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Airline Customer Experience and Passenger Data Management

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Presentation on theme: "Airline Customer Experience and Passenger Data Management"— Presentation transcript:

1 Airline Customer Experience and Passenger Data Management
Vijay V Anand Senior Director & Global Lead Travel, Transportation & Logistics Industries Xiang Cai Principal Member - Development

2 The following is intended to outline our general product direction
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. Here’s is Oracle’s Safe Harbor Statement for you to review.

3 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

4 Oracle Leadership Position in Travel and Transportation Industries
Airlines Airports Ports LSPs Shipping Lines Rail / Metro Hospitality Qantas Schipol PSA Corp Toll Logistics Maersk Network Rail Korean Air BAA Hutchison Ports Holdings Exel CMA CGM BNSF Wynn Resorts Cathay Pacific Vancover DP World (Dubai) DHL APL NOL CSX Dragon Air Thailand PTP Hanjin Shipping MTRC Hilton SAS BAX Mitsui MetroRail Taj Hotels Asciano Hong Kong ECT APL Logistics CSAV EuroStar Hyatt Sokhna Port MILS Finnlines Heathrow Express Air India Chengdu Jurong Port K&N SinoTrans SNCF CONFIDENTIAL: All capabilities and dates are for planning purposes only and may not be used in any contract 4

5 Key Business Processes In the Airline Industry

6 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

7 What Defines A Great Customer Experience ?
Recognition Consistent Experience Connected Interactions Personalized Journey Delightful Service Rewarding Relationship

8 UPSELLING AND ANCILLARY REVENUE

9 CUSTOMER INFORMATION AT ALL TOUCH POINTS

10 Frustrated Customers Lead to Lost Revenue, Loyalty and Share of Wallet
CUSTOMER FRUSTRATION LOST REVENUE 50% $338 Billion SPEED IN ACCESSING AND DEALING WITH INFORMATION IS CRUCIAL Percentage of customers dissatisfied with cross-channel experience1 59% Revenue lost by enterprises in 16 key global economies due to customer defections and abandoned purchases 2 50% of customers not satisfied with cross channel experience (Forrester) 59% of multi-channel customers switch vendors after a single bad experience (Gartner) Poor customer experience results into revenue lost to defections and abandoned purchases $83 Billion for enterprises in the US annually $23 Billion for UK enterprises in the UK annually $338 Billion for enterprises in 16 key global economies Percentage of multi-channel customers that switch vendors after a single bad experience

11 Social is Not Optional

12 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. Main Point: The Stakes Have Never Been Higher Whet It Comes to Customer Expectations – The United Breaks Guitars Story Script: Some dissatisfied customers can get particularly creative. Has anyone seen the Youtube video, “United Breaks Guitars?” When Canadian musician, David Carroll’s guitar was broken during a trip on United Airlines – other passengers claimed to see baggage handlers throwing his guitar -- and his claims for compensation were denied by the airline, he released his frustration in the form of song with an accompanying music video. When the humorous video was first posted to YouTube it amassed over 150,000 views in one day! By the time, UAL tried to rectify the situation, considerable damage had already been done. The Times of London reported that the ensuing PR crisis led to a 10% drop in the value of UAL stock within only four days of the video posting – a decline of $180 million in shareholder value! Today that video has been viewed over 11 million times. The stakes have never clearly never been higher when it comes to meeting customer expectations.

13 Creating Great experiences is the Imperative
AIRLINE PORTAL TRAVEL AGENCY PORTAL “meet me, and engage me” “delight me, and serve me” KIOSKS AIRLINE TICKET OFFICE SOCIAL “know me, and wow me “understand me, and reward me” MOBILE RESERVATIONS WEB

14 Enhancing the Customer Experience is the Top Priority For Airlines
Source: Airline Information Survey 2011 Source: Airline Information Survey 2011 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.

15 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

16 Airline Customer Experience Solution Framework
Travel Agencies Reservations SOCIAL Customer Engagement INSIGHT Customer Lifecycle Management Passenger Data Management

17 Passenger Data Management
Airline Customer Experience Management Functional Architecture Shop Buy Pre-Flight In-Flight Post-Flight Delight Social Networks Customer Service Reservations Ticket Counter Airline Portal Kiosk Agency Portal Smart Phone Tablet SOA/ESB/Middleware Customer Engagement Shopping Experience Booking Experience Pre-flight Experience In-Flight Experience Service Experience Search Experience Social Experience Mobile Experience SOA/ESB/Middleware Customer Lifecycle Management Marketing Sales Call Center Service Loyalty Management Analytics Transactional DB SOA/ESB/Middleware Customer Hub Passenger Data Management Oracle Airline Data Model Historical Enterprise DW and Pre-built Analytics Operational Data Store on Exadata GDS Customer Data Management PSS Loyalty

18 Relationship Management Passenger Data Management
Airline Customer Experience Management Architecture Shop Buy Pre-Flight In-Flight Post-Flight Delight Social Networks Customer Service Reservations Ticket Counter Airline Portal Kiosk Agency Portal Smart Phone Tablet SOA/ESB/Middleware Customer Engagement Commerce (ATG) Knowledge Management (Inquira) Commerce (Endeca) Web Center/Fatwire Real-time Decisions RightNow Social Relationship Management Mobility (ADF) SOA/ESB/Middleware Customer Lifecycle Management Siebel Marketing Sales Call Center Service Loyalty Analytics RightNow Transactional DB SOA/ESB/Middleware Customer Hub Passenger Data Management Oracle Airline Data Model Historical Enterprise DW and Pre-built Analytics Operational Data Store on Exadata GDS Passenger Data Management PSS Loyalty

19 Airline Customer Experience - Video
© 2013 Oracle Corporation – Proprietary and Confidential

20 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

21 Passenger Data Management
Airlines Data Model Business Intelligence Exadata 21

22 Oracle Airline Data Model
More Than Just a Data Model Industry-standard compliant based Enterprise-wide Data Model Over 370+ tables and 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 Derived Tables Foundation Layer Analytic Layer Presentation Layer

23 Where OADM Fits In the Data Warehouse (DWH) Reference Architecture

24 Oracle Airline Data Model Foundation Layer
Information Access Analytic Layer Foundation Layer 24 24 24

25 Foundation Layer Third 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

26 Oracle Airline Data Model Analytic Layer
Information Access Analytic Layer Foundation Layer 26 26 26

27 Analytic Layer Star 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)

28 Oracle Airline Data Model Information Access Layer
Analytic Layer Foundation Layer 28 28 28

29 Interactive Dashboards and Reports Empowering End Users
Example Analyses: Analyze Current Passenger Bookings Using Pre-built Analytics Forecast Passenger Volumes Likewise, targeted reports and dashboards are available to communication service providers. These informative interactive reports allow business analysts to : Identify customers that are likely to churn in a given area Monitor dropped call rates over time to detect failing network elements And analyze sales growth over time by product and organization The entire suite of reports draw from 8 business areas, including Network Analysis, Customer Management, Provisioning Services, Partner Management – and more. Revenue Dashboard Analyze Sales/Flown Revenue

30 Populating OADM Tables Automating Data Movement with Pre-built ETL
Source ETL (data quality/cleansing, staging interface) Oracle Airline Data Model Reference Base 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

31 Optimized for Oracle DB Technology Enabling Maximum Performance & Scalability
Data Warehousing Analytical Preparation OLAP Data Mining 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 31 31

32 Oracle Airline Data Model Major Business Areas Overview
Presentation Title Oracle Airline Data Model Major Business Areas Overview Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue OADM is meant to enable the business to answer 3 basic questions: What happened? Why did it happen? What will happen? 32 32 32

33 Oracle Airline Data Model Logical Data Model
Segment Loyalty Booking Flight Schedule Ticketing Carrier Checking 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 A Modular Logical Data Model Foundation Airline specific entities “Core Entities” Foundation used by all industries

34 Oracle Airline Data Model Foundation Layer
Booking Check-in PNR Coupon Ticket Traffic Flight Segment PAX DOCO/CA/CS Call Center Loyalty Carrier Revenue Calendar

35 Oracle Airline Data Model Conceptual Model

36 Oracle Airline Data Model Cross-Functional Data Models
Presentation Title Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue Reference Booking & Service Class: Booking Class Service Class Carrier Code Effective Dates Status Airport Codes: Airport Code City Code Geo Hierarchy City Region Country Continent Traffic Category: Traffic Category IATA Levels Geo Area Name Market Area Name Calculation Year Calculation Month Flight: Flight Number Flight Type Code Share Type Carrier Code Flight Status Base (3NF) Aggregations Segment: Segment Type Board Point and Off Point Airport Name Board Point and Off Point City Region Country Continent Carrier: 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 Booking Office: Booking Office Code City Code Country Code IATA Code Channel Type Office Type Agent Chain Status Derivations / Data Mining / OLAP 36 36

37 Oracle Airline Data Model Cross-Functional Data Models
Presentation Title Booking Check-in Flight Segment Loyalty Ticketing Revenue Carrier Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue Reference 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 PNR: Type Purge Date Group Name Journey Origin/Destination/Return Point Agent Frequent Flier Number GDS Booking TST: Transitional Store Ticket No. Origin Destination Ticket Type Fare Calculation Model Base (3NF) Aggregations Ticket: Primary Number Agent Currency Total Amount Issue Date Creation Date Tax, Payment and Service Fee 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 Flight Schedule: Flight Date. Flight No. Flight Carrier Code Segment ID LEG ID LEG Aircraft Configuration Code Total Saleable Capacity Nautical Miles Derivations / Data Mining / OLAP 37 37

38 Oracle Airline Data Model Cross-Functional Data Models
Presentation Title Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue Reference Booking: Booking Count by Time , Geography, Segment Booking Count by Channel, Agent, PNR Type, Class Average Fair Booking Status Change Trends – Load, Fair, Season Revenue: Issued and Flown Rev. Maximization by Optimization (dimensions) Agent Channel Corporate and Individual Frequent Flyer OD Special service revenue Agent Fraud Analysis: Channel Identification Agent Fraud patterns Duplicate booking Speculative bookings Duplicate ticket numbers Revenue loss Cancellation Fee Unused inventory Base (3NF) Aggregations 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 Customer Interaction: Onboard Service Satisfaction Rate Ground Service Satisfaction Rate Customer Complain Call Center Average waiting time Derivations / Data Mining / OLAP Copyright © 2009, Oracle and / or its affiliates. All rights reserved. 38 38

39 Oracle Airline Data Model Cross-Functional Data Models
Presentation Title Booking Ticketing Check-In Flight Carrier Segment Loyalty Revenue Reference 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 Base (3NF) Aggregations Derivations / Data Mining / OLAP Copyright © 2009, Oracle and / or its affiliates. All rights reserved. 39 39

40 Faster Time-to-Value Simplified Deployment, Predictable Cost
Build from Scratch Approach Oracle Airline Data Model Training & Roll-out Define Metrics & Dashboards Data Integration Training & Roll-out Analysis and Design Define Metrics/Dashboards Data Integration Sizing and Configuration Analysis and Design Sizing and Configuration Months or Years Weeks or Months 40

41 Typical OADM Implementation
Out-of-the-Box Functionality Reduces Cost and Implementation Time Oracle Airline Data Model 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 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 Extensions to data model Extensions to STAR, OLAP, & mining models (or create new) Reports, Dashboards Intra-ETL extensions Workflow extensions Extension to data model Relational interface 3NF, Lookup interface mapping extension Workflow extension Extending sample Connectors Source system ETL Architecture Staging (one or more) Cleansing MDM integration Connectors development Customer, SI, Partner Develop/Extend Customer, SI, Partner Develop/Extend Out-of-the-Box

42 Airline Customer Experience - Demo

43 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

44 ONLY ORACLE DELIVERS THE COMPLETE EXPERIENCE
“meet me, and engage” “delight me, and serve me” “know me, and wow me” “understand me, and reward me” Builds on CRM Investments INDIVIDUALIZED SITES GUIDED COMMERCE PERSONAL SERVICE Best-In-Class Customer Apps TARGETED COMMUNICATION NEXT BEST ACTION INTUITIVE SEARCH DEEP KNOWLEDGE Best-In-Class Industry Apps ORDER MANAGEMENT SERVICE MANAGEMENT BILLING AND PAYMENTS ADVANCED SERVICE Complete CUSTOMER DATA CUSTOMER INSIGHTS LOYALTY & UPGRADES

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