M2012094379 oct23 stevenson_ibm_iod_business_leadership_v07_d2

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COPYRIGHT © 2012 ALCATEL-LUCENT. ALL RIGHTS RESERVED.

CUSTOMER INSIGHTS IMPROVE BUSINESS PERFORMANCE
ANALYTICS KEY NEW TREND FOR TELCOS
David Stevenson, VP/GM Customer Experience Solutions
October 23, 2012


BIG DATA
PREDICTING THE FUTURE
• UK: one in five large UK businesses
assigning financial value to their
data on the company balance sheet
• NYPD: Uses Big Data to identify
crime “hot spots”
• Wal-Mart: Uses Big Data to fine-
tune merchandising store by store
• Service Providers: Starting to use
Big Data to improve Customer
Experience and Loyalty

Big Data Opportunity Heat Map by Industry

Source: Gartner, July 2012

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CUSTOMER EXPERIENCE RELATED
TO ENTIRE JOURNEY
THE CUSTOMER 1 2 3 4 5 6 7 8
Awareness Interact Agree/Get Consume Use/Support Pay Reward Leave
JOURNEY
1 2 3 4 5 6 7 8
SERVICE PROVIDER Market Fulfill Manage Service Charge Retain
Acquire Retire
JOURNEY Sell Order Customer Assurance Bill Optimize

YOU DON’T NEED HUNDREDS OF KPIs –
ONLY THE RIGHT KQIs TO MEASURE AND KBOs
IMPROVE CUSTOMER SATISFACTION Key business
objectives
e.g. increased
profitability
KBIs
DASHBOARDS Key business indicators
SELECTION OF KEY CUSTOMER AND e.g. average revenue
SERVICES IMPACTING KBOs per user (ARPU)
REPORTING
KQIs CUSTOMER
Key quality indicators
MAPPING STRUCTURE FOR EXPERIENCE
e.g. end-user satisfaction
CATEGORIES OF INDICATORS with video service quality
KPIs
Key performance indicators OPERATIONAL
MAPPING STRUCTURE FOR KQI
TO KPI RELATIONSHIP e.g. video packet loss EXCELLENCE

NETWORK LAYER

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IDENTIFY THE KEY KBO’S AND KQI’S ACROSS
ENTIRE CUSTOMER JOURNEYS
THE CUSTOMER JOURNEY SERVICE PROVIDER JOURNEY
1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8
Market Fulfill Manage Service Charge Retain
Awareness Interact Agree/Get Consume Use/Support Pay Reward Leave Acquire Retire
Sell Order Customer Assurance Bill Optimize

KBOs

Quality Care
Care Perception
Perception Ease
Value Value
& Ease

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TOP 10 WIRELESS NETWORK PROBLEMS AFFECTING
CUSTOMER EXPERIENCE
WHILE CALLING, MESSAGING AND USING DATA IN THE US
1 Dropped calls Still Picture or Evolving Landscape?
2 Calls not connected • Excessively slow mobile Web loading
3 Audio issues - 15 PP100 for 4G LTE-enabled devices
4 Failed/late voicemails - 22 PP100 for WiMAX devices
5 Lost calls - 23 PP100 for HSPA+ devices
6 Text transmission - vs. 20 PP100 industry average
failures
• Mobile hotspot adoption rate 35% higher for LTE
7 Late text message
notifications • LTE: best network performance (reliability,
spectrum efficiencies, increased data
8 Web connection errors connection speeds, etc.)
9
e-mail connection errors
10 Slow downloads PP100 = problems per 100 network connections

Source: J.D. Power and Associates, Aug. 2012

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IMPORTANCE OF THE
CEM-RELATED METRICS
Customer satisfaction 56 27 84

Network availability data 43 39 83

Service availability data 42 39 81
Time/cost to resolve
customer issue
38 43 80

First call resolution/CRR 37 42 79

Customer behavior data 44 34 78

Service usage data 48 27 75

Average call handle time 30 39 69

Time/cost to provision 26 43 68

Time to launch new service 27 39 67

0 10 20 30 40 50 60 70 80 90

Source: Heavy Reading, Sept. 2012

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MOVING FROM A FRAGMENTED VIEW TO AN
INTEGRATED CUSTOMER EXPERIENCE
OPTIMIZED CUSTOMER
EXPERIENCE THROUGH To integration
ANALYTICS AND ACTIONS

Optimization

Analysis &
Forecasting

Monitoring

From fragmentation

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CRITICAL FUNCTIONS FOR CUSTOMER
EXPERIENCE-DRIVEN DIFFERENTIATION
Support for big data 40 30 70

B/OSS integration 40 30 70
Individual service quality metrics for
customer care
36 34 70
Dashboard with tailored views for
different stakeholders
38 30 68

Service quality metrics for individual customers 40 25 65

Unified view of the customer 40 25 65
Per-subscriber, per service of network
performance
38 25 63
Library of ready-to-go customer experience
27 35 62
indicators
Consistent customer identity management
across services
31 30 61
Support for real-time zero touch
38 22 60
processes
Extensible analytics engine 24 31 55

Network probes/instrumentation 29 24 53

Third-party source integration 22 29 51

0 10 20 30 40 50 60 70 80
Critical Standard

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COMPLETE VIEW OF THE CUSTOMER
SUPPORTS DIFFERENT STAKEHOLDERS AND ACTIONS
Batch Usage and Customer Data
(OSS, BSS, CDRs, CSR, roaming
data, social media, etc.)

Marketing, customer care, etc. are
monitoring, analyzing, and optimizing the
CUSTOMER ANALYTICS individual customer’s (or group’s)
MINED
INSIGHTS experience.

Operations is monitoring, analyzing and
optimizing the services that are running
SERVICE QUALITY ANALYTICS over the network, performing root cause
MINED
INSIGHTS analysis, managing SLAs, etc

Engineering is monitoring, analyzing and
NETWORK AND DEVICE ANALYTICS optimizing network and device
MINED performance, capacity planning, etc.
INSIGHTS

Real time Network and
Customer Data (RAN, GGSN, IP
Core, etc.)

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MANAGING THROUGH ANALYTICS
BASED ACTIONS
$ Cumulated Cash
Upgrade: Flow over Customer
- Increased Lifetime
monthly bill
Cash generation: Up-sell:
- Activation fees -Trialing new features Downgrade:
- Monthly bills - Reduced bill

Churn:
- Stop using

Time
Care:
- Customer
care calls Retention:
- 1 Free month
Termination
cost:
- Administrative
Acquisition costs: - De-activation
- Promotion
- Device
$ - Activation
- Etc.

MAXIMIZING CUSTOMER LIFETIME VALUE (CLV)

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TOP RANKED
USE CASES ACTION USE CASE
1. Service Quality Analysis (4.0/ 5.0)

MANAGEMENT 2. Targeted Retention Campaign for VIP customers
Reduce Churn with high churn prediction (3.75/ 5.0)

3. Targeted campaign for Customers with poor
QoS(4.5/ 5.0)

Up-sell 4. Mobile Security Threat Remediation (4.0/ 5.0)
Revenue
5. Fraudulent Use Prevention (4.5/ 5.0)
Assurance
6. Root cause analysis for IPTV, on-line video, mobile
Troubleshooting
and fixed (including IMS) (4.5/ 5.0)
Proactive 7. Trends analysis and proactive problem solving
Customer Care (3.5/ 5.0)

OPTIMIZATION ANALYTICS Reactive
8. Customer problem solving (4.0/ 5.0)
Customer Care
Prioritized 9. Analytics Driven Intelligent Service Optimization
Access and Contextual Offers (4.25/ 5.0)

Capacity
10.Capacity Insights (3.5/ 5.0)
Planning

Ratings based on Service Provider survey, ALU June 2012

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TURNING CELL UTILIZATION INTO AN OPPORTUNITY
ANALYTICS DRIVEN INTELLIGENT SERVICE OPTIMIZATION AND
CONTEXTUAL OFFERS

LIST OF ALL USERS IN
4
CONGESTED
2 CELL IS SENT TO ANALYTICS ENGINE
1 OPTIMIZATION & PCC SCORES
USERS BY CLV AND
SYSTEMS
CHURN.
CONGESTED CELL 1 2
5 OPTIONAL:

CLV
TRIGGERS ALERT
3 4 EVALUATE TARIFF
PLAN AND QoE PER
Churn PERSONALISED CUSTOMER
CONTEXTUAL SERVICE
OFFER SENT TO
OPTIMIZED
3 CUSTOMERS

FLEXIBLE & SCALABLE POLICY AND
CHARGING CONTROL (PCC)
OPTIMIZES SERVICE DELIVERY BASED
UPON SUBSCRIBER PROFILE

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SECURING THE
CUSTOMER EXPERIENCE
DEVICE MANAGEMENT MAKES
SECURITY CLIENT
APPLICATION AVAILABLE &
CURRENT

7
4 SEND INFORMATION ON
COMPROMISED DEVICE TO CSR
1

DEVICE INFECTED WITH ANALYTICS IDENTIFIES VALUED
MALICIOUS APPS DEVICE REMEDIATED
8 ALERT 6 CUSTOMER AND SENDS OFFER
FOR MOBILE SECURITY
3 9

2 SEND INFORMATION ON
COMPROMISED DEVICE TO ADJUST POLICY FOR
POLICY SYSTEM 5 COMPROMISED DEVICE
THREATS DETECTED BY
NETWORK INTRUSION
DETECTION SENSOR 10 REINSTATE POLICY FOR
REMEDIATED DEVICE

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FRAUDULENT USE
DETECTION

USER RESPONDS (“ENABLE”
5 OR “DISABLE”)

IF RESPONSE IS “DISABLE”,
INFORM POLICY ENGINE TO
DISABLE DATA SERVICE UNTIL
ROAMING STATUS IS DISABLED

4 FOR CUSTOMER HAVING USAGE
PROFILE ALERTS, CALL TO
HOME PHONE FROM CALL
CENTER OR SYSTEM SENDS SMS
6
1 REQUESTING “ENABLE /
“DISABLE DATA” RESPONSE
SUBSCRIBER USAGE

ANALYTICS MONITORS
CUSTOMER USAGE FROM
2 3
NETWORK CDRs & ALSO
BILLING/CHARGING ANALYTICS DETECTS USAGE
RATED CDRs PATTERN NOT ALIGNED WITH
CUSTOMER USAGE PROFILE
(eg roaming calls for a customer
never been in foreign country,
nbof today’s calls x% higher than
usual)

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BEING PROACTIVE ABOUT
SERVICE INTERRUPTION
ARE MY CUSTOMERS SERVICE QUALITY
IMPACTED BY SERVICE INSIGHTS 2
1 INTERRUPTION?

SERVICE ANALYSIS PER
Alcatel-Lucent
KEY CUSTOMERS

3
4
SERVICE ANALYSIS AND CLV
DASHBOARDS
IDENTIFICATION OF
5 A FAULTY CELL

MARKETING
TO DECIDE IF
NOC INTERVENTION CUSTOMER 7
6 COMMUNICATION
REQUIRED
SERVICE INTERRUPTION
RESOLUTION

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PROACTIVE/REACTIVE CARE
ON SLA NOTIFICATIONS
MOTIVE / SMP
RECEIVES
4 3 TRANSACTION EVENT
PER SLA ALERTS
NOC
4
NOC IS ALERTED
AUTOMATICALLY
IPTV, MOBILE AND FIXED WITH SERVICE CUSTOMER CARE
KQI/SLA AGENT IS NOTIFIED
INFORMATION ON CUSTOMERS
HAVING SLA ALERTS
IN ORDER TO
ANALYTICS MONITORS PROCEED ACTION
SERVICE KPI & CUSTOMER KQI. (CALL, SMS, …)
GENERATES ALERTS WHEN KQI
DOESN’T MEET CUSTOMER SLA.
NETWORK DATA
COLLECTION
ON-THE-FLY 1
FOR ALL
2
CUSTOMERS

ANALYTICS

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BELL LABS RESEARCH ACTIVITIES
IN ANALYTICS
UNDERSTANDING SIGNALS AND UNDERSTANDING PEOPLE’S INTEREST AND
EQUIPMENT SYSTEMS BEHAVIOR
APPLICATIONS
Network Smart Grid Public Space Recommender
Monitoring Data Mining Surveillance Systems

Network Indoor Speaker Gesture Social Media
Performance Localization Recognition Monitoring
Diagnosis

Intrusion Customer
Detection Experience
Discovery
BASIC METHODOLOGIES
Compressive Sampling / Forecasting Sensor Text
Streaming Data Analysis Fusion Mining

Data Complexity & Anomaly Interactive Data Audio-Video
Model Selection Detection Visualization Analytics

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PREDICTIVE ANALYTICS
TRULY UNDERSTAND CUSTOMER BEHAVIOR

Personalize and differentiate service based
on a deep understanding of each customer.

Bell Labs worked with a range of partners
to build an analytics foundation, based on
developing analytic patterns for QoE,
propensity to churn, lifetime value, etc.

Customer Bell Labsalsoworkswith local data
Targeted Churn Customer
Campaign
Trends &
Prediction QoE analyticspartners (whereappropriate).
Patterns

CUSTOMER EXPERIENCE ANALYTICS

Analytics Better understanding of customer value,
Infrastructure happiness and influence are key enablers of
(ETL, DB Model & BI a differentiated service approach so that
Reports)
investments are better matched to the
expected returns per customer.

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KBO
CALIBRATION
Historical • Really KBO
Network Usage
Scores/Touchpo understand
KPIs/KQIs Metrics
ints drivers
• Build accurate KQI KQI KQI
KPIs/KQIs from KBO “formula”
other Touch
KPI KPI KPI
Statistical Analysis and Points
Customer Care
Machine Learning KPI KPI KPI
KPIs/KQIs
Models Additional
Subscriber Data KPI KPI

KPI
Calibration Example KBO Calibration:
Customer Satisfaction of KPI Identify key
data
Mobile Broadband Service and metrics
Key Drivers

KEY BUSINESS OBJECTIVES

QUALITY CARE PERCEPTION EASE VALUE

THE CUSTOMER JOURNEY SERVICE PROVIDER JOURNEY
1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8
Market Fulfill Manage Service Charge Retain
Awareness Interact Agree/Get Consume Use/Support Pay Reward Leave Acquire Retire
Sell Order Customer Assurance Bill Optimize

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NET PROMOTER SCORE
(NPS) PREDICTION
KBO

KQI KQI KQI

KPI KPI KPI

KPI KPI KPI
Historical
Network Usage
Scores/Touchpo KPI KPI
KPIs/KQIs Metrics
ints
KPI

KPIs/KQIs from KPI Identify key
other Touch metrics
Statistical Analysis and Points
Customer Care
Machine Learning
KPIs/KQIs
Models Additional
Overall NPS Scores
Subscriber Data

Statistical Analysis and
Key NPS Machine Learning
Touchpoint NPS Score Models
Metrics/Touchpoint

Predicted NPS Score
and Key NPS Drivers

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TOP 8 LAWS OF BIG DATA
ACCORDING TO FORBES

1. The faster you analyze your data, the greater its predictive value

2. Maintain one copy of your data, not dozens

3. Use more diverse data, not just more data

4. Data has value far beyond what you originally anticipate

5. Plan for exponential growth

6. Solve a real pain point

7. Put data and humans together to get the most insights

8. Big Data is transforming business the same way IT did

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CONSUMERS WANT SIMPLICITY
ANALYTICS ARE ENABLERS
The most effective marketers use
three tactics:
1. minimize the number of
information sources consumers
must touch as they move
confidently toward a purchase
2. provide trustworthy sources of
product information and
recommendations
3. offer tools that allow consumers to
weigh their options by identifying
the features that are most relevant
to them.
CONSUMERS' ACTUAL REASONS; BUSINESSES'
PERCEIVED REASONS (SOURCE IBM INSTITUTE
FOR BUSINESS VALUE)

Source: Harvard Business Review, May 2012

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THREE LARGEST BARRIERS TO IMPLEMENTING
CUSTOMER EXPERIENCE MANAGEMENT

Difficulty in securing cross-
organizational co-operation
17 25 13 55

Poor understanding of
benefits of improving CEM 15 22 17 54

Poor data quality 12 15 20 47

0 10 20 30 40 50 60

Most important Second most important Third most important


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CUSTOMER EXPERIENCE
MATTERS
• Study indicates that organizations may
be losing on average 14% of incremental
revenue per year by not fully leveraging
collected information
• Telcos are most progressive in Analytics –
many new use-cases possible to support
monetization of their Networks,
especially mobile
• In an environment where everyone has
the same devices and mobile
penetration is reaching saturation,
Customer Experience is a priority
and Analytics a key enabler for Service
Providers

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TITLE: CUSTOMER INSIGHTS IMPROVE BUSINESS PERFORMANCE:
ANALYTICS KEY NEW TREND FOR TELCOS
SHORT TITLE: ANALYTICS KEY NEW TREND FOR TELCOS
Abstract:
• As communications service providers (CSPs) search for new ways to stand
out from the competition, they are looking to customer experience
analytics solutions that deliver actionable insights from their wide-
reaching customer, network and service data. This session will provide
details on developing trends from the telco industry, including what
we’re hearing from our CSPs customers about the importance of
analytics. Alcatel-Lucent and IBM are collaborating to bring a joint
analytics story to the market that combines intellectual property from
Alcatel-Lucent and Bell Labs, with robust analytics software from IBM, to
give service providers predictive insights about customer behavior.

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