ISBM WebinarConjoint Analysis 1 - PowerPoint PPT Presentation

Title: ISBM WebinarConjoint Analysis 1


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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

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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)
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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
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Role of Good Design
Source Robert G. Cooper, Winning at New Products
(1993)
ISBM Webinar-Conjoint Analysis - 4
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Role of Good Design
Source Robert G. Cooper, Winning at New Products
(1993)
ISBM Webinar-Conjoint Analysis 5
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Role of Good Design
Source Robert G. Cooper (1993)
ISBM Webinar-Conjoint Analysis - 6
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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.

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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.)

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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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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.

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Overview Of Conjoint-Based Analysis
We can also reverse the process by determining
which product attributes maximize market share or
revenue.
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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
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Measuring Importance of Attributes
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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.

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Simple Example ofConjoint Analysis
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Simple Example ofConjoint Analysis
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Simple Example ofConjoint Analysis
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Simple Example ofConjoint Analysis
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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.
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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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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?

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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.
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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?

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ISBM Webinar-Conjoint Analysis - 24
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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!
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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?
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Data for Conjoint Analysis Full-Profile Ratings
or Ranks
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Example Part Worths forThree Respondents
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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.

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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.
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Market Share Computation (Dürr Environmental
Controls)

• Market consists of three products and three
  customers

Product
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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
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Demo of MEgtXL software for Conjoint
Live Meeting Sharing Slide

• Edit this slide by selecting Properties in the
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Market Performance ofNew Products Being
Considered
Via Maximum Utility Rule
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Identifying Segments Based onConjoint Part Worths
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Profiling the Segments(Firmographics)
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Profiling the Segments(Decision Processes)
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Profiling the Segments(Customer Business
Strategy)
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Types of Customers in Each Segment
Segment 1
Segment 2
Segment 3
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Performance of New Products in Segment 1(Maximum
Utility Rule)
Compare with performance for the whole market
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Performance of New Products in Segments 2 and
3(Maximum Utility Rule)
Compare with performance for the whole market
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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.

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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

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Example of Adjustments forAwareness and
Availability
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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)

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Choice-Based Conjoint Question
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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

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