Introduction to Revenue Management

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Introduction to Revenue Management

• MIST 8990
• Prof Jay Aronson
• University of Georgia
• Terry College of Business
• January 23, 2004

Presentation by Robert G. Cross
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Objectives ofRevenue Management

• Revenue and Profit Optimization
• Focus on revenue generation, not cost reduction,
  to increase profits
• Typical financial goal is to achieve a 4 to 8
  increase in top line revenues on an annual,
  recurring basis
• Flow-thru of incremental revenues are
  significant in high fixed asset businesses
• Central Repository of Corporate Market Knowledge
• Centerpiece for decision management database
• Anticipates future business conditions for both
  strategic and tactical responses

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Pricing Leverage
A 5 Improvement In
Increases Profits By
Source McKinsey Co.
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The Creation of Wealth in a Post-Capitalist
Society
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Technology as a Knowledge EnablerRevenue
Management as a Wealth Creator
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The Origin of ModernRevenue Management

• The Convergence of
• Airline Deregulation
• and
• Improvements in Information Technology

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Revenue Management
Economists Definition- A means of allocative
efficiency that maximizes economic wealth through
dynamically forecasting the self-seeking
activities of each individual consumer
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Price Differentiation ThroughRevenue Management
Selling the

• Right Product to the

• Right Customer at the

• Right Time for the

• Right Price

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No-Tech Revenue Management at Carols Barber
Shop
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Revenue Management-Process Flow
?
MarketSegmentation
Customer Demand Data
Forecasters
!
Constraints

Optimization
Market
Price and Availability Recommendations
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Price Differentiation the Key to
Effective Revenue Management
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Price Differentiation -

• Understanding What the Customer IsWilling To Pay

• Seller Charges Value Perceived By That Customer
  Segment

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Practical Problems withPrice Differentiation

• Customers Reluctant to Say How Much They Really
  Value a Product

• Perception of Value Changes Based on Time, Place,
  and Circumstance

• Competition/ Substitutable Alternatives Affect
  Price Perception

Revenue Management uses probable customer
behavior gleaned from data and statistical
analysis to optimize price
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Micro-Market Segmentation-- A Practical
Application of Micro-Economic Theory
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Single Price Optimization
100
REVENUE 2,500

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PRICE
1
1
50
100
DEMAND
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Price Differentiation - Multiple Prices
100
80
REVENUE 4,000
60
PRICE
40
20
1
1
20
40
60
80
100
DEMAND
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Price Differentiation-Differentiated Product
Creation
100
80
60
PRICE
40
20
1
1
20
40
60
80
100
DEMAND
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Real World Differential Pricing American
Airlines Case Study
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Real World Differential Pricing American
Airlines Case Study
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Break
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Customer Values Differ for Different Product
Attributes

• Physical Attributes
• Time Attributes
• Environmental Attributes
• Experiential Attributes
• Personal Perception Attributes

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Buying Behavior Matrix
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Customer Product/Price Trade-offs
Decision
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How Revenue Management Optimizes ProfitFor Any
Business
Predict Customer Demand
Optimize Price
Recalibrate Dynamically
Segment the Market
Segmentation based on purchasing behavior, not
just current or past classifications
Forecasts of demand and capacity at product/price
level
Continually monitor performance and update
market response
Mathematically determine capacity availability
and price that maximizes expected profit
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Step 1 Segment the Market

• Segment the account base according to
  price-response characteristics for each
• product
• The objective is to define observable market
  segments, each with different market response
• Clustering techniques are
• used in defining micro-
• markets

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Step 2 Determine Price-Response Influences
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Step 2 Measure Market Response By Market
Segment
100
90
80
70
Price Sensitivity
60
50
Probability of Winning Bid ()
40
Brand Preference
30
20
10
0
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
1.40
Our Price versus Competitor Price (Ratio)
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Step 3 Optimize Price / Maximize Profit
Cost Information
Contribution (100)
X
Net Price
Likelihood of Winning ()
Market Information and Strategic Goals
Net Price
Optimal Price
2005
Optimal Price
(c) 2004 Robert G. Cross
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Step 4 Dynamically Recalibrate
Customer Demand
Price and Availability
Results In Long-Term Profit Maximization
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Case Studies

• B2C High Dollar Retail Transactions
• B2B - Competitive Bid Situations
• ecommerce B2C - High Volume, Transparent
  Environment

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Case StudyFord Motor Company

• The Problem How to Optimize Customer Incentives
  over millions of vehicles
• The Solution

Predict Customer Behavior
Optimize Response
Dynamically Recalibrate
Segment the Market

• Geography
• Vehicle Type
• Incentive Device
• Competition

• Response to Promotion By Segment
• Probability of Winning
• Competitive Response

• Vary Discount
• Vary Device
• Vary Time

• Measure Response
• Update Models

Result Expected savings of 800 million per year
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Case StudyUnited Parcel Service

• The Problem How to Optimally Price a Hundred
  Thousand Annual Contracts
• The Solution

Predict Customer Behavior
Optimize Response
Dynamically Recalibrate
Segment the Market

• Calculate Optimal Point Maximizing Probability of
  Win at Greatest Margin

• Region
• Customer Type
• Competition
• Strategic Goals

• Probability of Winning
• Probable Margin

• Measure Success
• Update Models

Result Increased revenue and profit in excess of
120 million per year
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Case StudyTickets.com

• The Problem How to Maximize Event Attendance at
  the
• Highest Possible Price
• The Solution

Predict Customer Behavior
Optimize Response
Dynamically Recalibrate
Segment the Market

• Optimize Price
• Optimize Capacity

• Venue
• Event
• TOD/Dow
• Experience

• Response to Price
• Probability of Winning

• Measure Success
• Update Models

Result Increased revenue in excess of 8 to 12
per event
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Wealth Creation Through Pricing and Revenue
Management
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Questions?
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Introduction to Pricing and Revenue Management

• MIST 8990
• Prof Jay Aronson
• University of Georgia
• Terry College of Business
• January 23, 2004

Presentation by Robert G. Cross