Inspire 2015 - Wells Fargo: The Power of Building a Multi-dimensional View of Your Client

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The Power of Building a Multi-dimensional View of Your Client

Wednesday, May 20, 2015

Gary Class, Senior Vice President, Wells Fargo

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Who is Wells Fargo?

• Wells Fargo & Company is a diversified financial services company providing banking, insurance, investments, mortgage, and consumer and commercial finance through more than 8,700 locations and 12,500 ATMs across North America

• Wells Fargo has over 70 million Customers, more than $1.7 trillion in assets and more than 265,000 team members across our 80+ businesses

• At the end of fourth quarter 2014, Wells Fargo ranked fourth in assets among U.S. banks and was the world’s most valuable bank by stock market capitalization.

• Our vision: “We want to satisfy all our customers’ financial needs and help them succeed financially.”

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Developed at Wells Fargo:Branch & ATM Site Planning ModelsTeller Staffing & Scheduling ToolsOnline Banking Customer Data warehouseCustomer Behavior Predictive ModelsCustomer Profile Spanning Multiple Channels

Analytics to make Anytime, Anywhere Banking Happen

Who is Gary Class ?

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Customer Value Framework

Customer Experience Customer Experience Customer SatisfactionCustomer Satisfaction

EngagementEngagement

Overall SatisfactionWilling to RecommendOverall SatisfactionWilling to Recommend

Customer ExpectationCustomer

Expectation

ProfileProductsChannelsTenure

Customer PerceptionCustomer Perception

LoyaltyLoyalty

Engaged CustomersEngaged Customers

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5

Customer Experience Customer Experience ActionAction

DriversFeesWait TimeService Quality Sales Integrity


SatisfactionWilling to RecommendSatisfactionWilling to Recommend

Customer ExpectationCustomer

Expectation



Customer Action

Customer Action

LoyaltyLoyalty


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Customer Experience Customer Experience ResultsResults FinancialResults

FinancialResults

DriversFeesWait TimeService Quality Sales Integrity

RetentionCross-sellBalance Increase

RetentionCross-sellBalance Increase


SatisfactionWilling to Recommend

SatisfactionWilling to Recommend

$

NegativeNegative

Attrition InactivityBalance Decline

Attrition InactivityBalance Decline

($)Customer

ExpectationCustomer

Expectation



Customer Action

Customer Action

PositivePositive

LoyaltyLoyalty


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Customer Value Framework: Outcomes to ManageTo increase Customer Value, we need to manage:

Value Driver Outcome to ManageAcquisition On-boarding Customers

Retention Attrition Mitigation

Revenue Expansion Product Cross-sell

Margin Preservation Channel Usage

We discovered that we lacked the capability to track our Customers’ service interactions in the bank’s channels and, critically, the quality of Customer service.

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Customer Service Quality Trade-off

8

8

Direct Cost of Agent

TimeIndirect Benefit

of Customer Retention via

Quality Customer Service

…. Between current cost & future revenue

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Customer Service in Retail Banking:The Phone Banker Channel

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...Customer Service Metrics identify impact on Customers

Operational Customer-Centric

Average Speed of Answer

Cumulative Time Customer Waited Before Speaking With

an Agent

…which can be directly related to financial results

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Call Center Operational Metrics

Operational Metrics over-simplify…

Operational

Average Handle Time ; Half Hour Interval

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Operational Customer-Centric

Average Handle Time

Elapsed Time Until Customers' Problem Is

Resolved

…where the Quality of Customer Service Issue Resolution is critical

...Customer Service Metrics identify impact on Customers

Customer Service in Retail Banking: the Key Success Measure

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The key is to have a comprehensive & exhaustive understanding of the Customers’ “reason for the call”

Customer Service in Retail Banking:The Phone Banker Channel

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Customer Interactions: Phone Agent Channel

13

<Get Account_Number><Get Account_Balance>

Product: Forever Free CheckingAccount Number: 123456789Average Balance $1,235.45

User Client : Front-end System for Phone Agent

Business Service: Middleware Messages

System of Record: Checking Account Master File

Data: Checking Account Ledger

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Customer Interactions: SESSION

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For Inbound Phone Calls, “Passive Logging” Identifies:* Date & Time* Agent* Customer * Content of Interaction

Get Checking Account Balance

Return $1,235.45

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Finally, we can orient the disparate data by Customer & time to stitch together the customer’s “sojourn” through the bank

Note: Wait time is taken into account in Total Service Time.

Calc: 3 minutes (180 seconds)

5 minutes (300 \seconds)

A. Customer calls B. Customer is serviced by Agent 1

C. Agent 1 warm transfers to Agent 2

D. Agent 1 , Customer, and Agent 2 are all on the line

E. Customer and Agent 2 left on the line.

+ Calc: 1 minute (60 seconds)

+ Calc: 10 minutes (600 seconds)

Total Service Time = 19 minutes

(1,140 seconds)

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The over-arching goal is to transform the available Systems data into a model of the Business process that reflects the Customers’ experience in interacting with the Bank with as much detail and precision as possible.

We need to distill the following from each Channel interaction:

CUSTOMER = who is the party that is requesting service? (i.e. natural vs. legal person)

SESSION = Begin & end time of the authenticated activity in the Channel

SOJOURN = Beginning & end of the Customers’ journey across the Firm’s myriad of Channels to accomplish a Task

TASK = Inferred from the predicate knowledge about the Customer, the context of the interactions, the sequence of the interactions and any insight from primary research.

Customer Channel Interaction Data in Retail Banking

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Customer Channel Interaction Data: Finding a Solution• After accumulating the detailed Channel Interactions data from the

myriad of Channel application systems, we attempted to interweave these sessions into Customer Sojourns

• After 10,000 lines of SQL, we “broke our teeth” on this problem and despaired that we could ever directly observe our Customers’ Sojourns through multiple banking channels.

• Fortunately, our neighbors in the Silicon Valley had developed innovative Big Data technologies to deal with similar problems, notably the Map-Reduce paradigm.

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DATA PROCESSING PROBLEM:Inter-leaving on a common identifier and a common time standard a very large volume of interaction data of myriad data types: structured, semi-structured (e.g. application logs) & unstructured (e.g. text). ORGANIZATIONL PROBLEM:We didn’t want to be dependent on an army of supporting software engineers; we wanted to empower our modelers to leverage Big Data without retraining them.

SOLUTION:SQL-Map Reduce, which allows SQL conversant analysts with domain knowledge to invoke Map Reduce operations directly.

Finding a Solution: People

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Customer Service Interactions: a 360 degree view

Big Data Analytics

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Outcome to Manage Critical Questions that were answered

On-boarding How fast do new deposit Customers learn to use the ATM and Online Banking?

Attrition Mitigation The context of the last interaction with the banks’ representative prior to exit, i.e. the “path to

perdition”

Customer Value Framework: Managing Outcomes

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Customer Value Framework: Managing Outcomes

Outcome to Manage Critical Questions that were answered


Attrition Mitigation

The context of the last interaction with the banks’ representative prior to exit, i.e. the “path to perdition”

Product Cross-sell The channel interaction “signature” of prospects who converted, i.e. the “path to cross-sell”

Channel Usage The sequence of activity in banking channels that Customers use to solve a problem

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Customer Value Framework: Managing OutcomesOutcome to Manage Critical Questions that were answered


Attrition Mitigation

The context of the last interaction with the banks’ representative prior to exit, i.e. the “path to perdition”

Product Cross-sell The channel interaction “signature” of prospects who converted, i.e. the “path to cross-sell”

Channel Usage The sequence of activity in banking channels that Customers use to solve a problem

The key benefit of building a multi-dimensional view of the Customer has been to accelerate Customer issue resolution -- which has led to a corresponding improvement in Customer

satisfaction.

THANK YOU!

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Inspire 2015 - Wells Fargo: The Power of Building a Multi-dimensional View of Your Client

Data & Analytics

quality of customer

quality customer service

customer service metrics

customers service interactions

customers problem

customers financial

wells fargo company

banks channels