The use of Data Mining for marketing purpose.

1. DATA MINING IN
MARKETING
By Shweta Metar

2. Data Mining – Introduction
• Process of extracting hidden patterns from data.
• Process of analyzing data from different perspectives and summarizing it
into useful information.
• Process of finding correlations or patterns among dozens of fields in
large relational databases.

3. Data Mining – Process

4. Data Mining – Barriers
• User’s privacy at risk.
• Misuse of Information.
• Accuracy of data.
• Cost at implementation stage

5. Data Mining – Marketing
• Customer Decision Making.
• Improve CRM and Market analysis.
• Increase Return on Investment.
• Fraud detection and customer retention.
• Predict future trends.

6. Marketing – 4 P’s

7. Data Mining – Types
Knowledge Based Market Basket Analysis
Social Media Based

8. Data Mining – Techniques
• Cluster Analysis To Identify Single Target Groups:-
Eg: Showing toys advertisement to children.
• Regression Analysis To Make Marketing Forecasts:-
Eg: Men will also be using Fairness Cream
• Classification Analysis To Identify Spams:-
Eg: Not every person wants to buy product some are Window
Shoppers.

9. Data Mining – Techniques
• Association Rule Learning To Discover Links Between Data:-
Eg: 90% of customers who buy a product online then by another,
and always the same one.
• Intrusion Detection For Greater System Security:-
Eg: People who try to hack the database to get the details of the
customers.
• Neural Networks To Automate Learning:-
Eg: The computer managing your database, “learns” to identify a
certain pattern containing elements with precise relationships with each
other.

10. Example
• Amazon:-
Amazon is using the data they have
collected to improve the customer-service.
• Starbucks:-
Starbucks uses data to determine the
best locations for their stores.