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

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 IP Company, 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 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Trading Investing Advice

Approach to Serving the Individual Investor

Multi-Channel

Delivery Web Phone Branch RIAs

Full range of trading products, tools, and information; planning services; investment

and cash management products

Products/Open

Architecture

Client Needs

Education

TD Ameritrade — Overview

3 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

-20%

0%

20%

40%

2005 2006 2007 2008 2009 2010E

Client Asset Growth: RIA Retail AUM vs. Wirehouse Retail AUM

35 pts

Independent RIA Model Gaining Assets

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.

RIAs Wirehouses

+39%

+4%

The RIA Model is Winning

4 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

‘The problems of victory are more agreeable than those of defeat, but they are no less difficult.’ -Winston Churchill

5 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Our Moment of Truth: Growth Led to Declining Satisfaction with Service

Customer Satisfaction

Customer Loyalty

Asset Growth

Profitability

Growth / Scale

System Complexity

Competition

Expectations

Effects

Consequences Causes

In ‘07-’08, Customer Satisfaction Declined*

* Based on Client Satisfaction and Net Promoter scores from monthly TD Ameritrade Institutional surveys of representative panel of ~200

advisors, 2007 to 2008.

6 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Service Matters to RIAs…More Than Any Other Factor

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.

De

cisi

on

Fac

tors

5. Execution Speed

3. Fees

4. Reputation

2. Technology Platforms

1. Service

Reasons Given by Advisors for Their Choice of Custodian

7 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

“If You Can Measure It, You CAN Manage It”

8 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Example: Account Opening Metrics

Success: 90% Success: 90% Success: 90%

Success: 90% Success: 90% Success: 90%

Mail Room Receives

Application

Application Scanned into

Workflow

Task Assigned to

Workflow Queue

Account Setup Process

Compliance Review

Account Funding

1 2 3

4 5 6

Illustrative

9 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Adapting the “Service Profit Chain” Framework

Internal

Service

Quality

Employee

Satisfaction

Employee

Retention

Employee

Productivity

External

Service

Value

Customer

Satisfaction

Customer

Loyalty

Revenue

Growth

Profitability

workplace design

job design

employee selection

and development

employee rewards

and recognition

tools for serving

customers

service concept:

results for customers

service designed and

delivered to meet targeted

customers’ needs

retention

repeat business

referral

Source: James Heskett, Gary Loveman, Leonard Schlesinger et al.

Operating Strategy and Service Delivery System

10 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Our Organizing Framework: The Service Chain with TD Ameritrade Institutional

Factors Driving the Customer Experience

Customer Experience

Initiation

Expansion

Routine Services

Moments of Truth

Customer Behavior

Business Impact

Advocacy

Receptivity (to new info, offers, etc.)

Attrition/ Defection

New Accounts

Asset Inflow

Asset Outflow

Bottom Line: Profitable Asset

Growth

Service Expectations of

Customers

Service Provided

( = Result of Our Processes)

Loyalty

Products & Services

(including tech functionality)

Brand Values / Promises

Our Service Processes

Commitments

Competitor Benchmarks

Source: Adapted from Heskett, et al, Harvard Business Review, July 1, 2008

11 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Customer Experience Customer Sentiment Customer Actions =

Business Impact

Accuracy Rate

Time to Open Account

Customer Satisfaction Scores

Net Promoter Scores

New Account

Assets

Quality of Exception- Handling

Customer Service Quality

Quality

Speed

Experience

Experience

Example Causal Map: New Account Opening

12 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Example: Account Opening Metrics

Success: 90% Success: 90% Success: 90%

Success: 90% Success: 90% Success: 90%

Mail Room Receives

Application

Application Scanned into

Workflow

Task Assigned to

Workflow Queue

Account Setup Process

Compliance Review

Account Funding

1 2 3

4 5 6

Illustrative

13 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

And Metrics Alone Wouldn’t Change Customer Experience…

Dashboards… Gaps/Opportunities Process Enhancements

Which Created Better Results

Made it possible

to identify

Which pointed to needs

for

1 2

3 $

14 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Better Measurement Created a “Virtuous Cycle”

TD Ameritrade Institutional

Our Client/ Customers

Insights About Service Gaps

Improvement Opportunities For Our Clients

Improved Service

Client Operations Improved with Our

Help…

Led To

And

Led to

15 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Impact on Results was Significant and Lasting

78%

91%

75%

80%

85%

90%

95%

J F M A M J J A S O N D J F M A M J J A S O N D

2009 2010

Client Satisfaction Net Advocate

49%

75%

45%

50%

55%

60%

65%

70%

75%

J F M A M J J A S O N D J F M A M J J A S O N D

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.

16 Data-Driven Customer Satisfaction © 2011 Fitzgerald Analytics, Inc. All Rights Reserved

Our Journey: Data

Maturity Level

Data Barely exists in

usable form Exists in abundance, but

quality & value varies High impact metrics Better data mgt / data quality

Analysis Ad hoc 3-Inch Binders Static

Key scorecards Decision tools & models Data-driven learning

Mgmt Decisions

Gut decisions Informed / Educated Fact-based optimization People / Process / Data

integrated

Initiatives Opportunistic Reactive

Short list / rough prioritization

Resource allocation optimal ROI maximization

1. Early Stage 2. Mature 3. Next Generation

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Our Journey: Support

Maturity Level

Business Intelligence Community

Scattered / Ad-hoc Limited access Available, flexible,

dynamic

Experience Analyst

Constrained by data gaps Overwhelmed by data

deluge

Empowered by KPI production, analysis of drivers / causality

Databases Decentralized / Ad-hoc Centralized Made available

1. Early Stage 2. Mature 3. Next Generation

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Diverse Benefits from CXP Measurement System

1. People 2. Process

3. Technology 4. Other

Incentive Changes

Confidence in Decisions Up

Cultural Shift

Workflow Changes

Six Sigma Process Improvements

Earlier Detection of Issues/More Proactive Resolution

Changes to Technology and Systems More Efficient

Upgrades have been easier

Additional innovation built on top of measurement platform

Less Trees Cut Down

More Transparency with Advisors

Competitive Advantage in the Marketplace

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Key Concepts

Concept Key Implications

1. If you don’t measure what matters, you are managing the wrong things!

Agree on key drivers of results Measure the drivers and manage improvement

2. Better Metrics != Better Decisions Beware of unintended incentives “Walk through” processes carefully to find the real

opportunities to improve

3. Managers don’t care about process…

Managers care about results the most, and process the least.

This creates a challenge because process enhancements are essential to better results!

A clear causal model helped us a lot

4. Executive buy-in essential Demonstrate the need (tie back to pain!) Create proof of concept with early wins Iteratively fund additional investments

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Key Frameworks Integrated

Customer Experience

Balanced Scorecards

Data Management

Questions?