1. Introduction to Conjoint Analysis.

2. Different Perspectives, Different Goals Buyers: Most desirable features & lowest price Sellers: Maximize profits by: 1) minimizing costs of providing features 2) providing products that offer greater overall value than the competition

3. Demand Side of Equation Typical research: focus on demand Establish buyers wants/needs Assess if it can be built/provided in a cost- effective manner

4. Products/Services are Composed of Features/Attributes Credit Card: Brand + Interest Rate + Annual Fee + Credit Limit On-Line Brokerage: Brand + Fee + Speed of Transaction + Reliability of Transaction + Research/Charting Options

5. Learning What Customers Want: Alternative 1 Direct preference questions: –What brand do you prefer? –What Interest Rate would you like? –What Annual Fee would you like? –What Credit Limit would you like? Answers too simplistic –(e.g. respondents prefer low fees to high fees, higher credit limits to low credit limits)

6. Learning What Customers Want: Alternative 2 Ask about importances “How important is it that you get the best brand, lowest interest rate, lowest annual fee, and highest credit limit that you want?”

7. Results: Stated Importances Importance Ratings often have low discrimination

8. Learning What Customers Want: Alternative 3: Conjoint Analysis Developed early 1970s Measures valuation of components of a product/service bundle Dictionary definition: “Conjoint: Joined together, combined.” Marketer’s catch-phrase: “Features CONsidered JOINTly” Marketer’s catch-phrase: “Features CONsidered JOINTly”

9. How Does Conjoint Analysis Work? Vary product features (IVs) to build many (often >12) product concepts Ask respondents to rate/rank those concepts (DV) Determine unique value (utility) each features adds Interactions and tradeoffs identified

10. What’s Good about Conjoint? Realistic questions: Would you prefer... 210 Horsepower or 140 Horsepower 17 MPG 28 MPG Choose left: prefer Power. Choose right: prefer Economy Present realistic tradeoff scenarios and infer preferences from product choices Helps ID key features and boundaries (high and low)

11. Conjoint Steps: 1. Create Attribute List Attributes assumed to be independent (Sonites: Weight, Design, Volume, Max Freq, Power, and Price) Each attribute has varying degrees, or “levels” Levels assumed to be mutually exclusive of the others (a product has one and only one level level of that attribute) –Can “build in” real world constraints, e.g., weight and power

12. How to Formulate Attribute Levels Concrete/unambiguous meaning –“Very expensive” vs. “Costs $575” –“Weight: 5 to 7 kilos” vs. “Weight 6 kilos” Sonites: –Weight:10 -20 kg –Design (Index): 3 – 10 –Volume (dm3):20 - 100 –Max Freq (1000Hz):5 – 50 –Power (W):5 - 100 DO NOT leave meaning up to individual interpretation

13. Conjoint Output 1) Utilities (part worths) 2) Importances

14. Conjoint Output: Utilities (Part Worths) Numeric values that reflect how desirable different features are: FeatureUtility Vanilla2.5 Chocolate1.8 25¢5.3 35¢3.2 50¢1.4 The higher the utility, the better

15. Conjoint Output : Attribute Importances Measure how much influence each attribute has on choices Best minus worst level of each attribute, percentaged: FLAVOR: Vanilla - Chocolate (2.5 - 1.8) = 0.715.2% 25¢ - 50¢(5.3 - 1.4) = 3.984.8% ------------- Totals:4.6100.0% This buyer/group price sensitive NOTE: Importances directly affected by range of levels chosen for each attribute

16. For four (4) different “levels” of the top four (4) attributes, what are the utilities? Note: Weight & Volume excluded 1 2 1 2 3 3 1

17. NOTE: Inverse “U” relationship of attribute levels and utility

18. Summary Conjoint is one of several tools made available to aid in setting attribute values. Please note: This is not an exact science! Consumer preference may shift based on market and competitive dynamics.