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Title: ISBM WebinarConjoint Analysis 1


1
Design of New ProductsThrough Conjoint Analysis
  • Role of design in new product development
  • Conjoint Analysis for product (offering) design
  • Illustration of Dürr Environmental Controls
  • Caveats and Tips
  • QA

2
Role of Good Design
  • 80 of a products manufacturing costs are
    incurred during the first 20 of its design
    (varies with product category).

Source Reinersten (Mckinsey Company)
3
Role of Good Design
Based on a study of 203 products in B2B -- Robert
G. Cooper, Winning at New Products (1993)
. Success measured using four factors (1)
whether it met or exceeded managements criteria
for success, (2) the profitability level (1-10
scale), (3) market share at the end of three
years, and (4) whether it met company sales and
profit objectives (1-10 scale).
ISBM Webinar-Conjoint Analysis - 3
4
Role of Good Design
Source Robert G. Cooper, Winning at New Products
(1993)
ISBM Webinar-Conjoint Analysis - 4
5
Role of Good Design
Source Robert G. Cooper, Winning at New Products
(1993)
ISBM Webinar-Conjoint Analysis 5
6
Role of Good Design
Source Robert G. Cooper (1993)
ISBM Webinar-Conjoint Analysis - 6
7
What is Conjoint Analysis?
  • Conjoint Analysis is a systematic approach for
    matching product design with the needs and wants
    of customers, especially in the early stages of
    the New Product Development (NPD) process.
  • That is, it helps you design in a superior
    product early in the NPD process.

8
Conjoint Analysis in NPD
  • Conjoint Analysis is a way to determine what
    attributes/ features of a product (or service)
    would offer the most value to customers and the
    company, even before the product is designed or
    prototyped.
  • Customers cannot get everything they want in a
    product, especially all for the same price
  • The new product must win in the market place
    against existing competing products
  • There may be distinct segments of customers who
    prefer different features
  • The new product should meet management targets
    (for market share, profitability, etc.)

9
Poll
Live Meeting Poll
  • Have you been involved in conducting or using
    Conjoint analysis in the past three years?
  • Yes
  • No

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10
What Does Conjoint Analysis Do?(Measure
Importance by Assessing Preferences)
  • Provides numerical values associated with
  • the relative importance that customers attach to
    the attributes of a product category
  • The value (utility or part-worth) provided to
    customers by each potential feature (attribute
    option) of an offering
  • Helps identify product design(s) that maximize
    market share or other indices.

11
Overview Of Conjoint-Based Analysis
We can also reverse the process by determining
which product attributes maximize market share or
revenue.
12
Typical Approach to Measuring Importance of
Product Attributes
When choosing a restaurant, how important
is Circle one Not Very Important
Important Decor 1 2 3 4 5 6 7
8 9 Location 1 2 3 4 5 6 7 8
9 Quality of food 1 2 3 4 5 6 7
8 9 Price 1 2 3 4 5 6 7 8
9
13
Measuring Importance of Attributes
14
Determining Importance by Measuring Product
Preferences
  • The basic assumption of Conjoint Analysis is that
    customers cannot reliably express how they weight
    separate features of the product in forming their
    preferences. However, we can infer the relative
    weights by asking for their evaluations of
    alternate product concepts through Conjoint
    Analysis.

15
Simple Example ofConjoint Analysis
16
Simple Example ofConjoint Analysis
17
Simple Example ofConjoint Analysis
18
Simple Example ofConjoint Analysis
19
Converting Overall Ratings toPart-Worths for
Attribute Levels
  • Example Italian vs Thai 20 16 4 util
    units 10 vs 15 22 14
    8 util units
  • So Thai is worth 2.50 more than Italian for
    this customer

Þ Can use to obtain value to customer of
service (non-price) attributes.
20
Poll
Live Meeting Poll
  • Which one, if any, of the following is the most
    important issue with respect to your New Product
    Development process
  • New product priced incorrectly
  • New product not targeted to the right segments
  • Poor product definition in the early stages of
    development
  • Not sure how many different versions of our
    product to offer
  • Our new products rarely win in our markets
  • Other

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21
Examples of Business Issues Addressed by Conjoint
Analysis
  • Given a target cost for a product, would it be
    more profitable for us to enhance product
    reliability or its performance?
  • Are we pricing our new product according to its
    value for customers?
  • How many units of the new product can we hope to
    sell?
  • What will happen to sales of our product when a
    competitor alters its product line?
  • Which customer segments will find our new product
    to be most attractive?
  • Would it be profitable to offer different product
    versions to different segments?
  • How valuable is my brand to customers?
  • Why do our customers buy our product?

22
Conjoint Study Process
Stage 1Designing the conjoint study Step
1.1 Select attributes relevant to the product or
service category, Step 1.2 Select levels for
each attribute, and Step 1.3 Develop the
product bundles to be evaluated. Stage
2Obtaining data from a sample of
respondents Step 2.1 Design a data-collection
procedure, and Step 2.2 Select a computation
method for obtaining part-worth functions. Stage
3Evaluating product design options Step
3.1 Segment customers based on their part-worth
functions, Step 3.1 Select choice rule,
and Step 3.3 Design market simulations to
facilitate decision making.
23
Air Pollution Control System Example
  • Dürr Environmental Controls, Inc. is developing a
    new air pollution control system (thermal
    oxidizer) to compete against existing offerings
    from Waste Watch, Thermatrix, and Advanced Air.
  • Key offering attributes
  • Thermal efficiency
  • Delivery time
  • List price
  • Delivery terms
  • Q What to offer?
  • Who will buy/who to target?
  • Where will share come from?

24
ISBM Webinar-Conjoint Analysis - 24
25
An Example Conjoint StudyAir Pollution Control
Equipment
Attributes
  • Price (4 options)
  • Delivery_terms (4 options)
  • Performance specs (4 options)
  • Delivery time (4 options)

Efficiency Delivery time List Price Exceed
EPA by 9 6 months 600k Exceed EPA by
5 9 months 700k Meets EPA target
12 months 800k Short EPA by 5 15
months 900k Delivery terms Installed, 2-year
warranty Installed, 1-year warranty Installed,
service contract FOB seller, service contract A
total of 256 (4x4x4x4) different offerings can be
designed from these options!
26
Data for Conjoint Analysis Paired Comparisons
Deluxe Mid-level model model Efficiency Excee
d EPA by 9 Exceed EPA by 5 Delivery time 12
months 6 months List Price 800,000 700,000 Deliv
ery terms Installed, 1 year Installed, service
contract warranty Which do you prefer?
Which one would you buy?
27
Data for Conjoint Analysis Full-Profile Ratings
or Ranks
28
Example Part Worths forThree Respondents
29
Rules for Converting Preferences to Shares
Maximum utility rule Under this choice rule,
each customer selects the product that offers
him/her the highest utility among the competing
alternatives. Share of utility rule Under this
choice rule, the customer selects each product
with a probability that is proportional to the
utility of that compared to the total utility
derived from all the products in the choice set.

30
Other Choice Rules
Logit choice rule This is similar to the share
of utility rule, except that it gives larger
weights to more preferred alternatives and
smaller weights to less preferred
alternatives. Alpha rule Modified version of
share of utility rule. Before applying the share
of utility, the utility functions are modified by
an alpha factor so that the computed market
shares of existing products are as close as
possible to their actual market shares.
31
Market Share Computation (Dürr Environmental
Controls)
  • Market consists of three products and three
    customers

Product
32
Market Share Computation(Dürr Environmental
Controls)
Computed Utility for Products
  • Maximum utility Rule If we assume customers will
    only buy the product with the highest utility,
    the market share for Waste Watch is 2/3 and 1/3
    for Advanced Air.
  • Share of preference rule If we assume that each
    customer will buy each product in proportion to
    its utility relative to the other products, then
    market shares for the three products are

Thermatrix 34.8 Waste Watch 30.3
Advanced Air 34.9
33
Demo of MEgtXL software for Conjoint
Live Meeting Sharing Slide
  • Edit this slide by selecting Properties in the
    Live Meeting Presentation menu.

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displayed in Live Meeting. Edit this slide by
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34
Market Performance ofNew Products Being
Considered
Via Maximum Utility Rule
35
Identifying Segments Based onConjoint Part Worths
36
Profiling the Segments(Firmographics)
37
Profiling the Segments(Decision Processes)
38
Profiling the Segments(Customer Business
Strategy)
39
Types of Customers in Each Segment
Segment 1
Segment 2
Segment 3
40
Performance of New Products in Segment 1(Maximum
Utility Rule)
Compare with performance for the whole market
41
Performance of New Products in Segments 2 and
3(Maximum Utility Rule)
Compare with performance for the whole market
42
Dürr Environmental ControlsCompany Decisions
  • Operationally, it made sense to combine segments
    2 and 3 into one segment.
  • It was more profitable to offer two products to
    the market (instead of just one, Servair)
    Servair targeted at segment 1, and Premier
    targeted at segments 2 and 3.

43
Poll
Live Meeting Poll
  • Do you see any opportunities for applying
    Conjoint Analysis in your New Product Development
    efforts?
  • Yes
  • No

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44
Other Issues That Can Be Explored
  • Make adjustments to computed market shares to
    reflect levels of awareness and distribution for
    the competing products
  • Assess revenue/profit potential of a new product
  • Assess degree of cannibalization by the new
    product
  • Identify optimal products by segment

45
Example of Adjustments forAwareness and
Availability
46
The Well-Known Flavors of Conjoint Analysis
  • Traditional Conjoint (with OLS estimation)
  • Adaptive Conjoint
  • Hybrid Conjoint
  • Choice-Based Conjoint (with Hierarchical Bayes
    estimation)
  • Partial Profile Conjoint
  • Fast Polyhedral Conjoint (with Analytic Center
    estimation)

47
Choice-Based Conjoint Question
48
Some Caveats and Tips
  • Uses a compensatory model of customer utility
    (may not work well when customers have
    lexicographic preferences)
  • Do not ask respondents about things they would be
    unable to answer
  • Pre-test Try simple conjoint studies before
    investing a lot of money/time into such an effort
    (e.g., 4-6 attributes with 2-3 options each)
  • Present realistic product profile information to
    respondents (e.g., pictures)
  • Minimize respondent fatigue

49
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