This document discusses conjoint analysis and provides an example using SPSS. It defines conjoint analysis as a technique used to understand how consumers develop preferences for product attributes. The key steps are identified as identifying the problem, attributes and levels, methodology, collecting responses, analysis, interpretation and application. Types include traditional, adaptive choice-based conjoint analysis. An example uses attributes of cars to identify preferred combinations through partial profile surveys and estimating utilities in SPSS. The results show price, fuel type and model have most importance in driving sales.

1. Presenter:
Karan Bhandari
MBA(AB) 1st Year
IABM, Bikaner

2. Flow of Presentation
Introduction
Applications of Conjoint analysis
Process Flow of Conjoint analysis
Types of Conjoint analysis
How Conjoint analysis works
Partial Profile approach
Example-SPSS
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3. Introduction(1/2)
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Conjoint analysis is a statistical technique used in market research to determine
how people value different features that make up an individual product or service
It is a multivariate technique develop specifically to understand how respondents
develop preferences for any type of object
Conjoint analysis attempts to determine the relative importance, consumers attach
to salient attributes and the utilities they attach to the level of attributes
This information is derived from consumer evaluations of brand profiles
composed of these attributes and their levels

4. Introduction(2/2)
 The respondents are presented with stimuli that consists of attribute levels
 They are asked to evaluate these stimuli that consist of combinations of
attribute levels in terms of their desirability
 Based on the evaluations utility of each level of attribute is determined with help
of Conjoint analysis
 The preference with the highest utility is considered for final selection
 In this model, we think that each possible level of an attribute has a “part worth”
to a level of an attribute, and the sum of the part worthies of its attributes is the
“total worth” to a consumer of a product
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5. Samsung Galaxy Note 8
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BLACK GOLD
Attributes: Memory, Color and Price
Attribute Levels: 16GB, 32GB, 128GB
Black, Gold
₹ 29999, ₹ 34999, ₹ 39999
Profile: 3 x 2 x 3 =18 combinations

6. Applications of Conjoint Analysis
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What features
best optimizemy
product
Determining
composition of
most preferred
brand
How to measure
Brand Value among
competitors
How to do
Product Segmentation
&
Customer
Segmentation
New Product
planning
and design

7. Conjoint Analysis Process flow
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Stage 1
Identify the research
problem
Stage 2
Decide on the attributes
and their levels
Focused Group is the
most practiced
Stage 3
Chose the methodology
Traditional, Adaptive or
Choice Based
Stage 4
Collect responses
Rating or rank order
Stage 5
Run analysis
Individual or aggregative
Stage 6
Interpret results
Stage 7
Validate the results
External or internal
validity tests
Stage 8
Apply the Conjoint results
Product designing,
market segmentation etc.

8. Types of Conjoint Analysis(1/2)
 Traditional Conjoint
 Full Profile
 Partial Profile / Fractional Factorial Design
 Paired Comparison
 Self Explicated
 Adaptive Conjoint Analysis (ACA)
 Choice Based Conjoint (CBC)
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9. Types of Conjoint Analysis(2/2)
Full Profile method- Analysis carries on based on the respondent’s evaluation of all
the possible combinations in the stimuli
Fractional Factorial Design- Method of designing a stimuli that is a subset of the full
factorial design so as to estimate the results based on the assumed compositional rule
Paired Comparison method- Method of presenting a pair of stimuli to the respondent
for evaluation, with the respondent selecting one of the stimuli as preferred
Self Explicated model- compositional technique where the respondent provides the
Part- Worth estimates directlywithout making choices
Adaptive Conjoint Analysis- ACA asks respondents to evaluate attribute levels
directly, and then to assess the importance of each attribute, and finally to make
paired comparisons between profile descriptions
Choice Based Conjoint- An alternative form of conjoint analysis where the
respondent’s task is of choosing a preferred profile similar to what he would actually
buy in the marketplace
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10. How Conjoint Analysis Works(1/2)
 Decompose the overall utility into its individual attribute’s part-worths
Additive model- Overall utility = Sum total of all part-worths
Total worth/ Utility = Part- worth of level i for factor 1+ Part- worth of
level j for factor 2 + …. Part- worth of level n forfactor m
Interaction model- Overall utility > Sum total of all part-worths
Total worth/ Utility = Part- worth of level i for factor 1+ Part- worth of
level j for factor 2 + …. Part- worth of level n forfactor m + I
(Interaction effect between the attributes and theirlevel)
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11. How Conjoint Analysis Works(2/2)
The basic conjoint analysis model may be represented by the
following formula:
Where:
U(X) = overall utility of an alternative
∝𝑖𝑗 = the part-worth contribution or utility associated with
the j th level (j, j = 1, 2, . . . ki) of the i th attribute
(i, i = 1, 2, . . . m)
xjj = 1 if the j th level of the i th attribute is present
= 0 otherwise
ki = number of levels of attribute i
m = number of attributes
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xij
j
ij
m
i
k
XU
i

==
=
11
)( a

12. Partial Profile Approach
 Partial profile is a necessity when the number of attributes and the levels
within the attributes are large
 In such a case, it becomes almost impossible for the respondent to evaluate
the full profile
 4 attributes having 4 levels each will result in 4x4x4x4 = 256 profiles
 Partial profile considers a subset of the entire which would be representative
of the full profile
 This is done through an orthogonal process so thatthe profiles contain the levels
equally or in proportion
 Partial profile eases the pressure of evaluation for the respondent
 Out of 256 profiles, a partial profile might contain only 16 representative
profiles
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13. Example:
Preference of a Car
Attribute Description Levels
Model of the car SUV Sedan Convertible
Type of Fuel Petrol Diesel CNG
Airbags Yes No
Anti-Breaking System No Yes
Price of car 15 Lacs 20 Lacs 25 Lacs
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Problem statement:
In automobile industry what features are driving the sales?
Method used: (Partial Profile Design) Data collection method: (own workout)
There are 108 possible product concepts or cards that can be created from these five attributes:
3 models × 3 fuel types × 2 airbags choice × 2 ABS choice × 3 prices = 108 cards

14. Contd…
108 Cards combination is not feasible to be filled up by every respondent of our
study
So orthogonal design is constructed using SPSS which generates random cards out
of total cards combination which represents the actual cards combination
The cards obtained using orthogonal design are filled-up by the respondents and
asked for their preference order according to the attributes
In the end the Utility of each attribute and card combination is obtained in SPSS
which is used to determine the best possible combination of attributes and levels,
which is further considered for final product design and launch
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15. STEP-1
Generating Orthogonal Design
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16. STEP-2
Adding Factors
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17. STEP-3
Defining Values
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18. STEP-4
Deciding No. of Cases to generate
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19. STEP-5
Orthogonal Design-Data view
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20. STEP-6
Orthogonal Design-Variable view
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21. STEP-7
Display Orthogonal Design
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22. STEP-8
Plancards generated
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23. STEP-9
Dataset of Respondents
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24. STEP-10
Syntax Editor
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25. STEP-11
Syntax Coding
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26. STEP-12
Utility Estimate of Factors
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27. STEP-13
Importance values of Factors
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28. STEP-14
Summary Utilities (1/3)
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29. STEP-14
Summary Utilities (2/3)
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30. STEP-14
Summary Utilities (3/3)
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31. STEP-15
Importance Summary
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32. Conclusion
 Customers perceiving maximum utility from SUV (.750) compared to Sedan(-.288) &
Convertible(-.463)*
 Customers perceiving maximum utility from Diesel (1.071) compared to CNG (.046) &
Petrol(-1.117) *
 Customers perceiving maximum utility from Price worth of 15 Lacs (.600) compared to 20 Lacs
(.300) & 25 Lacs (-.900)*
 Customers perceiving maximum utility with No Airbags(.850) and Yes to Anti-Breaking
System(.788)*
 So, from all the above figures and combination the maximum utility (Total utility=2.421) can be
achieved with the combination of SUV with Diesel with no airbags but fitted with ABS and
Priced at 15 Lacs
 The minimum Utility (Total Utility= -2.234)is found in Convertible with Petrol with airbags
available and no fitting of ABS Priced at 25 Lacs *SlideNo.26
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33. References
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 S. K., Dr. (2017, April 06). 29 SPSS Conjoint Analysis in Hindi Part 1. Retrieved
December 03, 2017, from https://www.youtube.com/watch?v=UJw2C6pgo8Y
 S. K., Dr. (2017, April 06). 30 SPSS Conjoint Analysis in Hindi Part 2. Retrieved
December 03, 2017, from https://www.youtube.com/watch?v=BhBZNtJHd4Y&t=1s
 Curry, J. (1996). Understanding Conjoint Analysis in 15 Minutes
 What is Conjoint Analysis? (n.d.). Retrieved December 03, 2017, from
http://www.sawtoothsoftware.com/products/conjoint-choice-analysis/conjoint-analysis-
software
 Flavors or types of conjoint analysis. (n.d.). Retrieved December 03, 2017, from
http://www.dobney.com/Conjoint/conjoint_flavours.htm

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