1. MG 506 Fall 1999: Class 2 (9/21/99) Tuesday, September 21, 1999 u Marketing information systems u Announcements –email –Tapes –Cases –Teams –I’ll be out Thursday through Friday AM –Proquest u Case: MSA

2. MG 506 Fall 1999: Class 2 (9/21/99) The Market Driven Organization u Gathers information u Disseminates information u Uses information

3. MG 506 Fall 1999: Class 2 (9/21/99) Example: Celestial Seasonings u Taste tests on site u Weekly panels (3 sites/weekend) u Focus groups in 11 cities u Mall intercepts u National samples u Customer service – Tracy Jones

4. MG 506 Fall 1999: Class 2 (9/21/99) Market Research Process 1. Determine final uses of information 2. Determine final report format 3. Specify necessary analysis 4. Determine data requirements 5. Scan available secondary data sources 6. Design study 7. Implement field work 8. Analyze and report

5. MG 506 Fall 1999: Class 2 (9/21/99) Potential Problems in Research Use u Confusing managerial and statistical significance u Confusion relationships and causality u The use of inappropriate data u Overreliance on quantitative data u Pressure to generate desired solutions

6. MG 506 Fall 1999: Class 2 (9/21/99) Ethical Issues: The User u Issuing bid requests for free advice u Poor use of information u Making false promises u Access to information

7. MG 506 Fall 1999: Class 2 (9/21/99) Market Assessment

8. MG 506 Fall 1999: Class 2 (9/21/99) Uses of Conjoint Analysis u Product design u Market segmentation u Forecasting shares of product concepts u Pricing

9. MG 506 Fall 1999: Class 2 (9/21/99) Conjoint is Suitable When... u We must make tradeoffs between attributes and benefits in the product u We can decompose the product in ways that are meaningful for customers and product design u It is possible to describe the product bundles realistically

10. MG 506 Fall 1999: Class 2 (9/21/99) Product Design: Conjoint Analysis Derive utility values for attributes and attribute options based on customers’ stated overall preferences for different bundles of attributes. Example: Memory and Price bundles. Price Memory$1,000$1,500$2,000 32 Mb421 64 Mb753 128 Mb986 9 =Most preferred 1 =Least preferred

11. MG 506 Fall 1999: Class 2 (9/21/99) Simplified Utility Calculation PricePart- Memory$1,000$1,500$2,000Worth 32 Mb4217/32.3 64 Mb75315/35.0 128 Mb98623/37.7 20/315/310/3 Part-Worth:6.75.03.3 9 =Most preferred 1 =Least preferred

12. MG 506 Fall 1999: Class 2 (9/21/99) Utility for this Customer Example: 128 Mb vs. 64 Mb = 7.7 – 5.0=2.7 units $1,000 vs. $1,500 = 6.7 – 5.0=1.7 units So:  64 Mb is worth more than $500 to this customer.

13. MG 506 Fall 1999: Class 2 (9/21/99) Alternative: Pairwise Comparisons of Full Profiles u PII 233 u 64MB u 4.3 HD u DVD u $2299 u PII 233 u 64MB u 4.3 G HD u 24X CD u $1979 For example:

14. MG 506 Fall 1999: Class 2 (9/21/99) Designing the Conjoint Study u Determine relevant attributes u Determine attribute levels u Determine attribute combinations u Choose stimulus representations u Choose response type u Choose data analysis technique

15. MG 506 Fall 1999: Class 2 (9/21/99) Market Share Forecast u We can estimate market shares by estimating utility for different product offerings and calculating the percentages of preference for each product in the study

16. MG 506 Fall 1999: Class 2 (9/21/99) The Bass Diffusion Model u When will a customer adopt a new product or technology? u Useful when: –The product has been recently introduced –The product has not yet been introduced but there are reasonable parallels

17. MG 506 Fall 1999: Class 2 (9/21/99) Assumptions of the Basic Bass Model u Diffusion process is binary u Constant number of maximum potential buyers u All potential buyers will eventually purchase the product u No repeat purchases or replacement purchases u The impact or word of mouth is independent of adoption time u Innovation is considered independent of substitutes u The marketing strategies supporting the innovation are not explicitly included

18. MG 506 Fall 1999: Class 2 (9/21/99) The Bass Diffusion Model S t =p  Remaining+q  Adopters  PotentialRemaining Potential InnovationImitation EffectEffect where: S t =sales at time t p=“coefficient of innovation” q=“coefficient of imitation” # Adopters=S 0 + S 1 + + S t–1 Remaining=Total Potential – # Adopters Potential

19. MG 506 Fall 1999: Class 2 (9/21/99) Examples of Bass Model Parameters InnovationImitation Product/parameter parameter Technology (p)(q) B&W TV0.0280.25 Color TV0.0050.84 Air conditioners0.0100.42 Clothes dryers0.0170.36 Water softeners0.0180.30 Record players0.0250.65 Cellular telephones0.0041.76 Steam irons0.0290.33 Motels0.0070.36 McDonalds fast food0.0180.54 Hybrid corn0.0391.01 Electric blankets0.0060.24 A study by Sultan, Farley, and Lehmann in 1990 suggests an average value of 0.03 for p and an average value of 0.38 for q. Source: Lilien and Rangaswamy

20. MG 506 Fall 1999: Class 2 (9/21/99) Specification of the Model

21. MG 506 Fall 1999: Class 2 (9/21/99) Product Factors Affecting the Rate of Diffusion u High relative advantage over existing products u High degree of compatibility with existing approaches u Low complexity u Can be tried on a limited basis u Benefits are observable

22. MG 506 Fall 1999: Class 2 (9/21/99) Market Factors Affecting the Rate of Diffusion u Type of innovation adoption decision u Communication channels used u Nature of “links” among market participants u Nature and effect of promotional efforts

23. MG 506 Fall 1999: Class 2 (9/21/99) Caveat u Do customers have the ability to articulate preferences? u Market research is probably not helpful when a new technology is not tied to familiar applications –e.g., the personal computer, internet access

24. MG 506 Fall 1999: Class 2 (9/21/99) Observation Can Overcome... u Customers who don’t know possible applications u Unreliability of self reporting u Interruption/removal from natural use u Giving expected answers

25. MG 506 Fall 1999: Class 2 (9/21/99) Empathic Design (Leonard and Rayport) u Gathering, analyzing, and applying information gleaned from field observations u Requires creative interdisciplinary analysis

26. MG 506 Fall 1999: Class 2 (9/21/99) Learning from Observation u Triggers of use u Interactions with the user’s environment u User customization u Intangible product attributes u Unarticulated user needs

27. MG 506 Fall 1999: Class 2 (9/21/99) The Empathic Design Process u Observation u Capturing data u Reflection and analysis u Brainstorming for solutions u Developing prototypes of possible solutions

28. MG 506 Fall 1999: Class 2 (9/21/99) The Challenge u Linking technology with needs to develop solutions