Conjoint analysis

Outline Conjoint analysis as a decompositional preference model Steps in conjoint analysis Uses of conjoint analysis

Compositional vs. decompositional preference models Compositional: respondents evaluate all the features (levels of particular attributes) characterizing a product; combining these feature evaluations (possibly weighted by their importance) yields a product’s overall evaluation; Decompositional: respondents provide overall evaluations of a series of products composed of various combinations of attribute levels; the overall evaluations are then decomposed into the utilities associated with different levels of the various attributes;

Example of a compositional model Consider the following laptop computer: Dell 320 GB hard drive 4 GB of RAM 12.1 inch screen Price of $1,200 On a scale from 0 (lowest) to 10 (highest), how would you rate this computer on each attribute? Assign a total of 100 points to each of the 5 attributes so that the points reflect the relative importance of each attribute.

Example of a decompositional model Rank the following four descriptions of laptop computers in terms of overall preference: Profile 1 Profile 2 Profile 3 Brand Dell Apple Size of Hard Drive 320 160 Amount of RAM 2 4 Screen size 15.4 12.1 Price $1,200 $1,500 Rank

Basic idea of conjoint analysis Overall utility for a product can be decomposed into the utilities (called part-worths) associated with the levels of the individual attributes of the product; The relative importance of a given attribute is given by the ratio of the part-worth range for that attribute divided by the sum of all part-worth ranges;

Steps in conjoint analysis Determine attributes and attribute levels Select product profiles to be measured Choose a method of stimulus presentation Decide on the response method Collect and analyze the data Interpret the results

Attributes and attribute levels Identify the relevant product attributes that are considered during choice Select attribute levels that represent the options actually available in the market Trade-off between the completeness of the representation and the complexity of the design

Example: Laptop Profiles Brand Hard Drive RAM Screen Price Dell 320 GB 2 GB 15.4 in $1,200 Apple 4 GB 160 GB $900 12.1 in $1,500

Product profiles Full factorial designs: Fractional factorial designs: all possible combinations of the levels of the various attributes are used Fractional factorial designs: a subset of all possible combinations is used orthogonal designs in which each level of one attribute is paired equally with all the levels of other attributes are beneficial

Example: Laptop Profiles Brand Hard Drive RAM Screen Price Dell 320 GB 2 GB 15.4 in $1,200 Apple 4 GB 160 GB $900 12.1 in $1,500

Methods of stimulus presentation Verbal descriptions Pictures Actual products or prototypes Apple Laptop with 320 GB of Hard Disk Space, 4 GB of RAM, and a Screen Size of 15.4 inches – at a Price of $1,200.

Response method Rankings or ratings of the product profiles in terms of preference, purchase probability, etc. Pairwise comparisons of product profiles in terms of preference, purchase probability, etc. Choice of a product from a set of product profiles

Example: Laptop Profiles Brand Hard Drive RAM Screen Price A B Dell 320 GB 2 GB 15.4 in $1,200 9 6 Apple 4 GB 12 160 GB $900 5 11 12.1 in $1,500 4 3 1 10 8 7 2

In-class exercise Using the data in the table, answer the following questions: How much utility does each of the two consumers attach to the different levels of the five attributes? (Hint: Compute each consumer’s average rating of all the options with a given feature. For example, to figure out how much consumer A values the Apple brand name, compute the average rating of the six Apple laptops.) What’s the relative importance of the five attributes for the two consumers? Consider consumer A’s ratings. For this consumer, what’s the predicted utility of a Dell computer with 160 GB of hard drive space and 2 GB of RAM, a 12.1 inch screen, and a price of $1,200?

Consumer A Consumer B Apple 5.67 9.50 Dell 7.33 3.50 160HD 6.17 5.50 320HD 6.83 7.50 2RAM 6.33 6.00 4RAM 6.67 7.00 12.1in 5.83 5.33 15.4in 7.17 7.67 $900 10.25 6.75 $1200 $1500 2.5

Consumer A Consumer B Apple 5.67 -.83 9.50 +3.00 Dell 7.33 +.83 3.50 -3.00 160HD 6.17 -.33 5.50 -1.00 320HD 6.83 +.33 7.50 +1.00 2RAM 6.33 -.17 6.00 -.50 4RAM 6.67 +.17 7.00 +.50 12.1in 5.83 -.67 5.33 -1.17 15.4in 7.17 +.67 7.67 +1.17 $900 10.25 +3.75 6.75 +.25 $1200 $1500 2.5 -4.00

In-class exercise Using the data in the table, answer the following questions: How much utility does each of the two consumers attach to the different levels of the five attributes? (Hint: Compute each consumer’s average rating of all the options with a given feature. For example, to figure out how much consumer A values the Apple brand name, compute the average rating of the six Apple laptops.) What’s the relative importance of the five attributes for the two consumers? Consider consumer A’s ratings. For this consumer, what’s the predicted utility of a Dell computer with 160 GB of hard drive space and 2 GB of RAM, a 12.1 inch screen, and a price of $1,200?

Consumer A Consumer B Apple 5.67 -.83 1.66 14% 9.50 +3.00 6.00 50% Attribute level Mean for level across all profiles Mean as deviation from zero Range on attribute Percentage importance Apple 5.67 -.83 1.66 14% 9.50 +3.00 6.00 50% Dell 7.33 +.83 3.50 -3.00 160HD 6.17 -.33 .67 6% 5.50 -1.00 2.00 17% 320HD 6.83 +.33 7.50 +1.00 2RAM 6.33 -.17 .33 3% -.50 1.00 8% 4RAM 6.67 +.17 7.00 +.50 12.1in 5.83 -.67 1.33 11% 5.33 -1.17 2.33 19% 15.4in 7.17 +.67 7.67 +1.17 $900 10.25 +3.75 7.75 66% 6.75 +.25 .75 $1200 $1500 2.5 -4.00 =11.74

In-class exercise Using the data in the table, answer the following questions: How much utility does each of the two consumers attach to the different levels of the five attributes? (Hint: Compute each consumer’s average rating of all the options with a given feature. For example, to figure out how much consumer A values the Apple brand name, compute the average rating of the six Apple laptops.) What’s the relative importance of the five attributes for the two consumers? Consider consumer A’s ratings. For this consumer, what’s the predicted utility of a Dell computer with 160 GB of hard drive space and 2 GB of RAM, a 12.1 inch screen, and a price of $1,200?

Review questions What’s the difference between compositional and decompositional preference models? What’s a fractional factorial design in conjoint analysis and why is it useful? What are part-worths in a conjoint study?

Review questions (cont’d) A conjoint study was conducted for LCD TV’s, using three brands (LG, Samsung, and Sony), three screen sizes (46, 54, and 63 in.) and three price levels ($2,300; $2,800; and $3,600). The utility differences between the lowest and highest levels of each attribute were 3 for brand name, 2 for screen size, and 5 for price. Based on these findings, price is how many times more important than screen size?

ME output for laptop computer examples Respondents' Preference Partworths Respondents' preference partworths. The most preferred profiles sum up to 100, the least preferred to 0. Respondents / Attributes and Levels Apple Dell 160 320 2 4 Respondent 1 14 6 3 Respondent 2 50 17 8 Respondents / Attributes and Levels Respondent 1 Respondent 2 12.1 15.4 900 1200 1500 11 66 36 19 6

Software and computers Office Star data Conjoint Study Design Attributes and attribute levels of the Conjoint study. Attributes / Levels Level 1 Level 2 Level 3 Ordering Location Less than 2 miles Within 2-5 miles Within 5-10 miles Decreasing Office supplies Very large assortment Large assortment Limited Assortment Unordered Furniture Office Furniture No Furniture   Computers No computers Software only Software and computers

Office Star bundles Bundles Attribute levels for a full-profile, fractional design Conjoint study Attributes / Bundles Bundle 1 Bundle 2 Bundle 3 Bundle 4 Bundle 5 Bundle 6 Bundle 7 Bundle 8 Location Less than 2 miles Within 2-5 miles Office supplies Very large assortment Large assortment Limited Assortment Furniture Office Furniture No Furniture Computers No computers Software only Software and computers Bundle 9 Bundle 10 Bundle 11 Bundle 12 Bundle 13 Bundle 14 Bundle 15 Bundle 16 Within 5-10 miles Within 2-5 miles Very large assortment Large assortment Limited Assortment No Furniture Office Furniture Software and computers Software only No computers Attributes / Bundles Location Office supplies Furniture Computers

Respondents’ ratings of Office Star bundles Respondents' ratings for each bundle (use consistent scale, e.g., between 0 and 100) Respondents / Ratings Bundle 1 Bundle 2 Bundle 3 Bundle 4 Bundle 5 Bundle 6 Bundle 7 Bundle 8 Respondent 1 90 50 80 85 40 Respondent 2 55 95 Respondent 3 60 45 35 Respondent 4 75 70 65 Respondent 5 Respondents / Ratings Respondent 1 Respondent 2 Respondent 3 Respondent 4 Respondent 5 Bundle 9 Bundle 10 Bundle 11 Bundle 12 Bundle 13 Bundle 14 Bundle 15 Bundle 16 30 60 90 80 40 75 35 20 25 85 45 55 50 70 65

Estimating part-worths

Respondents’ part-worths for Office Star data Respondents' Preference Partworths Respondents' preference partworths. The most preferred profiles sum up to 100, the least preferred to 0. Respondents / Attributes and Levels Less than 2 miles Within 2-5 miles Within 5-10 miles Very large assortment Large assortment Limited Assortment Office Furniture No Furniture No computers Software only Software and computers Respondent 1 31 23 2 3 55 1 11 Respondent 2 16 7 61 Respondent 3 14 6 4 22 76 Respondent 4 17 47 9 27 Respondent 5 24 8 59 39 15 Respondent 6 49 12 26 Respondent 7 5 52 Respondent 8 68 Respondent 9 21 74 Respondent 10 18 43 20 Respondent 11 10 50 32 13 Respondent 12 Respondent 13 19 Respondent 14 29 58 Respondent 15 Respondent 16 51 Respondent 17 48 Respondent 18 45 33 Respondent 19 35 25 Respondent 20

Software and computers Detailed preference partworths (Enginius)   Less than 2 miles Within 2 to 5 miles Within 5 to 10 miles Very large assortment Large assortment Limited assortment Office furniture No furniture No computers Software only Software and computers 1 30.99 22.18 0.00 2.30 2.99 54.96 0.71 11.07 2 31.13 16.35 2.43 6.92 1.72 1.23 60.23 3 13.58 0.20 7.07 4.82 4.32 22.50 75.04 4 18.03 18.00 45.82 21.39 8.65 16.41 27.50 5 23.98 8.00 60.25 39.81 1.38 8.11 14.39 6 49.67 17.26 22.43 12.03 26.00 1.90 0.07 7 30.81 14.78 0.68 5.42 52.09 7.48 11.68 8 22.01 5.31 8.18 9.02 1.31 2.81 67.65 9 23.83 7.45 0.86 0.38 0.43 22.35 74.88 10 17.83 17.53 43.17 20.87 12.21 14.38 26.79 11 15.55 10.11 49.78 31.83 12.77 21.90 4.35 12 50.78 3.36 20.76 15.99 21.77 6.69 0.32 13 27.21 18.29 3.97 5.24 54.17 1.16 13.38 14 28.79 11.88 8.45 12.68 0.92 4.12 57.61 15 17.50 2.90 1.22 12.99 8.46 11.38 61.04 16 15.35 15.32 50.54 22.76 1.44 22.05 32.67 17 23.32 47.61 31.00 12.25 3.42 16.82 18 44.15 11.92 32.99 22.04 19.03 3.83 3.22 19 35.91 13.16 22.36 24.63 17.05 22.41 20 28.78 14.61 29.02 31.74 18.46 3.04 21.01

Summary statistics for preference partworths

Uses of conjoint analysis Market segmentation Q: How would you segment the market using individual-level conjoint analysis output? New product design Q: How can conjoint analysis be used for new product design? Trade-off analysis (esp. in pricing decisions) Q: How much could the price of a Dell computer with 160 GB of hard drive space and 2 GB of RAM, which currently sells for $1,200, be raised if the screen size were increased from 12.1 in to 15.4 in? Competitive analysis Q: How can conjoint analysis be used to simulate market shares?

Market share simulations

Choice rules for simulations First-choice rule: the option with the highest utility is chosen; Share of preference rule: the choice probability is equal to the utility of an option relative to the total utility of all options in the choice set; Alpha rule: a weighted combination of the first two rules which maximizes the correspondence with market shares; Logit choice rule: similar to the share of preference rule, but the choice probabilities are computed as in the logit model;

Market share simulations: Existing product profiles Labels and attribute levels for each existing product profile that already exists in the market. Attributes / Existing Product Profiles Office Equipment Department Store Location Within 2-5 miles Office supplies Large assortment Limited assortment Furniture Office furniture No furniture Computers Software and computers Software only

Market share simulations with optimal product profiles Market share predictions for different scenarios, using the Logit Rule. Scenario / Product profiles Office Equipment Department Store Market Share of Optimal Product Profile Predicted market shares 73% 27% n/a ...with Optimal Product 1 34% 13% 53% ...with Optimal Product 2 36% 14% 50% ...with Optimal Product 3 39% 47% ...with Optimal Product 4 40% 15% 45% ...with Optimal Product 5 41% 43%

Optimal product profiles Labels and attribute levels for each optimal product profile that the software recommends you introduce in this market Attributes / Optimal Product Profiles Optimal Product 1 Optimal Product 2 Optimal Product 3 Optimal Product 4 Optimal Product 5 Location Less than 2 miles Within 2-5 miles Office supplies Very large assortment Large assortment Furniture Office furniture No furniture Computers Software and computers

Review: Conjoint analysis Based on the conjoint study, LG management knows that a price increase from $2,300 to $2,800 leads to a decrease in utility of 3. If utility goes up by 1 when the screen size is increased from 46 to 54 inches, how much can LG charge for the TV set with the larger screen?

Next two classes Thursday: Text analysis and Google analytics In-class exercise: Ottos’ reviews from TripAdvisor Tuesday: Dürr Environmental, Inc No segmentation, introduction of 1 product only