1. Conjoint and Segmentation
Market Intelligence Julie Edell Britton
Session 8
September 26, 2009

2. Today’s Agenda Announcements Segmentation
IBM Global Mobile Computing Case: The Prometheus Project

3. Announcements
Submit WEMBA C by 10pm on Thursday, October 8. One solution per team. This is a major case write-up

4. Agenda 1st hour 2nd hour – Kevin Clark Market Segmentation
Perceptual mapping
Choosing basis for segmentation
Segmentation analyses
2nd hour – Kevin Clark
Program Director, Program Director, Brand and Values Experience
IBM Global Mobile Computing Segmentation case 4

5. Market Share of New or Changed Products
Developing effective new product introduction and product line strategies.
Estimating market shares for new product introductions and improvements.
Estimate profitability associated with new product introductions or improvements by integrating price and cost information. 5

6. Selling Plexiglas Aquaria to Builders
John Wolf is a manufacturer of Plexiglas spas sold to building contractors. He discovers that he has the technology to make large Plexiglas fish tanks cheaply. These tanks look very sharp and make it possible to burnish attractive designs on the back wall. He wants to manufacture Plexiglas tanks to sell into the commercial construction market for installation into banks, restaurants, and public places. 6

7. Examples of Acrylic Aquaria7

8. Selling Plexiglas Aquaria to Builders
Plexiglas fish tanks have heretofore garnered a small market share. Mr. Wolf assumes that this is due to the high price ($30,000) relative to the price of similar sized glass fish tanks ($10,000). Since he can produce Plexiglas fish tanks cheaply enough to make a sizeable profit based upon a price of $10,000, he thinks it can be a good new product offering.

9. CALCULATING PART WORTHS AND INFERRING THE VALUES OF UNMEASURED CELLS
STEP 1: Measure evaluations of a strategic subset of attribute combinations
Customer 1 (Data in 1st row of slide 35)

10. STEP 2: Decompose evaluation of each combo into a grand mean plus the contribution of each attribute.
u = Grand Mean
a1 = Mean of a1 cells – Grand Mean =
a2 = Mean of a2 cells – Grand Mean =
b1 = Mean of b1 cells – Grand Mean =
b2 = Mean of b2 cells – Grand Mean =
c1 = Mean of c1 cells – Grand Mean =
c2 = Mean of c2 cells – Grand Mean =

11. 11

12. STEP 3: Apply assumptions about market
Representative sample of 10 customers
- Each customer represents 10% of market.
- We have calculated each customer’s part- worths and product preferences.
Cells with a “C” are existing Competitors.
Cells with a “?” are contemplated entries by Wolf.
Cells with “NOT” are technologically infeasible (though customers would not know this).
Product ratings for cells 2, 3, 4, 7, and 8 are shown on next page.

13. Use the "U" to compute market shares. Cell 2 (A1B2C1) =
Scenario U: Status Quo
What is market shares for Cell 2 (Glass, $10K, Plain) and Cell 3 (Plexi, $30K, Plain)? Existing competitors.
Use the "U" to compute market shares.
Cell 2 (A1B2C1) =
Cell 3 (A2B1C1) = 13

14. Use the "U" to compute market shares. Cell 2 (A1B2C1) =
Scenario U: Status Quo
What is market shares for Cell 2 (Glass, $10K, Plain) and Cell 3 (Plexi, $30K, Plain)? Existing competitors.
Use the "U" to compute market shares.
Cell 2 (A1B2C1) =
Cell 3 (A2B1C1) = 14

15. 15

16. Scenario V: Wolf Introduces Plexiglas, $10K, Plain (cell 4)
1. What are the market shares for Cell 2, Cell 3, Cell 4 (Wolf)?
Use the "V" to compute market shares.
Cell 2 (A1B2C1) =
Cell 3 (A2B1C1) =
Cell 4 (A2B2C1) =
2. Suppose it cost Wolf $7500 to produce the Cell 4 product. Also suppose the market size is 1000 units. What is Wolf's expected profit?
How would you expect competition to respond?
How might Wolf respond to their response?
600*2500 =$1.5 million - Who does he take that share from – 75% drops to 35% 25% drops to 5% little guy drops proportionately – make same product offers for less 16

17. 17

18. Scenario V: Wolf Introduces Plexi, $10K, Plain18

19. Scenario W: Introduce Plexiglass, $10K, Design
1. What are the market shares for Cell 2, Cell 3, Cell 8 (Wolf)?
Use the "W" to compute market shares.
Cell 2 (A1B2C1) =
Cell 3 (A2B1C1) =
Cell 8 A2B2C2) =
2. Suppose it cost Wolf $8000 to produce the Cell 8 product and that the market size is 1000 units. What is Wolf's expected profit?
3. How would you expect Wolf's competitors to respond? Is this a better strategy than Option V? Is there a more profitable Option? What should Wolf be charging for their etched tank? 19

21. Scenario W: Wolf Introduces Plexi, $10K, Design
600 *2000 per unit =$1.2 million

22. Scenario X: Introduce Plexiglas, $30K, Design
1. What are the market shares for Cell 2, Cell 3, Cell 7 (Wolf)?
Use the "X" to compute market shares.
Cell 2 (A1B2C1)=
Cell 3 (A2B1C1) =
Cell 7 (A2B2C2) =
2. Suppose it cost Wolf $8000 to produce the Cell 7. Also suppose the market size is 1000 units. What is Wolf's expected profit?
3. Is this strategy better than Scenario V and W?
4. Can you draw a demand curve for etched plexiglass tanks?
5. Is this the best scenario? 22

24. Scenario X: Wolf Introduces Plexi, $30K Design

25. MR=MC Demand Curve

26. Conjoint Summary Experimental, so test threats to forecast validity
Conjoint is useful for
new & existing products
pricing
profit maximization when costs are incorporated
Product line decisions
Competition and cannibalization
For really new products, requires modification because people don’t have set tradeoffs

27. Perceptual Mapping Physical map of customer perceptions
Measuring similarity between two brands:
Ratings of similarity
Observed brand switching (switch to similar)
Correlation between brands in how they are rated on perceptual attributes (high correlation = similar)
Distance between two brands = f(dissimilarity)
Reposition by reformulating product or advertising
Expense = f(distance to be moved)
Sustainability = f(who can do it cheaper?) 27

28. Chicago Beer Market 28

29. Perceptual Mapping: Factor Analysis
Give consumers a list of brands (A, B, C, D, Miller, Hamms, Schlitz, Bud)
“With which are you familiar?”
Rate each on n attributes (mild flavor, malty, etc)
Factor analyze matrix of attribute ratings (use a separate row for each brand for each respondent)
Output shows
a) number dimensions
b) attributes most related to dimensions
c) brand locations 29

30. 30

31. Adding Customer Ideal Points
Add in preference data to get each consumer’s “ideal point.” Suppose ranking: Hamms, Schlitz, Bud, Miller, C, B, D, A.
Ideal closest to 1st ranked, 2nd closest to 2nd ranked, etc.
Cluster ideal points in segments.
Use to forecast shares. 31

32. 32

33. Perceptual Map Summary
Uses for Perceptual Maps:
Identify your closest competitors
Suggest repositioning strategies
Suggest advertising themes supporting repositioning
Identify brands that should be harvested
Identify new product opportunities where some segment not well served by current brands 33

34. Agenda 1st hour 2nd hour – Kevin Clark
Conjoint for product line extensions
Market Segmentation
Perceptual mapping (cont.)
Choosing basis for segmentation
Segmentation analyses
2nd hour – Kevin Clark
Program Director, Program Director, Brand and Values Experience
IBM Global Mobile Computing Segmentation case 34

35. Criteria for “Useful” Segments
Homogeneity within segment, heterogeneity between.
Systematic behaviors (Correlate segment membership w/ purchase, redemption, etc)
Marketing mix efficiency potential
Cost-driven (e.g., media to reach) or different elasticity with respect to some marketing mix variable.
Make more money treating as segments than if we treated market as unsegmented whole 35

36. Strategic v. Tactical
Strategic segmentation -- what product markets to serve? ESPN The Magazine, IBM which segments to deselect / select?
Tactical Segmentation -- should groups be treated same or differently wrt specific marketing decision variable?
Dog Food: Size of Dog as Segmentation
Hi Price, Meat & Cereal v. Lo Price, All Cereal
Ad Theme: Love of Master v. Dog’s Active Life 36

37. Analysis for Segmentation
Interaction and tactical market segmentation
A prior vs. clustering analytic approaches in segmentation 37

38. 38

39. Implications of Contrast
A variable that is an excellent basis for segmentation wrt 1 decision about a marketing mix element may be a poor basis for segmentation wrt another mix element
For any given mix element decision, when evaluating alternative bases for segmentation, look for ones with big differences in sensitivity to mix variable. 39

40. 40

41. Analysis: A Priori vs. Clustering Approaches
A priori -- Segments chosen by the analyst before collecting data
Gender (M,F), Age (20-39; 40-59;60+), Heavy v. medium v. light user
Clustering-based approaches (a posteriori)
Ask battery of questions (lifestyle, benefits sought, etc).
Find natural clusters/ segments. Approach taken in IBM case.
Don’t know going in how many segments
Describe segments by their mean answers to battery of usage situation questions 41

42. Summing Up Choosing a basis for segmentation Analysis for segmentation
3 Criteria for useful segments
Strategic vs. Tactical Segmentation
Analysis for segmentation
Interaction and Tactical Segmentation…A segmentation base that is useful for one tactical decision may be useless for another
A priori vs. clustering (a posteriori) approaches to segmentation 42