New Products

1
New Products

• Product Design using Conjoint Analysis
• Forecasting with Diffusion Models
• Pre-Test Market Models

2
New Product Decision Models

• Product design using conjoint analysis
• Forecasting the pattern of new product adoptions
  (Bass Model)
• Forecasting market share for new products in
  established categories (Assessor model)

3
Newness of Products

• Repositioning

• BreakthroughsMajor Product Modifications

New to World

• Line Extensions

• Me Too Products

New to Company
4
New Products as Part of Corporate Strategy
Markets
Existing
New
Market Penetration
Market Development
Existing
Products
New Product Development
New
(Diversification)
5
The New Product Development Process
Reposition
Harvest
Go
No
Design Identifying customer needs Sales
forecasting Product positioning Engineering Mark
eting mix assessment Segmentation
Go
No
Go
No
6
Some Product Design Questions
Should we offer our business travelers more room
space or a fax machine in their room? Should we
offer more leisure-time activities (sauna,
exercise room, tennis courts) or more food
related services (several dining options, vending
machines, in-room kitchen facilities)? Should we
use a steel or aluminium casing to increase
customer preference for our new extrusion
equipment?
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What is Conjoint Analysis?

• A way to incorporate the structure of customer
  preferences into the new product design process.
  It helps evaluate how customers make tradeoffs
  between various product attributes (a
  decompositional approach).
• The basic outputs of conjoint analysis are
• A numerical assessment of the relative importance
  each customers attaches to attributes of a
  product set.
• The value (utility) provided to each customer by
  each attribute option.

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Use of Conjoint Analysis

• Designing new products that enhance consumer
  utility.
• Forecasting sales/market share of alternative
  product concepts.
• Identifying market segments for which a given
  concept has high value.
• Identifying the best concept for a target
  segment.
• Pricing products/product bundles.
• Product line management.
• Positioning new products to different segments.

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Product Design Conjoint Analysis

• The approach derives customers utility values
  for attributes and attribute options based on
  customers stated overall preferences for
  different bundles of attributes. The following
  example shows Memory and Price bundles.

PriceMemory 1,000 1,500 2,000 8
Mb 4 2 1 16 Mb 7 5 3 24 Mb 9 8 6 9 Most
preferred 1 Least preferred
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Simplified Part-Worth(Utility) Calculation
Price Part- Memory 1,000 1,500 2,000 Wor
th 8 Mb 4 2 1 7/3 2.3 16 Mb 7 5 3 15/3 5.0 24
Mb 9 8 6 23/3 7.7 20/3 15/3 10/3 Part-Worth 6.7
5.0 3.3 9 Most preferred 1
Least preferred
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How to Use inDesign/Tradeoff Evaluation

• Example 24 Mb vs 16 Mb 7.7 5.0 2.7 units
• 1,000 vs 1,500 6.7 5.0 1.7 units
• So D 8 Mb is worth more than 500 to this
  customer.
• 2.7
• ( _at_ (1,500 1,000) _at_ 795)
• 1.7
• Can use to assess value to customer of
  non-product (service) attributes.

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Another Example to Illustrate the Concepts of
Conjoint Analysis Designing a Frozen Pizza
Attributes G Type of crust (3 types) G
Topping (4 varieties) G Type of cheese (3
types) G Amount of cheese (3 levels) G Price
(3 levels)
Crust Type of Cheese Price Pan Romano
9.99 Thin Mixed cheese 8.99
Thick Mozzeralla 7.99 Topping Amount of
Cheese Pineapple 2 oz. Veggie 4
oz. Sausage 6 oz. Pepperoni A total
of 324 (3 4 3 3 3) different pizzas can
be developed from these options!
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Designing a Frozen PizzaA More Complete Design
Attributes G Type of crust (3) G Amount of meat
(3) G Types of peppers (3) G Type of cheese
(3) G Type of sauce (3) G Presence of olives
(2) G Amount of cheese (3) G Amount of sauce
(3) G Presence of oil (2) G Type of meat
(3) G Presence of mushrooms (2) G Price
(3) Prototypes 81 prototype pizzas from 105,000
possible profiles. Person Attributes
G Sex G Household size G Category
usage G Age G Favorite brand G Region G Presence
of teenagers Study Approach G Each respondent
rates 3 of the 81 prototypes along with a
control. G Likelihood of purchase,
conditioned on price. G Appropriateness for
various meals/snacks. G Appropriateness for
various family members.
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Example Paired Comparison
Aloha Meat-lovers Special treat Crust Pan Thi
ck Topping Pineapple Pepperoni Type of
cheese Mozzarella Mixed cheese Amount of
cheese 4 oz 6 oz Price 8.99 9.99 Which do you
prefer? Which one would you buy?
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Example Ratings
Product ExampleBundle Type of
Amount PreferenceN umber Crust Topping
Cheese of Cheese Price Score 1 Pan Pineapple
Romano 2 oz 9.99 0 2 Thin Pineapple Mixed 6
oz 8.99 43 3 Thick Pineapple Mozzarella 4
oz 8.99 53 4 Thin Pineapple Mixed 4
oz 7.99 56 5 Pan Veggie Mixed 4
oz 8.99 41 6 Thin Veggie Romano 4
oz 7.99 63 7 Thick Veggie Mixed 6
oz 9.99 38 8 Thin Veggie Mozzarella 2
oz 8.99 53 9 Thick Pepperoni Mozzarella 6
oz 7.99 68 10 Thin Pepperoni Mixed 2
oz 8.99 46 11 Pan Pepperoni Romano 4
oz 8.99 80 12 Thin Pepperoni Mixed 4
oz 9.99 58 13 Pan Sausage Mixed 4
oz 8.99 61 14 Thin Sausage Mozzarella 4
oz 9.99 57 15 Thick Sausage Mixed 2
oz 7.99 83 16 Thin Sausage Romano 6 oz 8.99 70
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Example Computed Part-Worth for Attributes
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Example Part-Worths for Attribute Options
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Conjoint Computations
m ki U(P) å å aij xij i1 j1
where P a particular product/concept of
interest, U(P) the utility associated with
product P, aij Utility associated with the jth
level (j 1, 2, 3, . . . , ki) on the ith
attribute (part-worth), ki number of levels of
attribute i, m number of attributes,
and xij 1 if the jth level of the ith
attribute is present in product P, 0 otherwise.

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Market Share Forecast

• The relevant market consists of products P1, P2,
  . . . , PN. Some of theses may be existing
  products and, others concepts being evaluated.
• Each consumer will prefer to buy the product with
  the highest utility among those available.
• Then forecasted market share for products Pi is
  given by
• K Consumers who prefer i
• MS (Pi) å
• K1 K
• where K is the number of consumers who
  participated in the study.

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Example Market Share Computation (Frozen Pizza
Example)

• Market consists of three products and three
  consumers

Product (P1) (P2) (P3)
Aloha Meat-lovers Veggie Special Treat
Delite Crust Pan Thick Thin Topping Pineapple Pepp
eroni Veggie Type of cheese Mozzarella Mixed
cheese Romano Amt. of cheese 4 oz. 6 oz. 2
oz. Price 8.99 9.99 7.99
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Example Market Share Computation (Frozen Pizza
Example)
Consumers Part-Worths
C1 C2 C3 Base 1.3 2.4 3.2 Thin 0.2 0.5
1.0 Thick 0.4 0.75 1.1 Veggie 0.5 0.6 1.2 Sa
usage 0.1 0.2 0.2 Pepperoni 1.0 0.3 0.9 Mixe
d cheese 1.5 0.3 0.3 Mozzarella 0.5 1.2 0.1
4 oz. 1.5 2.1 0.2 6 oz. 3.0 1.5 0.3 8.99 0
.5 1.2 0.1 9.99 3.0 2.5 0.3
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Example Market Share Computation (Frozen Pizza
Example)

• Computed Utility for Products
• Customer P1 P2 P3
• C1 2.8 4.2 2.0
• C2 4.5 2.75 3.5
• C3 3.6 3.9 1.0
• Infrequently purchased productsConsumers only
  buy the brand with the highest utility. Then,
  the market share for each product is 1/3.
• Frequently purchased productsExample If
  consumers buy their most preferred brand 80 of
  the times, and their second most preferred brand
  20 of the times, then the market shares for the
  3 products are
• P1 6/15 P2 4/15 P3 5/15

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Translating Utility (Preference)to Choice
Probabilities

• Maximum utility rule (described
  earlier)
• uij
• Share of preference rule pij
• å uij
• j
• euij
• Logit choice rule pij
• å euij
• j

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Translating Choice Probabilitiesinto Market
Shares

• Describe competitive set
• Assign individual weights if any
• Compute market share
• å wi pij
• i
• mj
• å å wi pij
• j i
• mj market share of product j
• wi weights assigned to individual i

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Situations Where Conjoint Applications Might Be
Valuable

• The new concept involves important tradeoffs
  affecting design, production, marketing, or other
  operational variables.
• Product/service is realistically decomposable
  into a set of basic attributes.
• Product/service choice tends to be high
  involvement.
• Factorial combinations of basic attribute levels
  are believable.
• Desirable new-product alternatives can be
  synthesized from basic alternatives.
• Product/service alternatives can be realistically
  described, either verbally or pictorially.
  (Otherwise, actual product formulations should be
  considered).
• Perceptions of hypothetical combinations are
  reasonably homogeneous across members of the
  target group.

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Conjoint Study
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 3.2 Design market simulations,
and Step 3.3 Select choice rule.
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Some Commercial Applications of Conjoint Analysis
Consumer Industrial/BusinessNon-Durables Goods Ot
her Products 1. Bar soaps 1. Copying
machines 1. Automotive styling 2. Hair
shampoos 2. Printing equipment 2. Automobile
tires 3. Carpet cleaners 3. Fax
machines 3. Car batteries 4. Synthetic-fiber
garments 4. Data transmission 4. Ethical
drugs 5. Gasoline pricing 5. Lap top
computer 5. Employee benefit 6. Pantyhose 6. Jo
b offers to MBAs package Financial
Services Transportation Other Services 1. Branch
bank services 1. Air Canada 1. Car rental
agencies 2. Auto insurance policies 2. IATA 2.
Telephone service pricing 3. Health insurance
policies 3. American Airlines 3. Hotels 4. Cred
it card features 4. Canadian National
Railway 4. Medical laboratories 5. Consumer
discount card 5. Amtrak 5. Employment agencies