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Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond
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Jaime Fitzgerald on Data-Driven Customer Experience in Financial Services and Beyond

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  • 1. Data-Driven Customer Satisfaction Zohar Swaine, TD Ameritrade Institutional Jaime Fitzgerald, Fitzgerald Analytics, Inc. Architects of Fact-Based Decisions™This material is designed for an investment professional audience, primarily Registered Investment Advisors (RIAs) and is for illustrative and informational purposes only. TD Ameritrade Institutional,Division of TD Ameritrade, Inc., member FINRA/SIPC/NFA. TD Ameritrade is a trademark jointly owned by TD Ameritrade IP Company, Inc. and The Toronto-Dominion Bank. © 2011 TD Ameritrade IPCompany, Inc. All rights reserved. Used with permission. TD Ameritrade and Fitzgerald Analytics are separate and unaffiliated companies and are not responsible for each other’s policies and services.
  • 2. TD Ameritrade — Overview Approach to Serving the Individual Investor Client Needs Trading Investing Advice Multi-Channel Delivery Web Phone Branch Education RIAs Products/Open Full range of trading products, tools, and Architecture information; planning services; investment and cash management productsData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 2
  • 3. The RIA Model is Winning Independent RIA Model Gaining Assets Client Asset Growth: RIA Retail AUM vs. Wirehouse Retail AUM 40% +39% 20% 35 pts +4% 0% -20% 2005 2006 2007 2008 2009 2010E RIAs Wirehouses Sources: Cerulli “State of the Wirehouses” – Nov ’09, “RIA Service Agent Survey” – Q2 ’10, “Advisor Metrics” – 2010 Update. RIAs include dually registered advisors. 2010E represents estimated results based on industry publications, public filings, and TD Ameritrade internal analysis.Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 3
  • 4. ‘The problems of victory are more agreeable than those of defeat, but they are no less difficult.’ -Winston ChurchillData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 4
  • 5. Our Moment of Truth: Growth Led to Declining Satisfaction with Service Causes Effects Consequences Growth / In ‘07-’08, Customer Scale Satisfaction Declined* Customer Asset System Satisfaction Growth Complexity Competition Customer Loyalty Profitability Expectations * Based on Client Satisfaction and Net Promoter scores from monthly TD Ameritrade Institutional surveys of representative panel of ~200 advisors, 2007 to 2008.Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 5
  • 6. Service Matters to RIAs…More Than Any Other Factor Reasons Given by Advisors for Their Choice of Custodian 1. Service 2. Technology Platforms Decision Factors 3. Fees 4. Reputation 5. Execution Speed Source: “Cerulli Advisor Quantitative Update Report,” 2010, Cerulli Associates, in partnerships with the College for Financial Planning, the Financial Planning Association, the Investment Management Consultants Association, and Morningstar.Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 6
  • 7. “If You Can Measure It, You CAN Manage It”Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 7
  • 8. Example: Account Opening Metrics Illustrative 1 2 3 Mail Room Application Task Assigned Receives Scanned into to Application Workflow Workflow Queue  Success: 90%  Success: 90%  Success: 90% 4 5 6 Account Setup Compliance Account Process Review Funding  Success: 90%  Success: 90%  Success: 90%Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 8
  • 9. Adapting the “Service Profit Chain” Framework Operating Strategy and Service Delivery System Employee Revenue Retention Growth Internal External Employee Customer Customer Service Service Satisfaction Satisfaction Loyalty Quality Value Employee Productivity Profitability  workplace design  job design  service concept:  retention  employee selection results for customers  repeat business and development  referral  employee rewards and recognition  tools for serving  service designed and customers delivered to meet targeted customers’ needs Source: James Heskett, Gary Loveman, Leonard Schlesinger et al.Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 9
  • 10. Our Organizing Framework: The Service Chain with TD Ameritrade Institutional Factors Driving Customer Customer Business the Customer Experience Experience Behavior Impact Brand Values / Attrition/ Promises Loyalty Initiation Defection Products & Services Service (including tech Expectations of New functionality) Advocacy Customers Accounts Commitments Expansion Competitor Asset Benchmarks Inflow Routine Asset Receptivity Services Outflow Service (to new info, Our Service Provided offers, etc.) Processes ( = Result of Our Bottom Line: Processes) Moments Profitable Asset of Truth Growth Source: Adapted from Heskett, et al, Harvard Business Review, July 1, 2008Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 10
  • 11. Example Causal Map: New Account Opening Customer Actions = Customer Experience Customer Sentiment Business Impact Quality Customer Accuracy Rate New Account Satisfaction Scores Speed Time to Net Promoter Assets Open Account Scores Experience Quality of Exception- Handling Experience Customer Service QualityData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 11
  • 12. Example: Account Opening Metrics Illustrative 1 2 3 Mail Room Application Task Assigned Receives Scanned into to Application Workflow Workflow Queue  Success: 90%  Success: 90%  Success: 90% 4 5 6 Account Setup Compliance Account Process Review Funding  Success: 90%  Success: 90%  Success: 90%Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 12
  • 13. And Metrics Alone Wouldn’t Change Customer Experience… Dashboards… Gaps/Opportunities Process Enhancements Made it Which possible pointed 1 2 to to needs identify for 3 $ Which Created Better ResultsData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 13
  • 14. Better Measurement Created a “Virtuous Cycle” TD Led to Insights About Improved Ameritrade Service Gaps Service Institutional Led To Improvement And Client Operations Our Client/ Opportunities Improved with Our Customers For Our Clients Help…Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 14
  • 15. Impact on Results was Significant and Lasting Client Satisfaction Net Advocate 95% 75% 75% 91% 70% 90% 65% 85% 60% 55% 80% 50% 78% 49% 75% 45% J F M A M J J A S O ND J F M A M J J A S O ND J F M A M J J A S O ND J F M A M J J A S O ND 2009 2010 2009 2010 Scores are based on a 3-month rolling average. CSI is based on 11 point scale, that is, from 0 to 10, top 3 box = 8+9+10 rating points. Net Advocate is based on [10+9 ratings] – [0+1+2+3+4+5+6 ratings]. Results for Legacy TD Ameritrade and Legacy Fiserv Trust Company combined November 09 and forward.Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 15
  • 16. Our Journey: Data Maturity Level 1. Early Stage 2. Mature 3. Next Generation  Barely exists in  Exists in abundance, but  High impact metrics Data usable form quality & value varies  Better data mgt / data quality  Key scorecards  3-Inch Binders Analysis  Ad hoc  Decision tools & models  Static  Data-driven learning  Fact-based optimization Mgmt  Gut decisions  Informed / Educated  People / Process / Data Decisions integrated  Opportunistic  Short list / rough  Resource allocation optimal Initiatives  Reactive prioritization  ROI maximizationData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 16
  • 17. Our Journey: Support Maturity 1. Early Stage 2. Mature 3. Next Generation Level Business  Available, flexible, Intelligence  Scattered / Ad-hoc  Limited access dynamic Community  Empowered by KPI Experience  Overwhelmed by data  Constrained by data gaps production, analysis of Analyst deluge drivers / causality Databases  Decentralized / Ad-hoc  Centralized  Made availableData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 17
  • 18. Diverse Benefits from CXP Measurement System 1. People 2. Process  Incentive Changes  Workflow Changes  Confidence in Decisions Up  Six Sigma Process Improvements  Cultural Shift  Earlier Detection of Issues/More Proactive Resolution 3. Technology 4. Other  Changes to Technology and Systems More  Less Trees Cut Down Efficient  More Transparency with Advisors  Upgrades have been easier  Competitive Advantage in the Marketplace  Additional innovation built on top of measurement platformData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 18
  • 19. Key Concepts Concept Key Implications 1. If you don’t measure what  Agree on key drivers of results matters, you are managing the  Measure the drivers and manage improvement wrong things!  Beware of unintended incentives 2. Better Metrics != Better Decisions  “Walk through” processes carefully to find the real opportunities to improve  Managers care about results the most, and process the least. 3. Managers don’t care about  This creates a challenge because process process… enhancements are essential to better results!  A clear causal model helped us a lot  Demonstrate the need (tie back to pain!) 4. Executive buy-in essential  Create proof of concept with early wins  Iteratively fund additional investmentsData-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 19
  • 20. Key Frameworks Integrated Customer Experience Balanced Data Scorecards Management Questions?Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved 20

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