CRM Predictive Analytics: From Buzzwords to Business Value

CRM Predictive Analytics: From Buzzwords to Business Value

Liz RocheVice President & Director

CRM Infusion Program

liz.roche@metagroup.com

SUGI 29 Analytics

2© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Customer Marketing Backlash Reaching Epic Proportions? Technology, legislation and

societal norms all indicate greater marketing sensitivity

? Pressure on outbound marketing to transform from intrusive and privacy-insensitive to targeted at the needs of a particular individual or segment

? Predictive analytics – what are they?

Disenfranchised customers impact brand equity; apply EMM as part of a CRM strategy to enable better, not more, marketing

Business Scenario

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3© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Many CRM Systems Are “Live” —Few Are Raging Successes

? CRM ROI based on applying the “right” CRM treatment to the appropriate customer segment

? Marketing is part of CRM? Delivering on these returns

requires?creation of value-based

customer segments?application of predictive

models in real-time to optimize segments, offers, campaigns

Technology Scenario

Predictive analytics moves into the mainstream in support of CRM marketing initiatives

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4© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Critical Issues

?Understanding the CRM business system—& where analytics (predictive or otherwise) fit

?Applying predictive model-based analytics to look for patterns

?Executing campaigns and real time decision making

“Graphic Optional”This is a sample for general purposes

“A Journey of a thousand miles begins with a single step.” — Ancient Chinese Proverb

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5© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Understanding the CRM Business System

? Understanding the CRM end-game

? Pinpointing where analytics (predictive or otherwise) fit

? Exploring marketing’s role in “post-modern” CRM

The CRM End Game: CustomerLifecycle Management

Engage

Service

Customer Life Cycle

Fulfill

TransactCust.Pattern

Channels & “POIs”

Sales

“Offer”

Customer-RelatedBusiness Processes

Mktg. Service

CRM Technology“Ecosystem”

Collaborative Analytical

Operational

CRM is not an IT project — it is an iterative and continual transformation of people, process, and technology

Issue 1

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6© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Issue 1

CRM analytics are an integral part of the technology environment

Source: META Group, December 2003

Cus

tom

erIn

tera

ctio

nFr

ont

Off

ice

Bac

k O

ffic

eM

obile

O

ffic

e

Resp. Mgmt.Resp. Mgmt.Web ConfWeb Conf

E-MailConferencingVoiceVoice(IVR, ACD)(IVR, ACD)

WebWebStorefrontStorefront

Collaborative CRM

DirectDirectInteractionInteraction

1 4 1 4 1 44 41 41

ERP

SalesAutomation

ServiceAutomation

LegacySystems

MarketingAutomation

Mobile Sales(prod cfg)

FieldService

Operational CRM

Supply Chain Mgmt.

2 3

4

2 3

1 1

4 4

32

Order Mgmt.

Order Prom.

CampaignMgmt.

CustomerActivity

Data Mart

CustomerData Mart

ProductData Mart

DataWarehouse

Analytical CRM

CategoryMgmt.

1-4

1Vertical

AppsMarketing

Automation

Clo

sed-

Loop

Pro

cess

ing

(EA

I Too

lkits

, Em

bedd

ed/M

obile

Age

nts)

Pinpointing Where Analytics Fit in the CRM Technology Ecosystem

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7© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Cultivating the CRM Analytics Tree of Knowledge? Derived knowledge

? Analytic models and business rules are applied to information

? Feeds business processes to maximize business performance

? Captured information? Represents activities and

outcomes of points of interaction

? Chewing on bark?? External data

? Rounds out customer information

? Adds flavor & richness to the customer soup

Blend POI information with external data to yield consumable/actionable knowledge

PROFILEPROFILESEGMENTSEGMENT

SCORESCORE

PREDICTPREDICT

ENGAGE

TRANSACT

FULFILL

SERVICE

ENGAGE

TRANSACT

FULFILL

SERVICE

POSTAL “X”-OGRAPHICS

ASSOCIATE INDUSTRY

Actio

nab

le ?A

ctual ?

Ad

ditive

Issue 1

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8© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Customer life-cycle intersection analytics is not just for marketing — it is integral to process performance

EngageEngage

TransactTransact

FulfillFulfill

ServiceService EngageEngage

TransactTransact

FulfillFulfill

ServiceService

Sales

Point-of-Intersection Analytic Objectives

Marketing Service

Campaign Effectiveness

Visitor Experience

Predictive ModelingBacklog Reduction

Consumption Maximization

Production Imprvmt.

Churn ReductionComplementary

Offering Awareness

Pipeline ImprovementQualification

Interaction Performance

Cost of Sales

A/R ClosureDistribution

Effectiveness

Usage ImprovementCustomer Profiling

Support PlanningReputation Imprvmt.

Support Plan Implementation

Delivery Performance

Fulfillment Perf.Response Perf.

Satisfaction Improvement

Customer Flagging

Leveraging Analytics at Customer Life-Cycle Intersections

Issue 1

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9© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Information Velocity Mitosis

Integrating Analytic Solutions

? Balanced-scorecard analytics focus on strategic “macroanalytic” decision cycles

? Realtime recommendation analytics focus on tactical “microanalytic” decision cycles

? Be cautious of vendor solutions that promote disconnected analytical architecturesBalance information velocity against decision

cycles — unite decoupled analytic architectures

Quarterly

Monthly

Weekly

Daily

Hourly

Continuously

1999 2000 2003 2005

Tactical Microanalytics

Strategic Macroanalytics

DecisionDisconnect

ODS

DW

Issue 1

SUGI 29 Analytics

10© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

EE TT FF SS

Customer Pattern “Time Over Money”

DirectMail

EE TT FF SSFinancialAdvisor

Given outbound constraints, every interaction must be considered a marketing opportunity

? Sales: Order taking? Marketing: Bundle promo? Service: Order confirms

? Sales: Sat. monitoring? Marketing: Promotions? Service: Order satisfaction

? Sales: Account management? Marketing: Cross-sell/up-sell? Service: Issue resolution

? Sales: Lead management? Marketing: Campaigns? Service: Cross-sell/up-sell

EE TT FF SS CustomerInteraction

Center

Applying Predictive Model-based Analytics for Customer Pattern Discovery

Tra

nsa

ctFu

lfil

lS

erv

ice

En

gag

e

EE TT FF SS ElectronicBilling &Confirms

Issue 2

SUGI 29 Analytics

11© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Segmentation is About Clustering Customers And Developing Treatments

? Begin to identify distinct patterns of buying behavior – beyond simple demographics

? Group customers based on common buying patterns, preferences, value, etc.

? Focus on most profitable customer segments

Tracking Customer Behavior

Recognize exit barriers will be different for different types of customers

Issue 2

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12© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

The CRM Formula: Customer Patterns

? Customer Pattern = Segment + Treatment? Segment

?Segment = explicit + inferred information about customers (e.g., grouping similar characteristics)

?Input comes from demographics, psychographics, and other things needed to group by common characteristics

? Treatment?A treatment is the path through ETFS that an

organization chooses to enable for its customers

?Input comes from a customer’s ETFS preference, technology affinity, and lifetime value and scorecard metrics

Issue 2

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13© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Understanding Data Needs for Predictive Analytics

Profile

PrivacyPrivacyPoliciesPolicies

Adapt & Realign

Segmentation Data

Demographic Data

Psychographic Data

Transaction Data

Categorize

Reporting Apps

E-Commerce Apps

Marketing Apps

Service Apps

“Targeted” Content

Aggregate &Preprocess

Store

“Webhouse”

Warehouse

Line-of-Business Data, Customer Interaction Center Data, Third-Party Data Providers

Well-managed profile data adds to customer intelligence; mismanagement leads to alienation

Model

Analyze

Collect

On-Site Data

Off-Site Data

E-Mail Data

CIC Data

Issue 2

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14© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Stratifying Customer Behavior Modeling

Future Profit

Fu

ture

Lo

yalt

y

HighLow

Hig

hLo

w

Let Go ActivelyRetain

KeepUpgrade

Customer Retention ModelCustomer Acquisition & Growth ModelCompetitorCompany

Low

High

RO

CR

Based on Past Based on Future

Enterprise CRM applications that do not continuously stratify customer behavior are dead-

end streets

Issue 2

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15© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Executing Campaigns and Real Time Decision Making

?Defining realtime?Defining the Enterprise Marketing

Management (EMM) technology portfolio

?Handicapping the vendor landscape

Issue 3

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16© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Defining Real-Time

Enterprises should define real-time relative to business event integrity, not absolute time

Contextual Arbitrary

REACTTRANSACTINTERACT

Business Process Cycle Clock

Real-time a relative degree of latency that ensures the delivery or availability of fresh data representing a current business state

Near Real-Time a degree of latency that ensures data delivery/availability of data “fresh enough” (or “current within an established degree of certainty”) for the individual or process using it.

Real-time a relative degree of latency that ensures the delivery or availability of fresh data representing a current business state

Near Real-Time a degree of latency that ensures data delivery/availability of data “fresh enough” (or “current within an established degree of certainty”) for the individual or process using it.

Issue 3

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17© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Creating the Enterprise Marketing Management Technology Portfolio

? If customer interaction is not exploited in “right-time,” the opportunity likely lost?“Right-time” does not

necessarily equal “Real-time”

?Dynamism is key?EMM technology portfolio

ensures right approach? EMM processes are

involved in planning, executing, monitoring, and managing an organization’s marketing efforts

Issue 3

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18© 2003 META Group, Inc., Stamford, CT-USA, +1 (203) 973-6700, metagroup.com

Defining Enterprise Marketing Portfolio Management (EMM)

? EMM is a component of the CRM technology ecosystem, with a footprint in operational, analytical, and collaborative CRM.

? Campaign Mgmt -- right offer to be made to the right customer at the right time

? Operations Mgmt –automates workflow, resources, analytics of marketing department

? Lead Mgmt - qualifying leads; converting to opportunities

Issue 2

Lead Management

CampaignManagement

Operations Management

People

Tech

no

log

y

Process

Cu

stom

er C

en

tricity

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