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Enabling More Intelligent and Profitable Customer Interactions Using Oracle BI Real-Time Decisions (RTD)
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Agenda
• Introduction to Real-Time Decisions (RTD)• Solution Demo• Key Capabilities & Features• Q&A
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Introduction to RTD
Significant Business Challenges
Inefficient Service ProcessesInefficient Service Processes
Lack of Customer KnowledgeLack of Customer Knowledge
Customer AttritionCustomer Attrition
Do Not Call ListDo Not Call List
Inconsistent Delivery ChannelsInconsistent Delivery Channels
Low Share of WalletLow Share of Wallet
Inaccurate Customer SegmentationInaccurate Customer Segmentation
Price-based CompetitionPrice-based Competition
Employee AttritionEmployee Attrition
Marketing Collateral OverloadMarketing Collateral Overload
‘Back to the Basics’
“Customer retention should be your highest priority in your CRM strategy…After you have protected your customer asset through retention efforts, cross-selling is the CRM strategy for growing revenue.”
Kimberly Collins, Ph.D.CRM Summit Spring 2004
Customer Customer RetentionRetention
Revenue Revenue GrowthGrowth
Traditional Outbound Marketing Falls Short
• Privacy restrictions
• Customer opt outs
• Competitive clutter
• Growing resistance to marketing
efforts
• High cost/low response
of outbound marketing
Low responserates
Low ROI
• Offline and data-driven process
• Discrete and often disconnected
marketing efforts
• Offline arbitration of campaign and
channel conflicts
• Product-level analytics
• Resource and time intensive
WarehouseMarts Marts
ETL
EII
Metadata
Data Mining CM
ProductsScores
Web
Offer match
WarehouseMarts Marts
ETL
EII
Metadata
Data Mining BI CM
ProductsScores
Contact Center
Offer match lists
Campaign-Centric Approach for Inbound MarketingLimitations and Constraints
Data Mining BI CM
Interaction-Centric Approach for Inbound MarketingBenefits of Real-Time Recommendations
• Real-time and KPI-driven
• Centralized decision logic and
in-context predictive analytics
• Automated and integrated
decision services
• Leverages existing BI assets
and operational infrastructure
Contact Center Web
Decision Services
MetricsScores OLTP
POS
Real-Time Decision Engine
Data Warehouse
Campaign Management
DataMining
Web ATM Kiosk POSIVR
BusinessIntelligence
Contact Center
TelcoTelco FinsFins RetailRetail HealthHealth TravelTravel OthersOthers
Oracle RTD Provides a Real-Time Decision EngineDelivering Decisions as a Service
GovGov
• Pre-built application for Siebel Call Center • Intelligent offers and retention treatments embedded in Call Center• Data mapping to Financial Services and Communications data model • Shares Siebel Marketing offers and campaigns to coordinate inbound
and outbound• Leverages customer analytics and offline predictive models
Oracle RTD for CRM Intelligent Offer Generation and Retention Management Application
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Solution Demo
Demo Scenario
About National Bank• Fictional financial services provider• Customer base: 5 million• Assets: $69 billion • Revenue: $4.6 billion • Large volume Siebel Call Center
Business Challenges• High customer turnover rate of 14% per year• Associated replacement cost in millions per year• Average cost of new customer acquisition: $250• Currently 2 products per customer, goal of achieving 4 per customer
Demo Use Cases
Profile of caller (Linda Johnson):• Female, 28 years old, single• Holds checking and savings account at
National Bank• Medium-value customer• Calls to change address (due to new job
after grad school)
Business goals • Expand customer relationship through
real-time intelligentcross- and up-sell offers
Profile of Caller (Robert Knowles):• Male, 38 years old, married, homeowner• Holds several accounts at National Bank• High-value customer• Considers closing all accounts (unknown to
National Bank)• Calls to inquire about checking account
fees
Business goals• Retain customer relationship through real-
time retention treatment
Use Case # 1 : Intelligent Cross- and Up-Selling
Use Case # 2 : Proactive Real-Time Retention Management
“Appropriate”10x Success
Leveraging Inboundin Real TimeCustomer Initiated,
Relationship Driven
“Convenient”5x Success
Event DrivenCustomer Triggered
“Unexpected”1-5% Response
CampaignMarketing-initiated
CustomerEnterprise
Advanced real-time predictive analytics allow each interaction at any timeand any channel to be tailored for each customer
RTD Leverages Inbound Interactions
Source: Gareth Herschel, Gartner, ‘03
Call IVR Navigation CC Route
In-House CC Outsource CC Outsource CC
CSR Intro
Resolution? CSR Answer Cross Sell
Handoff Handoff
2nd Tier
Handoff
Yes
No
Agent / QueueRoute
End/Handoff
Skip IVR /Escalate immediately
Route to optimal CC
Route to optimal
queue / agent
Present targetedmarketing offers
List likely answers /resolutions
Escalate based on priority
Intelligent Contact Center Using RTD
Sales
Marketing
Service
RTD Drives Top & Bottom Line Benefits
• Incremental revenues through improved cross andup selling
• Improved long-term profitability through enhanced loyalty and retention
• Reduced acquisition costs through improved customer retention• Reduced outbound marketing spend through more effective
inbound marketing and leverage of insights into actual customer response behavior for outbound
• Reduced operating costs through more intelligent and streamlined business processes
• Improved agent productivity by enabling less experienced and skilled users
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Key Capabilities & Features
Gap Between BI and Operational Apps
OperationalApplications
BI & AnalyticsSolutions
OperationalApplications
Oracle RTD Bridges the Gap
BI & AnalyticsSolutions
Real-Time Decision Solutions
Bridge between operational and
analytical worlds
Operationalizes offline analytic
insight, models and scores
Creates new behavioral & contextual
insights through continuous learning
Unites channel experiences through
singular decision framework
Drives process behavior of both
technology and human resources
Challenge of Business Process OptimizationImproving the Process from the “Outside”
Process ImprovementProcess Improvement
Time Lag to Implement Change
Expensive and Lengthy Projects
Limited Adaptability to Changes
Process IntelligenceProcess Intelligence
Offline Analysis, Historical Data
Aggregated siloed data
Limited by Analyst Bandwidth
Today’s Process
A gap exists between A gap exists between process intelligence and improvementprocess intelligence and improvement
Performance Goal driven Continuous control Detects changes over time Decision service
Continuous learning Transaction level data Operationalize traditional analytics Process-oriented data model
Today’s Process
RTD Decision Server
Process ImprovementProcess Intelligence
Process Optimization via Real-Time DecisionsImproving the Process from the “Inside”
Performance Goals as First Class Citizens
Influence operational business process to optimize multiple competing performance goals, such as:
• Minimize Service Costs
• Maximize Revenue
• Expedite Customer Service
• Minimize Attrition Risks
Ability to arbitrate is a built-in feature of the product andnot implemented externally
Ability to arbitrate is a built-in feature of the product andnot implemented externally
Oracle RTD Decision FrameworkDriven by Domain Knowledge and Empirical data
Predictive Approach: Automation
• Prediction inferred from data vs. explicitly defined• Predictions [automatically] evolve based on
response patterns and changes• Requires a lot of data
RTD provides very granular control over the degree to whichrules and analytics can be used to drive the decision process
RTD provides very granular control over the degree to whichrules and analytics can be used to drive the decision process
• Rule-Driven Decisions
• When decisions are driven by declarative logic expressed by business users
• Model-Driven Decisions
• When decisions are driven by logic learned by models from empirical data
Rules Approach: Control
• Existing knowledge and logic can be leveraged• Convenient when decision needs to be
constrained• Does not scale with volume / interaction
complexity
Self-Learning: A Process Perspective
SourceDatabases
Analytical
Mart
Data MiningTools
Scoresand Lists
OperationalApplications
Traditional Learning Process: models lag by weeks or months
Continuous Self-Learning Process: models are updated in real-time
feedback: days or weeks
OperationalApplications
feedback: immediate
decisions
events
Self-LearningAnalytics
input fromexternal models
and lists
Advantages:
• Automatic model creation
• Quick to react when behavior changes
• Allows broader scope of analysis
• Simple to implement and run
Tracking Multiple Outcomes Over Time
• Predicting a single outcome froma decision does not model real buying processes, which have multiple steps over time
• Learning is limited as decisions are based on very limited criteria
• Decision Server tracks multiple outcomes from each decisionover time
“Free cablefor 30 days”
“Seminar onhome refinancing”
1. Interested
2. Registered
3. Attended
4. Applied forrefinance
1. Interested
2. Installed
3. Kept servicebeyond 30 days
Examples
(now)
(+10 days)
(+30 days)
(+5 mins)
(now)
(+7 days)
(+10 days)
Adapting to Changes in Behavior
• The Problem with Current Solutions:
• Other products treat old response data as if it is as relevant as newer data; this is a huge mistake
• How Businesses Try to Cope:
• Two choices: either run forever with undifferentiated data, or flush all of the data periodically
• No useful way to look at what has happened within and across time periods
• Decision Server Approach:
• Automatically track, weight, and report on response data over time via user-controlled criteria
Enabling True Multi-Channel Solutions
• Channels have varying response characteristics, so models that naively “pool” channel data are less effective
• Businesses should not build separate analytic solution “silos” for each channel
Choices, Rules,Models, Learnings
CC Decision App (silo)
Choices, Rules,Models, Learnings
Web Decision App (silo)
ContactCenter
Web
Other Products
Choices,Rules,Models,Learnings
Multi-Channel Decision App
Shared Set of: ContactCenter
Web
Decision Server
• Decision Server provides partitioned learning models, such that a single application can support true multi-channel decisions
Real-time Decision Process
EligibilityEngine
Prediction /Scoring Engine
Decision Server1. Send customer id
5. Determine eligible offers
6. Score eligible offers
7. Return ranked offers
LearningEngine
8. Send response9. Learn from response
3. Send context info2. Create session & load customer data
4. Request offers
CustomerInteraction
Touch Points
RTD Platform and Integration Points
Portals,PDAs, …
Publishers
CRMSystem
ContactData
Transaction Data
ContactData
Suppliers
AdvisorsInformants
Enterprise AppsSFA, CRM, Web Portals, …
DecisionServer
Profile Manager
Learning Engines
Decision Engines
Goal ManagerBusiness& IT UserInterface
Inline Inline ServiceService
• Informants & Advisors• Handle information events
and requests for decisions from enterprise applications
• Publishers• Deliver KPIs, alerts,
learnings, and other information to portals & external apps
• Suppliers• Deliver profile data on
demand
• User Interfaces• Analyze data, create offers,
configure system
Open and Flexible Integration Support
Oracle BIEE
Server
3rd PartyModel
Executable
ACD / IVR
XML / SOAP
.NET
HTTP
JDBCDecision Server
onJ2EE
Back-EndDatabase
Back-EndDatabase
Back-EndSystem
WebApp
Call Center App
Teller / ATMApp
Info
rma
ntA
dv
iso
r
JavaSmart Client
JSP Tags
Java / JNI
Data Mart / Warehouse
Data Mart / Warehouse
JDBCXML / SOAPJava
New Real-time Decision Paradigm
Producing scores to Managing goals
Refreshing models to Adjusting to changes
Response management to “Closed Loop” mgmt
Single channel to Multi channel analytics
“Out of context” to “In context” analytics
Resource intensive to Automated process
Replacing systems to Integrating systems
Helps companies shift their attention from …
Key Features of Oracle RTD
General Purpose Real-Time Decision Platform and Framework
Granular control over mix of rules and analytics, including built-in
self-learning predictive models, to provide decision services
Enterprise Alignment / Multiple KPI Prioritization
Every decision is measured against and arbitrated upon multiple
competing performance goals
Event-driven / SOA architecture
Decisions are provided as a service in real-time in the context
of an interaction workflow / operational process
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Questions & Answers