© 2015 IBM Corporation
Predictive Customer Intelligence
Sogeti 2015
Damiaan Zwietering
© 2015 IBM Corporation2
Trade with meSharing data, location, and new ideas in return for better products and value
Educate meBringing expertise to every customer interaction
Let me chooseOptions vs. prerequisites, roadmaps vs. checkboxes
Grow with meData and insight connecting the lives of customers, households
Find meUsing visualization and analytics to discover new customer segments
Ask meConsulting customers on products, services, and social issues
Know meOffer new products and services based on understanding my wants, needs
Excite meUnexpected services at unexpected moments
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Customer expectations are driving companies towards being customer centric
© 2015 IBM Corporation33
Organizational capabilities have been a hindrance to customer centricity
Inability to gather and synthesize insights to customer behavior, needs and preferences from analysis of multiple data sources
Difficult to deliver omni-channel customer analytics solution able to analyze, score and determine most appropriate action with individual customer
Only historical view of customer, resulting in inappropriate or incomplete offers or communications at the time of interaction
Challenged in using analytics to add short-term value or enhance long-term strategy
Lack of channel integration and siloed lines of business, causing inconsistent or tactical customer interactions
Inconsistent service delivery and weak customer relationships, resulting in low retention
Focus on uncoordinated marketing offers - one-hit selling, as opposed to lifetime value
© 2015 IBM Corporation4
Chat
Voice
Social media
Interactive voice response
Mobile
Short Message Service
Web
Acquisition models
Campaign response models
Churn models
Customer lifetime value
Price sensitivity
Product affinity models
Segmentation models
Sentiment models
Up-sell / Cross-sell models
Campaigns
Offers
Messaging
Lead management
Cross channel campaign management
Real time marketing
Marketing event detection
Digital marketing
Customer services
The optimized customer insight and engagement process
Data Predictive customer insightReal time or historical
Enterprise marketing
Multi-channel customer interactions
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Organizations can Acquire, Grow and Retain customers by harnessing all customer data to improve customer interactions and relationships
ACQUISITION
RETENTION
PERSONALIZATION
GROWTH
5
© 2015 IBM Corporation66
Predictive Customer Intelligence key capabilities
ANALYZE data to gain critical insights
DEPLOY to real-time channels for point-of-impact action
ACCELERATE time to value with focused solutions
© 2015 IBM Corporation7
Many, many rich modeling techniques
Social Network Analysis
DemographicSegmentation
Churn Modeling, Next Best Offer
Real-time Decision
Management
Campaign Management
Customer Value Calculation
Loyalty Segmentation
© 2015 IBM Corporation8
① An activity occurs that calls for a decision.
② The context from the activity is passed to the decision process.
③ The decision process augments the context with stored information and runs the decision model.
④ One or more actions are recommended to the activity.
⑤ The activity feeds back the results to help tune the model over time.
Real-time decision loop allows predictive models to get even smarter
Context
Action
Decision
Activity
Feedback
Information
Facts,recent events,
options
Decision input, actions and outcomes
3
5
3
2
14
© 2015 IBM Corporation9
Built-in Connectors provide enhanced functionalities
InfoSphere Streams Quickly ingest, analyze and correlate large data sets from real-time sources and interact with individual customers at scale.
IBM Interact Allow the power of the deep algorithms to be introduced at the moment of impact, including the inclusion of contextual data
IBM Customer Intelligence Optimizer, Lifetime Value Maximizer
Optimize customer-specific actions/ offers to maximize long term customer value by moving customers to a “higher value state”
IBM BigInsights (and other Hadoop Distribution)
Pull together large volumes of all different types of data including social/unstructured information and structured data like transaction details for enhanced discovery
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Industry accelerators
© 2015 IBM Corporation11
Online quote
(Adapted)
Terms & Conditions fine print
Advice from Agent
Policy paperwork
FirstPayment
AmendPolicy
First Claim
ComplaintResponse
Cross-sellCampaignBilling
dept.
Second payment
Marketing
Comparison website
Product development
Intermediary
Underwriting
Finance
Policy admin
Claims management
Marketing
Customer Service
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Customer Track(Nature of
Interactions)
AcquisitionChannel
Quality of ClaimExperience
Quality of Service Experience
Renewal Rate
Low
Very High
High
Medium
Percentage of customers Renewal rate
Phone
55% 72%
Claim only
6% 81%
Claim & Service
6% 72%
Service only
34% 66%
No Contact
54% 72%
PositiveExperience
32% 82%
NeutralExperience
55% 75%
NegativeExperience
13% 60%
Aggregator
50%23%
Web
22% 55%
PositiveExperience
NeutralExperience
NegativeExperience
PositiveExperience
NeutralExperience
NegativeExperience
PositiveExperience
NeutralExperience
NegativeExperience
© 2015 IBM Corporation13
Recommended Action:Service Offer
“Get ready for summer with a free airco check”
Recommended Action:Targeted Retention Offer
“10% discount with 2 year fixed price guarantee and lower deductible”
Recommended Action:Targeted Retention Offer
“10% discount and lower deductible”
Recommended Action:Targeted Retention Offer
“10% discount with 2 year fixed price guarantee”
Likelihood of Cancellation
Loss Ratio Prediction
The retention offer decision depends on the combination of
these three factors:Future Lifetime Value
© 2015 IBM Corporation14
Predictive Customer Intelligence Architecture Overview
PureData for Analytics
Deep customer analytics
Actionable customer data
Big InsightsExplore new
customer insights from all data
MDMTrusted
customer data
Predictive Modeling
and Optimization
Reporting
Real-time Scoring
Data Repository for
Real Time Analytics
WA
S / IB
M In
tegra
tion
Bu
s
Uns
tru
ctur
ed •
S
truc
ture
d
Data Sources Points of Interaction
Direct Mail
Chat
Call Center
Mobile Apps
Web
Social
Chat
Call Center
Mobile Apps
Web
TransactionalData
Model Repository(Industry-specific)
SegmentationModel
Sentiment Analysis
Churn Model
Up-sell / Cross-sell Model
AcquisitionModel
Campaign Response
Model
Lifetime Value MaximizerModel (GBS)
IBM Predictive Customer Intelligence
Inbou
nd In
teraction
sO
utbound
Inte ractions
GBS Lifetime Value MaximizerCustomer Lifetime Value & Segment
Migration
3rd pa
rty m
arke
ting
applica
tion
Cam
paig
n • I n
terac
t M
arketing exec utio
n &
recomm
enda
ti on eng
ine
External data- social, blog
CustomerDemographic Data
CustomerInteraction History
SMS
SMS
SMS
© 2015 IBM Corporation15
Behavior-Based Customer Insight Solution for Insurance
Integration into Marketing & Distribution Dashboards
Behavior-based Segmentation Analysis
• Generates advanced segmentation and individual insight based on behavior
• Identifies key target customers to retain
• Proactively identify "at-risk" customers early
• Enables channels to act
Behavior-based
Segmentation Segmentation Analysis drill-
down
Retention Monitor
Retention Reports
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The IBM difference
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