1 Ganesh Iyer Creating and Measuring Brand Equity “Intel Inside” EWMBA 206 Fall 2007

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

3 Ganesh Iyer IBM’s Problem l How much do consumers value “Intel Inside”? l Is it profitable for IBM to offer “Intel Inside”?

4 Ganesh Iyer The Conjoint Idea: “Products are Composed of Attributes” l Computer: Brand + Processor + RAM + Hard Disk + Monitor + Price

5 Ganesh Iyer Breaking Down IBM’s Problem l 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. l Similarly for Intel, they want to know what the relative value of the components are for the OEM’s.

6 Ganesh Iyer How to Learn What Customers Want? l 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? l What is the problem with this?

7 Ganesh Iyer Problems with Direct Questioning l 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”

8 Ganesh Iyer How to Learn What Is Important? l Ask Direct Questions about Importances »How important is it that you get the [Brand / Processor / RAM / Hard Disk / Monitor / Price] that you want? l What is the problem with this?

9 Ganesh Iyer Stated Importances l Importance Ratings often have low discrimination with most responses falling in most important categories:

10 Ganesh Iyer What is Conjoint Analysis? l Technique developed in early 1970s to measure how buyers value components of a product bundle and refined into the 2000’s. l Dictionary definition-- “Conjoint: Joined together, combined.” “Features CONsidered JOINTly” Important Original Summary l 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.

11 Ganesh Iyer How Does Conjoint Analysis Work? l We vary the product features (independent variables) to build many (usually 12 or more) product concepts l We ask respondents to rate/rank those product concepts (dependent variable) l Based on the respondents’ evaluations of the product concepts, we figure out how much unique value (utility) each of the features added l Regress dependent variable on independent variables; betas equal part worth utilities.

12 Ganesh Iyer How does Conjoint Analysis Work? l More realistic questions: Would you prefer or 386 DX AMD Intel l If choose left, you prefer _______. If choose right, you prefer _______. l Rather than ask directly whether you prefer Processor speed over Processor brand, we present realistic tradeoff scenarios and infer preferences from your product choices. l When respondents are forced to make difficult tradeoffs, we learn what they truly value

13 Ganesh Iyer First Step: Create Attribute List l Attributes assumed to be independent (Brand, Processor Speed, Processor Brand, Price) l 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 l Each level is assumed to be mutually exclusive of the others (a product has one and only one level of that attribute)

14 Ganesh Iyer 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:___________

15 Ganesh Iyer Conjoint Importances l Measure of how much influence each attribute has on people’s choices l Best minus worst level of each attribute, percentaged: 486 – 386DX ( ) = % $ $2500( ) = % Totals: % l Importances are directly affected by the range and number of levels you choose for each attribute

16 Ganesh Iyer Conjoint Design 81 Product Concepts: Challenging l For a conjoint study with: »3 brands »3 processor speeds »3 processor brands »3 prices l There are 3x3x3x3=81 possible product combinations in a full-factorial design. l What respondent would want to evaluate all 81 in a survey? l Hence fractional factorial designs are used.

17 Ganesh Iyer Conjoint Designs: Full-Factorial versus Fractional-Factorial l Full Factorial (a design in which all possible product combinations are shown) = 3x3x3x3=81 l 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

18 Ganesh Iyer Fractional Factorial Designs l Properties of appropriate fractional designs: »Balanced (each level is displayed an equal number of times) »Orthogonal (no correlation between any pairs of attributes) l How to get these designs? »Design catalogs »Software programs l Commercial Conjoint Market Research companies »

19 Ganesh Iyer Market Simulations l Make competitive market scenarios and predict which products respondents would choose l Accumulate (aggregate) respondent predictions to make “Shares of Preference” (some refer to them as “market shares”)

20 Ganesh Iyer Market Simulation Example l Predicting market shares for existing computers: Compaq 486AMD chip$2500 IBM486AMD chip$2000 Acer386DAMD chip$1500 l Respondent #1 “chooses” computer 1! l Repeat for rest of respondents...

21 Ganesh Iyer Market Simulation Results - I l Base Case: »Acer33.7 % »Compaq32.1 % »IBM34.2 % l Acer first adopts “Intel Inside”…

22 Ganesh Iyer Market Simulation Results - II l Base Case + Acer: »Acer37.7 % + 4 % »Compaq30.2 % - 2 % »IBM32.0 % - 2 % l Compaq next adopts “Intel Inside”…

23 Ganesh Iyer Market Simulation Results - III l Base Case + Acer + Compaq: »Acer35.6 % + 4 %+ 2 % »Compaq34.2 % - 2 %+ 2 % »IBM30.2 % - 2 %- 4 % l IBM next adopts “Intel Inside”…

24 Ganesh Iyer Market Simulation Results - IV l Base Case + Acer + Compaq + IBM: »Acer33.6 % + 4 %+ 2 %0 % »Compaq32.3 % - 2 %+ 2 %0 % »IBM34.0 % - 2 %- 4 %0 % l Prisoner’s Dilemma!

25 Ganesh Iyer Strategic Source of Brand Equity Prisoner’s Dilemma

26 Ganesh Iyer Question: How to Perform Conjoint with Actual Data Using Regression Analysis l 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. l Multiple regression analysis (Intel Example) l Where Y is the preference of the individual. And b 1,…,b 4 are the part- worth utilities. l MS Excel offers a simple multiple regression tool (Tools + Data Analysis + Regression with the Analysis Toolpak add-in installed). l Using the tool, »Specify the preference score (column Y) as the dependent variable »Four dummy-coded attribute columns as independent variables (Input X range).