1. What is the difference between?
• Mass Market
• Target Market
• Database Market

2. Customer Database
&
Database Marketing

3. Session Coverage
• Customer Databases
• Data Warehouses
• Data Mining

4. DATABASE MARKETING
• Companies treat all customers as one body, one
intellect or one segment
• Communication campaign (in most cases) send
the same message or make same offer to all the
customers
• This is against the strategic goal of database
marketing
• “It involves use of computers to capture
transaction information and track customer
profiles”

5. NEED FOR DATABASE
MARKETING

6. So Many Changes in Marketing
Retail / Banking
• Kariana Shops
(merchants)
• 18 Million in India
• Know you & family
• One to one relation
• Personal Service
• Recognize you, your
needs and want
• “Your Loyalty must for
their business”
• Retail Store Chains
• Impossible for them to
know each customer in
individualized fashion
• Only with sophisticated
marketing database
technology, we can
capture, analyze and act
on same interpersonal
marketing opportunities

7. Target Marketing Segmentation
Two Approaches
• Cognitive
• (look Like)
• Demographic
– Age, Income, Edu
• Psychographic
– VALS
“Very logical approach to
refine suspect to more
likely prospect”
•
•
•
•
Behavioral
How they act?
Requires base info
Requires all transaction
information electronically
– Date of last to most recent
purchase
– Frequency of purchase
– Av amount spent per
order
BUT..THIS IS ONLY THE ENTRY POINT INTO THE
PRACTICE OF INTELLIGENT MARKETING

8. Analysis can now begin
• RFM MODEL
• Sort customers by purchase date
• Divide customers list into 5 equal
segments
• Next sort customers by no of orders and
monetary value
• RFM Score-Best Customer Segment-111
• Worst Customer Segment-555

9. RFM Model

10. Results
• It answers-What %age of your sales has come
from which segment (80 / 20 rule)
• Implement new marketing campaign on certain
%ages of each segment
• Test their response
• Benefits:
• Easy and cost effective
• Increased response rates
• Greater Profit

11. Profit and Loss from RFM Cells

12. HP on Customer Loyalty
• A very satisfied customer is 6x more likely to
repurchase than a satisfied one
• The average customer with a problem
eventually tells 9 other people
• Acquiring a new customer costs 5-7x more
than retaining one
• An increase in customer retention of 5% can
boost profits 25-85%

13. Database Marketing System-Model
Memory
Intelligence
Output
Data
Other
Data
Customer
Data
Transaction
Data
Data
Warehouse
Database
Data Analytic
Tools/Software
Marketing
Decisions

14. Geo-demographic Database
Data
Techniques
Clusters
Pin codes
Demographics
Segmentation
Cluster
Distinct
Analysis
Purchase
Output/Application
Clusters
Targeting
used for
Advertising/Promotion
Different habits

15. Different Trends in terms of Clusters
Customers Same
Preferences, Existing
Brands would be Similar
Preferences-Scattered
throughout,1st brand to
position in center
Firms develop many
brands

16. Classification of Data
Classification
Internal Data
External Data

17. Internal Data
• Generated within the organization.
• May be readily available or may require
considerable processing before marketer can
use it.
• Sales and Cost data compiled in regular
accounting process.
• Importance:
• Reebok: Analyzed internal sales data and found
that internet sales was only 0.7% and retailers
had bad feelings about it. STOPPED