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
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Data Data Everywhere
Why is Data Quality important?
How to assess CRM Data Quality
Standardizing and Cleansing Data
Improving and Protecting Data
How to Get Started
Q&A
We gather automotive data, compile it, analyze it and provide intelligence to the automotive market.
• INDUSTRY: Automotive
• EMPLOYEES: 1,300
• GEOGRAPHY: Global
• # USERS: 415
• Login 85%
• PRODUCT(S) USED: Salesforce SFA & Service & Support, 16 Custom
Objects, 4 Custom Apps, 4 S-Controls, 2 AppExchange Applications
Why is data quality important?
Poor Data Quality Turns Into:
Inaccurate Reporting
Time Wasted
Lost Money Pursuing Bad Information
Kills Users Adoption
Why is Data Quality Important?
R. L. Polk did not have a data quality strategy and decided to run one direct mail campaign using the data in their CRM tool. Here was the impact to R. L. Polk’s bottom line…
The total cost of poor data quality to any marketing program cannot be fully quantified but can easily run 25% or more!
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
People Challenges• All users had the ability to add data to every object• No standards or guidelines on how data was to be entered
Process Challenges No required fields No field dependencies No validation rules No address validation No account hierarchy verification
Technology Challenges• No integration between systems or processes
Data Quality – The Solution
How did we address these challenges?• Required Fields
• Field Dependencies
• Validation Rules
• Visibility into the data
R. L. Polk has over a million records in Salesforce. Here are some highlights:
200,000 - Opportunities 100,000 - Contacts
85,000 - Cases 60,000 - Accounts 25,000 - Leads 3,500 - CARS 1,000 - Forecasts
• External Data Validation
• CRMfusion Data Therapist
• Processes & Guidelines
• Training
Data Quality – Results
What were the results?
Cost of poor data dropped from 25% to 3% for most campaigns
Improved forecast turnaround time from 1 week to real-time
Increased sales pipeline visibility from 60% to 95%
Increased management visibility into competitive losses
• Gathering data earlier within our process reduced the need to
re-key data down stream
• Year over year customer satisfaction increase
• CAR Process
R. L. Polk’s Data Strategy Today
Our Forecast is distributed every Monday
Reports, Dashboards, Escalation Rules
De-Duplication Tools; Demand Tools by CRM
Fusion
Data is shared with every level of management
within our company
Data Data Everywhere
Why is Data Quality important?
How to assess CRM Data Quality
Standardizing and Cleansing Data
Improving and Protecting Data
How to Get Started
Q&A
How to Assess a CRM Implementation’s Data Quality
Reports and Dashboards
De-Duplication Tools
Survey Your Users
Profile the Data
Analyze the Results
Data Quality Reports and Dashboards
Understand the Important Fields of Every Entity
Create Exceptions Reports for Each Entity
Create Data Quality Dashboards by Role
Scoring the Data Quality of Each Record
Leverage custom formula fields to score each record for data completeness. Sample Formula:
“IF( ISPICKVAL(Industry,""), 0,20) + IF( ISPICKVAL(Rating,""), 0,20) + IF( LEN(BillingCity) = 0, 0,20) + IF(LEN(Phone) = 0, 0,20) +
IF( ISPICKVAL(Type,""), 0,20)”
Use the Data Quality Dashboard on the AppExchange as a starting point:
Data Quality Analysis Dashboards 1.0
Demo Data Quality Scoring and Dashboards
Data Data Everywhere
Why is Data Quality important?
How to assess CRM Data Quality
Standardizing and Cleansing Data
Improving and Protecting Data
How to Get Started
Q&A
Matthew Evans
CRM Project Manager
The AdminExchange
www.adminexchange.wordpress.com
• INDUSTRY: Media
• EMPLOYEES: 610
• GEOGRAPHY: Global
• # USERS: 40 Currently, 200+ by 2007 year end
• Login 82%
• PRODUCT(S) USED: Salesforce SFA & Service & Support, 7 Custom
Objects, 2 downloaded AppExchange applications
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
1 2 4 5
StandardizeStandardize CleanseCleanse Enrich (Optional)Enrich (Optional) De-dupeDe-dupe ValidateValidate
US, U.S, U.S.A -> USA Acme-Widgets-453
Acme Inc HQAcme UK
J. Smith, John Smith – 80%
Hot HighCold 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
Tribune Problem – Bad Data!
Too many records
23,000 Accounts for client base of 3,000
Duplicates
Unused fields
Asking for redundant data
Fields never used
Bad naming of records
Multiple opportunities and accounts with the same name
No standardization of field inputs
Billing State: CA, Calif., California, Cal.
Pre-Define Data Management
Standardize and Cleanse Correct inaccuracies and inconsistencies in data
Make sure data ownership and sharing is accurate
Define your CRUD rights on each profile
Augment Add missing information from 3rd party DB’s
Understand what data would provide additional value
Add behavioral specific data
Integrate Understand your masters
Avoid stale information, misinformation from spreading
Create a true “360” view of your customer
Make some information read only
Tribune Game Plan Cleanse
Delete old/unused Accounts
Use Demand Tools to clean duplicates
Survey Users to remove bad fields
Standardize and Enforce Create naming standards for Accounts and Opportunities
Enforce naming standards and field inputs with validation rules and workflow rules
Train Users on new standardizations
Monitor Use the Adoptions Dashboards from AppExchange to track
data quality
Tribune Results Reduced number of workable
accounts to 8,000 3,000 Clients; 5,000 Prospects
Eliminated duplicates 2,500 duplicate accounts 1,500 duplicate contacts
Removed 15 unused fields from 4 standard objects Trained users on cleaner Salesforce and introduced
naming standards Created 16 validation rules and 6 field update workflows to
standardize field inputs Customized data quality reports and dashboards to meet
our needs
Data Data Everywhere
Why is Data Quality important?
How to assess CRM Data Quality
Standardizing and Cleansing Data
Improving and Protecting Data
How to Get Started
Q&A
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
TrainTrain
•User Training•Naming Conventions•Address Conventions•Dupe. Prevention Process•Data Importing Policies
•Required Fields•Default Values•Data Validation Rules•Workflow Field Updates•Web-to-Lead Restrictions
•Data Quality Dashboards•Data Quality Reassessment•AppExchange Tools
EnforceEnforce MonitorMonitor
Data Data Everywhere
Why is Data Quality important?
How to assess CRM Data Quality
Standardizing and Cleansing Data
Improving and Protecting Data
How to Get Started
Q&A
How to get Started
How to apply what you’ve learned when you get home
• Get Data Quality Dashboards from AppExchange
• (and/or User Adoption Dashboards)
• Survey your users
• Review available Data Quality tools and offerings
• Create Data Quality project plan
• Review this presentation
• Utilize Salesforce Data Quality Assessment and Cleansing
Solutions
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