Customer database and database marketing 19-10-13 [compatibility mode]
This document discusses database marketing and how it has become necessary for large retail chains and banks due to their inability to know each customer individually. It covers customer databases, data warehousing, and data mining. Database marketing involves using computer technology to track customer transactions and profiles to communicate with customers individually. The document then discusses how RFM analysis can segment customers into groups based on recency, frequency, and monetary value of purchases to implement targeted marketing campaigns. Maintaining high customer loyalty and retention is important for business profits. Database marketing systems combine customer, transaction, and other data with data analytics to generate targeted marketing decisions and customer clusters. Both internal and external data are important for database marketing analysis.
Customer database and database marketing 19-10-13 [compatibility mode]
- 1. What is the difference between? • Mass Market • Target Market • Database Market
- 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”
- 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