and Vealé, B.L., 2018. Strategies to enhance data collection and analysis in
qualitative research. Radiologic technology, 89(5), pp.482CT-485CT..

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