This document discusses how data mining can be used in the retail industry. It begins by introducing how retail industries collect large amounts of customer data. It then describes some of the major applications of retail data mining, including identifying customer behaviors, discovering shopping patterns and trends, and improving customer service. The document also outlines some common problems retail industries face, such as employee turnover, auditing issues, and economic challenges. It provides examples of how data mining can help with risk management, fraud detection, and acquiring/retaining customers. In conclusion, the document states data mining allows retailers to better understand customer needs based on purchase histories to target promotions and incentives.

1. DATA MINING IN
RETAIL INDUSTRY
1

2. ►INTRODUCTION
►APPLICATION OF RETAIL INDUSTRY
►MAJOR PROBLEM OF RETAIL INDUSTRY
►RISK MANAGEMENT
►FRAUD DETECTION
►CONCLUSION
2

3. INTRODUCTION
 Retail industry collects large amount of data on sales and
customer shopping history.
 The quantity of data collected continues to expand rapidly,
especially due to the increasing ease, availability and
popularity of the business conducted on web, or e-
commerce.
 Retail industry provides a rich source for data mining.
 Retail data mining can help identify customer behavior,
discover customer shopping patterns and trends, improve
the quality of customer service. 3

4. Applications of Retail Industry
 Retail industry: huge amounts of data on sales,
customer shopping history, etc.
Applications of retail data mining
 Identify customer buying behaviors
 Discover customer shopping patterns and trends
 Improve the quality of customer service
 Achieve better customer retention and satisfaction
 Enhance goods consumption ratios
 Design more effective goods transportation and
distribution policies 4

5. EXAMPLE FOR RETAIL: CRM
(Customer Relationship Management)
 Customer Relationship Management (CRM) is a business
philosophy involving identifying, understanding and better
providing for your customers while building a relationship with
each customer to improve customer satisfaction and maximize
profits. It’s about understanding and responding to customers’
needs.
 To manage the relationship with the customer a business needs
to collect the right information about its customers and organize
that information for proper analysis and action. It needs to keep
that information up-to-date, make it accessible to employees,
and provide the knowhow for employees to convert that data
into products better matched to customers’ needs.
5

6. 6

7. MAJOR POBLEMS OF RETAIL INDUSTRY
 Employee turnover
Employee turnover refers to the number or percentage of workers who leave an
organization and are replaced by new employees.
► Auditing
Financial auditing is the process of examining an organization's financial records to
determine if they are accurate and in accordance with any applicable regulations, and laws.
 Economic Challenges
Economic issues facing the world economy include prospects for growth, energy and the
environment, labor issues and the impact of new technologies.
 Technology
Speed and efficiency are expected of today’s retail businesses.
7

8. RISK MANAGEMENT
 Retail organizations use data mining to understand which
products may be vulnerable to competitive offers or changing
customer purchasing patterns.
 Data mining enables retailers to remain competitive and reduce
risks by helping them understand what their customers are
really doing.
 Retailers can then target those customers who are more likely
to buy a certain brand or product
8

9. FRAUD DETECTION
 Retail shrink because of dishonest employees.
 Some super-markets use CCTV, along with data mining, to
enable retail loss prevention to expose cashier stealing.
 Loss of data, credit card fraud, duplicate payment can be
avoided with the help of data mining
9

10. CONCLUSION
 Data mining helps in acquiring and retaining customers
in the retail industry.
 Retail industry deals with high levels of competition,
and can use data mining to better understand
customers’ needs.
 Retailer can study customers’ past purchasing histories
and know with what kinds of promotions and
incentives to target customers.
10

11. THANK YOU
11