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Oracle Hospitality Data Model (OHDM)

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Delivering a Superior Customer Experience

Requires the Organization to Align Around

The Customer

Customer

360

Personalized

Services

Relationship

Marketing

Customer

Service

Experience

Customer Experience Model

Know the

Customer

Deliver

Seamless,

Consistent,

World-class

Differentiated Service

Create valued

Offerings with

needs

Create a

relevant

Dialog

� Enterprise CEM strategy

� Executive championship

� Customer understanding

� Relevant, timely offerings

� Voice of the customer

� (social media)

� Seamless and consistent

experience across all touch

points

� Collaboration capabilities

� Employee empowerment

� Experience monitoring and

measurement capabilities

� Integrated technology

capabilities

The Customer Experience

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Pre-Arrival Check-In In-Room Tour & Travel Departure Retain Reward

Integrate

Objectives

Processes

Enablers

Results

Pre-Arrival Staying Experience Post -Departure

Effective Marketing

Effective Sales

Effective Promotions

Targeted Marketing

Marketing/Branding

Sales and Reservations

Revenue Management

Product/Package/

Scheme Development

Sales/Marketing

Reservations Revenue /

Yield Management

GDS/CRS/DCS

Market Share

Member/Corporate

Member Identification

Customized Services

Personalized Services

Arrival and Check-In

In-Room

Connection Service

Delivery

Middleware

Customer Master

GDS/CRS/DCS

Profitability

Re-Book

Reward

Recover

Measure

Follow –up

Loyalty

Customer Response

Loyalty

Analytics

Service & Billing

Satisfaction

CUSTOMER DATA

LOYALTY MANAGEMENT

Key Challenges Hospitality Industries

Faces With Customer Data

•Multiple Data Sources for Customer Data� Booking Data from Global Distribution System, Alliance Partner� Booking from Organization’s Portal and mobile devices� Direct Booking/Booking offices situated at different locations� Booking from Travel Agencies� Customer profiles and transactions from Loyalty Management platforms

• Multiple Internal Repositories For Customer Data� Customer Reservation System � Loyalty Management System� Customer Data Warehouses

• Historical Data From Legacy Systems That Need To Be Modernized � Booking Data� Loyalty transactions

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Customer Data Drives The Customer

Experience

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Social

Networks

Shopping

Experience

Marketing

§

§

Customer

Service

Experience

Marketing

§

§

Reservation

Shopping

Experience

Marketing

§

§

Front Office

/Booking

Counter

Shopping

Experience

§

§

§

Portal

S

Kiosk Agency

Portal

Marketing

§

§

§

Smart Phone

SCustomer

Management

Customer

Lifecycle

Management

Service

Experience

S

Search

Experience

Booking

Experience

In-Room

Experience

Pre-Booking

Experience

Social

Experience

Mobile

Experience

SOA/ESB/Middleware

SOA/ESB/Middleware

Marketing Sales Service Call Center Loyalty

ManagementLoyalty

Analytics

SOA/ESB/Middleware

� Oracle Hospitality Data Model

� Historical Enterprise DW and Pre-built Analytics

� Operational Data Store on Exadata

Customer Data

Management

GDS

CRS

Loyalty

Customer

Hub

Oracle Hospitality Data Model

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Reference

Base (3NF)

Aggregations

Derivations/

Data Mining

/OLAP

Reservation Check-In Room Tour & Packages Loyalty Revenue

Cross Functional Data Model

• Reservation Class

• Hourly Reservation

• Service Class

• Status

Reservation & Service Class

Segment

Segment

• Segment Type

• Arrival From

• Destination

• Region

• Country

• Continent

Reservation Office

• Reservation Office Code

• City Code

• Country Code

• Channel Type

• Agent Code

• Agent Type

• Status

Member/Guest

• Membership No.

• Card Carrier

• Membership Level

• Gender

• Date Of Birth

• Location

• Account Open Date

• Account Expire Date

• Corporate Account Code

Room

• Room No.

• Alliance/Partner Type

• Room Status

Hotel Codes

• Hotel Code

• City Code

• Geo Hierarchy

• City

• Region

• Country

• Continent

Packages/Offer

• Package Code

• Package Type

• Start Date

• End Date

Oracle Hospitality Data Model

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Reference

Base (3NF)

Aggregations

Derivations/

Data Mining

/OLAP

Reservation Check-In Room Tour & Packages Loyalty Revenue

Cross Functional Data Model

• Direct & Marketing

• Agent

• Frequent Member

• Group

• Corporate

• Preferences

• Special Request

• Hourly Reservation

• Reservation detail

Reservation

Segment

Confirmation

• Confirmation No.

• Agent/Other Resources

• Currency

• Total Amount

• Issue Date

• Creation Date

• Tax, Payment and Service

Fee

Check-In

• Room No.

• Agent/Other Resources

• Segment

Member/Guest Details

• Customer Nationality

• Address

• Travel Doc Type

• Issue Country

• Doc No.

• Gender

• Expiry Date

• Date Of Birth

Packages/Offer

• Offer no.

• Origin-Destination

• Agent/other resources

• Offer Amount

• Currency Details

Alliance/Partner Details

• Alliance/Partner Code

• Region

• City

• State

• Country

• Continent

• Share percentage

Oracle Hospitality Data Model

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Reference

Base (3NF)

Aggregations

Derivations/

Data Mining

/OLAP

Reservation Check-In Room Tour & Packages Loyalty Revenue

Cross Functional Data Model

• Booking Count by Time,

Geography, Segment

• Booking Count by Channel,

Agent, Booking Type, Class

• Average Tariff

• Materialization Rates

• Booking Status Change

• Trends – Load, Fair, Season

Reservation

Segment

Revenue

• Issued and Flown

• Rev. Maximization by

Optimization(Dimensions)

• Agent

• Channel

• Corporate and Individual

• Frequent Member/Guest

• OD

• Special Service Revenue

Frequent Member/Guest

• Loyalty Program Performance

• Earn/Burn Ratio

• Alliance/Partner Performance

• Promotion/Schemes

• Member Churn Analysis

• Revenue and Liability Analysis

Customer Interaction

• Customer Satisfaction

Rate

• Customer Complain

• Average Waiting Time

For any Service

Agent Fraud Analysis

• Channel Identification

• Agent Fraud Patterns

• Duplicate Booking

• Speculative Booking

• Duplicate Booking No.

• Revenue Loss

• Cancellation Fee

• Unused Inventory

Check - In

• Total Check -In Count

• Total Check –In Customer by’

Customer Type

Oracle Hospitality Data Model

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Reference

Base (3NF)

Aggregations

Derivations/

Data Mining

/OLAP

Reservation Check-In Room Tour & Packages Loyalty Revenue

Cross Functional Data Model

• Frequent Customer Profiling

• Non-Frequent Customer

Profiling

• Customer Segment

• Customer Loyalty

Classification

• Targeted Promotion

• Customer Life Time Value

Analysis

• Frequent Customer Prediction

Data Mining

Segment

OLAP

• Booking Count Time Series

Analysis

• Booking Office Ranking

• Sales Channel Sharing and Ranking

• Segment Ranking

• Current Frequent Customer Base

• Materialization Reports

• Seasonal Trend Reports

• Call Center Sales Performance Time

Series Analysis

• Customer Satisfaction Growth Trend

• Sales/Flown Revenue Growth Trend

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Business Insights To Help You Make The

Right Decisions

Business Area Covered

Reservation

Revenue Management

Tariff

Overall Operation

Alliances

Loyalty Management

Marketing

Sample Analysis

• What is the impact on the Guest as well as Corporate

Reservation during different seasons?

• How does the overbooking and load factors/occupancy compare

for Room and other facilities booking in this season?

• What are the numbers of walk in customers for restaurant in compare

to the occupied guest?

• What are the liking of the foods and beverages for different age group?

• What is the tariff/price elasticity as compare to the Market?

• What is the Reservation ratio through different booking Channel?

• How many reservations took places through Alliance/ partner or Direct?

• What is the impact on the members in case of offered Schemes or

loyalty promotions?

• What is the Scheme/offer option acceptance rate?

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Oracle Hospitality Data Model Sample

Report

• Reservation Analysis

• Agent/Partner Performance Analysis

• Channel Performance Analysis

• Revenue Analysis

• Call Center Performance Analysis

• Members Loyalty Analysis

• Members Vs. Corporate Analysis

• Seasonal Occupancy Analysis

• Group Reservation Vs. Individual Reservation Analysis

• Time to Time Load Factor Analysis

• Customers Age Group wise Service Preference Analysis

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Reservation Analysis

• Agent/Partner Reservation Analysis

• Reservation Segment Analysis

• Daily Reservation Analysis

• Room Reservation Analysis

• Group Reservation Analysis

• Monthly Reservation Analysis

• Quarterly Reservation Analysis

• Service Requested Analysis

• Weekly Reservation Analysis

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Revenue Analysis

• Agent/Partners/other resources of reservation Revenue Analysis

• Reservation Type/Class Revenue Analysis

• Channel Revenue Analysis

• Room and other services Revenue Analysis

• Revenue Per Sales Region

• Revenue per Sales Region and Service Type/Class

• Sales - Net Revenue Channel wise Flop 10

• Sales - Net Revenue Channel wise Top 10

• Sales - Net Revenue Flop 10 Countries/Region

• Sales - Net Revenue Top 10 Countries/Region

• Sales - Net Revenue Per Agency - Top 10 Revenue

• Segment Revenue Analysis

• Service Type/Class Revenue Analysis