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Marketing Lead Data:
Five Steps to Higher Revenue

           July 20, 2011
          David M. Raab
        Raab Associates Inc.


                               1
Data Problem? What Data Problem?

                   • top 3 marketing
                     problems:
                     technology, resources, pr
                     ocess (what about
                     data?)
                   • 2/3 of prospect data is
                     less than 75% accurate
                     (vs. 1/3 of customer data)
                   • data decays at 2% per
                     month




                                             2
Why Data Problems Matter
                 • your new marketing
                   automation system
                   will fail (the boss
                   won’t be happy)
                 • your email won’t get
                   delivered (or, even
                   worse, it will)
                 • opportunity costs
                   (wasted acquisitions,
                   lost revenue)
                 • salespeople won’t
                   follow up (55%
                   blame missing data;
                   next-highest reason
                   is 14%)
                                      3
Root Causes
• poor data capture    • less sales involvement
• user-provided data   • recycled operational
                         data




                                                  4
Solving the Problem: 5 Step Program

1.   Set a Baseline
2.   Organize for Action
3.   Make Improvements
4.   Measure Results
5.   Repeat as Needed



                                           5
1. Set a Baseline
              • research existing data
                • select key elements
                  (one word: email)
                • test for dupes and
                  errors
                • consider the source
                • document update
                  processes
              • identify opportunities
                for improvement
              • define value and
                prioritize


                                        6
2. Organize for Action
• governance
  • cross-department
    team
  • executive sponsor
  • departmental data
    stewards
• select projects
  • set goals
  • define metrics
  • track and report




                                         7
3. Make Improvements
              initial projects: simple,
              low cost, measurable
              • input: data capture, user
                registration, progressive
                profiling
              • import: processing rules,
                source priority
              • external data: validation,
                enhancement, refresh
              • process: sales and
                marketing coordination,
                training, feedback




                                          8
4. Measure Results
• measure types                         • always compare to something
 • effort (costs, processing volumes)     • goal, history, industry benchmark
 • results (changes, error
   rates, usage, attitudes)
                                        • make results accessible
 • business value (lower costs, more
   leads, higher revenues)                • dashboard, variance reports




                                                                            9
5. Repeat as Needed

              • (it’s always needed)
              • identify new
                opportunities
              • avoid back-sliding
                (maintain previous
                improvements)
              • on-going baseline
                measurements




                                       10
Tools Can Help
• data cleansing
  • name/address
    standardization, matchi
    ng, reference data
• real time validation
• periodic refresh
• no silver bullet




                                       11
Conclusion


       • quality pays
       • integrated
         systems magnify
         the value
       • quality programs
         set the stage for
         additional
         cooperation


                             12
Thank You.
David Raab
Raab Associates Inc.
draab@raabassociates.com
www.raabassociatesinc.om
Twitter: @draab



                           13

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Raab Reachforce AMA Data Quality

  • 1. Marketing Lead Data: Five Steps to Higher Revenue July 20, 2011 David M. Raab Raab Associates Inc. 1
  • 2. Data Problem? What Data Problem? • top 3 marketing problems: technology, resources, pr ocess (what about data?) • 2/3 of prospect data is less than 75% accurate (vs. 1/3 of customer data) • data decays at 2% per month 2
  • 3. Why Data Problems Matter • your new marketing automation system will fail (the boss won’t be happy) • your email won’t get delivered (or, even worse, it will) • opportunity costs (wasted acquisitions, lost revenue) • salespeople won’t follow up (55% blame missing data; next-highest reason is 14%) 3
  • 4. Root Causes • poor data capture • less sales involvement • user-provided data • recycled operational data 4
  • 5. Solving the Problem: 5 Step Program 1. Set a Baseline 2. Organize for Action 3. Make Improvements 4. Measure Results 5. Repeat as Needed 5
  • 6. 1. Set a Baseline • research existing data • select key elements (one word: email) • test for dupes and errors • consider the source • document update processes • identify opportunities for improvement • define value and prioritize 6
  • 7. 2. Organize for Action • governance • cross-department team • executive sponsor • departmental data stewards • select projects • set goals • define metrics • track and report 7
  • 8. 3. Make Improvements initial projects: simple, low cost, measurable • input: data capture, user registration, progressive profiling • import: processing rules, source priority • external data: validation, enhancement, refresh • process: sales and marketing coordination, training, feedback 8
  • 9. 4. Measure Results • measure types • always compare to something • effort (costs, processing volumes) • goal, history, industry benchmark • results (changes, error rates, usage, attitudes) • make results accessible • business value (lower costs, more leads, higher revenues) • dashboard, variance reports 9
  • 10. 5. Repeat as Needed • (it’s always needed) • identify new opportunities • avoid back-sliding (maintain previous improvements) • on-going baseline measurements 10
  • 11. Tools Can Help • data cleansing • name/address standardization, matchi ng, reference data • real time validation • periodic refresh • no silver bullet 11
  • 12. Conclusion • quality pays • integrated systems magnify the value • quality programs set the stage for additional cooperation 12
  • 13. Thank You. David Raab Raab Associates Inc. draab@raabassociates.com www.raabassociatesinc.om Twitter: @draab 13