1. Optimal Database Marketing Drozdenko & Drake, 2002 1

2. 2 Database Maintenance and Coding Copyright © 1999 by Ancell School of Business. All Rights Reserved. Chapter 4

3. Optimal Database Marketing Drozdenko & Drake, 2002 3 Objectives To evaluate the importance of database maintenance. To examine what aspects of the marketing database need to be maintained and updated. To consider how records on the database are coded to monitor marketing programs.

4. Optimal Database Marketing Drozdenko & Drake, 2002 4 Standard Database Maintenance Routines De-duping the customer file “Householding” the customer file Purging of old customer records Changes in contact information (address, phone number, e-mail) Address standardization Removal of names on databases at consumer’s request Identifying customers with match codes

5. Optimal Database Marketing Drozdenko & Drake, 2002 5 Database Maintenance, Other Issues… Merge/purge processing Coding source and promotional offers Adding decoy records (salting the customer file) Identifying credit risks and frauds Field updating rules Reporting summary and aggregate level information Database storage and security Database maintenance schedules Technical aspects of database maintenance

6. Optimal Database Marketing Drozdenko & Drake, 2002 6 Merge / Purge Databases are continually being modified to reflect changes to customer records. Merging refers to the process of combining two or more lists as occurs with data enhancement. Purging refers to the elimination of records for any of a number of purposes, such as for name duplication or for non-deliverable address.

7. Optimal Database Marketing Drozdenko & Drake, 2002 7 De-duping the Customer File Duplicate names on a marketing database can occur for a number of reasons: Customer’s name and/or address appeared different on an external list versus the house file. For a particular order, customer used a different mailing address. The direct marketer confused the bill to/ship to addresses in the system.

8. Optimal Database Marketing Drozdenko & Drake, 2002 8 Exhibit 4.1 As the percentage of duplicate records increases, so does the associated expense. The figure shows the costs of different levels of duplicates in files of various sizes assuming the cost of mailing is $.50 for each piece mailed. For example 50,000 X 10% = 5,000 x $.50 = $2,500

9. Optimal Database Marketing Drozdenko & Drake, 2002 9 “Householding” the Customer File When multiple contacts at one address are not desirable, as in the case of mailing a large annual catalog, direct marketers should identify multiple household accounts at a single address and thereby obtain promotional efficiencies and effectiveness. Depending on the situation, marketers may want to keep multiple contacts at the same address.

10. Optimal Database Marketing Drozdenko & Drake, 2002 10 Purging of Old Customer Records Examples of names purged include: Inactive for the past 3 years No promotions sent to the customer for the past 3 years Unable to be address confirmed for over 2 years Lack of external verification Deceased Non-deliverable (nixie)

11. Optimal Database Marketing Drozdenko & Drake, 2002 11 Changes in Contact Information For mail, a service called National Change of Address processing (NCOA processing) helps to eliminate non-deliverables (nixies). Incorrect E-mail addresses and telephone numbers also increase cost and should be changed or eliminated.

12. Optimal Database Marketing Drozdenko & Drake, 2002 12 Address Standardization By processing your list or file to meet USPS regulations, you can save money and stabilize postal rates. It also improves matching for purposes of de-duping or “householding” the customer file. The process of “cleaning up” a mailing list is known as address validation and standardization and is performed by the use of CASS (USPS Coding Accuracy Support System) certified software.

13. Optimal Database Marketing Drozdenko & Drake, 2002 13 Removal of Names from Databases at Consumer Request Some consumers do not want unsolicited offers from direct marketers. The Direct Marketing Association (DMA, http://www.the-dma.org) maintains a file of people who requested that their names be removed from mail, telephone and e-mail databases.

14. Optimal Database Marketing Drozdenko & Drake, 2002 14 Direct marketers are also required remove names from databases upon direct request from mail or phone call recipients. Direct marketers must be aware of federal and state laws regarding contacting customers and prospects. There are fines associated with non- compliance with these regulations. Removal of Names from Databases at Consumer Request

15. Optimal Database Marketing Drozdenko & Drake, 2002 15 Coding Records to Increase Performance customers the source of the record media marketing programs Codes are added to customer records to identify…

16. Optimal Database Marketing Drozdenko & Drake, 2002 16 Identifying Customers With Match Coding Duplicate records of the same customer occur. How can this happen? Names can be written different ways in different databases that are being merged. Ronald Drozdenko R. Drozdenko R. Drozenko Dr. Ronald Drozdenko

17. Optimal Database Marketing Drozdenko & Drake, 2002 17 Match coding involves taking elements of the name and address to develop a unique identifier of an individual Identifying Customers With Match Coding

18. Optimal Database Marketing Drozdenko & Drake, 2002 18 Purposes of Match Code Reduces contact costs due to redundancy Avoids contacting an individual who requested that their name be removed from the list Why would a direct marketer use match coding?

19. Optimal Database Marketing Drozdenko & Drake, 2002 19 Example of Match Coding

20. Optimal Database Marketing Drozdenko & Drake, 2002 20 Tight code matching increases duplicates; loose code matching reduces the probability of duplicates. Tight code matching increases the probability that legitimate customers will be included; loose code matching increases the probability that unqualified customers will be included. Match Coding Precision Loose versus Tight What are the advantages/disadvantages of loose versus tight matching?

21. Optimal Database Marketing Drozdenko & Drake, 2002 21 Match Codes Match code method will vary based on organizational needs. For some organizations, it is sufficient to code only by address and last name. Further, some organizations may only be concerned with address if they know it is not a multiple household dwelling. Cost of the mailing is a consideration.

22. Optimal Database Marketing Drozdenko & Drake, 2002 22 Coding Source and Promotional Offers Marketers code the original source of entry of a record onto the house file Individual records in a database can come from a number of sources. Lists purchased by the marketer Response to advertisements Cards filled out at retail location

23. Optimal Database Marketing Drozdenko & Drake, 2002 23 Exhibit 4.3 (Mailing Label from catalog) *********************ECRLOT**R-004 LAURA MARTIN 346 KETTLE RD WOODBURY CT 06798 -3901 3357231 853000922 E Key Code I.D. Code Media Code BULK RATE U.S. POSTAGE PAID EDDIE BAUER

24. Optimal Database Marketing Drozdenko & Drake, 2002 24 Source codes are used to evaluate the performance of the specific way that a record was acquired. Poor performing lists or promotions could be eliminated or modified. Good performing lists or promotions could be used as models for future list acquisitions or marketing programs. Source Code Why does a marketer need to know the source of the record?

25. Optimal Database Marketing Drozdenko & Drake, 2002 25 Coding Marketing Programs Organizations use a number of methods to code records as to which marketing programs have been received. Creative packages, media, offers, pricing, etc. can all be coded. Records are also identified as being part of control groups for testing.

26. Optimal Database Marketing Drozdenko & Drake, 2002 26 Some organizations call this coding “Key” coding. Other organizations have both “Key” and “Media” codes. Still other organizations code source and program information together. Coding Marketing Programs

27. Optimal Database Marketing Drozdenko & Drake, 2002 27 Key Code Each marketing activity should be identified in the database. For example, a company that markets CDs, videotapes, and books wants to relate each new mailing, direct response TV campaign, and magazine insert to an order. The Key Code allows the marketer to evaluate the performance of each marketing program.

28. Optimal Database Marketing Drozdenko & Drake, 2002 28 Other Codes Offer Catalog Test Payment Ordering Statistical Model Broker ID Ad Item Decile Based on organization needs, other types of codes have been developed.

29. Optimal Database Marketing Drozdenko & Drake, 2002 29 Owners of databases often include names in the file that are not real customers. Salting, Decoy Records

30. Optimal Database Marketing Drozdenko & Drake, 2002 30 Check the performance and security of outside services that are responsible for mailing the promotional offer or fulfilling orders. To monitor delivery of packages for timed programs. Salting, Decoy Records

31. Optimal Database Marketing Drozdenko & Drake, 2002 31 For companies that rent their lists to other companies the “decoy” names on the list can be used to verify adherence to the list rental agreement (e.g., one-time or limited use). Note: If a customer on a rented list responds to an offer, he/she can then be added to the marketer’s database for unlimited use. Salting, Decoy Records

32. Optimal Database Marketing Drozdenko & Drake, 2002 32 Identifying Credit Risks National credit services allow for the flagging or removal from files of an individual who is considered a poor credit risk. Credit evaluation allows promotions to be more cost effective by restricting offers to individuals who are likely to pay for products received.

33. Optimal Database Marketing Drozdenko & Drake, 2002 33 Highly personalized credit information about customers is only available to credit grantors (e.g., 30 day free trial agreements) and not available to organizations only making offers. Credit organization can, however, provide less personalized credit information based on modeling derived from aggregates. Identifying Credit Risks

34. Optimal Database Marketing Drozdenko & Drake, 2002 34 Some organizations will develop internal models to evaluate credit risk. These models use existing house data. Internal models may include zip level information. Identifying Credit Risks

35. Optimal Database Marketing Drozdenko & Drake, 2002 35 Field Updating Rules Every data item (field, variable) on a database has rules regarding how it will be maintained. When a promotion is sent, various fields will be updated: The promotion is marked on the file as being sent for each customer who received it. The “date of last promotion” field is updated. The “total number of promotions sent” field is updated.

36. Optimal Database Marketing Drozdenko & Drake, 2002 36 Field Updating Rules When payment for product arrives, the following types of fields will also be updated: The field “total dollars paid” will be updated. The field “total products paid” will be updated. The field “date of last payment” will be updated.

37. Optimal Database Marketing Drozdenko & Drake, 2002 37 Other fields feeding off of core payment fields will also be updated. For example, the field “Number of products paid in the last 12 months” will be updated. Field Updating Rules

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39. Optimal Database Marketing Drozdenko & Drake, 2002 39 Summary Information Total mailings Total purchases Total orders Total orders by source, key, media, etc. Cost per order In addition to updating individual records, aggregate data are also calculated and updated by day, week, month, etc. Sales per thousand pieces mailed Profit per thousand pieces mailed Average life-time value

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42. Optimal Database Marketing Drozdenko & Drake, 2002 42 Database Storage and Security The survival of direct marketing organizations is dependent on the database. Therefore, it is essential to protect it. Database files should be backed-up regularly. Back-up files should be stored in a safe location (often off-site) to protect from possible damage such as due to fire and water. Access to the file should be limited to essential personnel. Encryption techniques should be considered to protect the file from unauthorized use.

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44. Optimal Database Marketing Drozdenko & Drake, 2002 44 Database Maintenance Schedules Database maintenance involves a cost. Merging and purging names, flagging credit risks, updating file fields, backing-up files, etc. requires processing and human resource time. Therefore, maintenance should be performed at intervals that minimize maintenance costs while optimizing marketing efficiency and effectiveness.

45. Optimal Database Marketing Drozdenko & Drake, 2002 45 Often fields are automatically updated as new data are entered. This eliminates the need to perform specific updating procedures. However, some maintenance, such as address updating, should be performed as needed (e.g., just prior to mailings). Database Maintenance Schedules

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47. Optimal Database Marketing Drozdenko & Drake, 2002 47 Some Technical Aspects of Database Maintenance Most relational databases are manipulated with SQL. SQL (pronounced see-quill or S-Q-L) stands for structured query language. Queries are used to extract or count data. SQL is a simple set of 36 commands that are relatively complete. Examples of SQL commands are: Select, From, Where, Order By, Group By, And, Or

48. Optimal Database Marketing Drozdenko & Drake, 2002 48 Review Questions 1. What are some of the reasons for routinely maintaining the database? 2. What is meant by merge/purge? 3. What are some of the codes marketers place on individual records, and how are they used? 4. Why would a marketer put decoy records on a database? 5. When and how is a database updated? Give examples of some of the fields that would be routinely updated. 6. Why is database security important to both consumers and marketers?