

Critical area for marketing



Important for any industry



Always active!

But what is new??
1

• Repositioning

• Innovations

• Line
Extensions

• “Me Too”
Products

New to
World

New to Company
2

Markets

Existing

Existing

New

Market
Penetration

Market
Development

New Product
Development

(Diversification)

Products
New

3

Opportunity Identification
Design

Testing
Introduction
Life Cycle Management
4



Product Design



Forecasting

5

 Product

design using conjoint analysis

 Forecasting

the pattern of new product adoptions (Bass Diffusion Model)

6

Purpose:

To incorporate customer preferences into the new product design process.

Process:

By evaluating how customers make tradeoffs between various product attributes.

Output of CA:

- 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. 7

Input is overall preferences. Thus, CA links customers’ stated overall preferences to utility values. For example,

Memory

$1,000

Price
$1,500

8 Mb
16 Mb
24 Mb

4
7
9

2
5
8

$2,000
1
3
6

9 = Most preferred
•
•
•
1 = Least preferred

8

Memory

$1,000

Price
$1,500

8 Mb
16 Mb
24 Mb

4
7
9

2
5
8

1
3
6

20/3

15/3

10/3

=

=

=

6.7

5.0

3.3

Part-Worth:

$2,000

PartWorth
7/3 =
15/3 =
23/3 =

2.3
5.0
7.7

9

Example:
Utility of 24 Mb vs 16 Mb = 7.7 – 5.0 = 2.7 units, while
Utility of $1,000 vs $1,500 = 6.7 – 5.0 = 1.7 units

Thus, 8 Mb is worth more than $500 to this customer.
How does this help a manager?
If I have a 64 Mb product selling for $1600/-, how should I price a product if I add 8 Mb to it?

10

Another example: Input for Salsa
Thickness

Spiciness

Color

Actual
Ranking*

Regular
Regular
Regular
Regular
Regular
Regular
Thick
Thick
Thick
Thick
Thick
Thick
Extra-Thick
Extra-Thick
Extra-Thick
Extra-Thick
Extra-Thick
Extra-Thick

Mild
Mild
Medium-Hot
Medium-Hot
Extra-Hot
Extra-Hot
Mild
Mild
Medium-Hot
Medium-Hot
Extra-Hot
Extra-Hot
Mild
Mild
Medium-Hot
Medium-Hot
Extra-Hot
Extra-Hot

Red
Green
Red
Green
Red
Green
Red
Green
Red
Green
Red
Green
Red
Green
Red
Green
Red
Green

4
3
10
6
15
16
2
1
8
5
13
11
7
9
14
12
17
18

Ranking as
Estimated
by Model
4
3
10
8
16
15
2
1
6
5
13
11
7
9
14
12
18
17

* 1 = most preferred, 18 = least preferred.
11

Conjoint Analysis: Graphical Output
Thickness

Spiciness

Color

2
1
0
-1
-2

Regular

0.161

Thick

0.913

Ex-Thick

Mild

-1.074 1.667

Medium-Hot

0.105

Ex-Hot

Red

-1.774 -0.161

Green

0.161

Range of utility = {(.913, -1.074), (1.667, -1.774), (-.161, .161)}
= {1.987, 3.441, .322}
Total = 5.75
Ideal Product??
Second Best??
12

0

20

40

60

Spiciness

100 %

59.8%

Thickness
Color

80

34.6%
5.6%

13

 Maximum

utility rule

 Share

of preference rule

 Logit

choice rule

14

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.

15

Stage 1—Designing the conjoint study:
Step 1.1:
Step 1.2:
Step 1.3:

Select attributes relevant to the product or service category,
Select levels for each attribute, and
Develop the product bundles to be evaluated.

Stage 2—Obtaining data from a sample of respondents:
Step 2.1:
Step 2.2:

Design a data-collection procedure, and
Select a computation method for obtaining part-worth functions. Stage 3—Evaluating product design options:
Step 3.1:
Step 3.2:
Step 3.3:

Segment customers based on their part-worth functions,
Design market simulations, and
Select choice rule.

16

Running Conjoint Analysis:
Example: Bicycle design

Set Up

17

Model designed to answer the question:
When will customers adopt a new product or technology? 18

Total Sales at time ‘t’ =
From ‘innovators’+ From