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

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Transcript

  • 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

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