Spring Cleaning: Easy Ways to Tidy your Customer Data
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Spring Cleaning: Easy Ways to Tidy your Customer Data

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October Ivins (speaker), Christine Orr (speaker)

October Ivins (speaker), Christine Orr (speaker)

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Spring Cleaning: Easy Ways to Tidy your Customer Data Spring Cleaning: Easy Ways to Tidy your Customer Data Presentation Transcript

  • October Ivins, MLS october.ivins@mindspring.com Charleston Conference November 8, 2013
  •      Introduction - Christine Why is Data Important? - October The Causes of Bad Data – October Getting Ready to Clean - Christine How to Clean - Christine ◦ Easy tips ◦ More long term solutions  Questions and Discussion - You 1
  • Just because it’s a cliché doesn’t mean it isn’t true…  Garbage in, garbage out.  If you can’t measure it, you can’t manage it. o How can you tell whether a change made a difference, either positive or negative? o Are you collecting all of the revenue you are owed? o You can’t support good customer service, marketing or sales with bad data. o Messy data wastes time. 2
  • Multiple names for the same institution: o CSU Sacramento vs. Cal State Sacramento o UMass vs. Univ. of Mass Amherst vs. Univ o Berkeley vs. UC Berkeley vs. Univ of CA Berkeley Same institution, different locations Queens College (New York USA, Newfoundland, Canada; Cambridge and Oxford, UK; Melbourne, Australia and more)  Punctuation matters in alphabetical sorts  Transposed letters Even harder- STM, research institutes at campus, departments 3
  • State, Country confusion o Ala, (AL Alabama, AK Alaska) o Canadian addresses with no country entered o Countries change names Partial names- “Trinity” College, University, Community College, etc.? Phone numbers with no area code Inappropriate use of notes field 4
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  • An association moved to package pricing for all of its titles….  Contracted for a project for subcontractors to call and offer trial subscriptions….  De-duping institutional and individual….  Domestic decline masked by international increase….  Determine Carnegie Classifications for market analysis or tiered pricing… http://classifications.carnegiefoundation.org /  6
  •     Offer from a consortium. Which members are already customers and how much are they paying? Setting prices for the next year. How many cancellations were there after the last one? Any evidence they were related to the increase? Your press has an opportunity to acquire a journal. How do you assess your ability to increase subscriptions? What should you offer? A librarian insists electronic access has been canceled in error. Can you tell from your data or do you just take his word for it and reinstate? 7
  •  Incomplete  Inaccurate  ◦ ◦ May lack key fields, too few for addresses ◦ No unique customer number ◦ Free text without review ◦ Drop down menus better ◦ Standard source for institutional names? Multiple Entry Points/No Style sheet ◦ Many departments/offices/staff enter without coordination ◦ Poor data integration from multiple vendors Poor Documentation/Training ◦ Style sheet? ◦ Instructions that limit creating new customer records? ◦ Checklist, review of new employees’ work? 8
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  • October Ivins, MLS october.ivins@mindspring.com