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Week 4: Product management II - Coggle Diagram
Week 4: Product management II
Conjoint analysis
understand how consumers
develop preferences
for products/ services
asks them to
choose
between
products that have different levels of attributes
=> determine
part- worth
of each attribute (
example
: thin crust pizza for $10 or thick for $12)
can be used to
Identify
customers' willingness to pay
for different attributes/ products
Develop
forecasts
of sales and market share
Identify
relative importance of different attributes
to consumers
Identify
consumers' preferences
for different product combinations
Intuition behind (
p.8
)
Conjoint
compares all products options
and
computes average change in utility
when an attribute is changed
limitations (
p.25
)
Steps in conjoint analysis
Collect data
Pair- wise comparisons: comparing 2 products
Rank ordering: in the order of preferences (1 being most preferred)
Rating scale evaluation: 0 - 100
Obtain part- worth and compute utilities
can be derived using
regression analysis
linear regression (p.17)
dummy variable regression (p.18)
utility = sum of part- worths
example
: p.19- 22
Range of PWs = Max PW - Min PW
(it can be negative)
Identify product profile
Identify attributes and their levels
: through focus group, descriptive research, exploratory research, expert judgement, ...
Develop
product bundles
to evaluate: possible
product combinations
(full factorial vs fractional factorial - p.11&12)
Evaluate product options (p.24)
Estimates
market share
and identify
prospective products
Segments customers based on part- worth
Research
objectives (p. 27)
research design
respondents
data collection methodology
conjoint design (p. 29)
relative importance of attributes (p. 30)
estimated choice probabilities (p. 31)
Management implications
use conjoint analysis when
Product is
decomposable
into set of attributes
High involvement product
New concept
involves important trade- offs
Alternatives can be easily described
verbally or pictorially