CRM Overview

CRM Overview Kevin M. Messer, Accenture Senior Manager

University of Dayton 2 November 2001

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Accenture Facts Accenture is an $11.4 billion global management and technology consulting organization working to bring innovation and to improve the way the world works and lives.

 Over $11.4 Billion in Revenue, an increase of 17% in revenue from 2000

  10% Reinvestment in Training   110 Offices in 46 Countries  Over 75,000 Professionals  Serve over 75% of Fortune 100 companies   Industry Expertise:

 Communications & High Tech, Financial Services,

 Products, Resources, Government

Growth in Professionals

Growth in Revenues

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“I know half the money I spend on advertising is wasted…

I just don’t know which half.”

– John Wanamaker Retail and Advertising Innovator

Pioneer of the Modern Day Department Store (1810-1891)

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Capability Investments

Financial Performance Product

Development

Marketing Planning

Sales Force

Customer Service

Human Performance

Alliances

Customer Knowledge Advertising

Channel Strategy

Limited Resources Force Executives to Choose

Where to Invest

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The Challenges for Our Clients

"   Consumers are becoming inherently less loyal

"   Use many new sources of information to build impressions and make decisions

"   Expectations for consistent treatment are rising

"   Much greater intolerance for failing to get the basics right

"   Over 3,000 one-way messages besiege the average consumer every day!

"   Data and analytical capabilities "   More data, more ways to

analyze "   Potential for closed loop,

real-time, and segment of one

"   Limited impact to date on driving effectiveness of $400B spend

"   Misapplication of technology "   Consumers bombarded by

high-tech, often at expense of high touch interaction

Consumer Behavior is Changing Technology Role is Evolving

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Customer Acquisition and Retention Costs

Source: BAI Global, Inc., U.S. Census Bureau

Banking: Acquisition Costs are Increasing Percent Response to Credit Card Direct Mail Offers

Source: Accenture research based cross-industry sources.

Per Subscriber Economics

Telco: Time to Break Even is Lengthening

1998 6.8

1999 6.7

2000 6.6

2001 6.8

2002 6.9

2003 7.2

Dol

lars

per

Cus

tom

er

Six-Month Revenues

Acquisition Costs

1.2%

-2.3%

Months to Breakeven

0

150

200

250

300

350

400

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Customer Relationship Management (CRM)

•  Who are your best customers?

•  How do you serve them?

•  How do you measure success?

•  How do you prioritize investments?

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CRM according to Accenture

CRM is about acquiring, developing and retaining satisfied, loyal customers; achieving profitable growth; and, creating economic value in the client’s brand.

"   At the heart of CRM is the objective to deliver a consistently differentiated, and personalized, customer experience, regardless of the interaction channel chosen by the customer.

"   CRM brings together a company's efforts in marketing, sales, and service that would traditionally have been pursued in separate, ad hoc ways.

"   It constitutes a more comprehensive, methodical approach to identifying, attracting, and retaining the most valuable customers.

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Which CRM Investment?

Implication: Could be expensive and resource intensive to support multiple channels.

32%

48%

17%

3% *Percent of CIOs who ranked channel as most important (Source: Siebel/FCW Survey of Public Sector CIOs, Fall 1999)

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Accenture’s Customer Capabilities Research

•  First study to: – Quantify the impact of

CRM on financial performance

–  Identify the capabilities that have the greatest financial impact*

* As measured by Return on Sales (ROS) which is defined as Earnings Before Interest, Taxes, Depreciation and Amortization, divided by Sales.

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•  430 Questions: •  Marketing •  Sales •  Service •  Technology

• Quantitative Analysis: •  Correlation •  Derived importance

(multiple regression) • Qualitative Analysis:

•  In-depth interviews with 50 senior executives

•  537 Surveys

•  264 Companies

• North America

• Communications

• Chemicals

• Pharmaceuticals

• Retail

• Electronics/High Tech

•  Forest Products

• Cross-Industry View of All 6

Research Overview Survey Scope/

Methodology Survey

Response Industry Segments

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Key Findings

•  Many CRM investments lack focus or metrics •  When focused, CRM has a major impact on financial

performance, yielding large returns •  21 capabilities drive the most value •  Almost 1/3 of the total impact stems from people

capabilities •  Customer insight is a valuable asset and key

differentiator •  Technology plays a critical role, directly driving 40% of

total impact •  Having a good strategy is important, but the key is in

execution

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Brand Management

Motivating and Rewarding People Customer Service

Turning Customer Info into Insight Attracting and Retaining People

Building Selling and Service Skills Strong Value Propositions

Partner and Alliance Management eCRM

Sales Planning Key Account Management

Advertising Customer Retention and Acquisition

Managing Product and Service Mix Promotion

Ability to Change the Organization Measuring Profitability

New Products and Services

Segmentation Building Service Culture

Channel Management

1.5

13.0 13.0

12.0 10.0

9.5 9.0 9.0

8.0 7.5

6.0 5.5 5.5

5.0 5.0 5.0

4.5 3.5

2.5 2.0

3.0

Impact of moving from average to high

performance ($M for a $1B company.,

USD)

21 Profitable Capabilities

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$40-50

$120-150

By improving all 21 CRM capabilities, companies can yield significant pre-tax profits:

Average to High Performance

(30% Improvement)

10% Improvement

($US millions for a $1 billion company)

Skill Improvement Yields Large Returns

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Top Five CRM Capabilities Across

Industries

$9.5

$10

$12

$13

$13

$0 $2 $4 $6 $8 $10 $12 $14

Building Selling/Service Skills

Attracting/Retaining People

Turning Customer Information into Insight

Customer Service

Incenting/Rewarding People

$ Millions

16 Brand Management











Channel Management

1.5

13.0 13.0

12.0 10.0

9.5 9.0 9.0

8.0 7.5

6.0 5.5 5.5

5.0 5.0 5.0

4.5 3.5

2.5 2.0

3.0


performance ($M for a $1B co., USD)

= people impact

People Capabilities Provide Almost 1/3rd of Impact

17 Brand Management











Channel Management

1.5

13.0 13.0

12.0 10.0

9.5 9.0 9.0

8.0 7.5

6.0 5.5 5.5

5.0 5.0 5.0

4.5 3.5

2.5 2.0

3.0


performance ($M for a $1B co., USD)

= technology impact

Technology Drives 40% of Impact

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Technology-related Skills Lead in Impact on

Profitability

Several of the highest-potential skills in each of the industries also depend on powerful systems and high-quality data:

–  Communications: Pricing and billing-related skills –  Chemicals: Technology-enabled customer contact –  High tech: Proactively identifying problems and

communicating resolution options –  Pharmaceuticals: Measuring and analyzing customer

acquisition, retention and switching costs –  Retail: Managing details of product and customer

profitability –  Forest Products: Influencing industry price levels

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Physical Interaction: •  Walk-in/Face-to-Face •  Mail •  Paper-based

Branches/Offices &

Field Sales/Service

Telephone-Centric: •  Telephone, Fax •  Mainly real-time

human-to-human •  Self-Service capable (IVR) •  Voice Messaging •  Call-specific reporting

Call Centers

Multiple Interaction: •  Multiple channels

Web, Voice (Phone, IVR), email, Fax, TV, MMP, PDA, WAP…

•  Not necessarily real-time •  Self-Service focused •  Speech recognition •  Business-based reporting

Contact Centers

Vision: Evolving Interaction

Models

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CRM Technologies for Customer Insight:

Data Mining

“Data Mining is the

process of applying

sophisticated analytical

and computational

techniques to discover

exploitable patterns in

complex data”

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Sources of Customer Data

•  Pervasive collection of electronic data – Credit Cards, ATMs, Debit – Phone Records, Check Scans

•  Exchange of electronic data –  Insurance, medical diagnosis, employment

verification, tax collections •  Archived electronic records

– Credit History, Criminal Records, Property Transactions, Licenses & Permits

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The Data Challenge

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Data Warehouses consolidate vast amounts

of data

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Customer Segmentation and Profiling

Who are our customers?

Most Common

Least Loyal

Most Loyal

Least Profitable Most

Profitable

Biggest Spenders Smallest

Spenders

Typical Questions Answered

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What are their interests and values?

Attitudinal Analysis


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Where are our

customers?


Geographic Mapping


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Most Common

Least Profitable

Basket Analysis

What are the typical purchase affinities?


Most Profitable

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Who Buys What?


Basket Analysis


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What is the impact of

promotions?


Promotions Analysis

Basket Analysis


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Who is most likely

to respond to a marketing campaign?



Predictive Modeling

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Who is most likely to spend

most?



Predictive Modeling

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Who is most likely to defect?



Predictive Modeling

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Predictive Modeling

Descriptive Modeling

Who/where are our

customers and what do they need ?

What’s the most profitable way of communicating

with each individual ?

Two Main Types of Data Mining

Unsupervised Learning Supervised Learning

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Functions and Benefits •  Segmentation — Identifies groups of customers with statistically

similar behavior –  demographic –  psychodemographic –  behavioral –  attitudinal

•  Profiling — Provides an understanding of the size and characteristic profiles of major customer groups

•  Classification — Identifies the likely profiles of new customers –  Affinity and sensitivity analysis –  Finds patterns of behavior –  Identifies “unusual” individuals –  e.g., fraud identification

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Technical approaches

•  K-Means clustering •  Unsupervised learning neural networks

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Age

Inco

me

K-means Clustering

•  Identifies groups of customers with similar characteristics

–  Decide the maximum number of clusters, K

–  Randomly assign cluster ‘seeds’ across n-dimensional space (n = no of variables)

–  For each customer, compute the Euclidean distance between the customer data point and each cluster mean

–  Assign each customer to the nearest cluster

–  Move each cluster center to the mean of the current cluster grouping.

–  Repeat the process until convergence.

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Age

Inco

me

Unsupervised Learning Neural Networks

•  Similar to K-means clustering, but will find “important” specialist groupings

•  Not as statistically rigorous as K-means clustering, but superior for pure “discovery” work

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Descriptive Modeling Case Study

Behavioral Segmentation and Micromarketing Strategy Development

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Business Context

•  High street retailer •  Launch of card-based loyalty scheme •  Large quantity of data

–  card registrations •  demographics •  interests

–  transactions •  Requirement for customer insight to drive

micro-marketing strategy

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Male

Female

Children

No Children

Gender

Children

Age Profile

Boy Racers Declared Interests

Sport, cars, motorsport, computers, travel, films, music

Magazines Read

Very infrequently

Purchase Preferences

Videos and CDs, plus books, cards, stationery

Basket Size Small

Basket Value Good

Visit Frequency

Low

Total Spend Average

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Mature Browsers

Male

Female

Children

No Children

Gender

Children

Age Profile

Declared Interests

Gardening, food and wine, reading, travel, films, music

Magazines Read

Occasional reader of popular titles


Books, cards, stationery

Basket Size Average

Basket Value Low

Visit Frequency

Low

Total Spend Low

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Bookworms

Male

Female

Children

No Children

Gender

Children

Age Profile

Declared Interests

Reading

Magazines Read

Frequent readers of a wide selection


Books, + cards, artist materials and stationery

Basket Size Good

Basket Value High

Visit Frequency

Very Good

Total Spend Excellent

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Couch Potatoes

Male

Female

Children

No Children

Gender

Children

Age Profile

Declared Interests

None

Magazines Read

Very infrequently


Books, children’s books and cards

Basket Size Average

Basket Value Average

Visit Frequency

Low

Total Spend Low

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Young Spenders

Male

Female

Children

No Children

Gender

Children

Age Profile

Declared Interests

Films and music, plus reading

Magazines Read

Very infrequently


Videos, CDs, books and cards

Basket Size Small

Basket Value Low

Visit Frequency

Low

Total Spend Poor

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Examples in Government

•  Citizen service efficiencies –  License renewals – Tax assessment and collection – Child-support enforcement

•  Law enforcement & civil defense – Potential terrorist threats – Surveillance and Tracking

•  Fraud detection •  Supplier management

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Questions

?

Documents

CRM Overview