University of Washington EMBA ProgramRegional 20

“Conjoint Analysis”

TA: Rory McLeodOctober 7, 2003

What is Conjoint Analysis?

• A quantitative analysis used to estimate customers’ value systems

• Requires that a product be broken down into a set of attributes

• Value system: how much value a consumer puts on each level of each of the attributes

Uses of Conjoint Analysis

• Learning more about your potential customer segments– Further market segmentation

• New product development– Extending types of products within a category– Entering a new category

• Determining optimal positioning

Conjoint Analysis Method

• Step 1 – Identify key product attributes and levels of attributes for the product class– Focus groups / managerial input

• Step 2 – Select combinations of attributes and attribute levels– Can the customers figure out the differences in the attributes and how

they impact the benefits?• Step 3 – Prepare a representation of each design

– Prototypes / sketches• Step 4 – Subjects rank the designs• Step 5 – Analyze data to develop relative importance of each

attribute

Example: Personal Computers

Step 1. Key Attributes and Levels of Attributes

1. Speed (1X, 2X, 3X)2. Software (None, Limited, Extensive)3. Price (Current, 20% Higher, 40% Higher)4. Supplier (Compaq, Packard Bell, Toshiba)

Example: Personal ComputersStep 2. Combinations of Attribute Levels

System A:Speed – 1X

Software – LimitedPrice – Current

Supplier – Compaq

System G:Speed – 3X

Software – NonePrice – Current

Supplier – Packard Bell

System D:Speed – 2X

Software – ExtensivePrice – Current

Supplier – Toshiba

System H:Speed – 3X

Software – LimitedPrice – 20% HigherSupplier – Toshiba

System E:Speed – 2X

Software – NonePrice – 20% HigherSupplier – Compaq

System I:Speed – 3X

Software – ExtensivePrice – 40% HigherSupplier – Compaq

System F:Speed – 2X

Software – LimitedPrice – 40% Higher

Supplier – Packard Bell

System C:Speed – 1X

Software – NonePrice – 40% HigherSupplier – Toshiba

System B:Speed – 1X

Software – ExtensivePrice – 20% Higher

Supplier – Packard Bell

Use software to select product combinations such that attributes are uncorrelated (orthogonal).

Example: Personal ComputersStep 3/4. Designs are ranked

Customer Preference (most preferred to least): D,H,G,I,A,B,E,C,F

System A: 5Speed – 1X

Software – LimitedPrice – Current

Supplier – Compaq

System G: 3Speed – 3X

Software – NonePrice – Current

Supplier – Packard Bell

System D: 1Speed – 2X

Software – ExtensivePrice – Current

Supplier – Toshiba

System H: 2Speed – 3X

Software – LimitedPrice – 20% HigherSupplier – Toshiba

System E: 7Speed – 2X

Software – NonePrice – 20% HigherSupplier – Compaq

System I: 4Speed – 3X

Software – ExtensivePrice – 40% HigherSupplier – Compaq

System F: 9Speed – 2X

Software – LimitedPrice – 40% Higher

Supplier – Packard Bell

System C: 8Speed – 1X

Software – NonePrice – 40% HigherSupplier – Toshiba

System B: 6Speed – 1X

Software – ExtensivePrice – 20% Higher

Supplier – Packard Bell

Example: Personal ComputersStep 5. Data AnalysisA. Determine individual scores for each attribute

by summing the scores for that attribute.

System A: 5Speed – 1X

Software – LimitedPrice – Current

Supplier – Compaq

System G: 3Speed – 3X

Software – NonePrice – Current

Supplier – Packard Bell

System D: 1Speed – 2X

Software – ExtensivePrice – Current

Supplier – Toshiba

System H: 2Speed – 3X

Software – LimitedPrice – 20% HigherSupplier – Toshiba

System E: 7Speed – 2X

Software – NonePrice – 20% HigherSupplier – Compaq

System I: 4Speed – 3X

Software – ExtensivePrice – 40% HigherSupplier – Compaq

System F: 9Speed – 2X

Software – LimitedPrice – 40% Higher

Supplier – Packard Bell

System C: 8Speed – 1X

Software – NonePrice – 40% HigherSupplier – Toshiba

System B: 6Speed – 1X

Software – ExtensivePrice – 20% Higher

Supplier – Packard Bell

Software:None = 8+7+3 = 18Limited = 5+9+2 = 16Extensive = 6+1+4 = 11

Manufacturer:Compaq = 5+7+4 = 16Toshiba = 8+1+2 = 11Packard Bell = 6+1+4 = 11

Price:Current = 5+1+3 = 920% Higher = 6+7+2 = 1540% Higher = 8+9+4 = 21

Speed:1X = 5+6+8 = 192X = 1+7+9 = 173X = 3+2+4 = 9

Example: Personal ComputersStep 5. Data Analysis

B. Rank attributes and summed attribute scores from lowest to highest (X’s below).

C. Determine the maximum score and minimum score.

D. Rescale the raw scores using the following Normalization Formula:

minmax

max

XXXXY

X Y3X Speed 9 1.00Current Price 9 1.00Extensive Software 11 0.83Toshiba 11 0.83Price + 20% 15 0.50Limited Software 16 0.42Compaq 16 0.422X Speed 17 0.33No Software 18 0.25Packard Bell 18 0.251X Speed 19 0.17Price + 40% 21 0.00

Example: Personal ComputersFor each attribute, determine its importance and plot a preference curve.

Benefit Range Importance

Speed 0.83 28% (.83 / 2.99)

Software 0.58 19%

Price 1.00 34%

Manufacturer 0.58 19%

Total 2.99 100%

Example: Personal ComputersFor each attribute, determine its importance and plot a preference curve.

Example: Personal ComputersYou can then evaluate the attractiveness of actual products you might bring to market…

Toshiba Compaq Packard Bell

Benefit Product Position

Customer Value

Product Position

Customer Value

Product Position

Customer Value

Speed 3X 1.00 2X 0.33 1X 0.17

Software Extensive 0.83 Extensive 0.83 None 0.25

Price +40% 0.00 +20% 0.50 Current 1.00

Manufacturer Toshiba 0.83 Compaq 0.42 Packard Bell

0.25

Overall Attractiveness

2.66 2.08 1.67

Additional Comments…

• For more accurate data analysis, can use multivariate regression (for rankings) or ANOVA (for ratings)

• Always test the validity of your results– Red-Face Test: Do the results make sense?– Holdout Prediction (a small # of the ranked products

are held out of the calculations)– Actual vs. predicted market share

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