Creating and Measuring Brand Equity
“Intel Inside”
XMBA 206.1
Summer, 2008
Ganesh Iyer
1
If you were Andy Grove what do you want to know before
deciding to take IBM and Compaq to the wall on Intel inside?
Ganesh Iyer
2
IBM’s Problem

How much do consumers value “Intel Inside”?

Is it profitable for IBM to offer “Intel Inside”?
Ganesh Iyer
3
The Conjoint Idea:
“Products are Composed of Attributes”

Computer:
Brand + Processor + RAM + Hard Disk + Monitor + Price
Ganesh Iyer
4
Breaking Down IBM’s Problem

If IBM learns how buyers value the components (i.e. attributes) of a
computer, they are in a better position to assess whether the “Intel
Inside” attribute will be profitable.

Similarly for Intel, they want to know what the relative value of the
components are for the OEM’s.
Ganesh Iyer
5
How to Learn What Customers Want?

Ask Direct Questions about preference:
»
»
»
»
»
»

What brand do you prefer?
What processor do you prefer?
How much RAM do you prefer?
How much hard disk space do you prefer?
What type of monitor do you prefer?
What price do you prefer?
What is the problem with this?
Ganesh Iyer
6
Problems with Direct Questioning

Answers are often trivial and unenlightening
»
»
»
»
“I prefer more processor speed to less”
“I prefer more RAM to less”
“I prefer more hard disk space to less”
“I prefer a lower price to a higher price”
Ganesh Iyer
7
How to Learn What Is Important?

Ask Direct Questions about Importances
» How important is it that you get the [Brand / Processor / RAM /
Hard Disk / Monitor / Price] that you want?

What is the problem with this?
Ganesh Iyer
8
Stated Importances

Importance Ratings often have low discrimination with most
responses falling in most important categories:
Average Importance Ratings
6.7
Brand
7.2
Processor
8.1
RAM
7.5
Price
0
5
10
Ganesh Iyer
9
What is Conjoint Analysis?

Technique developed in early 1970s to measure how buyers value
components of a product bundle and refined into the 2000’s.

Dictionary definition-- “Conjoint: Joined together, combined.”
“Features CONsidered JOINTly”
Important Original Summary
 Green, Paul and V. Srinivasan (1978), “Conjoint Analysis in
Marketing: New Development with Implications for Research and
Practice,” Journal of Marketing, 54 (Oct), 3-19.
Ganesh Iyer
10
How Does Conjoint Analysis Work?

We vary the product features (independent variables) to build
many (usually 12 or more) product concepts

We ask respondents to rate/rank those product concepts
(dependent variable)

Based on the respondents’ evaluations of the product concepts, we
figure out how much unique value (utility) each of the features
added

Regress dependent variable on independent variables; betas equal
part worth utilities.
Ganesh Iyer
11
How does Conjoint Analysis Work?

More realistic questions:
Would you prefer . . .
486
AMD
or
386 DX
Intel

If choose left, you prefer _______. If choose right, you prefer _______.

Rather than ask directly whether you prefer Processor speed over Processor
brand, we present realistic tradeoff scenarios and infer preferences from your
product choices.

When respondents are forced to make difficult tradeoffs, we learn what they truly
value
Ganesh Iyer
12
First Step: Create Attribute List

Attributes assumed to be independent (Brand, Processor
Speed, Processor Brand, Price)

Each attribute has varying degrees, or “levels”
»
»
»
»

Brand: Compaq, IBM, Acer
Processor Speed: 486, 386DX, 386SX
Processor Brand: Intel, AMD, Cyrix
Price: $1500, $2000, $2500
Each level is assumed to be mutually exclusive of the others (a
product has one and only one level of that attribute)
Ganesh Iyer
13
Traditional Conjoint: Card-Sort Method
Using a 100-pt scale where 0 means definitely
would NOT and 100 means definitely WOULD…
How likely are you to purchase…
Compaq
Intel
486
$2,900
Your Answer:___________
Ganesh Iyer
14
Conjoint Importances

Measure of how much influence each attribute has on people’s
choices

Best minus worst level of each attribute, percentaged:
486 – 386DX
$1500 - $2500
(2.5 - 1.8) =
(5.3 - 1.4) =
Totals:

0.7
3.9
----4.6
15.2%
84.8%
-------100.0%
Importances are directly affected by the range and number of
levels you choose for each attribute
Ganesh Iyer
15
Conjoint Design
81 Product Concepts: Challenging

For a conjoint study with:
»
»
»
»
3 brands
3 processor speeds
3 processor brands
3 prices

There are 3x3x3x3=81 possible product combinations in a full-factorial
design.

What respondent would want to evaluate all 81 in a survey?

Hence fractional factorial designs are used.
Ganesh Iyer
16
Conjoint Designs:
Full-Factorial versus Fractional-Factorial

Full Factorial (a design in which all possible product combinations are
shown)
= 3x3x3x3=81

Fractional Factorial (a design in which only a subset of all possible
product combinations are shown)
» e.g., a subset of 9 appropriately chosen product combinations
Ganesh Iyer
17
Fractional Factorial Designs

Properties of appropriate fractional designs:
» Balanced (each level is displayed an equal number of times)
» Orthogonal (no correlation between any pairs of attributes)

How to get these designs?
» Design catalogs
» Software programs

Commercial Conjoint Market Research companies
» http://www.sawtoothsoftware.com/
Ganesh Iyer
18
Market Simulations

Make competitive market scenarios and predict which products
respondents would choose

Accumulate (aggregate) respondent predictions to make
“Shares of Preference” (some refer to them as “market shares”)
Ganesh Iyer
19
Market Simulation Example

Predicting market shares for existing computers:
Compaq 486 AMD chip
IBM 486
AMD chip
Acer 386D
AMD chip

Respondent #1 “chooses” computer 1!

Repeat for rest of respondents. . .
$2500
$2000
$1500
Ganesh Iyer
20
Market Simulation Results - I

Base Case:
» Acer
» Compaq
» IBM

33.7 %
32.1 %
34.2 %
Acer first adopts “Intel Inside”…
Ganesh Iyer
21
Market Simulation Results - II

Base Case + Acer:
» Acer
» Compaq
» IBM

37.7 %
30.2 %
32.0 %
+4%
-2%
-2%
Compaq next adopts “Intel Inside”…
Ganesh Iyer
22
Market Simulation Results - III

Base Case + Acer + Compaq:
» Acer
» Compaq
» IBM

35.6 %
34.2 %
30.2 %
+4%
-2%
-2%
+2%
+2%
-4%
IBM next adopts “Intel Inside”…
Ganesh Iyer
23
Market Simulation Results - IV

Base Case + Acer + Compaq + IBM:
» Acer
» Compaq
» IBM

33.6 % + 4 %
32.3 % - 2 %
34.0 % - 2 %
+2%
+2%
-4%
0%
0%
0%
Prisoner’s Dilemma!
Ganesh Iyer
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Strategic Source of Brand Equity
Prisoner’s Dilemma
Ganesh Iyer
25
Question: How to Perform Conjoint with Actual Data
Using Regression Analysis

In actual research the company may conduct a survey to collect data
from a large sample of consumers from the target audience, say n=200.

Multiple regression analysis (Intel Example)
Y  b0  b1 (OEM _ BRAND )  b2 (SPEED)  b3 ( PROS _ BRAND )  b4 ( PRICE )  e

Where Y is the preference of the individual. And b1,…,b4 are the partworth utilities.

MS Excel offers a simple multiple regression tool (Tools + Data
Analysis + Regression with the Analysis Toolpak add-in installed).

Using the tool,
» Specify the preference score (column Y) as the dependent variable
» Four dummy-coded attribute columns as independent variables (Input X
range).
Ganesh Iyer
26