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Trillium Software CRMUG Webinar August 6, 2013


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Avoiding Data Quality Pain in Customer Relationship Management (CRM) applications. The Impact on User Adoption...

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Trillium Software CRMUG Webinar August 6, 2013

  1. 1. CRMUG SIG Avoiding Data Quality Pain in CRM The Impact on User Adoption Be Certain. Be Trillium Certain. August 6, 2013
  2. 2. Agenda Introductions & Expectations Trillium Software Overview Facts on CRM User Adoption Impact of Data Quality on User Adoption Steps to Avoid the Pain Associated with Poor Data Quality Questions & Answers 2
  3. 3. About Dave Pietropaolo With over 25 years experience in the Information Technology industry, Dave has held numerous customer and partner-facing positions with Trillium Software for the past 17 years. He is a member of Trillium Software’s Executive Council and currently Vice President of Global Alliances. Trillium Software A Division of Harte Hanks, Inc. 300 Concord Road, Suite 200 Billerica, MA 01821 978-671-6008 3
  4. 4. Who is Trillium Software? Trillium is a global provider and innovator of data quality solutions • A business unit of Harte-Hanks (HHS-NYSE) - $1+B revenue & 6000 employees worldwide • Over 2 decades in business with specific focus on data quality solutions market • Solution platform (technology + domain expertise) addresses business critical, enterprise data quality requirements • Our Mission - “To enable our clients to develop data quality management programs that support on-going improvements in business performance” Best in class, proven technology leader… ..with deep data quality expertise • Gartner • CRM, CDI & MDM • 2012 Magic Quadrant: Leader • Rated as leader for over 10 years • Forrester • Forrester Wave – Leader • Current Analysis: Very threatening to competition • Bloor Research (UK): • Best in Class • Single Customer view • Vertical applications • Business Intelligence
  5. 5. Trillium Software Customers Insurance and Healthcare Financial Services Retail and Energy Manufacturing Hospitality/Transportation Technology Pharma/Life Sciences
  6. 6. Trillium/Microsoft Partnership Recognized leader – Gartner Magic Quadrant & Forrester Wave Courted by Microsoft Used by Microsoft internally Managed in “Top 200 ISVs” Complimentary Technology Expertise Oracle & SAP compete Best in class solution for enterprise data quality leveraged internally by Microsoft for over a decade CRM Orion TAP Beta Participant “We are pleased to be working with Trillium Software to deliver strong value to current customers while enabling expansion into new growth markets.” – Mark Albrecht, Microsoft Dynamics Director, ISV Strategy Accurate data increase adoption rate of CRM & other Microsoft technologies Proven Enterprise Data Quality technology 30+ Years experience in data management Integration w/Dynamics CRM Online & On Premise Over 2,000 implementation around the globe Silver Application Development Partner
  7. 7. Data Quality Defined Data Quality Basics? Data can be seen as high quality if it is fit for its intended uses in operational, decision making/analytical and planning processes Factors that influence Data Quality? The number of potential definitions of “the customer” defined by user communities; departments, channels, business units, regions, etc. Business rules controlling cleansing and matching logic must be flexible and powerful Co-mingled, global data; diverse business standards, languages, character sets, addressing formats, naming conventions, business rules and expectations Integration within CRM must provide real-time interactive and high-volume batch processing Data Quality should be integrated as a natural part of the CRM user’s experience
  8. 8. Industry Research: Just the Facts Companies implement CRM systems so they can answer important questions about their customers. Many companies believe that investing in a CRM solution, in and of itself, will result in the much-sought-after 360° view of customer relationships. However 50% or more of companies with CRM programs are not satisfied with the customer views they get, citing distrust of the data among those who are supposed to use them. They are finding that investing in data integrity, reliability, and completeness is also critical—both for integrating diverse data for use in CRM systems and keeping that valuable information up-to-date. Source:
  9. 9. Industry Research: Just the Facts At least 25% of most companies’ data is probably inaccurate, according to industry analysts at Gartner. If your data was cleansed at integration, you may breathe a little easier—but not much. Even clean data can degrade. Consider: 2% of all customer data becomes stale monthly, for an annual rate of 25%. 70% of people change at least one item on their business cards each year. 7-10% of consumers and businesses relocate every year. Given the data challenges, it’s not surprising that companies report having as many as 40 - 400 disjointed records for one corporate customer. Source:
  10. 10. Customer Data Cleansing and Matching Across Multiple User Communities Sales Contact Service Contact Marketing Lead John Nicoli Jack Nicoli John Nicole Alpha Imports, Inc. Alpha Importers Co. AIC 501 6th Avenue, Suite 700 501 Avenue of the Americas 501 6th Ave. New York, NY 10071 Manhattan, NY 10071 New York, NY Direct: 212-345-5000,ext.101 Direct: 212-345-5101 Main: 212-345-5000 Mobile: 917-625-4546 Service Id# 87005 Service Contact John (Jack) Nicoli Alpha Importers, Inc. 501 Avenue of the Americas Suite 700 Manhattan, NY 10071 Direct: 212-345-5000, ext.2101 Mobile: 917-625-4546 Service Id# 87005
  11. 11. Industry Research: Just the Facts Changing data — An accurate, up-to-date, and integrated record for each customer is difficult to achieve because the facts themselves keep changing. Every transaction registers some change. In addition, about 2% of all customer data becomes stale each month. Integrated, clean data is what successful companies strive for, yet only 15% of businesses report full integration among their customer data systems. Analysts believe poor data quality is a primary reason that 40% of all CRM business initiatives fail to achieve their targeted benefits. Source:
  12. 12. Why Tackle Data Quality Along With CRM? Because Data Quality degrades due to normal, everyday CRM business processes Real-time data entry by diverse sets of users Different departments and channels have different data needs and standards Integration with other applications and systems, e.g. ERP Mergers/Acquisition require CRM integration List imports/external data Reference data feeds
  13. 13. Adoption Defined: 1. To take and follow by choice or assent: for example a course of action or a new technique 2. To take up and make one's own: adopt a new idea 3. To take on or assume: adopt as important 4. To vote to accept: agree to a resolution 5. To choose as standard or required: adopt a new line of thinking or process to pursue
  14. 14. CRMUG Whitepaper Driving User Adoption, August 2012 Top Five Common Causes of Poor User Adoption 1. Poor data accuracy and lack of a management plan 2. The application is not set up to work the way an organization does 3. Insufficient training 4. Missing executive sponsor 5. Several things can lead to confusion and frustration when learning new software Top Five Excuses 1. I don’t trust the data. 2. I don’t know how to use the software. 3. It takes too much time. 4. It doesn’t follow our business process or work the way we work. 5. Management doesn’t use it, why should I?
  15. 15. Data Quality Impacts All Areas of CRM Need to Involve all User Communities CRM objectives Increase revenue per sales rep Shorten sales cycle Increase average order size Increase close rate Increase conversion rate Increase revenue per customer Increase campaign response rate Decrease leadgeneration cost Decrease customer acquisition cost Increase marketing sourced revenue Improve targeted prospecting Accelerate lead maturation Increase customer retention Increase customer service productivity Reduce customer service costs Decrease service response times Decrease call waiting times Decrease request solution time Sales Business function Marketing Service Source: Forrester Research
  16. 16. Sales • Data collection and content management • Correspondence processing • Opportunity management • Pipeline tracking • Sales team collaboration • Task and activity management • Order processing and delivery • Proposal and sales history • ………
  17. 17. Sales Operations & Management • Pipeline Management • Opportunity inspection & strategy • Activity analysis and trending • Revenue forecasting • Reporting • Analytics • Channel Management • Partner analysis, promotion and growth • ……….
  18. 18. Marketing • Target marketing and demand creation • Data acquisition and management • Lead nurturing and development • Campaign management • Multi-channel marketing • Customer retention and growth • Reporting & analytics • Senior management dashboarding • ……….
  19. 19. Services • Customer care and lifecycle management • Contact management and correspondence • Case management and service history • Escalation • Collaboration with professional services • Closed loop w/product management and development • Reporting, trending and analytics • ……….
  20. 20. Aberdeen Group Research Study Leveraging Data Quality Best Practices and Technologies to Improve Sales Effectiveness Net result: better data created significant efficiencies and time is money, thus best-in-class had more opportunity to succeed. Data quality had direct impact on user adoption based on the realized value of being able to maximize “quality customer facing time”.
  21. 21. Aberdeen Group Research Study continued The study included strategies for integrating, standardizing and cleansing customer data For more details, download the study from our website
  22. 22. Industry Research: Recommendations 1. Recognize the value of 360°customer view 2. Define data business rules across lines of business to establish a 360°customer view 3. Implement customer data integration (CDI) tool to cleanse, de-duplicate, merge and manage customer data 4. Employ clean data to integrate sales, marketing and customer service standards 5. Increase user adoption rates through confidence in your data 6. Data Quality Management is not a one-time event, it is a journey Forrester Research: Data Management Fundamentals for CRM
  23. 23. What are enterprises doing to realize value from CRM? Source: Forrester Research
  24. 24. 10 Steps to Ensure Data Quality Adoption 1. Establish clear objectives you can measure and are aligned with organizational goals – outline your vision, e.g. single customer views 2. Recognize that data quality is not just an IT issue, business involvement and ownership required 3. Really understand the technology and how it will fit short and long term 4. Senior management sponsor along with project (and data) champions Excerpts from: Nigel Turner, Strategic Consulting Services, Trillium Software
  25. 25. 10 Steps to Ensure Data Quality Adoption 5. Remember, Slow and Steady Wins the Race; Change must occur - process, culture and behavior… and don’t forget data will change!! 6. Ensure high quality data for both operational and analytical purposes… and fit-for-purpose for each constituent group 7. Training is vital, not only how…by why are we doing this? 8. Establish a governance approach 9. Apply intentional energy to adoption 10.Track and measure ROI Excerpts from: Nigel Turner, Strategic Consulting Services, Trillium Software
  26. 26. CRM Adoption = Strategic and Operation Usage CRM must be core to business process Every day/hour/minute usage Must provide significant, recognized value to the user’s every-day role, activities and responsibilities Must be embraced by the user community based on value, usability and purpose
  27. 27. Data Quality Value to CRM Data Quality Helping Deliver Business Value to CRM Programs will Foster User Adoption: • Deliver a complete understanding of total customer value and total household value across accounts, products, and divisions • Reduce risks and errors in data consolidation and data migration for a CRM package through data discovery and integrated cleansing • Resolve customer data anomalies before they enter operational systems and impact relationship management decisions • Form the basis for accurate analytics, reporting, forecasting, profiling, scoring, segmenting, and targeting • Enforce your definition of customer, prospect, household, contact, etc. and how that information is to be recorded and reflected within your organization
  28. 28. Factors that Influence Successful Data Quality Management Business Rules and Processes – robust, best practice business rules delivered with the software to leverage for rapid results Tunable rules with traceable results – adapt to specific business requirements & defend why results were produced Deep data quality subject matter knowledge – provide thought leadership, independence and over 30 years of experience Context-sensitive processing – superior approach for cleansing and matching data regardless of data domain High performance for real-time and high volumes deployments – designed from inception for complex, operational deployments Global reach – wide & deep worldwide coverage Architecture - Enterprise scalability & availability – single, fault-tolerant platform to support all business processes, applications and platforms
  29. 29. Data Quality Management When & Where Data Quality Processes Applied to: CUSTOMER DATA 1. New CRM Implementations • Data Migration and Conversions • Initial Cleanse CUSTOMER DATA CUSTOMER DATA 2. Existing CRM Implementations with Data Challenges • Data Assessments & Analysis • Initial Cleanse • Integrated within the CRM application 3. Integrated within the CRM Application • DQ processes embedded as filters within batch and real-time CRM processes Cleanse & Cleanse & Migrate Migrate Dynamics CRM
  30. 30. Ideal Resource & Activities Mix for CRM Initiatives User Adoption has its own program track with major focus and effort to drive value, usage and adoption Adoption is derived from strategy definition, objective setting and defining of new processes
  31. 31. Data Quality Management and CRM In Summary: • CRM is highly data centric and requires data quality management to fully realize program potential • Clear objectives must be established in order to set expectations, manage change and measure success • Collectively CRM & data quality must be leveraged at all levels • Natural Progression = Data Accuracy and understanding Trust & Confidence Derived Business Value User Adoption!!
  32. 32. Recommended Reading CRMUG Whitepaper, Driving User Adoption Gartner, The Eight Building Blocks of CRM: Data and Information Aberdeen Research, Leveraging CRM in the Pursuit of the Elusive “Single View of the Customer” Forrester Research; Best Practices: Getting The Most From Your CRM Deployment
  33. 33. Questions?