Data, Data, Data: Start Your Spring Cleaning Now

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Data, Data, Data Start Your Spring Cleaning Now!
Track Marketing Executives

• Katrina Perano, SunGard
• Paul Young, CommVault
• Daryl Spreiter, salesforce.com

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Other Data Quality Sessions

• Check back on www.salesforce.com/community for
  these recorded presentations
• Admin Track - No More Bad Data
• Admin Track Clean Your Database and Keep It
  Clean with CRMFusion
• Admin Track The Power of the Force Platform in
  Action Real Solutions to Business Challenges
• Sales Executives Turning Around Your Data
  Quality Dilemma

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Agenda

• Introduction to the Importance of Data Quality
• Paul Young CommVault
• Katrina Perano - SunGard
• Lessons in Data Quality
• Tools Take-Aways
• Question Answer

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Why is Data Quality important?

• Marketing wastes money and effort when working
  with bad data
• Company image and brand can be negatively
  impacted
• Understanding your customer becomes impossible
• Inaccurate report metrics impact ROI
• User get frustrated, you lose valuable buy-in and
  adoption
• Poor data can be bad for the environment
• Analysts rate bad data as one of the top 3
  reasons for CRM failure

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Please Welcome.

• Paul Young
• Global Manager of CRM

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Data Quality

• Boring, but so is wearing a 
• seat belt

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CommVault and salesforce.com

• 450 licensed users on 6 continents
• 200 other people deriving data from Salesforce
  CRM
• 800 custom fields
• 30 record types
• Dozens of validation rules
• 50 Workflows and alerts
• Many custom objects
• Formulas, S-Controls, Triggers, Force.com
  platform
• More than 10 major app exchange packages in use

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Four things to take away

• 1.  Data quality is important
• 2.  Prevention is preferable to cure
• 3.  Don't ignore chest pains

Where's number four??
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What your users expect of the data

• Clean -no dupes, no duds, no incompletes
• Comprehensive-customers, contacts, leads,
  prospects, products, opportunities it all needs
  to be there
• Coherent-that mean reportable and repeatable

I'm from the auditors and I'm here to help.
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Which is easier?
Clean up pollution
Keep it pure
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How do we keep data clean?
Defense in DepthThe Rings of Steel
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Ring 1Good Policy

• What constitutes good data?
• Who has authority to override that definition?
• In trade offs, what are the priorities? (More
  leads? Fewer dupes? Mining the install base?)
• Who can make changes to the data?
• WRITE IT DOWN AND GET SIGNOFF!

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Ring 2Training

• Uneducated end users are the single biggest
  source of contamination
• Make them understand the connection between the
  data and their paycheck
• Give them simple, concrete, steps to follow

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Ring 3Trend Monitoring

• Lead influx trends looking for abnormal upsurges
  in imports and unusual patterns of usage.
• Record completeness survey looking for missing or
  incomplete fields.
• Formal and informal user feedback.

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Ring 4Cleanup-the Maginot Line
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If you have to do constant, significant cleanup,
you have failed.
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OK, OK, I've failed. What now?

• No magic bullet
• Automated programs will work 0-70
• Human eyeballs can get you to 95-95
• Make backups before cleaning
• Don't give up

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Write this down

• Data quality is critical to business success
• Prevention is better than cure
• Defense in depth
• Good Policy
• Training
• Trend Monitoring
• Cleanup
• Don't give up!

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Thanks from your friends atCommVault!www.commv
ault.com
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Please Welcome.
Katrina Perano Marketing Operations
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Agenda

• Who is SunGard?
• Data quality strategy Why is it important
• Key data challengers
• How we over came this
• Conclusions

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All About SunGard
With annual revenue of 5 billion, SunGard is a
global leader in software and processing
solutions for financial services, higher
education and the public sector. SunGard also
helps information-dependent enterprises of all
types to ensure the continuity of their business.
SunGard serves more than 25,000 customers in more
than 50 countries, including the world's 50
largest financial services companies.

• INDUSTRY Software IT Services
• EMPLOYEES 16,000
• GEOGRAPHY Global
• USERS 1500
• PRODUCT(S) USED SFA, Service Support, 5
  downloaded AppExchange applications

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Data quality strategy Why is it important

• SunGard is a global company made up of
  acquisitions
• Our primary SFDC goals are
• Present one face to our customer
• Have a centralized system for sales, marketing
  and customer support for global processes and
  reporting
• For visibility and reporting it is key for all of
  SunGard to be on one open SFDC instance
• We share accounts and contacts across all
  segments so it is key to avoid duplication and
  ensure data quality
• Leads represent potential opportunities (above
  the funnel information) so we have genuine
  duplicate leads across our segments but we are
  aware they represent future (and existing)
  accounts and contacts as well

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Lead to Opportunity Pipeline
7 - MARKETING QUALIFIED
6 - OPPORTUNITY QUALIFIED
8 - OPEN
5 - NEEDS ANALYSIS
4 - SOLUTION PROPOSAL
3 - VENDOR FINALIST
2 - VERBAL ACCEPTANCE
1 - IN LEGAL
0 - CLOSED
9 - LEAD POOL
Opportunity
Lead
Account
Assets
Cases
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Key data challenges

• Huge amounts of shared data (many hands in the
  cookie jar)
• Avoiding duplicate accounts and contacts
• Managing genuine duplicate leads while still
  having visibility into the individual across
  multiple records
• Data ownership for shared data

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How we over came this

• Company data standardizations
• Centralized account creation
• Centralized lead conversion
• Defined and monitored process for lead imports
• Monthly adoption metrics distributed to all
  Presidents with corresponding adoption dashboards
  monitored by Super Users
• SPOT Single Point of Truth custom object
• Custom buttons for data clean up
• SunGard Roles custom object for multiple contact
  owners

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SPOT Single Point of Truth custom object

• SPOT single point of truth custom object that
  links all leads/contact with the same email
  address and stores subscription preferences
  including Email Opt-Out
• Global view of a person across contact and
  multiple leads
• What marketing activities have they been targeted
  across all segments
• What leads are being pursued within a segment and
  across all segments
• For lead owners easy visibility into contact
  ownership
• Captures segment-specific subscription
  preferences versus only a global opt-out for more
  targeted marketing
• 3 Leads 1 Contact

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SPOT cont
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Data quality custom buttons

• Ability to flag contacts as duplicates for
  merging
• Creates a case for our centralized administration
  team
• Centralized administration team then searches and
  merges the duplicates
• Ability to mark contacts as Former Contacts
• For account-level history we maintain former
  contact association
• Appends (FORMER CONTACT) to the contact name so
  it is recognized immediately by users
• Updates a Contact Management custom field for
  excluding them from lists

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SunGard Roles custom object

• SunGard Roles are used to identify multiple
  owners of a shared contact.

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Conclusion

• Its important to have processes to deal with data
  quality
• Processes around imports
• Management of huge amounts of data
• Cost effective ways
• Import templates
• User awareness
• SPOT
• Custom Buttons

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Please Welcome.me!

• Daryl Spreiter
• Customer Success Manager

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Domains of SuccessKey elements for achieving
continuous value
Vision and Strategy
Business Measures
Adoption
Sponsorship Governance
Processes
Roadmap
Technology Data
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Data Quality Industry TrendsMaintaining data
quality is a challenge

75 of commercial businesses believe that they
are losing as much as 73 of revenue due to poor
data quality
75 of respondents

Experian - QAS U.S. Business Losing Revenue
Through Poorly Managed Customer Data

41 of respondents

• Poor data quality costs U.S. businesses more than
  600 billion annually

Data Warehousing Institute
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Executives are Achieving These Business
Objectives with Salesforce.com
Revenue Enhancement Customer Loyalty
Satisfaction
Source Salesforce.com Customer Relationship
Survey July 07 and Feb. 08 conducted by
independent third-party CustomerSat Inc.
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Math Quiz
1 Million Records 5 bad data (50K) Quarterly
Communication 50K x 4qr 200K Avg cost
1.05 _______________ 210,000 ? 420K Saved
1 Million Records 15 bad data (150K) Quarterly
communication 150K x 4qr 600K pieces Avg cost
1.05 ________________ 630,000 wasted

• There is a cost to bad data!

Bob Orf. "Improving data quality without breaking
the bank." BtoB May 27, 2008
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4 Lessons in Data Quality
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Lesson 1 No Old Data No Bad Data

• Always Start with Current Clean Data
• Do not import incomplete data scrub it first
• Question old, untouched leads, contacts
  accounts
• Excel Connector (all editions) Data Loader (EE,
  UE)

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Lesson 2 Apply Best Practices

• Create a Data Management Strategy
• Establish a De-Duping Process
• Ensure there are executives willing to own data
  quality (CMO/CFO?)
• Centralize and control the creation of Accounts
  by Sales Ops/Data Quality team
• Develop and articulate data segmentation needs to
  support departmental marketing efforts
• Ensure that users are incented to keep it clean
• Ensure you have the tools to make sure quality
  does not degrade again
• Hold your teams accountable
• Data elements must be updated in x amount of time
• Apply the Whats in it for me? strategy

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Lesson 3 Leverage Salesforce.com Tools

• Leverage the tools you already have
• Data Quality Analysis Dashboards 1.0
• Record De-Dup
• Mass Update Anything
• Stay-in-Touch emails
• Validation Rules
• Workflow Rules
• SPOT
• Excel Connector
• Data Loader

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Lesson 4 Leverage the AppExchange

• Leverage the expertise of third-party apps
• Account Intelligence 2.0 by OneSource
• DB Customer Data Integrator by Astadia
• PostCode Anywhere
• CRMFusion DemandTools, PeopleImport,
  Dupe-Checker
• RingLead Declone
• ActivePrime CRM
• Informatica Data Quality Assessment Service
  (promo )

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What Did We Learn Today?

• Start with Clean Data
• Establish a Data Quality Strategy and Stick With
  It
• Identify Data Owners
• Make use of the tools and capabilities inside
  Salesforce CRM
• Leverage 3rd party groups to minimize the amount
  of data entry your team has to do and optimize
  your system to support good data
• Recognize the cost of bad data and make a
  commitment to keeping it clean

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Additional Resources

• Best Practices
• Reach out to your Customer Success Managers
• Review Data Quality Best Practices Presentation
  on Salesforce.com Community
• Excel Connector
• Data Loader (Setup/Administration/Data
  Management)
• Salesforce Professional Services
• Data Management
• Data Quality Assessment and Cleansing Solutions

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In Closing
Where do you want your Data Quality to be in 2009?
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QUESTION ANSWER SESSION
Katrina Perano
Marketing Operations
Paul Young
Global Manager of CRM
Daryl Spreiter
Customer Success Manager