Data Insights and Business Decisions in the Retail Industry Report

This report provides an overview of data insights and their application in the retail industry. It begins by introducing the concept of data insights and highlights the types of data collected, including the use of big data for customer recommendations and market trend analysis. The report then contrasts orthodox market research with big data approaches and details how information is captured and stored using both structured and unstructured databases. It explores the impact of technological developments on the retail industry, such as increased sales and improved customer retention. The report also discusses how information systems support day-to-day operations and suggests methods to improve data capture and utilization, including the use of Optical Character Recognition. The conclusion emphasizes the importance of data insights for strategic decision-making and enhanced competitiveness in the retail sector, supported by references to relevant books and online resources.

Data insights for business
decisions

Table of content
 Introduction
 Presenting the type of data collected by retail industry
 Orthodox market research
 How information is captured and stored with reference to type of database
 Impact of technological development within retail industry
 How information is used within day to operations of organization within
sector
 How to improve the data capture and use in sector
 Conclusion
 References

Introduction
 Data insights are the knowledge which company gain from
analysing the sets of information pertaining to different situation.
 The present PPT will highlight the importance of tool used by the
retail industry and also examine the role of information within the
same.

Presenting the type of data collected
by retail industry
 Retail industry uses big data
which enable companies to
create customer
recommendations based upon
their purchase history.
 This in turn assists them to
improve the customer service
and result in personalized
shopping experience.
 In this, super-sized data also
help in forecasting trend as
well as making strategic
decision based upon the
market analysis.

Orthodox market research
 Orthodox market research is recognized as those market research
which companies performed in their past times.
 This includes survey, observation, questionnaire through which
company determine the changing nature of customers so that they
make effective suggestion.
 Orthodox market research is completely differ from big data such
that big data is made up of large, unstructured and complex data
sets which gathered in a real time,
 Also, it can be stated that through big data, market research
replaced. It is relied upon the advance technologies which assist
them to determine the actual trend through the purchasing power of
customers.

How information is captured and
stored with reference to type of
database
In retail industry there are two
types of database uses such as
structured and unstructured Database
Structured
Transaction data,
CRM data
POS transaction
Unstructured
social media feeds,
videos
digital images

Impact of technological development
within retail industry
 Technology development plays an
important role in the welfare of the
company such that with use of data,
companies increase sales, reduce
shop-lifting and eliminate the lines
in order to make better decision.
 Along with this, it is also identified
that through technology
development, like AR companies
increases their customer retention
rates and by analysing their
purchasing trend, it aware
companies to make decision for the
welfare of the business.

How information is used within day
to operations of organization within
sector
 Information system is used by the company in order to use the
information when it comes to storing the operational data,
communication records and documents so that companies make
strategic decision for the welfare of the company.
 Every organization needs records of all its activities, at that time,
advance technology plays an important role to solve and store the
information for the longer term.

How to improve the data capture and
use in sector
 In order to improve the data within retail sector, analyst must use
advance technologies within a workplace so that they make
effective results for the welfare of a company.
 In this, company may use Optical character recognition which
reduces the labour cost as well as manual keying of data. This in
turn assist them to improve the data capture and increase the
performance as well.

Conclusion
 By summing up above it has been concluded that big data has been
used by the retail industry in order to make better decisions for
future.
 The study also summarized that information gained through big
data and advance technologies system can be assist to make future
decision so that companies increases the competitiveness.

References
Books and Journals
Carmichael, G., Chen, Y.W. and Luo, C., 2018, May. Data-driven
segmentation of consumers' purchase behaviour in the retail industry. In 2018
4th International Conference on Information Management (ICIM) (pp. 215-
219). IEEE.
Cheng, W. and Wang, J., 2019. Big Data Analytics in the E-commerce Retail
Industry. International Journal of Engineering Intelligent Systems. 27(4).
Jabado, R. and Jallouli, R., 2021. An Enriched Framework for CRM Success
Factors Outlining Data Analytics Capabilities’ Dimension: A Case Study from
the Retail Industry. The Importance of New Technologies and
Entrepreneurship in Business Development: In The Context of Economic
Diversity in Developing Countries. 194. p.102.
Santoro, G., Fiano, F., Bertoldi, B. and Ciampi, F., 2019. Big data for business
management in the retail industry. Management Decision.

Continued…
Sibdari, S., 2019, September. Customer Data Security in Retail
Industry with Profit Maximization. In FIRST WORKSHOP ON
INFORMATION SECURITY (ISec2019) (p. 33).
Online
How do global retail leaders uses big data. 2020. [Online]. Available
through: <https://blog.datumize.com/how-do-global-retail-leaders-use-
big-data-5-real-life-examples>.