What is the difference between?
• Mass Market
• Target Market
• Database Market
Customer Database
&
Database Marketing
Session Coverage
• Customer Databases
• Data Warehouses
• Data Mining
DATABASE MARKETING
• Companies treat all customers as one body, one
intellect or one segment
• Communication campaign (in ...
NEED FOR DATABASE
MARKETING
So Many Changes in Marketing
Retail / Banking
• Kariana Shops
(merchants)
• 18 Million in India
• Know you & family
• One ...
Target Marketing Segmentation
Two Approaches
• Cognitive
• (look Like)
• Demographic
– Age, Income, Edu

• Psychographic
–...
Analysis can now begin
• RFM MODEL
• Sort customers by purchase date
• Divide customers list into 5 equal
segments
• Next ...
RFM Model
Results
• It answers-What %age of your sales has come
from which segment (80 / 20 rule)
• Implement new marketing campaign...
Profit and Loss from RFM Cells
HP on Customer Loyalty
• A very satisfied customer is 6x more likely to
repurchase than a satisfied one
• The average cust...
Database Marketing System-Model
Memory

Intelligence

Output

Data
Other
Data

Customer
Data

Transaction
Data

Data
Wareh...
Geo-demographic Database
Data

Techniques

Clusters

Pin codes

Demographics

Segmentation

Cluster

Distinct

Analysis
Pu...
Different Trends in terms of Clusters

Customers Same
Preferences, Existing
Brands would be Similar

Preferences-Scattered...
Classification of Data
Classification

Internal Data

External Data
Internal Data
• Generated within the organization.
• May be readily available or may require
considerable processing befor...
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Customer database and database marketing 19-10-13 [compatibility mode]

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Customer database and database marketing 19-10-13 [compatibility mode]

  1. 1. What is the difference between? • Mass Market • Target Market • Database Market
  2. 2. Customer Database & Database Marketing
  3. 3. Session Coverage • Customer Databases • Data Warehouses • Data Mining
  4. 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. 5. NEED FOR DATABASE MARKETING
  6. 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. 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. 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. 9. RFM Model
  10. 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. 11. Profit and Loss from RFM Cells
  12. 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. 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. 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. 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. 16. Classification of Data Classification Internal Data External Data
  17. 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
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