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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 24 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