5 Data Quality Issues

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5 Data Quality Issues and How to Fix Them - Eloqua, Social123, & Blue Coat

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  • SiriusDecisions, a sales and marketing research firm,quantifies data quality using the 1-10-100 rule, which says "It takes $1 to verify a record as it'sentered, $10 to cleanse and de-dupe it and $100 if nothing is done, as the ramifications of themistakes are felt over and over again."
  • Forward thinking companies are looking to understand their customers and prospects better, not only from an employment perspective but their interests as wellSocial Lead Generation: Search groups, skills, titles, geographies, and competition to build targeted lead lists.  Powerful and enriched results are delivered via CSV equipped with Title, Employer, Social URL, and Email Address. Real-Time Email Validation: Validate email addresses in real-time for the most accurate deliverability and notify of any catch-alls or high risk email addresses in your list.
  • Forward thinking companies are looking to understand their customers and prospects better, not only from an employment perspective but their interests as well.
  • Forward thinking companies are looking to understand their customers and prospects better, not only from an employment perspective but their interests as well.
  • Reference the email validate
  • 5 Data Quality Issues

    1. 1. 1 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    2. 2. 5 Data Quality Issues and How To Fix Them Oracle | Eloqua Power Hour
    3. 3. Presenters Ian Ingar Brown  Marketing Advisor, Oracle | Eloqua  Former Eloqua Customer  Eloqua User Since 2005  Markie Award Winner  Most Recent, Sr. Director of Marketing  Based in the San Francisco Bay Area 3 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    4. 4. Presenters Joe McKenna  Sr. Director, Social123  10+ years in Sales and Marketing  Oracle | Eloqua AppCloud Partner  Based in Atlanta, GA 4 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    5. 5. Presenters Manu Kaushik  Dir. Marketing Ops, Blue Coat Systems  Oracle | Eloqua Customer  Markie Award Winner 2013!! – Data Clean House  Based in the San Francisco Bay Area 5 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    6. 6. Power Hour Agenda – What You Will Learn  Why Data Quality Matters  Reasons Why Bad Data Causes Issues  Practical Ways to Manage Your Data (It doesn’t take much.)  How You Can Use 3rd Party Tools to Manage Your Data  How a Markie Award Winner Manages Data Quality 6 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    7. 7. Why Data Quality Matters 7 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    8. 8. This is Our World. Data coming and going from multiple directions. 8 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    9. 9. Why Data Quality Matters  Segmentation and Targeting  Right Message. Right Time.  Campaign Measurement  Marketing Attribution to Revenue 9 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    10. 10. Why Data Quality Matters Cost of Unusable Data? Billion/Year - The Data Warehousing Institute Survey from 2002! Number possibly higher today + Mobile Devices + Anytime, Anywhere Consumer 10 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    11. 11. Top 5 Data Quality Issues  Incomplete Data  Incorrect / Wrong Data  Aging Data  Duplicate Data  Data Reconciliation Between Sources 11 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    12. 12. Top 5 Data Quality Issues – Incorrect Data  What Causes Incorrect Data? – Web forms are too long! – Unnecessarily gated content – Manual / erroneous data entry  Resulting Issues – Poor segmentation and metrics for marketing campaigns – Misinformed actions by marketing and sales – Unhappy prospects & customers  Resolution – – Test your forms (A and B landing pages in Eloqua) – Pre-filled and drop down fields using Eloqua – 12 Gate only high value content - eBooks, live event registrations, webinars (Eloqua tracking of downloads & video views) Normalize your data using a “Contact Washing Machine” Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    13. 13. Top 5 Data Quality Issues – Incorrect Data The Contact Washing Machine  What is a Contact Washing Machine? – The normalization of data using Eloqua automation (ex. Change “Chief Operating Officer” to “COO”) – Combination of Eloqua programs and update rules  Results – Forrester Research, Inc. (EE 2013 Speaker)  64% to 84%  30% unqualified  96 hours  Resources – – 13 Topliners Article: Data Cleansing Best Practices/How To Setup a “Contact Washing Machine” http://topliners.eloqua.com/docs/DOC-2402 EE „13 Presentation: Forrester Research – “The power of a data washing machine in lead creation” http://topliners.eloqua.com/docs/DOC-4624 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    14. 14. Top 5 Data Quality Issues - Incomplete Data  What Causes Incomplete Data? – Manual entry (Forms, CRM, Eloqua) – Data Imports (Events/Tradeshows, CRM to Eloqua)  Resulting Issues – Poor segmentation for marketing campaigns  Resolution – Add required fields to forms (Note: Request the right data based on targeted personas!) – Use Drop Downs on your forms (Job Role, Country, Industry, etc.) – Capture or append data through 3rd party applications 14 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    15. 15. Presenters Joe McKenna  Sr. Director, Social123  10+ years in Sales and Marketing  Oracle | Eloqua AppCloud Partner  Based in Atlanta, GA 15 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    16. 16. What makes Social123 unique? 1. 300 Million professionals from 2 Million public sources 2. We provide a link to the source for reliability 3. We validate every email address at the point of purchase 16 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    17. 17. Social123 by the Numbers  300 Million Professionals  2 Million Sources  2000 Customers  43 Countries  25 Fields of Data  2 Week Data Refresh 17 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    18. 18. Quantifying the Impact of Data Quality The 1-10-100 rule "It takes $1 to verify a record as it's entered, $10 to cleanse and de-dupe it and $100 if nothing is done, as the ramifications of the mistakes are felt over and over again.“ - SiriusDecisions 18 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    19. 19. Quantifying the Impact of Data Quality On the revenue side of the equation… “…a data quality strategy and targeted data quality improvement efforts that solve conflicts at the source can lead to a 25% increase in converting inquiries to marketing-qualified leads.” "Data Quality Practices Boost Revenue by 66 Percent." - destinationCRM.com 19 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    20. 20. Social123 + Eloqua = Sales Success  Eloqua AppCloud for over two years – Social Data tool – a powerful data appending utility that provides the most accurate and detailed information about contacts inside of Eloqua. – Most recently we rolled out two additional services, email validation and social lead generation. 20 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    21. 21. Social123 + Eloqua = Sales Success  Social Data – Largest, most accurate and detailed information available – Append social data to your existing contact records with over 25 additional fields of data -- all provided from the contacts themselves  The Social123 Impact: – More personal and targeted outbound campaigns – Increased ability to reach more potential buyers – Improved email deliverability rates 21 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    22. 22. Social123 + Eloqua = Sales Success 22 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    23. 23. The Impact of Aging Data on Productivity “… according to MarketingProfs ,B2B data expires at a 25% rate per year. That trend manifests itself in decreased open rates, calls to action and eventually less revenue.”  The Impact: – Reduced customer satisfaction – Damage to reputation and brand – Decline in user adoption – Wasted time and opportunity – Most importantly…the decreasing inability to segment and target the most appropriate prospects with the right messages 23 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    24. 24. Let’s Connect! Joe McKenna  Joe.McKenna@Social123.com  404-966-6604  www.Social123.com 24 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    25. 25. Top 5 Data Quality Issues – Aging Data  What Causes Aging Data? – Poor data management  Resulting Issues – Poor segmentation and metrics for marketing campaigns  Resolution – Re-Engagement nurturing campaign – Review your buyer personas and customer experience journeys 25 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    26. 26. Top 5 Data Quality Issues – Aging Data The Re-Engagement Nurturing Campaign 26 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    27. 27. Top 5 Data Quality Issues – Duplicates  What Causes Duplicate Data? – Manual or automated entry without set rules – Multiple unique email addresses for the same person  Resulting Issues – Multiple communications sent to the same recipient – Campaign measurement – Marketing and sales alignment  Resolution – Create rules around your data  Event Data – Use a template for capturing and importing leads  CRM – Restrict access to import or manipulate data  Regular data maintenance 27 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    28. 28. Top 5 Data Quality Issues – Data Reconciliation  What Causes Data Reconciliation Issues? – Manual or automated entry with or without set rules  Technical issues  Imports through spreadsheets  Resulting Issues – Poor segmentation and metrics – Negative feedback (customers, prospects, team members, etc.) – Marketing and sales alignment  Resolution – Leverage Eloqua‟s API (Application Programming Interface)  Connect to your favorite CRM or data warehouse  CRM – Restrict access to import or manipulate data  Regular data maintenance 28 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    29. 29. Presenters Manu Kaushik  Dir. Marketing Ops, Blue Coat Systems  Oracle | Eloqua Customer  Markie Award Winner 2013!! – Data Clean House  Based in the San Francisco Bay Area 29 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    30. 30. Blue Coat Systems: Markie Award winner journey  Blue Coat Introduction – Web security and WAN optimization company – 15,000 customers (86% Fortune 500 companies) – More than 1,300 employees  2013 Eloqua Markie Award: Data Clean House – Extended focus on Data quality recognized during Eloqua experience – Amazing platform with lots of motivation and ideas – Excited to take our efforts to the next level of success and ready to help other companies by sharing our journey…. 30 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    31. 31. Data Quality Challenges  Inconsistent and Unstandardized data – Campaign segmentation issues – Difficult for creating personalized and relevant experience for users – Ineffective lead management within SFDC – Misaligned lead scoring model – Lead assignment issues  Reporting – Close loop reports weren‟t possible – Different underlying data for sales and marketing reports – Inaccuracy with ROI computation 31 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    32. 32. Data Cleansing Effort Overview  Data Fields cleanup – Thorough audit for all important fields in the database – SQL database connected with Eloqua to enhance automation abilities – Review of all data sources for critical contact/account fields  Contact Cleanup/Enrichment – Hard Bounced/Junk records – Email/Contact Review & Validation – Data Enrichment using external sources  Contact suppression business rules – Channel Partners, Competitors, Internal employees etc – Contact profile center for subscription management 32 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    33. 33. Data Cleansing Effort Overview  Data Source Cleanup – Web forms – List Imports  Data standardization/cleanup automation – Data standardization scripts created – Custom fields created to support additional data needs  System integration review – Eloqua-SFDC integration audited and optimized  Lead Scoring – Data regression for effective lead scoring model – Gained alignment (Sales-Marketing) on criterion and definitions 33 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    34. 34. Results, Lessons and Suggestions  Results – MQL volume increase by 25% – 85% contact profile completeness – 80% marketing influenced pipeline  Lessons/Suggestions – DATA is most vital for success; Needs extra attention – Align your data processes with the business needs of sales and marketing and gain alignment at every step – Unleash the power of marketing automation – Documentation and Training is critical – Effective audit reports and regular feedback is needed 34 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    35. 35. Power Hour Agenda – Takeaways  Standardize your data entry points to prevent incorrect data from entering your database (Templates, Required Fields, Drop Downs, Auto-Populate)  Use 3rd party applications to facilitate your data maintenance  Automate your data processes (Contact Washing Machines, Re-Engagement Campaigns)  Start with practical data management and then graduate into the advance  Make data maintenance a part of your marketing automation life! 35 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    36. 36. Connect Thank You Ian Ingar Brown Joe McKenna Manu Kaushik Marketing Advisor Sr. Director, Social123 Dir. Marketing Ops Twitter: @ingarbrown joe.mckenna@social123.com www.bluecoat.com 36 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    37. 37. Q&A 37 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    38. 38. 38 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
    39. 39. 39 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.

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