analytics 2.0: turning call data into caller data

Jim Dickey, Peppers & Rogers Group

Niren Sirohi, iKnowtion

Analytics 2.0: Turning Call

Data into Caller Data

June 10, 2014

©2014 TeleTech Holdings, Inc. Confidential and Proprietary 2

Speakers

Niren Sirohi

Vice President, Predictive Analytics

iKnowtion

Niren Sirohi [[email protected]]

Jim Dickey

Vice President and Managing Director,

Business Intelligence and Simulation

Peppers and Rogers Group

[email protected]


• Introductions

• Contact Center Realities and Opportunities

• Breakout Session 1

• Break

• Putting Data into Context

• Breakout Session 2

• Case Studies and Framework to Get Started: Data-Driving Customer

Experience

• Q&A and Wrap-up

Agenda


Customer Landscape is Shifting

The customer landscape is shifting


Customer contact patterns are changing

Explosion in Contact Channels

There has been a 12% rise in web self-service usage, a 24% rise in chat usage, and a 25% increase in community usage for customer service in the past three years. Forrester’s Top 15 trends for Customer Service in 2013, January 2013

http://www.colocationamerica.com/voip/ip-ivr.htm

http://www.cloudplugfest.org/cloud-interoperability-week

http://peperonity.com/go/sites/mview/bmon.citycell/35219474

http://gesterling.wordpress.com/2010/01/25/the-return-of-click-to-call/

http://www.empowernetwork.com/abundantbizzness/blog/how-to-use-online-forums-to-get-traffic/

http://www.forbes.com/sites/benkerschberg/2011/09/28/managing-information-risk-and-archiving-social-media/

http://lagos.all.biz/gts-infotel-nigeria-ltd-e1292

http://dichvuso.edu.vn/

http://www.panarabco.com/Customers.aspx


Self service is highly valued

It is preferred for well-defined tasks

Customers today value self service as much as using the phone

Unfortunately it is not always intelligent:

57% of inbound calls come from customers who first attempted to

resolve their issue on the website and over 30% of callers are on the

website when talking to a rep on the phone

Why your customers don’t want to talk to you, HBR blog, July 2010

http://www.nad.org/news?page=8


Customer experience breakdowns are commonplace

More likely during channel handoffs

62% of customers have switched brands in the past year due to poor customer service Accenture 2012 Global Consumer Pulse Research

This is John Smith at 200 Same Ave,

Gainesville, FL. My internet is not

working

At this point, we have tried

everything. Please call 1-800-fix-help

This is John Smith at 200 Same Ave,

Gainesville, FL. My internet is not

working

How can I help you?


Word of mouth is amplified

Customer Experience

Challenges and Opportunities


Customer engagement leaders outperform the market

Leaders vs. Laggards vs. S&P 500 (2007-2012)

50%

40%

30%

20%

10%

0%

-10%

-20%

-30%

-40%

Cu

mu

lati

ve

To

tal R

etu

rn

Customer

Experience

Laggards

S&P 500

Index

Customer

Experience

Leaders Leaders Outperform

Laggards by

77%

-34%

14.5%

+43%

Source: Forrester and Watermark


CX disconnect…

93% consider

customer experience a

top strategic priority

But 86% say they

don’t expect

much value from

customer experience

investments

Source: Forrester Research, The State of Customer Experience Management: 2013


…reflected in budgets

Source: Forrester Research, The State of Customer Experience Management: 2013

Only 37% of

companies have

earmarked a budget

for customer

experience initiatives


The contact center of the future

Opportunity to prove the value of CX

Cost Center Superior Experience Creator


What will it take to get there?

Proactively Data

Driven

Embrace Predictive

Analytics

Technology

Innovator

Test and Learn

Mindset

Customer Centric


Bring in caller (customer) data

Key Customer Data Elements:

■ Customer Tenure

■ Products / services purchased

■ Responses to customer surveys

■ Region / Geography

■ Customer Value

■ Demographics / Psychographics

■ Customer Key (unique ID)

Key Contact / Call Characteristics:

■ Date and time of interaction

■ Duration of interaction

■ Call repeat pairings

■ Call reasons

■ Call resolutions

■ Customer Key (unique ID)

■ Agent ID

Key Agent / Workforce Characteristics:

■ Agent ID

■ Region / Geography

■ Tenure

■ Skills

■ Agent notes

■ Performance

■ Stack Ranking

Customer Data

Agent / Workforce

Data

Contact / Call Data

http://openclipart.org/detail/89275/computer-icon-by-kuba


Structured

(Quantitative)

Unstructured

(Qualitative)

Customer-Initiated Company-Initiated

Voice of Customer Categories

De

pth

of In

sig

ht

Representativeness of Feedback

Incorporate unstructured data

Unstructured VoC data can drive more meaningful insights and help explain

“why” customers have certain attitudes/perceptions about your brand

http://teenspeak.org/2011/11/23/the-latest-facebook-virus/

http://teenspeak.org/2011/11/23/the-latest-facebook-virus/

http://theinspirationroom.com/daily/2012/twitter-logo-redesigned/

http://www.global-atg.com/customer-support/phone-and-live-chat-support


Enable Voice of the Customer with

technology-enabled analytics

Go beyond just measuring NPS to

understanding its drivers

Leverage your contact center as a test bed

for customer experience

Sample opportunities

Use predictive analytics to pre-empt repeat

calls

Breakout Session:

Understanding and Assessing

Your Environment


Data strategy will enable answering the following three

fundamental strategic questions and add value to business

understand predict act

Timely Decisions Stay Ahead Strategic and

Tactical Actions

What is happening in

my business?

What will happen

next?

What can I do to

influence it?

1 2 3


Customer engagement model

Listen

Learn Adapt

Listen


Contact center data can be used in multiple ways to

leverage customer engagement

Integration of Customer

Touch point Data

1

Speech/Text

Analytics

2

Segmentation-based

Contact Center Strategies

3

Revenue uplift using

Outbound Campaigns

4





Touchpoint Data

1

Speech/Text

Analytics

2

Segmentation based


3


Outbound Campaigns

4


Cu

sto

me

r In

itia

ted

/

Co

ntr

oll

ed

AA

In

itia

ted

/

Co

ntr

oll

ed

Mapping customers’ journey across touchpoints is a

first step in understanding customer engagement

Delay

notifi-

cation

AA

advert-

ising

/mktg

Pricing

& fees

Confirm

standby

Check

baggage

Upgrades

Gate

info

On-time

departure

Delay

mgmt.

Flight

cancelled/

oversold

Boarding

Carry-on

bags

& gate

check

Boarding

Find

space for

carry-on

Find

seat

Evaluate

Aircraft

Select

F&B

svc.

Take-off

announce-

ments

Use

IFE

Use

onboard

amenities

Reserve

seats

Select

channel

Select

ticket

Check

flight

info

Navigate

airport

Obtain

boarding

pass

Security

wait

Visit

Admirals

club

Find

gate

Check

baggage

Purchase

ticket

Change

ticket

Wait

at gate

Duty

free

sales

Landing

prep.

Pre-take

off svcs. Complaint

Baggage

resolution

Exit

airport

Transfer

to gate

Customs/

Immigration

Collect

bags

Deplane

Award

ticket

Admirals

club

Rebook

missed

flights

Cabin

interiors

Pre-take

off svcx.

F&B

quantity

F&B

quality/

variety

IFE

options

IFE

equip.

Landing

info

On-time

arrival

Taxiing

& jet

-bridge

Deplaning

Connec-

tions

Baggage

delivery

Complaint

resolution

Baggage

resolution

Customer travel experience

EXAMPLE

Source: AA Customer Engagement presentation


Using analytical engines, unstructured touchpoint data is converted to usable

information that can be leveraged for various analytical and marketing purposes

Delivery

Costs

CSAT

and NPS Revenue Brand

Reputation

Self-Service | Chat | Mobile | Video Voice | E-mail

Traditional Channels Evolving Channels

Reputation Monitoring | Communities |

Social Associates

Social CRM

Outcomes that Differentiate


Integrating contact center data with various other data sources

into a single data mart to understand 360° view of customer

Third Party Data

Demographics

Geo-demographics

Cluster segments

Customer Segments

Product owners

- Combinations

Ethnic groups

Lifestage groups

Engagement levels

Loyalty program members

Value groups

Customer History

Product Ownership / Usage

Recurring and variable

revenue

Servicing activity / cost Contact History

Customer Care

Social Media

Forums

Analytic Data Mart

Key Metrics

Tenure

Content consumption

Purchase activity

Engagement

Service activity

Attrition activity

Recurring / variable revenue


Creating a data strategy leveraging on both strategic and tactical

requirements is key for consistent management of customers

Customer Data Mart

Call Center

Internet

Direct

Account Managers

Customer Hub

• Segmentation

• Churn Prediction

• Cross-sell / Up –sell tendency

• Credit Scoring

• Payment Behavior Analysis

• Customer priorities

• Open complaints / requests

• Missed payments

• Customized offers / campaigns

• Churn possibility

• Product ownership / uptake

• Missing critical information

►Better decision making based on

customer information

►Building relationships with

customers

►Profit maximization

►Unified and most relevant batch

customer information

environment

Enabling Strategic Decision Making

through Customer Analytics

Analytical Customer

Information

Operational Customer

Information

►Smoother flow of customer processes

► Improved customer service levels

► Fully integrated and online customer

information environment

Enabling Tactical Decision Making

through Informed Channels





Touch point Data

1

Speech/Text

Analytics

2

Segmentation based


3


Outbound Campaigns

4


What is speech/text analytics?

Internet Channels

Email/Chat

Voice

Elements of Analytics

Phonetic indexing • Breaks down speech into phonemes

• Creates an indexed voice database

Speech-to-text

transcription

• Transcription of calls from spoken to

written words

• Enables text and data mining

distress

Speaker separation • Who said it…agent or customer

• Valuable context for customer

interaction

Emotion detection • Analyzes the voice of the speaker

and identifies emotion

• Reliable gauge of both customer

dissatisfaction and agent skills

Talk-over analysis • Identifies portions of calls in which

the customer and agent are talking

simultaneously

• Gaps in agent knowledge are

identified

Min

ing

th

e d

ata


Multichannel data into comprehensive analytics

Speech/Text Analytics can be a useful tool for driving the value of

interactions with your customers

Te

xt

Dear DirectCom Online Service, I have a question about my

most recent bill. I paid the full balance online in the amount of

47.61$ on February 16th. When I checked back the payment

didn’t show up, and I was charged 50$ fee on top of that. This

is not acceptable! The online payment confirmation number

back the payment didn’t show up, and I was charged 50 and I

was charged 50 and I was $ fee on top of that. This is not is

49733. Please verify and make sure I get the fee back to my

account. This is not the first time I have a problem with the

online payment. Best regards, Gina Lowell.

Sp

ee

ch

C

on

tex

t Misinformed

Frustrating

This is the 2nd time I’m calling

Phone

Social Media

Chat

Email

Web

Phone Survey

Keywords and Topics

Talk Over Analysis

Emotion Detection

Call Flow Analysis

So confusing

Sick and tired

Desktop Analytics

Customer Demographics

Interaction History

Customer Feedback

Keywords and Topics

Sentiment Analysis

Chat Response Time

Social Buzz


Value of analytics

Interact Root Cause on

Customer Interaction

Brand New Marketing

Campaigns

Program Changes

Agent

Performance Efficiency and

effectiveness

Process

Improvement Reducing cost while

maximizing

efficiencies

Customer Insight Operational Improvements

Uncovering the Root Cause to deliver exceptional results


What does it mean to you?

New Marketing Campaigns

Program Changes

► Identify the customer’s emotion to the

changes

► Impact to the brand

► Identify if customers are leaving due

to the program changes

►Mimic Voice of the Customer data

through call listening

What are the customers saying when

you change a program?



Root Cause on

Customer Interaction

The data shows that:

►Customers who got a free loaner

vehicle tend to be the happiest;

►Customers who got a rental vehicle

but are asked to pay for it are upset;

►Customer who didn't get a loaner

vehicle at all are more upset

Root Cause on Services Provided?

Emotion influenced by loaner availability?



Agent Performance

Efficiency and

Effectiveness

► Time and motion study on a per step

level for specific call scenarios

►AHT and dead air count and average

measurements

► Identifying the Root Cause on AHT

increases

Improving Agent Performance?



Process Improvement

reducing cost while

maximizing efficiencies

►Utilizing Queries to understand the

reason for AHT increases

►Analyzing AHT by call type or by

agent or by date which results in

focused areas of improvement

►Root Cause analysis on call driver

which resulted in new subscription

tools to be utilized by the customer

Operational Improvements

Results:

• Delays caused by subscription sales/activations

• Delays caused by complex issues that require consultations/escalations





Touch point Data

1

Speech/Text

Analytics

2

Segmentation-based


3


Outbound Campaigns

4


Segmentation helps to combines value, needs, and

behavior of the customer

Research and Purchased

Data

Client and Purchased Data

Value Dimension Behavior Dimension Needs Dimension

Value

Behavior

Needs

Patient

Drives Generates

The motives and needs that

drive the behaviors of

consumers.

Consumer behaviors when

making decisions about, or

using, healthcare products and

services.

The value the customer

currently creates (or destroys)

for the business.


3-Dimensional segmentation results in actionable segments

that can form the basis for decision making

1 Segment integration focuses on business attractiveness

2 Manageable number of customer segments is created by integrating segments

3 Provides capability to design specific treatments for specific “types” of customers

NEEDS

BEHAVIOR

VALUE

Going Green

Cherry Pickers

Luxury Lovers

Techies

Loss

Functionals

Guidance

Seeker

Youngsters

Working Out Value & Extended Value

For The

Family

Super most

Valuable

Customers

Medium Value

Low Value

Most Valuable

Home Sweet Home

Below Zero

Below Zero


Combining segmentation with contact data enables

organizations to have customer contact segments

Satisfaction

Contact Details Outbound Strategy

Complaint Price/Device/Data/

Network

Information Tariff / Campaign /

Subscriber

Action

Suggestion /

Thanks

Retention

Cross-sell/

Up-sell

Customer Contact Segments

Contact Frequency

New pack intro

Forward to Care

Center

Tariff application

Feedback for

suggestion

Advocate

program


Integrated segmentation will support the organization –

both at strategic and tactical levels

Identify values of

pocket in the

consumer base

Identify substitution

and revenue

cannibalization risks

Understand

positioning in key

consumer

segments

Support

development of

FMC strategy

Support

consolidation

strategy

Establish the

unified data

environment

Feed CRM system

with unified

customer value

Feed Marketing

efforts with unified

opportunities

Enable consumer

retention with full

view on total

customer value

Leverage below

the line channels

to their full

potential

Strategic

advantages

1

Tactical

advantages

2





Touch point Data

1

Speech/Text

Analytics

2

Segmentation based


3


Outbound Campaigns

4


Using historical data to identify customer needs and the

products they prefer

Identify which customers are most

likely to buy

Target the right customers at the

right time through the right

channel

Determine which products they

are most likely to buy next

• Achieve higher

conversion rates for

cross-sell campaigns

• Take full advantage

of customer contacts

to promote sales

Company Perspective

Increased satisfaction raising the

perception of obtaining “value for

money”

Customer Perspective

Increased value from customers

with the right product or service to

augment each channel

• “Don’t try to sell me something I don’t need”

• “I will appreciate suggestions for additional products

and services that stem from genuine care and concern

for my needs”


Adaptive engagement framework translates the needs

of customer to action oriented initiatives

Analyze

Create

Offer /

Treatment

Validate

Roll Out

Usage

Profile

Subscription

VoC

Contact Data

Direct Mail

SMS

E-mail

Outbound

Call lists

Internet

Continues Feedback / Improvement

Hunt for behavior

patterns

Observe the base and

act on triggers by using

complex event

processing tools Act in real time with the

right offers, through the

right channel

1

2

3

Adaptive Engagement as the Operational Framework for Outbound Marketing


Understanding customer segments, and which strategy

to use, is crucial for customer engagement

Segment Profile Segment Profile

Segment Profile

Product Value Channel

1.98%

34%

53%

43%

0.64%

13%

10%

20%Credit Card

Consumer

Loan

Supplementary

Account

Payments

7%3%

34%

17%

39%

TL Curent

Foreign Currency Current

TL Time Deposit

FC Time Dep. Investment

35%

45%

20%

0%

Branch

ATM

İnternet

Phone

Active Products: 4,6 (Ort: 2,6)

Gender RegionAge Marital Status

0 0

25%

47%

28%

0 0

21

Altı

21

-30

31

-40

41

-50

51

-60

61

-70

70

…

72%

28%

Male Femaile

100%

0% 0%

Married Single3%

5%

6%

13%

12%

12%

18%

14%

16%Bağ.

İstanbul

Ege

Akdeniz

Mar.

Ankara

Doğu

Kara.

Orta

Karlılık SFO KFO Kredi Kartı Harcama

57 TL

231 TL

633 TL

2,168

TL

523 TL

2,693

TL

569 TL

1,977

TL

Profit AUM RUM Credit Card Vol.

Segment Profile

• Macro Segment: Mass

• Extended Value Segment: Super

Growable

• Behavior Segment: Techies

• Needs Segment: Functionalist

• Segment Strategy: Grow

• Cross-Sell Potential: Very high

• ....

Segment Strategy

• How should we set our short-term and long-term targets for this segment?

• How can we drive credit acquisitions through customer targeting?

• When and in what sequence should we offer which products and services?

• Which targeted campaigns should be designed for which customer groups

at what time?

Campaign Management

Targeted Customer Value

Time

Auto Loan Mortgage

Credit Card

IRAs and CDs


Customer information is integrated, updated regularly

and made accessible across touchpoints

Customer Personal

Information/ Product

catalog/ Billing

Customer Contact

History

Recent touchpoint

activity

Customer Value/

Needs/Behavior

Segment

Customer Churn

Probability

Cross/Up Sell

Product list &

likelihood


Frontline agents are empowered across touchpoints to

use this information to drive sales and retention


Challenges and pitfalls to transition to a customer

engagement organization

Organization

Process

Information

Technology

• Organizational willingness and having in place a go to strategy

• Aligning Business Units to provide similar customer experience

• Building a cross-functional team that combines all the skills

(Marketing + Analytics)

• Design a process for rapid Time-To-Market (months days)

• Document and sign-off all processes with Technical teams

• Take calculated risks, pilot, learn and then go for full launch

• Ensure summarized customer information is available and accessible on

timely basis

• Build and manage your campaign communication Datamarts to track

customer interaction and results

• Ensure information flow and learnings across Organization

• Invest in analytical tools to avail data mining and analysis from

data warehouse

• Invest in campaign process management tools to decrease the amount of

manual work required

Breakout Session


Applying caller-centric analytics to predict repeat calls

Using information and insights about the ‘call’ and the ‘caller’ to identify

opportunities to improve First Call Resolution (FCR)

Performed a Customer

Interaction Diagnostic to

identify several targeted

opportunities to improve

the customer

experience

• Drive call deflection

• Improve the service

programs operational

effectiveness, particularly

by reducing repeat calls

• Deliver a superior

customer experience

Telecom client

challenged customer

care business partners to

identify transformational

program enhancements

that will:

A full year of

customer interactions

(23M interactions) belonging

to 7M unique customers were

included in the analysis

The univariate and

multivariate analysis was

designed to evaluate customer

interactions across multiple

dimensions such as: customer

lifecycle, product mix and

call reasons

Utilized analysis insights to

develop several pilot

program recommendations

to drive significant FCR

improvement

Ap

pro

ac

h

Ba

ck

gro

un

d

Case Study


Critical to conduct multi-dimensional analysis

Diagnosing drivers of repeat call behaviors requires an analysis of the

call and caller data

Customer Lifecycle

Call Reasons Customer

Segmentation

Customer

Interactions

• 20% of all calls are made by customers in their first

month of tenure

• Repeat call rates are 40% higher during the customers

first month of tenure

• 21% of the callers made 49% of the total calls

• Customers with 3 or more services call 42% more often

than customers with only 1 active service

• The transaction NPS of even the most loyal customers

drops by 18 points if the problem was not resolved in

the first call

• Calls regarding outages, truck rolls, appointment

management have the highest repeat call rates

• Customers calling for Internet product information

have 55% higher repeat rates than customers calling

for Phone product information

Case Study


Many factors contribute to repeat call behavior

Analytical techniques can isolate key drivers of repeat interactions and predict which calls

are most likely to generate repeat interactions so that corrective actions can be deployed

Selected Drivers

Converted into

Predictions

Key Driver Analysis Predictive Analytics

0%

10%

20%

30%

40%

1 2 3 4 5 6 7 8 9 10 C

on

tacts

Re

qu

irin

g

Re

pe

at

Co

nve

rsa

tio

ns

Models can proactively predict behaviors and drive highly

targeted customer experiences

Higher Likelihood Lower Likelihood

Repeat Interaction

Likelihood

Model

• Customer interactions classified in the top decile (top

10%) are 53 times more likely to require a repeat

contact than interactions in the bottom decile

Model Decile Ranking

Service Mix

Types of

services

purchased

# of services

purchased

Drivers of

Repeat

Interactions CSAT/NPS

Surveys

Prior NPS

scores

Call History

Total call

count

Prior repeat

incidence

Customer

Lifecycle

Customer

Tenure

Call Type

Detailed call

reason

Handle time

Last call

reason

Time of

Interaction

Date

Day of Week

Hour

Case Study


Identifying opportunity segments

The customer interaction diagnostic isolates focused areas of opportunity

to test new approaches to improve FCR

0%

10%

20%

30%

40%

Re

pe

at

Ra

tes

Authentication and Misdirects (2%)

Note: Bubble size represents % of annual calls

Information & Education (25%)

Outage Notification Calls (1%)

Account and Appointment

Management (14%)

Referral/Escalation

(20%) Diagnostics and Guidance (13%)

Truck Roll Calls (8%)

Darker blue bubbles

represent call types with

higher expected likelihood

to improve FCR

Customer Segment: Owners of 3+ Services

Customer Lifecycle: Tenure < 90 Days

Case Study


Developing pilot tests

Need to be able to set-up a test and learn environment to quickly and

accurately measure test results and make well-informed refinements

• Route in-bound calls to “best agent” based on caller segment profile, call reason and agent skills

Intelligent Call Routing

• Use predictive models to provide agent with timely information about other potential customer support needs

Multiple Problem Resolution

• Direct trigger-based, personalized communications towards customers most likely to repeat

Proactive Customer Education

Case Study


Repeat call prediction: TeleTech framework

TeleTech utilizes a comprehensive Listen – Interpret – Act framework to

maximize the business impact of the insights

Model Scoring

During Call

Next Likely

Reason(s)

Model

Likelihood of

Repeat Call

Model

Event

Orchestration

During Call

LISTEN INTERPRET ACT

call

caller

agent


Situation overview

• The Client developed a segmentation

model based on customer needs and

behaviors and started to rethink its

value propositions across different

macro and micro segments

• Inconsistency of performance within

the sales and service model was

identified as an issue

• The Client wanted to align the sales

and service model and balance cost-to-

serve with level of service

Situation

• Explore potential for transaction

migration to contact center from over

the counter

• Analyze branch and contact center

staffing model and task distribution to

better align them with strategic

objectives and enhance branch

performance

• Determine reasons for low sales

productivity at contact centers despite

the availability of dedicated resources

Objectives


Project approach

Sales and Service

Model Design Inputs

Customer

Segmentation and

CVPs

Benchmarks and

PRG Expertise

Current State

Assessment

The Client Strategic

Objectives

Requirements for

Sales and Service

Model

Enhancement

Opportunities

The Client

Capabilities

Guiding Principles

Options for Integrated

Sales and Service

Model

ROI Model

Options Impact

Analysis

Enhanced Sales and Service

Model

Consensus and Decision Sales and Service

Model Design

Current and Planned Sales and Service Model Initiatives

Customer

Differentiation

Cost-to-serve

Channel

Integration

the Client Enhanced S and S Roadmap


Project output

Roadmap Design Multi-Channel Sales &

Service Model Alignment Current State Assessment

1. Current state assessment report

Sales and service components of channels

Service Levels

Relationship and portfolio management principles

Channel-based product and transactional analysis

Summary of benchmarks and best practices

2. Mapping of the current state sales and service model

2 3 1

1. Critical success factors and dependencies

2. Detailed roadmap for new and ongoing initiatives

Analysis of impact and implementation considerations

1. Primary and secondary sales and service channels per segment, product and transactions (Multichannel Matrix)

2. Enhancement of relationship and portfolio management principles

3. Service level and business rules per segment across channels

4. Recommendations on performance measures, compensation and target setting framework

5. Capacity planning assessment and recommendations

6. Target state organization and governance report

7. Target state sales and service model map


The four pillar customer value proposition framework guided

the re-alignment of the sales and service model at the client

Target State options

Segment differentiated

customer treatment from

an experience and ease

of use perspective

Customer

Experience

Multichannel

Integration Cost to Serve

Roadmap

design

CV

P R

efi

nem

en

t

Prioritize and Select

ROI Model

Customer shape

ROE increase

Strategic

objectives

Focus on serving

customers in a cost

efficient fashion

Focus on utilizing

distribution capabilities to

optimally address

customer needs


A channel capability analysis illustrated the extent to which

channels were suitable for conducting key interactions

Create awareness 2 1 1

Identify potential customer

needs** 2 1 0

Provide product & service

information 2 3 2

Manage a sales lead** 2 1 1

Process the product/service

application** 1 1 1

Deliver the product/service 2 N/A N/A

Onboard customer*** 3 3 3

Check/Update customer

information** 3 3 1

Deliver customer

statements**** 3 N/A 3

Manage customer inquiries

and complaints ** 2 2 1

Retain customer 1 1 0

Pre

-Sa

les

Sa

les

Se

rvic

e

Aft

er

Sa

les

Branch Call Center Digital*

* Digital channel is formed of ATM, Internet, Mobile *** PRG Onboarding Project Outputs in POC

** Interaction is applicable for Internet only within Digital channel

**** Interaction is applicable for ATM & Internet within Digital channel


Transaction analysis showed that some low value\high frequency transactions

are facilitated by all channels, indicating transaction migration opportunities

Branch ATM Call Center Internet Mobile

Silv

er/

Aff

o

rda

ble

Go

ld/

Ba

sic

Pla

tin

um

/

Fu

ll V

alu

e

Dia

mo

nd

/

Exclu

siv

e

Silv

er/

Aff

o

rda

ble

Go

ld/

Ba

sic

Pla

tin

um

/

Fu

ll V

alu

e

Dia

mo

nd

/

Exclu

siv

e

Silv

er/

Aff

o

rda

ble

Go

ld/

Ba

sic

Pla

tin

um

/

Fu

ll V

alu

e

Dia

mo

nd

/

Exclu

siv

e

Silv

er/

Aff

o

rda

ble

Go

ld/

Ba

sic

Pla

tin

um

/

Fu

ll V

alu

e

Dia

mo

nd

/

Exclu

siv

e

Silv

er/

Aff

o

rda

ble

Go

ld/

Ba

sic

Pla

tin

um

/

Fu

ll V

alu

e

Dia

mo

nd

/

Exclu

siv

e

Channels

Segments

Interactions

Transaction occurs in channel

Cash Withdrawals

Balance Enquiry

Transfers Out

Prepaid Airtime

Conduct Enquiries

Other Enquiries

Cash Deposits

Bill Payments (online)

Cheque Deposits

Cheque Withdrawals

*

* Transaction occurred 322 times in 2010

Does not occur


Summary of key observations: call center

There are too many disparate dial-in numbers for customers

IVR has limited call fulfilmentt and customer need analysis capabilities

There is no single view of customer across different inbound & outbound teams due to different front-end

systems

Fulfilment processes are product specific and partially in-house

Product centric organization and different front-end systems result in limited multi-skilling of agents per process

Agent utilization is relatively low

Strict regulations deteriorate end-to-end sales and service processes within call center

X-sell and up-sell approaches via add-on product offerings are not advanced. There is no CRM tools in use

Outbound sales CPA for most of the lending products is high due to pre-sales wastage

There are no inbound retention teams

Voice/Agent interactions are the most common contact type for the Client (75% of all calls)

Sales productivity is significantly low compared to best practices

Most of the important functionalities and workforce management gaps are addressed by various POCs

Annual Call Volume ~ 15 MM

Number of agents ~ 900

Best Practice Example

Garanti Bank/ Turkey

~ 35 M

~ 500

Number of products

Sold per annum 100 M 450 M

the Client

Case Study: Garanti Bank Turkey

Excluding cash transactions, ~2% of all Garanti customer transactions are executed via the call center (Similar to the Client)

Depending on the product, 30-90% of Garanti’s sales are generated through the call center

Call Centre operatives are equipped with web-based desktop systems as well as access to CRM tools


Situation overview

• The goal of the 10-week assessment

was to develop a cohesive contact

center strategy, integrating the 2017

target state with the Client’s strategic

priorities, resulting in an executable

framework.

• The member-centric strategy would

align processes, systems, and

employees to the sales and service

plan.

Situation

• Connect disparate member

experiences (traditionally built to

support individual business needs

resulting in missing functionality)

• Determine how to integrate multiple

contact center projects across the

Client to a single strategy

Objectives


A strategic realignment of the contact center was the

overarching goal of the project

1 single target state Strategic Re-Alignment

• One integrated program, calendar, and budgeting

process will align all initiatives for synchronized

planning and coordination

• Prioritization and resource allocation based on

budgets needs to be part of the overall cohesive

strategy

• Last year individual roadmaps have been

developed and validated across business lines,

but critical risks and dependencies between them

have not been identified. This prevents most

projects from launching.

• Five-year planning with strategic milestones

needs to be codified and institutionalized

• Decision making process may hinder overall

strategy development process with the need to

satisfy every stakeholder by consensus…in a

battle one general is needed but the organization

currently has many

The actual discussion content

turned out to be focused on Contact

Center Tactics (1 year) and

Enterprisewide Strategy

CRM MS

CC

S&S

CM


Project overview

Strategies

Disconnected

Contact Center

Strategy

Connects Ecosystems

Channel

Mktg Analytics

IT 3rd Party

MSR

MX

Product

Resource

Business

Channel

Mktg

Analytics IT

3rd Party

MSR

MX

Product

Resource

Business

Fragmented Ambiguous

Concerted Well

Define

d

Marketing

Strategy

MX

Strategy

Business

Plans

Enabling

Technolog

y

2012 2013 2014 2015 2016 2017

Implications of existings

strategies/plans on CC

CC Benchmarks within

Financial Services Industry

Existing challenges and

improvement opportunities

Cohesive

Contact

Center

Strategy

Today

Tomorrow


Project phases and approach

Review

Understand

Strategies and

Implications

Existing Strategies

Review Report

Conduct Interviews

with Key

Stakeholders

Review Strategies

and Business Plans

Identify Implications

on Contact Center

Analysis

Assess Processes

and Performance

Contact Center

Metrics Analysis

Channel Usage

Analysis

Member Satisfaction

Data Analysis

Member

Demographics

Analysis

Technology

Architecture Analysis

Improvement

Opportunities Report

Strategy

Develop a Cohesive

and Integrated

Strategy

Define Contact

Center Target State

Define Contact

Center Processes

Define Contact

Center Information

Mgmt

Define Contact

Center Technology

Rqmts

Contact Center

Strategy Document

Roadmap

Develop Roadmap to

Execute the Strategy

Identify Initiatives to

Execute Strategy

Prioritization of

Initiatives

Timeline

Contact Center

Roadmap Document

Determine Initiative

Execution Rqmts


A target state was then defined - core processes across operations,

planning, and employee retention required adjustment to fit

Current State Target State

Planning

Employee Retention

and Growth

Member Operations

• Planning based primarily around

servicing and handling peak loads,

not sales related initiatives

• MSR staffing based upon relationship

management or strong sales

focus/lead generation

• Proactively educate and shift

members to self service channels to

unlock capacity for high touch

service and sales opportunities

• Members routed based on MSR skill

type

• Non-tailored treatment

• Segmentation allows member needs

to be serviced based upon factors

such as value, stricter service levels,

and stated and inferred preferences

from similar members

• MSRs trained in the servicing of

products with sales skills provided for

smaller groups

• Leadership development centered

more around interaction skills and

recognizing opportunities with members

• Specific groups trained more in service

with basic sales skills

• Specific groups trained for more

complex sales opportunities

The areas outlined below are key to updating processes in the contact center so

they are aligned with the desired target state

1

2

3


• Key opportunities for improvement at the Client were discovered including

establishment of a clear contact center strategy, refining and applying

segmentation, and measuring project outcomes

• PRG identified methods to decrease cost and improve quality in the contact

center using migration of non-value added transactions to low cost, high

growth channels

• Areas of disconnect between management objectives and current operations

were highlighted using the executive questionnaire, many which had not been

seen or realized by management previously

• Inspired by the strategic dialogue that PRG facilitated, the Client stakeholders

unanimously chose a Segment and Event driven model for the target state

from several options designed by the project team

• The selected model prioritized the application of member segmentation in the

CC and differentiated modules focused on deepening, growing and serving

members

Through this project, the client was able to

accomplish multiple goals


• Client # 1

• Client # 2

• Client # 3

Table of contents


Situation overview

• Decrease AHT for Billing calls via

Speech Analytics

• Identify the inconsistencies among

agents AHT

• Why are Customers calling us and what

are we doing to retain them?

Situation

• Develop queries for identifying

billing calls

• Identify the root cause for

billing inquiries

• Provide recommendations for

improving AHT

Objectives


Developing effective queries

Query Name Billing Sub-Type Used Phrases

Billing - Update

Account Info

1) Update account info Username and password, "credit

card information", "update billing

information"

Billing - Refund 2) Refund/reimbursement

inquiry

refund, "P O box three zero seven",

"credit", remove "credit card" and

"time credit"

Billing - 15 Day 3) Explain 15 day billing fifteen day

Billing - Recurring 4) Explain Recurring Billing thirty day, "recurring billing", remove

"thirty day time credit" and "regular

billing"

Billing - Time Credit 5) Time credit inquiry time credit

na 6) Receipt request na

Billing - Discounts 7) Available discounts promotions

na 8) Inquire about insurance

reimbursement eligibility

na

Creating effective queries within Speech Analytics provides the

bases for identifying the root cause


Bubble chart

• "Update Account Info" is the subtype with the most volume, as well as the lowest

AHT (only one to go below 700s), and 2nd lowest standard deviation.

• In general, sub-types with larger volume have lower AHT.

• "Update Account Info" and "Refund" make up 71% of our total volume.


Descriptive statistics table

Descriptive Statistics

Update

Account

Info

Refund 15 Day Time

Credit Recurring Discounts

Count 1899 1477 386 381 327 256

Mean 692.6 716.1 729.1 821.3 793.7 793.3

Stdev 598.7 593.6 637.3 701.9 697.7 633.3

Range 4838 4554 4366 4350 4830 4373

Minimum 41 33 78 94 49 71

25th Percentile (Q1) 307 330 300 357 322 359.25

50th Percentile (Median) 513 523 506.5 593 576 596

75th Percentile (Q3) 858 894.5 903 1015 1039 964.75

Maximum 4879 4587 4444 4444 4879 4444

%Count 40% 31% 8% 8% 7% 5%

AHT Opportunity

(based on 450 secs) -97.5 -83.2 -22.8 -29.9 -23.8 -18.6

It was agreed that the focus sub-types will be “update account info” &/or “refund” due to sheer volume.

* - AHT Opportunity = %count * (450 – AHT), where 450 is our ideal AHT.


Volume distribution

Almost 20% of billing calls involve subscription sales/activation procedures.


AHT trend comparison

• Comparing "Subscription Sales and Activation" calls versus general

"Billing - Update Account Info" calls…

• Calls that involve subscriptions normally take 1.5x longer to finish.

Exhibiting a 1076 second AHT average in 7 weeks, compared to Account

Update's of 690 seconds


Process map

• Step 1: Agent opening. Customer’s reason for calling. Agent rephrase

• Step 2: Account verification. First and last name, zip code, date of birth

• Step 3: Usually, expectation settings from the agent. Any sort of research. Initial troubleshooting. (duplicate

account, password reset, supervisor consultations, strange account issues, etc.)

• Step 4: Due to one reason or another, perform a subscription sale or subscription activation. (height,

weight, birth date, pregnancy/bulimia nervosa, username, temporary password, security question, credit

card number & expiry date, mailing address, shipping address, terms & conditions, monthly pass ID)

• Step 5: Closing spiel. Sometimes can be awkward due to it’s length. Recap, additional questions,

motivation, survey reminder, agent name, and the thank you

• Step 6: Any follow-up questions that the customer may have after the closing spiel. Varies greatly, from 0

to 565 seconds. Happened only in 4 out of 10 calls

• A process step is VA (value adding) to them if it is part of the main reason why a customer is calling

• Step 4 is non-VA since customers usually don’t expect this step as part of updating their billing info

• Step 5 is non-VA since customers don’t necessarily need all of it (such as the survey reminder)

1) Intro, Reason, Rephrase

Value Adding

2) Verif ication

VA

3) Research & Resolution

VA

4) Subscription Walkthrough

Non-VA

5) Closing

Non-VA

6) Post-closing questions

VA

50 s 38 s 645 s (0:10:45) 699 s (0:11:39) 41 s 111 s


Reasons for the subscription step

• Out of 30 listened calls, "Deactivated account" and "Online not set-up" consist of 77% of the

reasons why regular "update info" calls, evolve into "sales" or "activations" calls

• Deactivated account - Happens usually when a customer forgot or incorrectly updated their billing

information. Causing recurring billing errors, and in turn deactivating their account

• Online not set-up - Are customers that did not have an online account, and did not know that it is

required in updating their billing info


Root causes

“Deactivated account” and “online not set-up” delays

1) Customer did not receive the

warning about their recurring

billing failure (outdated

email/spam) 2) Meeting locations that are not

asking if a customer has a

previous account with us, and

giving user/pass combinations

instead of an activation code

3) For customers that are previous

members, a cancellation,

reactivation needs to be

performed 4) There are times where there is dead-air

during the subscription sales step.

Subscription sales should be a flowing

process of fields to fill-out

5) Wait time in getting activation codes

6) Customer does not know their password

7) Customer does not really care

about online tools, and just

wants meetings

8) Reset password link not working

9) Reset password email not reaching the customer

10) Customer confused as to what

the username and temporary

password is

11) Customer that goes

through sales and

activation in the same call

12) System latency during the sales procedure


Questions

Niren Sirohi

Vice President, Predictive Analytics

iKnowtion

Niren Sirohi [[email protected]]

Jim Dickey

Vice President and Managing Director,

Business Intelligence and Simulation

Peppers and Rogers Group

[email protected]