1. Conjoint analysis

2. Outline Conjoint analysis as a decompositional preference model
Steps in conjoint analysis
Uses of conjoint analysis

3. 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;

4. 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.

5. Example of a decompositional model
Rank the following four descriptions of laptop computers in terms of overall preference:
Profile 1
Profile 2
Profile 3
Brand
Dell
Apple
Size of Hard Drive
320
160
Amount of RAM 2 4
Screen size
15.4
12.1
Price
$1,200
$1,500
Rank

6. 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;

7. 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

8. 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

9. Example: Laptop Profiles
Brand
Hard Drive
RAM
Screen
Price
Dell
320 GB
2 GB
15.4 in
$1,200
Apple
4 GB
160 GB
$900
12.1 in
$1,500

10. Product profiles Full factorial designs: Fractional 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

11. Example: Laptop Profiles
Brand
Hard Drive
RAM
Screen
Price
Dell
320 GB
2 GB
15.4 in
$1,200
Apple
4 GB
160 GB
$900
12.1 in
$1,500

12. 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.

13. 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

14. Example: Laptop Profiles
Brand
Hard Drive
RAM
Screen
Price A B
Dell
320 GB
2 GB
15.4 in
$1,200 9 6
Apple
4 GB 12
160 GB
$900 5 11
12.1 in
$1,500 4 3 1 10 8 7 2

15. In-class exercise
Using the data in the table, answer the following questions:
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.)
What’s the relative importance of the five attributes for the two consumers?
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?

16. Consumer A
Consumer B
Apple
5.67
9.50
Dell
7.33
3.50
160HD
6.17
5.50
320HD
6.83
7.50
2RAM
6.33
6.00
4RAM
6.67
7.00
12.1in
5.83
5.33
15.4in
7.17
7.67
$900
10.25
6.75
$1200
$1500
2.5

17. Consumer A
Consumer B
Apple
5.67
-.83
9.50
+3.00
Dell
7.33
+.83
3.50
-3.00
160HD
6.17
-.33
5.50
-1.00
320HD
6.83
+.33
7.50
+1.00
2RAM
6.33
-.17
6.00
-.50
4RAM
6.67
+.17
7.00
+.50
12.1in
5.83
-.67
5.33
-1.17
15.4in
7.17
+.67
7.67
+1.17
$900
10.25
+3.75
6.75
+.25
$1200
$1500
2.5
-4.00

19. In-class exercise
Using the data in the table, answer the following questions:
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.)
What’s the relative importance of the five attributes for the two consumers?
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?

20. Consumer A Consumer B Apple 5.67 -.83 1.66 14% 9.50 +3.00 6.00 50%
Attribute level
Mean for level across all profiles
Mean as deviation from zero
Range on attribute
Percentage importance
Apple
5.67
-.83
1.66
14%
9.50
+3.00
6.00
50%
Dell
7.33
+.83
3.50
-3.00
160HD
6.17
-.33
.67 6%
5.50
-1.00
2.00
17%
320HD
6.83
+.33
7.50
+1.00
2RAM
6.33
-.17
.33 3%
-.50
1.00 8%
4RAM
6.67
+.17
7.00
+.50
12.1in
5.83
-.67
1.33
11%
5.33
-1.17
2.33
19%
15.4in
7.17
+.67
7.67
+1.17
$900
10.25
+3.75
7.75
66%
6.75
+.25
.75
$1200
$1500
2.5
-4.00
=11.74

21. In-class exercise
Using the data in the table, answer the following questions:
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.)
What’s the relative importance of the five attributes for the two consumers?
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?

22. 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?

23. 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?

24. 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 14 6 3
Respondent 2 50 17 8
Respondents / Attributes and Levels
Respondent 1
Respondent 2
12.1
15.4
900
1200
1500 11 66 36 19 6

25. Software and computers
Office Star data
Conjoint Study Design
Attributes and attribute levels of the Conjoint study.
Attributes / Levels
Level 1
Level 2
Level 3
Ordering
Location
Less than 2 miles
Within 2-5 miles
Within 5-10 miles
Decreasing
Office supplies
Very large assortment
Large assortment
Limited Assortment
Unordered
Furniture
Office Furniture
No Furniture
Computers
No computers
Software only
Software and computers

26. Office Star bundles Bundles
Attribute 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
Location
Less than 2 miles
Within 2-5 miles
Office supplies
Very large assortment
Large assortment
Limited Assortment
Furniture
Office Furniture
No Furniture
Computers
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 2-5 miles
Very large assortment
Large assortment
Limited Assortment
No Furniture
Office Furniture
Software and computers
Software only
No computers
Attributes / Bundles
Location
Office supplies
Furniture
Computers

27. Respondents’ ratings of Office Star bundles
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 80 85 40
Respondent 2 55 95
Respondent 3 60 45 35
Respondent 4 75 70 65
Respondent 5
Respondents / Ratings
Respondent 1
Respondent 2
Respondent 3
Respondent 4
Respondent 5
Bundle 9
Bundle 10
Bundle 11
Bundle 12
Bundle 13
Bundle 14
Bundle 15
Bundle 16 30 60 90 80 40 75 35 20 25 85 45 55 50 70 65

28. Estimating part-worths

30. Respondents’ part-worths for Office Star data
Respondents' Preference Partworths
Respondents' 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
Very large assortment
Large assortment
Limited Assortment
Office Furniture
No Furniture
No computers
Software only
Software and computers
Respondent 1 31 23 2 3 55 1 11
Respondent 2 16 7 61
Respondent 3 14 6 4 22 76
Respondent 4 17 47 9 27
Respondent 5 24 8 59 39 15
Respondent 6 49 12 26
Respondent 7 5 52
Respondent 8 68
Respondent 9 21 74
Respondent 10 18 43 20
Respondent 11 10 50 32 13
Respondent 12
Respondent 13 19
Respondent 14 29 58
Respondent 15
Respondent 16 51
Respondent 17 48
Respondent 18 45 33
Respondent 19 35 25
Respondent 20

31. Software and computers
Detailed preference partworths (Enginius)
Less than 2 miles
Within 2 to 5 miles
Within 5 to 10 miles
Very large assortment
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
54.96
0.71
11.07 2
31.13
16.35
2.43
6.92
1.72
1.23
60.23 3
13.58
0.20
7.07
4.82
4.32
22.50
75.04 4
18.03
18.00
45.82
21.39
8.65
16.41
27.50 5
23.98
8.00
60.25
39.81
1.38
8.11
14.39 6
49.67
17.26
22.43
12.03
26.00
1.90
0.07 7
30.81
14.78
0.68
5.42
52.09
7.48
11.68 8
22.01
5.31
8.18
9.02
1.31
2.81
67.65 9
23.83
7.45
0.86
0.38
0.43
22.35
74.88 10
17.83
17.53
43.17
20.87
12.21
14.38
26.79 11
15.55
10.11
49.78
31.83
12.77
21.90
4.35 12
50.78
3.36
20.76
15.99
21.77
6.69
0.32 13
27.21
18.29
3.97
5.24
54.17
1.16
13.38 14
28.79
11.88
8.45
12.68
0.92
4.12
57.61 15
17.50
2.90
1.22
12.99
8.46
11.38
61.04 16
15.35
15.32
50.54
22.76
1.44
22.05
32.67 17
23.32
47.61
31.00
12.25
3.42
16.82 18
44.15
11.92
32.99
22.04
19.03
3.83
3.22 19
35.91
13.16
22.36
24.63
17.05
22.41 20
28.78
14.61
29.02
31.74
18.46
3.04
21.01

32. Summary statistics for preference partworths

35. 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?

36. Market share simulations

37. 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;

38. Market share simulations: 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
Office supplies
Large assortment
Limited assortment
Furniture
Office furniture
No furniture
Computers
Software and computers
Software only

39. Market share simulations with optimal product profiles
Market share predictions for different scenarios, using the Logit Rule.
Scenario / Product profiles
Office Equipment
Department Store
Market Share of Optimal Product Profile
Predicted market shares
73%
27%
n/a
...with Optimal Product 1
34%
13%
53%
...with Optimal Product 2
36%
14%
50%
...with Optimal Product 3
39%
47%
...with Optimal Product 4
40%
15%
45%
...with Optimal Product 5
41%
43%

40. Optimal product profiles
Labels 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
Location
Less than 2 miles
Within 2-5 miles
Office supplies
Very large assortment
Large assortment
Furniture
Office furniture
No furniture
Computers
Software and computers

41. 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?

42. 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