1. Chapter 3: Using Databases

2. 2 V. Kumar and W. Reinartz – Customer Relationship Management Overview Topics discussed:  Types of databases  Categorization based on information in the databases  Categorization based on the nature of the underlying marketing activities  Categorization based on the database technology  The benefits of marketing databases  The uses of marketing databases

3. 3 V. Kumar and W. Reinartz – Customer Relationship Management Overview  Categorization  Based on their main business functions  Databases managing business operations  Databases supporting decision-making activities  Alternate categorization:  Information included in the databases  Nature of the underlying marketing activities  Database technology used

4. 4 V. Kumar and W. Reinartz – Customer Relationship Management Customer Database Prospect Database Cluster Database Enhancement Database Categorization Based on Information in the Databases

5. 5 V. Kumar and W. Reinartz – Customer Relationship Management Customer Database  Data from active and inactive customers  Information included in customer databases:  Basic information: name, address, zip code, and telephone number  Demographic information: age, gender, marital status, education, number of people in household, income  Psychographic information: values, activities, interests, preference  Transaction history: frequency of purchase, amount of spending  Other relevant information: inquiries and referrals, satisfaction, loyalty

6. 6 V. Kumar and W. Reinartz – Customer Relationship Management Customer Database (2)  Data from Inactive Customers:  How long have the customers been inactive?  How long have they been active?  What was their purchasing pattern when they were active?  How much did they spend?  How were they initially acquired?  Why are they inactive?

7. 7 V. Kumar and W. Reinartz – Customer Relationship Management Examples for Customer Database  D&B’s U.S Marketing File: Customer database comprising of telemarketing, direct mail, competitor analysis and other types of data pertaining to 130 million companies in more than 190 countries  InfoBase eProducts –from Acxiom provides the user companies with the email addresses of their customers  Email Marketing: most inexpensive profit-generating marketing tool to augment companies’ direct mail or other channels of communication with customers

8. 8 V. Kumar and W. Reinartz – Customer Relationship Management Prospect Database  Non-customers that have profiles that are similar to the profiles of existing customers  Segments prospects and positions the company’s differentiated products to the prospects’ specific needs  Examples of some Prospect databases used in the industry:  InfoBase List: Offers a collection of US consumer data available in one source for list rentals covering 120 million households and 190 million individuals  Harris Selectory Online: A prospect database from D&B which helps companies find new customers allowing companies to:  Qualify leads that they are developing  Contact the decision-maker best suited to hear their sales pitch  Research potential opportunities

9. 9 V. Kumar and W. Reinartz – Customer Relationship Management Cluster Database  Clusters defined based on geographic reference groups, affinity groups, and lifestyle reference groups  Depending on the membership of prospective customers to specific clusters, firms can customize their marketing communications  Example: The Prizm database  Segments every U.S neighborhood into 62 distinct areas  Every Prizm database is categorized into groups with every group having clusters 5 clusters with the nation‘s most affluent social people S1 (Elite Suburbs) Executives and professionals U1 (Urban Uptown) 3 clusters making the upper crust of America‘s second and satellite cities C1 (City Society) Clusters comprise of multi-income families with school age kids and are headed by well-educated executives and professionals T1 (Landed Gentry)

10. 10 V. Kumar and W. Reinartz – Customer Relationship Management Enhancement Database  Used to transfer additional information on customers and prospects  An overlaying process is used that eliminates duplications  Enhancements may include: demographic and psychographic data, transaction history, changes in address, changes in income levels, privacy status, new product categories bought recently  Example: InfoBase Enhanced  InfoBase provides a large collection of U.S customer information like telephone & address data, mailing lists including hotline files, e-mail data  InfoBase Enhanced provides the ability to append the latest demographics, socio- economic and lifestyle data to your existing in-house customer database

11. 11 V. Kumar and W. Reinartz – Customer Relationship Management Categorization Based on The Nature of Underlying Marketing Activities  Passive marketing database  A mailing list that passively stores information about acquired customers  Future marketing efforts target the same customers in the list Campaign 1DatabaseCampaign 2 Customer List Customer List

12. 12 V. Kumar and W. Reinartz – Customer Relationship Management Categorization Based on The Nature of Underlying Marketing Activities (2)  Active Marketing Database Strategic Marketing Plan ExecutionResultsData UpdatesDatabase Marketing Program

13. 13 V. Kumar and W. Reinartz – Customer Relationship Management Categorization Based on Database Technology  Hierarchical database  Inverted database  Relational database

14. 14 V. Kumar and W. Reinartz – Customer Relationship Management Hierarchical Database  All information pertaining to a customer will be in a master record  Useful when the queries are standard and routine but high speed processing is required  Preferred in the banking, airline, and hotel industries  Organized in a tree-like structure  Example of a custom mill business database:

15. 15 V. Kumar and W. Reinartz – Customer Relationship Management Inverted Database & Relational Database  Inverted Database  Suited for direct marketing application  Has speed and flexibility to respond to unanticipated questions  Easy to add new elements, when updated information is acquired  Relational Database  Has the greatest flexibility  Users can create queries to extract and combine information  Examples of Relational Database:  Oracle, SQL Server, and Microsoft Access

16. 16 V. Kumar and W. Reinartz – Customer Relationship Management Benefits of Marketing Databases  Ability to carry out profitable segmentation  Ability to retain customers and repeat business  Ability to spot potential profitable customers

17. 17 V. Kumar and W. Reinartz – Customer Relationship Management Uses of Marketing Databases Uses of Marketing Database Uses of Marketing Database Uses that directly influence other Business Operations Uses that directly influence Customer Relationship

18. 18 V. Kumar and W. Reinartz – Customer Relationship Management Uses of Marketing Databases (2) Uses that directly influence Customer Relationship:  Identify and profile the best customers  Develop new customers  Deliver customized messages consistent with product/service usage  Send follow-up messages to customers for post-purchase reinforcement  Cross-sell products/services  Ensure cost-effective communication with customers  Improve promotion result by efficient targeting  Personalize customer service  Stealth communication with customers

19. 19 V. Kumar and W. Reinartz – Customer Relationship Management Uses of Marketing Databases (3) Uses that directly influence other business operations:  Evaluate and refine existing marketing practice  Maintain brand equity  Increase effectiveness of distribution channels  Conduct product and market research  Integrate the marketing program  Create a new valuable management resource

20. 20 V. Kumar and W. Reinartz – Customer Relationship Management CRM at Work  Effective use of email marketing  Emails are the most financially efficient form of direct communication between firms and customers  Most effective day of the week to communicate with potential customer:  B2C firms: Wednesday and Friday  B2B firms: Monday or Tuesday  American Express and Database Clustering  American Express clusters customers’ purchasing behavior data and provide upgrades or cross-selling offers based on the customer’s change in cluster group  Accurate database clustering is important for marketers, as customer databases evolve over time  Evolving and moving clustering system allows customers to move freely in and out of clusters as is warranted by their purchase behavior

21. 21 V. Kumar and W. Reinartz – Customer Relationship Management CRM at Work (2)  Enhancement Database  County drains, a drainage service company, has built its business around superior customer service  Challenged to provide premium customer service, as its customer base was expanding rapidly  Chose an adaptive database, GoldMine Premium Edition, which allowed County Drains to : a) continue with it premium customer service and (b) proactively engage with customer to provide more relevant services  Active Marketing Database  Harrah’s Casino constantly update its customer data through the customers’ use of its loyalty card  The updated customer data allows Harrah’s to create a customized rewards system  Success of this program can be seen in Harrah’s expansion and profitability  In 2003, opened 26 new casinos and earned $4 million more than the prior year

22. 22 V. Kumar and W. Reinartz – Customer Relationship Management Summary  Effective Database analysis is important for successful CRM  Data from active and inactive customers are important to ensure efficient marketing function  Marketing databases allow marketers to analyze customers and classify them into different groups to implement different marketing programs effectively  Databases also enable marketers to determine critical factors influencing customer satisfaction and take measures to retain existing customers at lowest cost