T1 Conjoint Analysis

Question 1

Conjoint Analysis (CA)

purpose:

2 problems

Answer 1

measuring customer preference

• customers may not have enough introspection to know their own preference
• they may answer in a socially desirable way

Question 2

at which of the 5 phases of purchasing is preference involved?

Answer 2

1. recognition of need
2. info search

–> 3. evaluation of alternatives

4. purchase decision
5. post-purchase cognitions

Question 3

3 elements of CA

Answer 3

1. attributes

2. attributes levels

3. products = combinations of attributes levels

Question 4

Procedure of a basic conjoint analysis - in 5 steps

Answer 4

1. Acquire the preference scores of products, then
   * as.paw.ri.ri!*
2. Compute the average score for each attribute level
3. Compute the part worth for each attribute level
4. Compute the raw importance for each attribute
5. Compute the relative importance for each attribute

Question 5

part worth:

meaning

formula

Answer 5

normalized score in CA

part_worth( attribute_level ) =

( avg_score( attribute_level ) - min_avg_score(all) ) /

( max_avg_score(all) - min_avg_score(all) )

Question 6

raw importance of an attribute:

meaning

formula

Answer 6

def = influence on customer preference

raw_importance = max_for_attrib( PW ) - min_for_attrib( PW )

Question 7

relative importance of an attribute:

meaning

formula

Answer 7

how influential is that attribute on customer preference

relative_importance = raw_importance / sum(raw_importances)

Question 8

3 problems of CA

Answer 8

• it is key for you to identify the attributes well beforehand
• it is difficult to measure image & brand impact
• customers can easily be overloaded by choices