Conjoint analysis - Pennsylvania State University analysis Compositional vs. decompositional...

Conjoint analysis

Conjoint analysis

Outline

▪ Conjoint analysis as a decompositional

preference model

▪ Steps in conjoint analysis

▪ Uses of conjoint analysis

Conjoint analysis

Compositional vs. decompositional

preference models

▪ Compositional: respondents evaluate all the

features (levels of particular attributes) characterizing

a product; combining these feature evaluations

(possibly weighted by their importance) yields a

product’s overall evaluation;

▪ Decompositional: respondents provide overall

evaluations of a series of products composed of

various combinations of attribute levels; the overall

evaluations are then decomposed into the utilities

associated with different levels of the various

attributes;

Conjoint analysis

Example of a compositional model

▪ Consider the following laptop computer:

□ Dell

□ 320 GB hard drive

□ 4 GB of RAM

□ 12.1 inch screen

□ Price of $1,200

▪ On a scale from 0 (lowest) to 10 (highest), how

would you rate this computer on each attribute?

▪ Assign a total of 100 points to each of the 5

attributes so that the points reflect the relative

importance of each attribute.

Conjoint analysis

Example of a decompositional model

▪ Rank the following four descriptions of laptop

computers in terms of overall preference:

Profile 1 Profile 2 Profile 3 Profile 3

Brand Dell Apple Dell Apple

Size of Hard

Drive320 320 320 160

Amount of

RAM2 4 4 4

Screen size 15.4 15.4 12.1 12.1

Price $1,200 $1,200 $1,500 $1,200

Rank

Conjoint analysis

Basic idea of conjoint analysis

▪ Overall utility for a product can be decomposed

into the utilities (called part-worths) associated with

the levels of the individual attributes of the product;

▪ The relative importance of a given attribute is

given by the ratio of the part-worth range for that

attribute divided by the sum of all part-worth

ranges;

Conjoint analysis

Steps in conjoint analysis

▪ Determine attributes and attribute levels

▪ Select product profiles to be measured

▪ Choose a method of stimulus presentation

▪ Decide on the response method

▪ Collect and analyze the data

▪ Interpret the results

Conjoint analysis

Attributes and attribute levels

▪ Identify the relevant product attributes that are

considered during choice

▪ Select attribute levels that represent the options

actually available in the market

▪ Trade-off between the completeness of the

representation and the complexity of the design

Conjoint analysis

Example: Laptop Profiles

Brand Hard Drive RAM Screen Price

Dell 320 GB 2 GB 15.4 in $1,200

Apple 320 GB 4 GB 15.4 in $1,200

Dell 160 GB 4 GB 15.4 in $900

Apple 320 GB 2 GB 15.4 in $900

Dell 320 GB 4 GB 12.1 in $1,500

Apple 320 GB 2 GB 12.1 in $1,500

Apple 160 GB 4 GB 15.4 in $1,500

Apple 160 GB 2 GB 12.1 in $900

Apple 160 GB 4 GB 12.1 in $1,200

Dell 160 GB 2 GB 12.1 in $1,200

Dell 320 GB 4 GB 12.1 in $900

Dell 160 GB 2 GB 15.4 in $1,500

Conjoint analysis

Product profiles

▪ Full factorial designs:

all possible combinations of the levels of the various

attributes are used

▪ Fractional factorial designs:

□ a subset of all possible combinations is used

□ orthogonal designs in which each level of one

attribute is paired equally with all the levels of other

attributes are beneficial

Conjoint analysis


Brand Hard Drive RAM Screen Price

Dell 320 GB 2 GB 15.4 in $1,200

Apple 320 GB 4 GB 15.4 in $1,200

Dell 160 GB 4 GB 15.4 in $900

Apple 320 GB 2 GB 15.4 in $900

Dell 320 GB 4 GB 12.1 in $1,500

Apple 320 GB 2 GB 12.1 in $1,500

Apple 160 GB 4 GB 15.4 in $1,500

Apple 160 GB 2 GB 12.1 in $900

Apple 160 GB 4 GB 12.1 in $1,200

Dell 160 GB 2 GB 12.1 in $1,200

Dell 320 GB 4 GB 12.1 in $900

Dell 160 GB 2 GB 15.4 in $1,500

Conjoint analysis

Methods of stimulus presentation

▪ Verbal descriptions

▪ Pictures

▪ Actual products or prototypes

Apple Laptop

with 320 GB of Hard Disk Space,

4 GB of RAM, and a

Screen Size of 15.4 inches –

at a Price of $1,200.

Conjoint analysis

Response method

▪ Rankings or ratings of the product profiles in terms

of preference, purchase probability, etc.

▪ Pairwise comparisons of product profiles in terms of

preference, purchase probability, etc.

▪ Choice of a product from a set of product profiles

Conjoint analysis

Brand Hard Drive RAM Screen Price A B

Dell 320 GB 2 GB 15.4 in $1,200 9 6

Apple 320 GB 4 GB 15.4 in $1,200 6 12

Dell 160 GB 4 GB 15.4 in $900 12 5

Apple 320 GB 2 GB 15.4 in $900 11 11

Dell 320 GB 4 GB 12.1 in $1,500 4 3

Apple 320 GB 2 GB 12.1 in $1,500 1 9

Apple 160 GB 4 GB 15.4 in $1,500 3 10

Apple 160 GB 2 GB 12.1 in $900 8 7

Apple 160 GB 4 GB 12.1 in $1,200 5 8

Dell 160 GB 2 GB 12.1 in $1,200 7 1

Dell 320 GB 4 GB 12.1 in $900 10 4

Dell 160 GB 2 GB 15.4 in $1,500 2 2


Conjoint analysis

In-class exerciseUsing the data in the table, answer the following questions:

a. How much utility does each of the two consumers attach to the

different levels of the five attributes? (Hint: Compute each

consumer’s average rating of all the options with a given

feature. For example, to figure out how much consumer A

values the Apple brand name, compute the average rating of

the six Apple laptops.)

b. What’s the relative importance of the five attributes for the two

consumers?

c. Consider consumer A’s ratings. For this consumer, what’s the

predicted utility of a Dell computer with 160 GB of hard drive

space and 2 GB of RAM, a 12.1 inch screen, and a price of

$1,200?

-4

-3

-2

-1

0

1

2

3

4

Apple Dell

A

B

-4

-3

-2

-1

0

1

2

3

4

HD 160 GB HD 320 GB

A

B

-4

-3

-2

-1

0

1

2

3

4

2 GB RAM 4 GB RAM

A

B

-4

-3

-2

-1

0

1

2

3

4

$900 $1,200 $1,500

A

B

-4

-3

-2

-1

0

1

2

3

4

12.1 in Screen 15.4 in Screen

A

B

Conjoint analysis

In-class exercise

Using the data in the table, answer the following questions:

a. How much utility does each of the two consumers attach to the

different levels of the five attributes? (Hint: Compute each

consumer’s average rating of all the options with a given

feature. For example, to figure out how much consumer A

values the Apple brand name, compute the average rating of

the six Apple laptops.)

b. What’s the relative importance of the five attributes for the two

consumers?

c. Consider consumer A’s ratings. For this consumer, what’s the

predicted utility of a Dell computer with 160 GB of hard drive

space and 2 GB of RAM, a 12.1 inch screen, and a price of

$1,200?

Conjoint analysis

Review questions

▪ What’s the difference between compositional and

decompositional preference models?

▪ What’s a fractional factorial design in conjoint

analysis and why is it useful?

▪ What are part-worths in a conjoint study?

Conjoint analysis

Review questions (cont’d)

• A conjoint study was conducted for LCD TV’s,

using three brands (LG, Samsung, and Sony),

three screen sizes (46, 54, and 63 in.) and three

price levels ($2,300; $2,800; and $3,600).

• The utility differences between the lowest and

highest levels of each attribute were 3 for brand

name, 2 for screen size, and 5 for price.

• Based on these findings, price is how many times

more important than screen size?

Conjoint analysis

ME output for laptop computer examples

Respondents' Preference Partworths

Respondents' preference partworths. The most preferred profiles sum up to 100, the least preferred to 0.

Respondents / Attributes and Levels

Apple Dell 160 320 2 4

Respondent 1 0 14 0 6 0 3

Respondent 2 50 0 0 17 0 8

12.1 15.4 900 1200 1500

0 11 66 36 0

0 19 6 6 0

Respondents / Attributes and Levels

Respondent 1

Respondent 2

Conjoint analysis

Office Star data

Conjoint Study Design

Attributes and attribute levels of the Conjoint study.

Attributes / Levels Level 1 Level 2 Level 3 Ordering

LocationLess than 2

milesWithin 2-5

milesWithin 5-10

milesDecreasing

Office suppliesVery large

assortmentLarge

assortmentLimited

AssortmentUnordered

FurnitureOffice

FurnitureNo Furniture Unordered

Computers No computers Software onlySoftware and

computersUnordered

Conjoint analysis

Office Star bundles

BundlesAttribute levels for a full-profile, fractional design Conjoint study

Attributes / Bundles Bundle 1 Bundle 2 Bundle 3 Bundle 4 Bundle 5 Bundle 6 Bundle 7 Bundle 8

LocationLess than 2

milesLess than 2

milesLess than 2

milesLess than 2

milesWithin 2-5

milesWithin 2-5

milesWithin 2-5

milesWithin 2-5

miles


assortmentLarge

assortmentLimited

AssortmentLarge

assortmentVery large

assortmentLarge

assortmentLimited

AssortmentLarge

assortment

FurnitureOffice

FurnitureNo Furniture No Furniture

Office Furniture

Office Furniture

No Furniture No FurnitureOffice

Furniture

Computers No computers Software onlySoftware and

computersSoftware only Software only No computers Software only

Software and computers

Bundle 9 Bundle 10 Bundle 11 Bundle 12 Bundle 13 Bundle 14 Bundle 15 Bundle 16

Within 5-10 miles

Within 5-10 miles

Within 5-10 miles

Within 5-10 miles

Within 2-5 miles

Within 2-5 miles

Within 2-5 miles

Within 2-5 miles

Very large assortment

Large assortment

Limited Assortment

Large assortment


Large assortment

Limited Assortment

Large assortment

No FurnitureOffice

FurnitureOffice

FurnitureNo Furniture No Furniture

Office Furniture

Office Furniture

No Furniture

Software and computers

Software only No computers Software only Software onlySoftware and

computersSoftware only No computers

Attributes / Bundles

Location

Office supplies

Furniture

Computers

Conjoint analysis

Respondents’ ratings of Office Star bundles

Respondents' Ratings

Respondents' ratings for each bundle (use consistent scale, e.g., between 0 and 100)

Respondents / Ratings Bundle 1 Bundle 2 Bundle 3 Bundle 4 Bundle 5 Bundle 6 Bundle 7 Bundle 8

Respondent 1 90 50 50 80 85 40 40 90

Respondent 2 50 55 95 50 50 40 40 85

Respondent 3 40 60 90 60 45 35 45 85

Respondent 4 75 80 60 70 90 65 60 85

Respondent 5 90 80 70 70 80 75 50 75

Bundle 9 Bundle 10 Bundle 11 Bundle 12 Bundle 13 Bundle 14 Bundle 15 Bundle 16

30 60 60 30 30 90 80 40

75 35 20 25 25 85 35 45

80 55 40 45 50 85 50 35

85 70 55 60 90 85 70 65

80 75 50 60 80 75 50 75

Respondents / Ratings

Respondent 1

Respondent 2

Respondent 3

Respondent 4

Respondent 5

Conjoint analysis

Estimating part-worths

Conjoint analysis

Conjoint analysis

Respondents' Preference PartworthsRespondents' preference partworths. The most preferred profiles sum up to 100, the least preferred to 0.Respondents / Attributes and Levels

Less than 2 miles

Within 2-5 miles

Within 5-10 miles


Large assortment

Limited Assortment

Office Furniture

No FurnitureNo

computersSoftware

onlySoftware and

computers

Respondent 1 31 23 0 2 3 0 55 0 1 0 11

Respondent 2 31 16 0 3 7 0 2 0 0 1 61

Respondent 3 14 0 0 0 6 4 4 0 0 22 76

Respondent 4 17 17 0 47 22 0 9 0 0 17 27

Respondent 5 24 8 0 59 39 0 0 1 9 0 15

Respondent 6 49 17 0 22 12 0 26 0 2 0 0

Respondent 7 31 15 0 0 5 0 52 0 8 0 12

Respondent 8 22 6 0 8 9 0 0 1 3 0 68

Respondent 9 24 7 0 0 1 0 0 1 0 21 74

Respondent 10 18 18 0 43 20 0 12 0 0 15 27

Respondent 11 15 10 0 50 32 0 0 13 22 0 4

Respondent 12 50 3 0 21 17 0 22 0 7 0 1

Respondent 13 27 19 0 4 5 0 55 0 0 1 13

Respondent 14 29 12 0 9 13 0 1 0 4 0 58

Respondent 15 17 3 0 0 1 13 0 9 0 11 61

Respondent 16 16 16 0 51 24 0 2 0 0 21 32

Respondent 17 23 0 0 48 31 0 0 12 0 4 17

Respondent 18 45 12 0 33 22 0 18 0 4 4 0

Respondent 19 35 13 0 22 25 0 17 0 0 6 22

Respondent 20 29 15 0 29 32 0 18 0 3 0 21

Respondents’ part-worths for Office Star data

Conjoint analysis

Detailed preference partworths (Enginius)

Less than 2 miles

Within 2 to 5 miles

Within 5 to 10 miles


Large assortment

Limited assortment

Office furniture

No furniture

No computers

Software only

Software and

computers

1 30.99 22.18 0.00 2.30 2.99 0.00 54.96 0.00 0.71 0.00 11.07

2 31.13 16.35 0.00 2.43 6.92 0.00 1.72 0.00 0.00 1.23 60.23

3 13.58 0.20 0.00 0.00 7.07 4.82 4.32 0.00 0.00 22.50 75.04

4 18.03 18.00 0.00 45.82 21.39 0.00 8.65 0.00 0.00 16.41 27.50

5 23.98 8.00 0.00 60.25 39.81 0.00 0.00 1.38 8.11 0.00 14.39

6 49.67 17.26 0.00 22.43 12.03 0.00 26.00 0.00 1.90 0.00 0.07

7 30.81 14.78 0.00 0.68 5.42 0.00 52.09 0.00 7.48 0.00 11.68

8 22.01 5.31 0.00 8.18 9.02 0.00 0.00 1.31 2.81 0.00 67.65

9 23.83 7.45 0.00 0.00 0.86 0.38 0.00 0.43 0.00 22.35 74.88

10 17.83 17.53 0.00 43.17 20.87 0.00 12.21 0.00 0.00 14.38 26.79

11 15.55 10.11 0.00 49.78 31.83 0.00 0.00 12.77 21.90 0.00 4.35

12 50.78 3.36 0.00 20.76 15.99 0.00 21.77 0.00 6.69 0.00 0.32

13 27.21 18.29 0.00 3.97 5.24 0.00 54.17 0.00 0.00 1.16 13.38

14 28.79 11.88 0.00 8.45 12.68 0.00 0.92 0.00 4.12 0.00 57.61

15 17.50 2.90 0.00 0.00 1.22 12.99 0.00 8.46 0.00 11.38 61.04

16 15.35 15.32 0.00 50.54 22.76 0.00 1.44 0.00 0.00 22.05 32.67

17 23.32 0.00 0.38 47.61 31.00 0.00 0.00 12.25 0.00 3.42 16.82

18 44.15 11.92 0.00 32.99 22.04 0.00 19.03 0.00 3.83 3.22 0.00

19 35.91 13.16 0.00 22.36 24.63 0.00 17.05 0.00 0.00 5.31 22.41

20 28.78 14.61 0.00 29.02 31.74 0.00 18.46 0.00 3.04 0.00 21.01

Conjoint analysis

Summary statistics for preference partworths

Conjoint analysis

Conjoint analysis

Uses of conjoint analysis▪ Market segmentation

Q: How would you segment the market using individual-level

conjoint analysis output?

▪ New product design

Q: How can conjoint analysis be used for new product design?

▪ Trade-off analysis (esp. in pricing decisions)

Q: How much could the price of a Dell computer with 160 GB of

hard drive space and 2 GB of RAM, which currently sells for

$1,200, be raised if the screen size were increased from

12.1 in to 15.4 in?

▪ Competitive analysis

Q: How can conjoint analysis be used to simulate market

shares?

Conjoint analysis

Market share simulations

Conjoint analysis

Choice rules for simulations

▪ First-choice rule: the option with the highest utility

is chosen;

▪ Share of preference rule: the choice probability is

equal to the utility of an option relative to the total

utility of all options in the choice set;

▪ Alpha rule: a weighted combination of the first two

rules which maximizes the correspondence with

market shares;

▪ Logit choice rule: similar to the share of preference

rule, but the choice probabilities are computed as in

the logit model;

Conjoint analysis

Market share simulations:

Existing product profiles

Existing Product Profiles

Labels and attribute levels for each existing product profile that already exists in the market.

Attributes / Existing Product Profiles

Office Equipment Department Store

Location Within 2-5 miles Within 2-5 miles

Office supplies Large assortment Limited assortment

Furniture Office furniture No furniture

Computers Software and computers Software only

Conjoint analysis

Market share simulations with

optimal product profiles

Market Share Simulations

Market share predictions for different scenarios, using the Logit Rule.

Scenario / Product profiles

Office Equipment Department StoreMarket Share of Optimal Product

Profile

Predicted market shares 73% 27% n/a

...with Optimal Product 1 34% 13% 53%





Conjoint analysis

Optimal product profiles

Optimal Product ProfilesLabels and attribute levels for each optimal product profile that the software recommends you introduce in this market

Attributes / Optimal Product Profiles

Optimal Product 1

Optimal Product 2

Optimal Product 3

Optimal Product 4

Optimal Product 5

LocationLess than 2

milesLess than 2

milesLess than 2

milesWithin 2-5 miles

Less than 2 miles


assortmentLarge



assortmentLarge

assortment

Furniture Office furniture Office furniture No furniture Office furniture No furniture

ComputersSoftware and

computersSoftware and




computers

Conjoint analysis

Review: Conjoint analysis

Based on the conjoint study, LG management

knows that a price increase from $2,300 to $2,800

leads to a decrease in utility of 3. If utility goes up

by 1 when the screen size is increased from 46 to

54 inches, how much can LG charge for the TV set

with the larger screen?

Conjoint analysis

Next two classes

▪ Thursday: Text analysis and Google analytics

□ In-class exercise: Ottos’ reviews from TripAdvisor

▪ Tuesday: Dürr Environmental, Inc

□ No segmentation, introduction of 1 product only

Conjoint analysis - Pennsylvania State University analysis Compositional vs. decompositional...

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