University of Washington EMBA Program Regional 20 “Conjoint Analysis” TA: Rory McLeod October 7, 2003

What is Conjoint Analysis? A quantitative analysis used to estimate customers’ value systems Requires that a product be broken down into a set of attributes Value system: how much value a consumer puts on each level of each of the attributes

Uses of Conjoint Analysis Learning more about your potential customer segments –Further market segmentation New product development –Extending types of products within a category –Entering a new category Determining optimal positioning

Conjoint Analysis Method Step 1 – Identify key product attributes and levels of attributes for the product class –Focus groups / managerial input Step 2 – Select combinations of attributes and attribute levels –Can the customers figure out the differences in the attributes and how they impact the benefits? Step 3 – Prepare a representation of each design –Prototypes / sketches Step 4 – Subjects rank the designs Step 5 – Analyze data to develop relative importance of each attribute

Example: Personal Computers Step 1. Key Attributes and Levels of Attributes 1.Speed (1X, 2X, 3X) 2.Software (None, Limited, Extensive) 3.Price (Current, 20% Higher, 40% Higher) 4.Supplier (Compaq, Packard Bell, Toshiba)

Example: Personal Computers Step 2. Combinations of Attribute Levels System A: Speed – 1X Software – Limited Price – Current Supplier – Compaq System G: Speed – 3X Software – None Price – Current Supplier – Packard Bell System D: Speed – 2X Software – Extensive Price – Current Supplier – Toshiba System H: Speed – 3X Software – Limited Price – 20% Higher Supplier – Toshiba System E: Speed – 2X Software – None Price – 20% Higher Supplier – Compaq System I: Speed – 3X Software – Extensive Price – 40% Higher Supplier – Compaq System F: Speed – 2X Software – Limited Price – 40% Higher Supplier – Packard Bell System C: Speed – 1X Software – None Price – 40% Higher Supplier – Toshiba System B: Speed – 1X Software – Extensive Price – 20% Higher Supplier – Packard Bell Use software to select product combinations such that attributes are uncorrelated (orthogonal).

Example: Personal Computers Step 3/4. Designs are ranked Customer Preference (most preferred to least): D,H,G,I,A,B,E,C,F System A: 5 Speed – 1X Software – Limited Price – Current Supplier – Compaq System G: 3 Speed – 3X Software – None Price – Current Supplier – Packard Bell System D: 1 Speed – 2X Software – Extensive Price – Current Supplier – Toshiba System H: 2 Speed – 3X Software – Limited Price – 20% Higher Supplier – Toshiba System E: 7 Speed – 2X Software – None Price – 20% Higher Supplier – Compaq System I: 4 Speed – 3X Software – Extensive Price – 40% Higher Supplier – Compaq System F: 9 Speed – 2X Software – Limited Price – 40% Higher Supplier – Packard Bell System C: 8 Speed – 1X Software – None Price – 40% Higher Supplier – Toshiba System B: 6 Speed – 1X Software – Extensive Price – 20% Higher Supplier – Packard Bell

Example: Personal Computers Step 5. Data Analysis A.Determine individual scores for each attribute by summing the scores for that attribute. System A: 5 Speed – 1X Software – Limited Price – Current Supplier – Compaq System G: 3 Speed – 3X Software – None Price – Current Supplier – Packard Bell System D: 1 Speed – 2X Software – Extensive Price – Current Supplier – Toshiba System H: 2 Speed – 3X Software – Limited Price – 20% Higher Supplier – Toshiba System E: 7 Speed – 2X Software – None Price – 20% Higher Supplier – Compaq System I: 4 Speed – 3X Software – Extensive Price – 40% Higher Supplier – Compaq System F: 9 Speed – 2X Software – Limited Price – 40% Higher Supplier – Packard Bell System C: 8 Speed – 1X Software – None Price – 40% Higher Supplier – Toshiba System B: 6 Speed – 1X Software – Extensive Price – 20% Higher Supplier – Packard Bell Software: None = = 18 Limited = = 16 Extensive = = 11 Manufacturer: Compaq = = 16 Toshiba = = 11 Packard Bell = = 11 Price: Current = = 9 20% Higher = = 15 40% Higher = = 21 Speed: 1X = = 19 2X = = 17 3X = = 9

Example: Personal Computers Step 5. Data Analysis B.Rank attributes and summed attribute scores from lowest to highest (X’s below). C.Determine the maximum score and minimum score. D.Rescale the raw scores using the following Normalization Formula: XY 3X Speed91.00 Current Price91.00 Extensive Software Toshiba Price + 20% Limited Software Compaq X Speed No Software Packard Bell X Speed Price + 40%210.00

Example: Personal Computers For each attribute, determine its importance and plot a preference curve. BenefitRangeImportance Speed0.8328% (.83 / 2.99) Software0.5819% Price1.0034% Manufacturer0.5819% Total %

Example: Personal Computers For each attribute, determine its importance and plot a preference curve.

Example: Personal Computers You can then evaluate the attractiveness of actual products you might bring to market… ToshibaCompaqPackard Bell BenefitProduct Position Customer Value Product Position Customer Value Product Position Customer Value Speed3X1.002X0.331X0.17 SoftwareExtensive0.83Extensive0.83None0.25 Price+40% %0.50Current1.00 Manufacturer Toshiba0.83Compaq0.42Packard Bell 0.25 Overall Attractiveness

Additional Comments… For more accurate data analysis, can use multivariate regression (for rankings) or ANOVA (for ratings) Always test the validity of your results –Red-Face Test: Do the results make sense? –Holdout Prediction (a small # of the ranked products are held out of the calculations) –Actual vs. predicted market share