pricing analytics: segmenting customers to maximize revenue

PRICING ANALYTICS Segmenting Customers to Maximize Revenue

Customer Segmentation • Customers can be segmented into value groups in some

markets • High valuation groups are willing to pay more for a product or service

• Low valuation groups are only willing to spend less for the same product or service

Airline Customer Segmentation • Older method used Saturday night stay to separate leisure and

business passengers

• Modern methods use advance purchase time as a primary discriminator

• The later a passenger purchases a ticket, the more they’re willing to pay

Example: Malaysia Airlines Flight 19 • Maximize revenue on MH Flight 19 (Amsterdam to Kuala

Lumpur)

• Surveyed 2% of market (10 people) on their valuation of flight

$463 $732

$569 $701

$457 $746

$719 $607

$758 $685

Example: Malaysia Airlines Flight 19 • Valuations effectively the same as points on the demand curve

• Calculate demand by finding number of people who would buy tickets at each price point

$463 $732

$569 $701

$457 $746

$719 $607

$758 $685

$463 $732

$569 $701

$457 $746

$719 $607

$758 $685

Enter fare valuations from passenger survey

Enter demand summing formula: =COUNTIF($C$2:$C:$11,“>=”&C2)

Accept formula

Select handle at bottom right of formula cell, then drag down

Enter market adjustment formula: =A2*50

Accept formula

Select handle at bottom right of formula cell, then drag down

Select cells containing demand and price data

Choose “Scatter With Only Markers”

d = a - bp

Right-click one of the data points

Choose “Add Trendline…”

Select “Linear”

Check “Display Equation on Chart”

Click “Close”

a b

d = 838.9 – 0.7p

Enter guess for optimal single price

Enter demand curve formula: =838.9-0.7*E14

Accept formula

Enter total revenue formula: =E15*E14

Accept formula

Launch Excel’s Solver tool

Maximize

Revenue

Ticket Price

Choose GRG Nonlinear solving method

Click “Solve”

Click “OK”

Optimized ticket price: $599

Optimized revenue: $251,340

Yield Management • Goal: charge a set of customers more for the same product to

increase revenue

• Ideal (from the airline’s perspective): charge rich people and desperate people more money

• Doing that’s illegal (at least in US and EU) – discrimination

• Legal method: yield management

Yield Management • We need to find some variable that strongly correlates to how

much a customer is willing to pay

• Airline example: how early a passenger buys a ticket before a flight • Low-valuation customers (tourists, students, bargain hunters) buy tickets

long before a flight

• High-value customers (business travel, emergencies, HBS alumni) buy tickets last-minute

Modeling Yield Management • Incorporate two price points into our existing single-price

model

• High-value customer demand formula (same as single price):

High Value Demand = 838.9 – 0.7 x High Price

• Low-value customer demand formula:

Low Value Demand = (838.9 – 0.7 x Low Price) -

High Value Demand

Enter guess for low price point

Enter guess for high price point

Enter low price demand formula: =(838.9-0.7*B1)-B5

Accept formula

Enter high price demand formula: =838.9-0.7*B2

Accept formula

Enter low price revenue formula: =B4*B1

Accept formula

Enter high price revenue formula: =B5*B2

Accept formula

Enter revenue summing formula: =SUM(B7:B8)

Accept formula

Launch Excel’s Solver tool

Maximize

Total Revenue

Ticket Prices

Choose GRG Nonlinear solving method

Click “Solve”

Click “OK”

Optimized ticket price for low-value passengers: $399

Optimized revenue: $335,121

Optimized ticket price for high-value passengers: $799

33%

Increase

Capacity Constraints • Current model assumes an unlimited number of

seats on airplane

• Need to add a capacity constraint to accurately model pricing

• Aircraft (Boeing 777) holds 341 passengers

Enter total # passengers formula: =B4+B5

Accept formula

Restart Excel’s Solver tool

Click Add button

Total passengers

Less than/equal to

Aircraft capacity: 341

Click OK

Click Solve button

Click OK button

Optimized ticket price for low-value passengers: $711

Optimized ticket price for high-value passengers: $955