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Creating and Measuring Brand Equity “Intel Inside”

EWMBA 206

Fall 2007

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If you were Andy Grove what do you want to know before deciding to take IBM and Compaq to the wall on Intel inside?

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IBM’s Problem

How much do consumers value “Intel Inside”?

Is it profitable for IBM to offer “Intel Inside”?

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The Conjoint Idea:“Products are Composed of Attributes”

Computer:

Brand + Processor + RAM + Hard Disk + Monitor + Price

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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.

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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?

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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”

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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?

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Stated Importances

Importance Ratings often have low discrimination with most responses falling in most important categories:

Average Importance Ratings

7.5

8.1

7.2

6.7

0 5 10

Price

RAM

Processor

Brand

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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.

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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.

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How does Conjoint Analysis Work?

More realistic questions:

Would you prefer . . .

486 or 386 DXAMD 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

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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)

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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:___________

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Conjoint Importances

Measure of how much influence each attribute has on people’s choices

Best minus worst level of each attribute, percentaged:

486 – 386DX (2.5 - 1.8) = 0.7 15.2%$1500 - $2500 (5.3 - 1.4) = 3.9 84.8%

----- --------Totals: 4.6 100.0%

Importances are directly affected by the range and number of levels you choose for each attribute

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Conjoint Design81 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.

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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

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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/

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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”)

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Market Simulation Example

Predicting market shares for existing computers:

Compaq 486 AMD chip $2500IBM 486 AMD chip $2000 Acer 386D AMD chip $1500

Respondent #1 “chooses” computer 1!

Repeat for rest of respondents. . .

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Market Simulation Results - I

Base Case: » Acer 33.7 %

» Compaq 32.1 %

» IBM 34.2 %

Acer first adopts “Intel Inside”…

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Market Simulation Results - II

Base Case + Acer: » Acer 37.7 % + 4 %

» Compaq 30.2 % - 2 %

» IBM 32.0 % - 2 %

Compaq next adopts “Intel Inside”…

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Market Simulation Results - III

Base Case + Acer + Compaq: » Acer 35.6 % + 4 % + 2 %

» Compaq 34.2 % - 2 % + 2 %

» IBM 30.2 % - 2 % - 4 %

IBM next adopts “Intel Inside”…

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Market Simulation Results - IV

Base Case + Acer + Compaq + IBM: » Acer 33.6 % + 4 % + 2 % 0 %

» Compaq 32.3 % - 2 % + 2 % 0 %

» IBM 34.0 % - 2 % - 4 % 0 %

Prisoner’s Dilemma!

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Strategic Source of Brand EquityPrisoner’s Dilemma

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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)

Where Y is the preference of the individual. And b1,…,b4 are the part-worth 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).

ePRICEbBRANDPROSbSPEEDbBRANDOEMbbY )()_()()_( 43210