The Devil Is In The Data

430 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
430
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

The Devil Is In The Data

  1. 1. The Devil Is In The Data DMB Conference March, 2001 JOHN M. COE, President Database Marketing Associates, Inc. 480-778-9900
  2. 2. The Importance of B2B Data <ul><li>Business data used in a direct marketing campaign accounts for 50-75% of the leverage for success </li></ul><ul><li>Other levers include: </li></ul><ul><ul><li>Offer (20% - 30%) </li></ul></ul><ul><ul><li>Media + seq./freq. (20% - 25%) </li></ul></ul><ul><ul><li>Creative (10% - 15%) </li></ul></ul>
  3. 3. The Good News <ul><li>More business data available today </li></ul><ul><li>More sources both internal and external </li></ul><ul><li>New developments </li></ul><ul><ul><li>co-op databases </li></ul></ul><ul><ul><li>strategic partnerships </li></ul></ul><ul><li>New tools </li></ul><ul><ul><li>on-line count systems </li></ul></ul><ul><ul><li>B2B service bureaus </li></ul></ul>
  4. 4. The Bad News <ul><li>Accuracy continues to be a problem </li></ul><ul><li>SIC to NAICS conversion process </li></ul><ul><li>Decay rate of information on individuals is increasing </li></ul><ul><li>Most data sources are plagued by incompleteness and poor accuracy </li></ul><ul><li>Job titles do not describe function </li></ul>
  5. 5. Job Titles <ul><li>Title vs function is a key issue </li></ul><ul><li>Some new titles (WSJ Sept. 2000) </li></ul><ul><ul><li>Chief Morale Officer </li></ul></ul><ul><ul><li>Vice President of People </li></ul></ul><ul><ul><li>Chief Catalyst </li></ul></ul><ul><ul><li>Chief Listener </li></ul></ul><ul><ul><li>Code Therapist </li></ul></ul><ul><ul><li>Sex Librarian </li></ul></ul>
  6. 6. Just How Bad Is It? <ul><li>A recent telephone survey of 50 random selected records from each of three B2B data sources inaccuracies in contact name/title, phone number, company name and company address </li></ul><ul><li>Data Source % of Inaccuracies </li></ul><ul><li>B2B Trade Assn. Members 40% </li></ul><ul><li>B2B Data Compiler 50% </li></ul><ul><li>Year 2000 Industry Directory 100% </li></ul><ul><li>2.5%/month decay rate on business establishments </li></ul>
  7. 7. Business Card Test <ul><li>Pull out your business card (paper) </li></ul><ul><li>Check each element that has changed from one year ago. </li></ul><ul><ul><li>Name </li></ul></ul><ul><ul><li>Title and/or function </li></ul></ul><ul><ul><li>Company Name </li></ul></ul><ul><ul><li>Address </li></ul></ul><ul><ul><li>Phone number </li></ul></ul><ul><ul><li>E-mail address </li></ul></ul><ul><ul><li>In return for your “checked” card we will </li></ul></ul><ul><ul><li>place you on our “white paper” </li></ul></ul><ul><ul><li>subscription list. </li></ul></ul>
  8. 8. SIC to NAICS Codes <ul><li>Coding is complete </li></ul><ul><li>Early 1999 data on number of employees, establishments and revenue was completed </li></ul><ul><li>March, 2000 data bridge built </li></ul><ul><ul><li>4-digit SIC to 6-digit NAICS </li></ul></ul><ul><ul><li>Conversion tables available from Dept. of Commerce (www.doc.com) </li></ul></ul><ul><li>New UN sponsored world wide coding system on the drawing boards </li></ul>
  9. 9. NAICS Differences <ul><li>New technology sectors </li></ul><ul><li>More meaningful sectors </li></ul><ul><li>NAFTA consistency </li></ul><ul><li>5 year vs. 10 year review </li></ul><ul><li>Business process-based vs. based on companies output </li></ul>
  10. 10. B2B Data Sources <ul><li>Compiled data </li></ul><ul><li>Response lists </li></ul><ul><li>Directories </li></ul><ul><li>Trade Associations </li></ul><ul><li>Co-op databases </li></ul><ul><li>Internal sources - many </li></ul><ul><li>Customer-provided </li></ul>
  11. 11. Internal Data – Common Sources and Problems <ul><li>Accounting/financial </li></ul><ul><li>Sales force or business partners </li></ul><ul><li>Marketing </li></ul><ul><ul><li>Inquiries and leads </li></ul></ul><ul><ul><li>Trade shows/seminars </li></ul></ul><ul><ul><li>In bound call centers </li></ul></ul><ul><ul><li>Web responses </li></ul></ul><ul><li>Customer service </li></ul>
  12. 12. Frequently Encountered Data Problems <ul><li>Different address/same company </li></ul><ul><li>Characters inverted during data entry </li></ul><ul><li>Different spellings/same name </li></ul><ul><li>Last name only (no first name) </li></ul><ul><li>Different company spellings </li></ul><ul><li>No company name </li></ul><ul><li>Missing information </li></ul><ul><li>Duplicate records (customer files) </li></ul>
  13. 13. File Enhancement (Overlays) <ul><li>Match rates often lower than desired (65-70% but improving) </li></ul><ul><ul><li>Service bureaus getting better at B2B data processing </li></ul></ul><ul><ul><li>More enhancement data available </li></ul></ul><ul><li>Should be mission-specific </li></ul><ul><li>Must be refreshed often due to decay </li></ul>
  14. 14. Compiled Data <ul><li>Data gathered from diverse sources and compiled into a common format </li></ul><ul><li>For B2B data, refers to businesses, not individuals (except top person) </li></ul><ul><li>Think of compiled data as an electronic directory of businesses </li></ul><ul><li>Information often updated via phone survey (Experian called us last year) </li></ul>
  15. 15. Compiled Data Elements <ul><li>Demographic </li></ul><ul><ul><li>Address and full postal </li></ul></ul><ul><ul><li>Location type (HQ, Franchise, plant) </li></ul></ul><ul><ul><li>Ownership type </li></ul></ul><ul><li>Geographic – several types </li></ul><ul><li>Industry (up to 3 SIC/NAICS codes) </li></ul><ul><li>Size in employees or dollars </li></ul><ul><li>Credit score/risk: other financial info. </li></ul><ul><li>Executive contact(s) </li></ul>
  16. 16. What’s Good About Compiled Data? <ul><li>Widely available </li></ul><ul><li>Selectable by an array of elements that cover the target market </li></ul><ul><li>Elements often available for response analysis/profiling </li></ul><ul><li>Access to quick counts on-line </li></ul><ul><li>Relatively inexpensive </li></ul>
  17. 17. What’s Not So Good About Compiled Data? <ul><li>High rate of inaccuracy </li></ul><ul><ul><li>Contact information highly inaccurate </li></ul></ul><ul><ul><li>Company information somewhat inaccurate </li></ul></ul><ul><li>Not the fault of the data compiler </li></ul><ul><ul><li>A reflection of business today </li></ul></ul><ul><ul><li>Source information is yellow pages </li></ul></ul><ul><ul><li>No business person NCOA </li></ul></ul>
  18. 18. Response Data <ul><li>Lists of individuals that have done something specific, such as: </li></ul><ul><ul><li>Subscribed to a particular publication </li></ul></ul><ul><ul><li>Joined an industry organization </li></ul></ul><ul><ul><li>Attended a trade show </li></ul></ul><ul><ul><li>Attended a seminar </li></ul></ul><ul><ul><li>Added their name to an opt-in list </li></ul></ul><ul><ul><li>Responded to an offer </li></ul></ul><ul><ul><li>Purchased a product or service </li></ul></ul>
  19. 19. What’s Good About Response Data? <ul><li>Highly deliverable </li></ul><ul><li>New names added frequently </li></ul><ul><li>Contains product interest information </li></ul><ul><li>Source often available as select </li></ul><ul><ul><li>Direct mail, telemarketing, internet </li></ul></ul><ul><li>Offers for similar products or products in the same category often work well (affinity) </li></ul>
  20. 20. What’s Not So Good About Response Data? <ul><li>More expensive than compiled data </li></ul><ul><li>May not work if specific “targeting” selects are not available </li></ul><ul><li>Addressing problems (records not collected for DM purposes) </li></ul><ul><li>Targeted universe may be incomplete </li></ul><ul><li>Penetration within target companies likely incomplete (paid vs. controlled circulation) </li></ul>
  21. 21. A Word About eData <ul><li>Beware of non-opt-in lists </li></ul><ul><ul><li>Some double opt-in lists available </li></ul></ul><ul><ul><li>Make sure to offer “unsubscribe” option </li></ul></ul><ul><li>Do not assume that e-mail direct marketing is less expensive </li></ul><ul><ul><li>Base conclusions on complete response analysis (cost per sale vs. cost per response) </li></ul></ul><ul><li>Understand the “clutter factor” </li></ul><ul><li>Test everything </li></ul>
  22. 22. Developed Lists: The Best of Both Worlds <ul><li>Driven by segmentation strategy </li></ul><ul><li>Combine multiple data types and sources </li></ul><ul><ul><li>Compiled company information </li></ul></ul><ul><ul><li>Individual response data </li></ul></ul><ul><ul><li>Add data overlays </li></ul></ul><ul><li>Allow marketer to develop a list of individuals from specific companies who have exhibited desired behavior </li></ul>
  23. 23. Why Bother? <ul><li>Address many of the B2B data problems discussed earlier </li></ul><ul><ul><li>“The list I need isn’t available anywhere” </li></ul></ul><ul><ul><li>Inaccurate, inappropriate or missing contact name </li></ul></ul><ul><ul><li>Greatly enhanced selection criteria </li></ul></ul><ul><li>Increases response </li></ul><ul><li>Facilitates more accurate response analysis, profiling and modeling </li></ul>
  24. 24. Building Developed Lists <ul><li>Requires merging (and purging) multiple files from multiple sources </li></ul><ul><ul><li>Sophisticated B2B DP experience a must </li></ul></ul><ul><li>Necessitates paying for data you won’t use </li></ul><ul><ul><li>Higher response may justify additional costs </li></ul></ul><ul><li>Consider outsourcing entire process </li></ul>
  25. 25. Developed List Value Proposition Low Public Sourced Data Basic Compiled Business Lists Demographic Overlay Data Response Lists Developed List Co-op Data The price to value ratio of a developed list is based upon the increase in response (closed sales) it produces Price Value High Low High
  26. 26. Selecting An Outside Vendor <ul><li>Key questions to ask </li></ul><ul><ul><li>B2B specialization and understanding </li></ul></ul><ul><ul><li>Standard record layouts for B2B </li></ul></ul><ul><ul><li>Full description of capabilities </li></ul></ul><ul><li>Request a sample B2B merge/purge report package </li></ul><ul><li>Ask for a trial run and inspect results </li></ul><ul><li>Check client references </li></ul>
  27. 27. Data Hygiene <ul><li>Who wants to be a hygienist? </li></ul><ul><li>It’s everybody’s job </li></ul><ul><li>There should be a budget for hygiene </li></ul><ul><li>Standard methods of updating & cleaning B2B data </li></ul><ul><li>Some unique approaches and ideas </li></ul><ul><li>The Internet can play a powerful role </li></ul>
  28. 29. That’s all folks <ul><li>White Papers in return for your card </li></ul><ul><li>Fill out evaluations </li></ul><ul><li>Questions and Answers </li></ul><ul><li>[email_address] </li></ul>

×