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Assumption that electronic markets have less friction than comparable markets.
• Search costs lower• Competition increases• Average prices should fall, converging on
market level
Study of prices of books and CDs and software sold on internet:
Higher prices & greater variance in electronic channel !!!!!
Price Levels
uu
uu
1. Superior disc. pricing techniques: lower registration and menu costs
2. Heterogeneity: wine in store or restaurant• Versioning
3. Temporal preference: consumer behavior and types
4. Imperfect information: bait and switch
5. Neural real estate: 5% sites/75% traffic
6. Market immaturity: eMarkets too young
Possible Causes
P
Q
$1.00
1 Coke
Fixed Prices
P
Q
P
Q
Fixed Prices
Consumers Surplus
Dead Weight Loss MC
P
Q
P2
Q2
P3
P1
Q1 Q3
Get a little more revenue
2nd Degree Price Discrimination
“product line pricing”, “market segmentation”, “versioning”
Gold Club, Platinum Club, Titanium Club, Synthetic Polymer Club
First Class, Business Class, World Traveler Class
Professional Version, Home Office
3rd Degree Price Discrimination
The practice of charging different groups of consumers different prices for the same product
Examples include student discounts, senior citizen’s discounts, regional & international pricing, coupons
P
Q
Maximize the Revenue !Perfect (1st degree) Price Disc.
Perfect Price Discrimination
Price $
Quantity
D
10
8
6
4
2
1 2 3 4 5
Profits:.5(4-0)(10 - 2)
= $16
Total Cost
MC
Prefect Price Discrimination
Practice of charging each consumer the maximum amount he or she will pay for each incremental unit
Permits a firm to extract all surplus from consumers
Difficult: airlines, professionals and car dealers come closest
Caveats:
In practice, transactions costs and information constraints make this is difficult to implement perfectly (but car dealers and some professionals come close).
Price discrimination won’t work if you cannot control three things: Preference profiles Personalized billing; (anonymous
transactions lesson seller’s discriminatory power over consumers)
Consumer arbitrage
What is different about this site?
1. Internet double edged sword:
• Consumers enjoy lower search costs, but…
• eMarketers have superior tools to register your consumption patterns and price sensitivity
2. The end of fixed pricing???
• Fixed pricing as an institution only 100 years old!!
• Developed in response to large scale economies/production models….with standard products !!!!
Conclusions
Horizontal Differentiation
The game of location (proximity to customer’s tastes)
Alice
Bob
1/2A
lice
Bob
Vertical Differentiation
Price
Quality
High
Low
1. Versions
2. Timing and delays
3. Ease of use
4. Pathways into site
5. Segregation of markets and users
6. Analysis of click stream and previous
purchasing history
How???
Making Self-Selection Work
May need to cut price of high end May need to cut quality at low end Value-subtracted versions
May cost more to produce the low-quality version.
In design, make sure you can turn features off!
How Many Versions?
One is too few Ten is (probably) too many Two things to do
Analyze market Analyze product
Analyze Your Market
Does it naturally subdivide into different categories? AND
Are their behaviors sufficiently different?
Example: Airlines Tourists v. Business travelers
“This created visible differentiation in customer service. It was essential for our customers to see the perks that the others were getting.”
Analyze Your Product
Dimensions to version High and low end for each dimension Design for high end, reduce quality
for low end Low end advertises for high end in
service industries – Cheap rates High end – Flagship products -
advertises for low end in many products.
Goldilocks Pricing
Mass market software (word, spreadsheets) Network effects User confusion
Default choice: 3 versions Extremeness aversion Small/large v. small/large/jumbo
Extremes Aversion
Bargain basement at $109, midrange at $179 Midrange chosen 45% of time
High-end at $199 added Mid-range chosen 60% of time
Wines Second-lowest price
“Framing effects”-example
Cross-Subsidies
Prices charged for one product are subsidized by the sale of another product
May be profitable when there are significant demand complementarities effects
Examples Browser and server software Drinks and meals at restaurants Long distance and local access Auto spare parts Razor & Blades Burger, fries, drinks Auto financing
Lessons
Version your product Delay, interface, resolution, speed, etc. Add value to online information Use natural segments Otherwise use 3 Control the browser, access,
comparisons, etc. Bundling & cross subsidies may reduce
dispersion
Down & Dirty
First degree (perfect) price discrimination “market of one”
Second degree price discrimination “product line pricing”, “market
segmentation”, “versioning” Third degree price discrimination
“different prices to different groups”
Other definitions in literature…
RM coming of age
Airline deregulation in the U.S. People Express vs. American Airlines
Edelman Award: RM for AA $1.4 billion in 3 years virtually every airline has implemented RM National Car Rental (vs. GM)
Edelman Award: RM for SNCF AA: $1 billion incremental revenues from RM Marriott Int’l RM: 4.7% increase in room revenue
Deregulation Europe: telecom, media, energy … e-distribution supports dynamic pricing & profiling
Dell, Amazon & Coca Cola experiment dynamic pricing
RM spans wide range of industries …
1985:
1978:
1992:
2000-01:
1997:
1999:
2003:
RM Evolution
1980
AirlinesAirlines
1985
RailTransp.
RailTransp.
1990
HotelsHotels
Car rentalCar rental
2000
MediaMedia
EnergyEnergy
Cruise linesCruise lines
Telco/ISPTelco/ISP
1995
Tour Operators
Tour Operators
Freight,Cargo
Freight,Cargo
SportsParksSportsParks
EntertainmentEntertainment
HealthCare/Hospitals
HealthCare/Hospitals
Insurance/banking
Insurance/banking
Manufact.Manufact.
RetailersRetailers
Revenue Management
Strategies & tactics for OPTIMIZING PROFITS
based on
DYNAMIC PRICE INVENTORY SETTING CONTROL
under real-time, disaggregate updating of
DEMAND FORECASTS
The RM Challenge
Arrivals of high paying customers…Closer to departure!
Arrivals of low paying customers…Earlier!
Overbooking metrics
Service level based: P(denial) =0.05 E[#denials]=2 Etc.
Cost based: assign a cost to each and optimizeOverbooking cost (airlines): Direct compensation cost Provision cost of hotel/meal Reaccom cost (another flight/airline) Ill-will cost (~ “lifetime customer value”)
Industries
Overbooking Airlines Hotels Car rentals Education Manufacturing Media
No Overbooking Restos Movies, shows Events Resort hotels Cruise lines
...Decisions Are Not Always “Rational”
Tickets; $7.95
$1.00 Discount for Children &
Seniors
Tickets; $7.95
$1.00 Discount for Children &
Seniors
Tickets; $6.95
$1.00 Extrafor Middle Aged
People
Tickets; $6.95
$1.00 Extrafor Middle Aged
People
Price Perception Issues are Complex...
More Acceptable Pricing Product-Based Open Discretionary Discounts and
Promotions Rewards
Less Acceptable Pricing Customer-Based Hidden Imposed Surcharges Penalties
CRM “Attract & retain
customers” maximize profit from
each customer Segment by customer
LTV Price/availability= fct. of
forecasted customer LTV to the organization
Ignores capacity issues and opportunity costs (displacement)
Wealth of data
DPRM “generate revenue” maximize profit from
available assets Segment by customer
WTP Price/availability = fct.
of forecasted demand & available supply
Ignores customer value issues and long term revenues
Quantifiable value
Maximize long-term profits
CRM & RM
Variables to track
Actual win or loss Number of days played Credit history Length of stay at hotel Individual spending preferences Demographics Psychographic profiles
Theoretical Revenue
Theoretical = (total amount wagered) X(house advantage)
100$ hand x 10 hours x 100 Hands/hour x .01 (house adv. 49/51) = $1,000
Can you track every single person???
Not always Difficult in table games Theoretical =
(total amount wagered) X(house advantage)
Where..Total amount wagered = estimated
average bet x estimated time played
Future estimates…
ADT = Average Daily Theoretical Revenue
Assumes that this level is constant Multiply by estimated # of days of
future trip to gain value Combined with CRM data on
consumption of food and beverage, entertainment, pshychographics, etc
Rooms, a scarce resource
Heads in beds: make money on gaming
Comp. Rooms: traditionally a fixed number of rooms given to big gamblers
Used averages to cost out, did not dynamically look at “opportunity cost”
ReInvestment amount
% of the ADT ADT $1,000 Reinvestment amount = 30% = $300 Total value of the room, F&B,
Entertainment, etc. must be less than the Room 200, F&B 100, Ent. 80..more than
ADT x reinvest. Ergo…try and sell room.. Sophisticated applications use dynamic
pricing to asses opportunity costs..
Requirements
RM – Yield management like the airlines..
Player tracking systems..Use cards like Harras, to register all activity and psychographic profiles
POS resturants, theaters, spas, retail stores, entertainment, etc…
CRM integrates all of the above!! Statistical analysis and optimization
applications.
