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Tuesday, September 21, 1999

Tuesday, September 21, 1999. Marketing information systems Announcements email Tapes Cases Teams I’ll be out Thursday through Friday AM Proquest Case: MSA. The Market Driven Organization. Gathers information Disseminates information Uses information. Example: Celestial Seasonings.

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Tuesday, September 21, 1999

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

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

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

  4. 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 MG 506 Fall 1999: Class 2 (9/21/99)

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

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

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

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

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

  10. 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. PriceMemory $1,000 $1,500 $2,000 32 Mb 4 2 1 64 Mb 7 5 3 128 Mb 9 8 6 9 = Most preferred • • • 1 = Least preferred MG 506 Fall 1999: Class 2 (9/21/99)

  11. Simplified Utility Calculation Price Part- Memory $1,000 $1,500 $2,000 Worth 32 Mb 4 2 1 7/3 2.3 64 Mb 7 5 3 15/3 5.0 128 Mb 9 8 6 23/3 7.7 20/3 15/3 10/3 Part-Worth: 6.7 5.0 3.3 9 = Most preferred • • • 1 = Least preferred MG 506 Fall 1999: Class 2 (9/21/99)

  12. 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: D 64 Mb is worth more than $500 to this customer. MG 506 Fall 1999: Class 2 (9/21/99)

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

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

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

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

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

  18. The Bass Diffusion Model St = p ´ Remaining + q ´ Adopters ´ Potential Remaining Potential Innovation Imitation Effect Effect where: St = sales at time t p = “coefficient of innovation” q = “coefficient of imitation” # Adopters = S0 + S1 + • • • + St–1 Remaining = Total Potential – # Adopters Potential MG 506 Fall 1999: Class 2 (9/21/99)

  19. Examples of Bass Model Parameters Innovation Imitation Product/ parameter parameter Technology (p) (q) B&W TV 0.028 0.25 Color TV 0.005 0.84 Air conditioners 0.010 0.42 Clothes dryers 0.017 0.36 Water softeners 0.018 0.30 Record players 0.025 0.65 Cellular telephones 0.004 1.76 Steam irons 0.029 0.33 Motels 0.007 0.36 McDonalds fast food 0.018 0.54 Hybrid corn 0.039 1.01 Electric blankets 0.006 0.24 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 MG 506 Fall 1999: Class 2 (9/21/99)

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

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

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

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

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

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

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

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

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

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