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Data Data Everywhere! Matthew Evans, Tribune Media Services Erica Stowe, R. L. Polk Deborah Sanford, salesforce.com Kevin Smith, salesforce.com Admin I: Getting Started
Safe Harbor Statement ,[object Object],[object Object],[object Object]
Data Data Everywhere ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Erica Stowe CRM Process Manager [email_address]
We gather automotive data, compile it, analyze it and provide intelligence to the automotive market. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why is data quality important? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Why is Data Quality Important? ,[object Object],[object Object],4,000 Fulfillment Packages $80,000 500 Bad Addresses $10,000 1,000 Duplicates Time spent 500 Pricing Errors Due to Account Hierarchy Issues  $ 10,000 Minimum Cost of Poor Data $20,000
Data Quality – Key Challenges ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Quality – The Solution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Quality – Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
R. L. Polk’s  Data Strategy Today ,[object Object],[object Object],[object Object],[object Object]
Data Data Everywhere ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How to Assess a CRM Implementation’s Data Quality ,[object Object],[object Object],[object Object],[object Object],[object Object]
Data Quality Reports and Dashboards ,[object Object],[object Object],[object Object]
Scoring the Data Quality of Each Record ,[object Object],[object Object],[object Object],[object Object],[object Object]
Demo Data Quality Scoring and Dashboards
Data Data Everywhere ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Matthew Evans CRM Project Manager [email_address]   The AdminExchange www.adminexchange.wordpress.com
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Tribune Media Services, a subsidiary of Tribune Company, is a leading provider of information and entertainment products for print, electronic and on-air media.
Standardizing & Cleansing Data Names Company  Name & Address Identify,  Match & Score Load to  Sandbox Find &  Replace 2 4 5 Standardize Cleanse Enrich  (Optional) De-dupe Validate US, U.S, U.S.A -> USA  Acme-Widgets-453 Acme Inc HQ Acme UK J. Smith, John Smith – 80% Hot    High Cold    Low Data Transformation Hierarchy Data Demographics Re-parent  Child Records acme incorp.-> Acme Inc Account:  Division, Opportunity, Contact Naming Conventions Addresses Merge Mergers, acquisitions,  spin-offs 3 Postal  Standards J. Smith, John Smith ->  John Smith Archiving & Filtering Validate  &   Modify Load to  Production 1
Tribune Problem – Bad Data! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Pre-Define Data Management ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tribune Game Plan ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tribune Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Data Everywhere ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Protect Data quality decays rapidly  & enterprises should follow a methodology that includes regular measurement of data  quality with goals for improvement & deployment of process improvements & technology ” “ Safeguard your cleansed data and prevent future deterioration Train ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Enforce Monitor
Data Data Everywhere ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How to get Started ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Session Feedback Let us know how we’re doing! ,[object Object],[object Object],[object Object],[object Object],[object Object],We strive to improve, t hank you for filling out our survey. ,[object Object],[object Object]
Question and Answers

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A G S004 Smith 091707

  • 1. Data Data Everywhere! Matthew Evans, Tribune Media Services Erica Stowe, R. L. Polk Deborah Sanford, salesforce.com Kevin Smith, salesforce.com Admin I: Getting Started
  • 2.
  • 3.
  • 4. Erica Stowe CRM Process Manager [email_address]
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16. Demo Data Quality Scoring and Dashboards
  • 17.
  • 18. Matthew Evans CRM Project Manager [email_address] The AdminExchange www.adminexchange.wordpress.com
  • 19.
  • 20. Standardizing & Cleansing Data Names Company Name & Address Identify, Match & Score Load to Sandbox Find & Replace 2 4 5 Standardize Cleanse Enrich (Optional) De-dupe Validate US, U.S, U.S.A -> USA Acme-Widgets-453 Acme Inc HQ Acme UK J. Smith, John Smith – 80% Hot  High Cold  Low Data Transformation Hierarchy Data Demographics Re-parent Child Records acme incorp.-> Acme Inc Account: Division, Opportunity, Contact Naming Conventions Addresses Merge Mergers, acquisitions, spin-offs 3 Postal Standards J. Smith, John Smith -> John Smith Archiving & Filtering Validate & Modify Load to Production 1
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.