Dynamic pricing: Lessons from Airline Revenue Management
Lessons from Airline Revenue Management
“Dynamic pricing” is practiced across the globe in a
variety of industries
Personalized pricing strategies based on sophisticated analytics and Big Data
Reduced “consumer surplus” as every individual customer pays close to his
Facilitated by the internet and e-tailing
Pioneered by airlines in the ‘80’s in the form of
A multitude of rapidly changing fares exploiting elasticities of different segments
Airlines continue to perfect the craft. Key features are:
Creative Market Segmentation
Big Data Analytics
Unbundling and Rebundling
Y S O
CREATIVE MARKET SEGMENTATION
Elasticity-based segmentation techniques
Huge range of elasticities across customers – and the
same customer at different times
Reliance on behavioral “proxies” correlated with
Airlines may have 100+ different fares paid by
travelers on the same flight
Fare rules designed to keep more price-inelastic
travelers from paying lower fares
Forecast systems predicting demand in $15-$25
Ancillary fees exploiting observed lower price
elasticity of certain additional features
2 1 2
2 1 2 1
Q Q P P
P P Q Q
Price with extras
BIG DATA ANALYTICS
Airlines forecast demand for each fare level by flight
up to a year in advance – a 50 aircraft fleet requires
a million forecasts at a time
Seasonal, day-of-week and time-of-day patterns
Regression models tapping into 3-5 years of history
Allocations designed to optimize an entire network
Forecasts updated automatically each night
Allocations based on both forecast demand levels & uncertainty
Real-time inventory adjustments as bookings come in
Just as critically, airlines have developed processes
to actively manage the models
Reports, alerts, cross-functional meetings; metrics,
Consumer products companies and e-tailers
experience similar product proliferation (SKU’s) and
rely heavily on computer demand models
Real-time updates based on actual orders across disperse
( ) u h l
o u h
C f f
F n x
C C f
Airlines have historically monitored competitors’ fares
multiple times a day – matching low fares within 3 hours
Reliance on third party distribution channels commoditized air travel
More recently, competitive analysis has become more
New investment in their own websites; changing content on third
New systems calculate elasticity for a fare premium or discount
“Screen scraper” systems monitor fares on multiple outlets
Business rules adjust allocations based on demand and fare levels
More generally, however, airlines are advised to adopt a
proactive, internally-consistent, stable pricing strategy
Based on demand for its unique network, product, brand, etc.
Unbundling further exploits elasticity
differences among customer segments
“Pay for what you use”
Bag fees add revenue & reduce handling costs
New value added services can make trip easier for
those willing to pay more
Spirit Airlines now reports ancillary @ 45% revenue
Rebundling drives new differentiation; can
target certain segments for further upsell
Frontier was first in U.S. to launch “branded fares”
Service Fee Service Fee
1st bag $30 Same Day Stby $50
2nd bag $25 Priority Bdg $5
Chng fee $150 Resrved Seat $5
Onbd Meal $8 Double miles $8
Video $6 WIFI $8
Drink $6 Big Seat $35
With variety of fares and fees, customers have new
choice – but can become overwhelmed
Transparency is more important
Third party distribution is particularly weak in conveying rules & fees
Sell-up is maximized by the right offers at the right time
in booking process
Personalized offers help individual customers navigate
Frequency of Fare
Inspire Research Plan Book Sell-up Travel Share
Organization must match sophistication of forecast
system; many other elements to consider…
Dynamic pricing cannot be silo’ed
Requires collaboration across Pricing, Marketing,
Distribution, e-commerce, Loyalty, and Operations
Speedy response to market requires a flat organization
Organization must be learning oriented
Constant, disciplined hypothesis testing
Continual questioning of conventional wisdom
Open to new ideas
To keep everyone aligned, metrics must be
similarly aligned across functions
DO YOU PRICE DYNAMICALLY?
How granularly do you segment demand?
Do you understand the elasticity of different segments?
Do you adjust prices based on forecast demand by market segment?
Do you update the forecast algorithms frequently based on the latest data?
Do you factor in forecast accuracy in decision making? What is the relative cost of over- vs.
Do you distinguish between “actual” underlying demand and “observed” demand based on
supply, merchandising, and pricing decisions?
Do you regularly test for higher fare demand?
Do you know your competitors’ pricing?
Can you predict their response to your pricing actions?
Can you charge separately for different features/services?
Can you personalize offers?
Do you integrate Pricing with the rest of the organization? How linked are
pricing and merchandising?
Do you have a culture that supports Big Data Analytics?
DO YOU PRICE DYNAMICALLY?
Tom Bacon has applied Big Data Analytics and Merchandising to
support dynamic pricing at numerous airlines
He has led RM and commercial initiatives as an executive at 5 carriers
Restructured carriers in changing markets or facing new competition
All sectors: global legacy carriers, LCC’s, regionals, and niche carriers
Global: North America, Asia, Middle East, Europe
Assessed RM systems & modules; and airline’s success in RM management
Implemented new RM organizational structure and competitive fare tracking at Gulf airline
Evaluated competing RM systems in context of an airline merger
Recommended process changes at European carrier
Persistent advocate for cross-functional collaboration between RM and other departments
Quadrupled ancillary revenue at Frontier Airlines
Launched first branded fares in U.S.
To implement dynamic pricing in your organization please contact
Tom at email@example.com