3. Conjoint Analysis and Concept
Testing
Concept testing
Show one product concept and get overall “Purchase
Intent” feedback
Also get product diagnostics
Conjoint Analysis
Show multiple concepts and ask for overall preference
Concepts differ on Attributes and levels within an
attribute
Based on overall preference get “part-worths” for
attributes and levels within an attribute
4. A Survey
Familiarity & usage of value assessment methods
58 industrial firms in the top 125 of the Fortune 500
list
16 market research firms from the top 40
6. Conjoint Analysis in Product
Design
Should we offer our business travelers more room space or a
fax machine in their room?
Given a target cost for a product, should we enhance product
reliability or its performance?
Should we use a steel or aluminum casing to increase
customer preference for the new equipment?
7. P&G and Disposable Diapers
Question: What value do consumers associate with two
improved features in disposable diapers:
Improved absorbency
Elastic waistband
8. Conjoint Analysis Assumption
Products can be defined by their individual
attributes and levels within the attribute
Consumer responses to the overall preference
can be then partitioned to attributes
17. Notebook computer example
Processing speed:
2) Hard drive:
3) Memory:
1.5 GHz or 2.5 GHz
120 GB or 160 GB
1 GB or 2 GB RAM
There are 8 different combinations of notebook - defined as product profiles:
20. Part Worth Estimation
Regression of ranks vs the attributes
U = a + b1*Processor + b2*Hard Drive + b3*Memory
The intution
U 1 a b1 0 b2 0 b3 0 a
U 2 a b1 1 b2 0 b3 0 a b1
U 3 a b1 0 b2 1 b3 0 a b2
U 4 a b1 0 b2 0 b 3 1 a b3
a U 1 1
b1 U 2 U 1 5 1 4
b2 U 3 U 1 3 1 2
b3 U 4 U 1 2 1 1
21. Forecast preferences to check
accuracy
U5 a b1 1 b2 1 b3 0 7
U6 a b1 0 b2 1 b3 1 4
U7 a b1 1 b2 0 b3 1 6
U8 a b1 1 b2 1 b3 1 8
22. Weightage and Relative Importance of Each Attribute
b1 4
b1 b2 b3 7
b2 2
b1 b2 b3 7
b3 1
b1 b2 b3 7
Processo
r Speed
Hard
Drive
Memory
= 57%
= 29%
= 14%
23. Segment consumers based on
preferences
Are there segments in terms of preferences?
Here preference is the “basis” and “age” could be
the descriptor
24. Eg. Packaged Soup
Which is the most important attribute & which is the best product to
introduce?
25. Conjoint Simulation - The Motivation
1. What share can the new brand obtain?
2. Where does this share will come from?
26. Conjoint Simulation - The Principle
Before introduction share: A=40%, B=60%.
After introduction share: A=20%,B=50%, and New=30%.
28. Stage 1—Design the conjoint study:
Step 1.1:
Step 1.2:
Step 1.3:
Select attributes relevant to the product or service category,
Select levels for each attribute, and
Develop the product bundles to be evaluated.
Stage 2—Obtain data from a sample of respondents:
Step 2.1:
Step 2.2:
Design a data-collection procedure, and
Select a computation method for obtaining part-worth
functions.
Stage 3—Evaluate product design options:
Step 3.1:
Step 3.2:
Step 3.3:
Segment customers based on their part-worth functions,
Design market simulations, and
Select choice rule.
Conjoint Study Process
29. 29
Attributes Should Be…
Determinant
Easily measured and communicated
Controllable by the company
Realistic
Such that there will be preferences for some
levels over others
Compensatory
As a set, sufficient to define the choice
situation
Without built-in redundancies
30. 30
How Many Levels per Attribute?
Levels and range should be
meaningful, informative, and realistic to
consumers and producers
Avoiding absurd configurations
Marginal increases in levels can greatly
increase respondent’s task
31. 31
Which Data Collection Method?
Full profile: Show complete list of attributes
Limited to 6-7 attributes
Pair-wise: Show pairs of attributes in matrix; each cell
rated from most to least preferred
Lacks realism
Inconsistent responses likely
32. Designing a Frozen Pizza – Paired
Comparison Approach
1. Crust 2. Type of Cheese 3. Price
Pan Romano $ 9.99
Thin Mixed cheese $ 8.99
Thick Mozzeralla $ 7.99
4. Topping
Pineapple
Veggie
Sausage
Pepperoni
5. Amount of Cheese
2 oz.
4 oz.
6 oz.
A total of 324 (3 * 4 * 3 * 3 * 3) different pizzas can be developed from these options!
