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Copyright © 2012, Oracle and/or its affiliates. All rights reserved.1
Airline Customer Experience and Passenger Data Management
Vijay V AnandSenior Director & Global LeadTravel, Transportation & Logistics Industries
Xiang CaiPrincipal Member - Development
Copyright © 2012, Oracle and/or its affiliates. All rights reserved.2
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
Agenda• Introductions
• Customer Experience in the Airline Industry
• Oracle Customer Experience Management Solution
• Solution Overview
• Passenger Data Management and Oracle Airline Data Model
• Summary and next actions
Oracle Leadership Position in Travel and Transportation Industries
MTRC
BNSF
Network Rail
Rail / Metro
CSX
MetroRail
EuroStar
Heathrow Express
SNCF
Hanjin Shipping
CMA CGM
Shipping Lines
SinoTrans
Maersk
CSAV
Finnlines
Mitsui
APL NOL
Asciano
Sokhna Port
DP World (Dubai)
Hutchison Ports Holdings
PSA Corp
Ports
PTP
Jurong Port
ECT
Qantas
Airlines
Dragon Air
SAS
Korean Air
Cathay Pacific
Air India
APL Logistics
DHL
Exel
Toll Logistics
LSPs
MILS
BAX
K&N
Schipol
Airports
Thailand
BAA
Vancover
Hong Kong
Hilton
Wynn Resorts
Hospitality
Taj Hotels
Hyatt
Chengdu
CONFIDENTIAL: All capabilities and dates are for planning purposes only and may not be used in any contract 4
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Key Business Processes In the Airline Industry
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Agenda
• Introductions
• Customer Experience in the Airline Industry
• Oracle Customer Experience Management Solution
• Solution Overview
• Passenger Data Management and Oracle Airline Data Model
• Summary and next actions
Copyright © 2012, Oracle and/or its affiliates. All rights reserved.7
What Defines A Great Customer Experience ?
Recognition
Consistent Experience
Connected Interactions
Personalized Journey
Delightful Service
Rewarding Relationship
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UPSELLINGAND ANCILLARYREVENUE
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CUSTOMER INFORMATION AT ALL TOUCH POINTS
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Frustrated Customers Lead to Lost Revenue, Loyalty and Share of Wallet
50%Percentage of customers dissatisfied with cross-channel experience1
Percentage of multi-channel customers that switch vendors after a single bad experience
CUSTOMER FRUSTRATION
LOST REVENUE
$338 BillionRevenue lost by enterprises in 16 key global economies due to customer defections and abandoned purchases 2
59% SPEED IN ACCESSING AND DEALING WITH INFORMATION IS CRUCIAL
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Social is Not Optional
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UNHAPPY CUSTOMERS TELL OTHERS
“UNITED BREAKS GUITARS” CASE
• When United Airlines denied claim for broken guitar, musician tells his story on YouTube.
• The company’s stock dropped 10% within 4 days of the music video posting.
• Today, this video has been viewed over 11 million times.
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CREATING GREAT EXPERIENCES IS THE IMPERATIVE
AIRLINE PORTAL
TRAVEL AGENCY PORTAL
AIRLINE TICKET OFFICE
RESERVATIONS
WEB
MOBILE
SOCIAL
KIOSKS
“know me, and wow me
“understand me, and reward me”
“meet me, and engage me”
“delight me, and serve me”
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Enhancing the Customer Experience is the Top Priority For Airlines
• Improving the customer experience is the key focus for airlines as they track data to understand customer segments and preferences while looking for ways to add value beyond the customer journey
• Airlines want to improve the customer experience, but this is still very much a work in progress as airlines work to identify touchpoints, identify improvements, and implement their improvements
• Passenger data will play a central role in enhancing the customer experience --- to personalize and differentiate the customer experience, airlines need to empower employees with knowledge of the passenger at each touch point.
Source: Airline Information Survey 2011 Source: Airline Information Survey 2011
Yes but we have not yet_x000d_implemented any_x000d_
improvements
Yes but we have identified_x000d_the touchpoints
No but we are planning to
No and we don't plan to
26.7%
50.0%
23.3%
0.0%
Progress Made on Top Priorities
Improving the customer experience
Increasing revenue from the sale of _x000d_ancillary products
Increasing revenue from selling _x000d_more tickets (of the core product)
Reducing the miles/point liability
Reducing the cost of providing _x000d_customer support
86.7%
56.7%
60.0%
23.3%
36.7%
Top Airline Priorities for 2011
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Agenda
• Introductions
• Customer Experience in the Airline Industry
• Oracle Customer Experience Management Solution
• Solution Overview
• Passenger Data Management and Oracle Airline Data Model
• Summary and next actions
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Airline Customer Experience Solution Framework
S O CI A L
Customer Engagement
Customer Lifecycle Management
Passenger Data Management
I N SI G H T
Travel Agencies Reservations
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Customer
Data
Management
Social
NetworksCustomer
ServiceReservations
Ticket
Counter
Shopping
Experience
Booking
Experience
In-Flight
Experience
Pre-flight
Experience
Service
ExperienceSearch
ExperienceSocial
Experience
Airline
PortalKiosk
Smart
PhoneAgency
PortalTablet
GDS
PSS
Transactional DB
Customer
Engagement
SOA/ESB/Middleware
SOA/ESB/Middleware
Loyalty
Customer
Hub
Oracle Airline Data Model
Historical Enterprise DW and Pre-built Analytics
Operational Data Store on Exadata
Passenger Data Management
Airline Customer Experience Management Functional Architecture
Marketing Sales Call CenterServiceLoyalty
ManagementLoyalty
Analytics
Customer
Lifecycle
Management
Post-Flight Delight
SOA/ESB/Middleware
In-FlightPre-FlightBuyShop
Mobile Experience
Passenger
Data
Management
Social
NetworksCustomer
ServiceReservations
Ticket
Counter
Commerce
(ATG)Web
Center/Fatwire
Knowledge Management
(Inquira)
Real-time
Decisions RightNow
Airline
PortalKiosk
Smart
PhoneAgency
PortalTablet
GDS
PSS
Transactional DB
Customer
Engagement
SOA/ESB/Middleware
SOA/ESB/Middleware
Loyalty
Customer
Hub
Oracle Airline Data Model
Historical Enterprise DW and Pre-built Analytics
Operational Data Store on Exadata
Passenger Data Management
Airline Customer Experience Management Architecture
Siebel
Marketing
Siebel
Sales
Siebel
Call Center
Siebel
ServiceSiebel
LoyaltyLoyalty
Analytics
Post-Flight Delight
SOA/ESB/Middleware
In-FlightPre-FlightBuyShop
Mobility
(ADF)
RightNowCustomer
Lifecycle
Management
Social
Relationship Management
Commerce
(Endeca)
© 2013 Oracle Corporation – Proprietary and Confidential
Airline Customer Experience - Video
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Agenda
• Introductions
• Customer Experience in the Airline Industry
• Oracle Customer Experience Management Solution
• Solution Overview
• Passenger Data Management and Oracle Airline Data Model
• Summary and next actions
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Passenger Data Management
Airlines Data Model
Exadata
Business Intelligence
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• Industry-standard compliant based Enterprise-wide Data Model – Over 370+ tables and 8500+ columns– Over 250+ industry measures and KPIs
• Contains Logical and Physical Data Models Third Normal Atomic, Dimensional Schema
• Industry specific Airlines Measures and KPI• Pre-built OLAP cubes, Mining Models & Reports• Automatic Data Movement Among Layers• Extensive business intelligence metadata• Easily extensible and customizable• Usable within any GDS, DCS Applications• Central repository for atomic level data• Complete metadata (end-to-end)• Rapid implementation
Oracle Airline Data Model More Than Just a Data Model
FoundationLayer
AnalyticLayer
PresentationLayer
Oracle Airline Data Model
Derived Tables
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Where OADM FitsIn the Data Warehouse (DWH) Reference Architecture
OADM
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Oracle Airline Data ModelFoundation Layer
Oracle Airline Data Model
Base, Reference and Lookup Tables
Derived
TRANS-
FORMATION
Aggregate
Sample OBIEEMetadata & Reports
Base, Reference and Lookup Tables
Derived
TRANS-
FORMATION
TRANS-
FORMATION
Aggregate
Sample OBIEEMetadata & Reports
InformationAccess
AnalyticLayer
FoundationLayer
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Foundation LayerThird Normal Form (3NF)
Stores data at lowest level of granularity; detailed record of each transaction
Maintained in a third normal form (3NF) model / schema
Eliminates data redundancy through normalization
Stores data in business neutral model; eliminates need for data restructuring as the business evolves
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Oracle Airline Data ModelAnalytic Layer
Oracle Airline Data Model
Base, Reference and Lookup Tables
Derived
TRANS-
FORMATION
Aggregate
Sample OBIEEMetadata & Reports
Base, Reference and Lookup Tables
Derived
TRANS-
FORMATION
TRANS-
FORMATION
Aggregate
Sample OBIEEMetadata & Reports
InformationAccess
AnalyticLayer
FoundationLayer
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Analytic LayerStar Schemas, OLAP Cubes, Materialized Views
Abstraction layer to simplify analytical access; consists of aggregates, summaries, hierarchical relationships, etc.
Subject oriented representation of data Composed of OLAP cubes, star schemas, materialized views, etc. Easily understood by end-users; simpler to navigate Populated via intra-ETL process from data in the Foundation Data Layer (FDL)
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Oracle Airline Data ModelInformation Access Layer
Oracle Airline Data Model
Base, Reference and Lookup Tables
Derived
TRANS-
FORMATION
Aggregate
Sample OBIEEMetadata & Reports
Base, Reference and Lookup Tables
Derived
TRANS-
FORMATION
TRANS-
FORMATION
Aggregate
Sample OBIEEMetadata & Reports
InformationAccess
AnalyticLayer
FoundationLayer
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Interactive Dashboards and ReportsEmpowering End Users
Analyze Current Passenger Bookings
Example Analyses:
Using Pre-built Analytics Forecast Passenger Volumes
Revenue Dashboard Analyze Sales/Flown Revenue
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Populating OADM TablesAutomating Data Movement with Pre-built ETL
Source ETL(data quality/cleansing, staging interface)
Oracle Airline Data Model
ReferenceBase Lookup
Derived
Aggregate
Derived Intra-ETL
Aggregate Intra-ETL
Source Applications
Two types of ETL operations used to populate OADM tables
– Source ETL – populates base, reference and lookup tables
– Intra-ETL – populates derived and aggregate tables; automates data movement
Prebuilt Intra-ETL scripts available with OADM
– Developed using PL/SQL
Minimizes ETL development effort; saving time and costs
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Optimized for Oracle DB TechnologyEnabling Maximum Performance & Scalability
• Partitioning• Base and derived tables all partitioned by default• Also aggregate materialized views corresponding to base
•Compression• Used for all base, derived and aggregates tables• Significantly reduces disk utilization• Improves large data movement performance
•Parallel Execution• Parallel query and parallel DML features leveraged by
all base, derived and aggregate tables•Materialized Views
• All aggregate tables are either MV or its derivatives• Partition change tracking supports fast refresh of MV
• Intra-ETL• Utilizes pipeline function for in-memory processing
Data Warehousing
Analytical Preparation
OLAP
Data Mining
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Oracle Airline Data ModelMajor Business Areas Overview
Booking Check-In Flight Carrier Segment RevenueTicketing Loyalty
OADM is meant to enable the business to answer 3 basic questions:
• What happened?• Why did it happen?• What will happen?
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“Core Entities” Foundation used by all industries
Airline specific entities
A ModularLogical Data ModelFoundation
Oracle Airline Data Model Logical Data Model
Define your own scope for implementation– Implement in phases as needed
– Implement directly with minor modifications
– Implement during data mart/DW consolidation
– Use as a corporate data architecture guide
– Extend with new LoB from merger & acquisition or Your Own
Segment
…
Loyalty
Booking
Flight Schedu
le
Ticketing
Carrier
Checking
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Oracle Airline Data Model Foundation Layer
Booking
Check-in
PNR
Coupon
Ticket
Traffic
Flight
Segment
PAX DOCO/CA/CS
Call Center
LoyaltyCarrier
RevenueCalendar
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Oracle Airline Data ModelConceptual Model
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Oracle Airline Data ModelCross-Functional Data Models
Reference
Base (3NF)
Aggregations
Derivations / Data Mining / OLAP
Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue
Traffic Category:• Traffic Category• IATA Levels• Geo Area Name• Market Area Name• Calculation Year• Calculation Month
Segment:• Segment Type• Board Point and Off
Point Airport Name• Board Point and Off
Point City• Region• Country • Continent
Booking & Service Class:• Booking Class• Service Class• Carrier Code• Effective Dates• Status
Airport Codes:• Airport Code• City Code• Geo Hierarchy• City• Region• Country • ContinentCarrier:• Carrier Code• Description• Carrier Type• Legal Name• Trading Name• Address• Status
Frequent Flyer:• Frequent Flyer No.• Card Carrier• Airline Member
Level• Alliance Member
Level• Gender• Date of Birth• Address Location
Flight:• Flight Number• Flight Type• Code Share Type• Carrier Code• Flight Status
Booking Office:• Booking Office Code• City Code• Country Code• IATA Code• Channel Type• Office Type• Agent Chain• Status
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Reference
Base (3NF)
Aggregations
Derivations / Data Mining / OLAP
Booking Check-in Flight Segment Loyalty Ticketing Revenue Carrier
PNR:• Type• Purge Date• Group Name• Journey
Origin/Destination/Return Point• Agent• Frequent Flier Number• GDS
Ticket:• Primary Number• Agent• Currency• Total Amount• Issue Date• Creation Date• Tax, Payment and Service Fee
Booking:• Operating and Marketing Flight • Agent• Class• Origin-Destination• Frequent Flier• Group• Seat Details and Preferences• Special Requests
Check-in:• Carrier• Check-In Channel• Agent• Airport• Segment• Boarding Status• Baggage Status
Coupon:• Coupon Number• Origin-Destination• Agent• Ticket Number• Coupon Amount• Currency Details• Flight Details
PAX/DOCO/CA/CS:• Passenger Nationality• Address• Travel Doc Type• Issue Country• Expiry Date• Doc Number• Gender• DOB• Passport Hold Indicator
Booking TST:• Transitional Store Ticket No. • Origin• Destination• Ticket Type• Fare Calculation Model
Flight Schedule:• Flight Date. • Flight No.• Flight Carrier Code• Segment ID• LEG ID• LEG Aircraft Configuration Code• Total Saleable Capacity• Nautical Miles
Oracle Airline Data ModelCross-Functional Data Models
Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue
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Reference
Base (3NF)
Aggregations
Derivations / Data Mining / OLAP
Booking: • Booking Count by Time ,
Geography, Segment• Booking Count by Channel, Agent,
PNR Type, Class• Average Fair• Booking Status Change • Trends – Load, Fair, Season
Customer Interaction:• Onboard Service Satisfaction
Rate• Ground Service Satisfaction
Rate• Customer Complain• Call Center Average waiting
time
Agent Fraud Analysis:• Channel Identification• Agent Fraud patterns• Duplicate booking• Speculative bookings• Duplicate ticket numbers• Revenue loss • Cancellation Fee • Unused inventory
Revenue:• Issued and Flown • Rev. Maximization by
Optimization (dimensions)• Agent• Channel• Corporate and Individual• Frequent Flyer• OD• Special service revenue Check-in:
• Total Check in Count• Total Group Baggage Count• Total Check in Passenger by
Passenger Type• Total Baggage Count• Total Boarded Count• No-Show Rate• Load Factor
Frequent Flyer:• Loyalty Program Performance• Earn/Burn Ratio• Partner Performance (Airline
and Non-Airline)• Tier Movements• Promotions• Member Churn Analysis• Revenue and Liability Analysis
Oracle Airline Data ModelCross-Functional Data Models
Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue
Copyright © 2012, Oracle and/or its affiliates. All rights reserved.39Copyright © 2009, Oracle and / or its affiliates. All rights reserved.
Reference
Base (3NF)
Aggregations
Derivations / Data Mining / OLAP
Data Mining:• Frequent Flyer Passenger
Profiling• Non- Frequent Flyer Passenger
Profiling• Customer Segment • Customer Loyalty Classification• Targeted Promotion• Customer Life Time Value
Analysis• Frequent Flyer Passenger
Prediction
OLAP: • Booking Count Time Series Analysis (YoY,
MoM, Percent Change)• Booking Office Ranking• Sales Channel Sharing and Ranking• Segment Ranking• Passenger Feedback Reports• Current FF Base• Materialization Reports• Seasonal Trend Report• ASK Time Series Forecast• Route Passenger Count Time Series
Forecast• Call Center Sales Performance Time
Series Analysis• Customer Satisfaction Growth Trend• Sales/Flown Revenue Growth Trend
Oracle Airline Data ModelCross-Functional Data Models
Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue
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Faster Time-to-ValueSimplified Deployment, Predictable Cost
Build from Scratch Approach
Weeks or MonthsMonths or Years
Sizing and Configuration
Define Metrics & Dashboards
Training & Roll-out
Data Integration
Data Integration
Sizing and Configuration
Analysis and Design Define Metrics/Dashboards
Analysis and Design
Training & Roll-out
Oracle Airline Data Model
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Extension to data model
Relational interface 3NF, Lookup interface mapping extension
Workflow extension
Extending sample Connectors
Extensions to data model
Extensions to STAR, OLAP, & mining models (or create new)
Reports, Dashboards
Intra-ETL extensions
Workflow extensions
LDM, PDM (3NF, STAR)
Pre-built OLAP cubes
Pre-built Mining models
Intra-ETL among schema
Intra ETL for OLAP & mining workflow
Base, Reference, Lookup
Aggregate & Derived
Sample OBIEE metadata
Sample OBIEE Dashboards & Reports
Sample interface mapping
Sample source system connectors
Source system ETL
Architecture
Staging (one or more)
Cleansing
MDM integration
Connectors development
BI & Dashboards
Defining roles
Development of role-based Dashboards
Customization/creation of
- sample reports
- OLAP models
- Mining models
Defining KPIs, thresholds, and alerts
Guided analytics
Closing the loop with source
Customer, SI, Partner Develop/Extend
Typical OADM ImplementationOut-of-the-Box Functionality Reduces Cost and Implementation Time
OracleAirline Data Model
Customer, SI, Partner Develop/Extend
Out-of-the-Box
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Airline Customer Experience - Demo
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Agenda
• Introductions
• Customer Experience in the Airline Industry
• Oracle Customer Experience Management Solution
• Solution Overview
• Passenger Data Management and Oracle Airline Data Model
• Summary and next actions
Copyright © 2012, Oracle and/or its affiliates. All rights reserved.44
INDIVIDUALIZED SITES GUIDED COMMERCE PERSONAL SERVICE
Builds on CRM Investments
Best-In-Class Industry Apps
Best-In-Class Customer Apps
Complete
ONLY ORACLE DELIVERS THE COMPLETE EXPERIENCE
LOYALTY & UPGRADES CUSTOMER DATA CUSTOMER INSIGHTS
ORDER MANAGEMENT SERVICE MANAGEMENT ADVANCED SERVICEBILLING AND PAYMENTS
NEXT BEST ACTION INTUITIVE SEARCH DEEP KNOWLEDGETARGETED COMMUNICATION
“meet me, and engage”“delight me, and serve me”
“understand me, andreward me”
“know me, andwow me”
Copyright © 2012, Oracle and/or its affiliates. All rights reserved.45
Copyright © 2012, Oracle and/or its affiliates. All rights reserved.46