mg 506 fall 1999: class 2 (9/21/99) tuesday, september 21, 1999 u marketing information systems u...
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MG 506 Fall 1999: Class 2 (9/21/99)
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)
The Market Driven Organization
Gathers information Disseminates information Uses information
MG 506 Fall 1999: Class 2 (9/21/99)
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)
Market Research Process
1. Determine final uses of information2. Determine final report format3. Specify necessary analysis4. Determine data requirements5. Scan available secondary data sources6. Design study7. Implement field work8. Analyze and report
MG 506 Fall 1999: Class 2 (9/21/99)
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)
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)
Uses of Conjoint Analysis
Product design Market segmentation Forecasting shares of product concepts Pricing
MG 506 Fall 1999: Class 2 (9/21/99)
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)
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 2 164 Mb 7 5 3
128 Mb 9 8 6
9 = Most preferred•••
1 = Least preferred
MG 506 Fall 1999: Class 2 (9/21/99)
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 5.0128 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)
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.
MG 506 Fall 1999: Class 2 (9/21/99)
Alternative: Pairwise Comparisons of Full Profiles
PII 233 64MB 4.3 HD DVD $2299
PII 233 64MB 4.3 G HD 24X CD $1979
For example:
MG 506 Fall 1999: Class 2 (9/21/99)
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)
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)
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)
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)
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 – # AdoptersPotential
MG 506 Fall 1999: Class 2 (9/21/99)
Examples of Bass Model Parameters
Innovation ImitationProduct/ parameter
parameter Technology (p) (q)
B&W TV 0.028 0.25Color TV 0.005 0.84Air conditioners 0.010 0.42Clothes dryers 0.017 0.36Water softeners 0.018 0.30Record players 0.025 0.65Cellular telephones 0.004 1.76Steam irons 0.029 0.33Motels 0.007 0.36McDonalds fast food 0.018 0.54Hybrid corn 0.039 1.01Electric 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)
Specification of the Model
imitation oft coefficien the q
innovation oft coefficien the p
segment adopting in the customers ofnumber totalN
tby time innovation the adopted have whocustomers of # N(t) :where
)]([)()()( 2
tNN
qtNpqNptn
MG 506 Fall 1999: Class 2 (9/21/99)
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)
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)
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)
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)
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)
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)
The Empathic Design Process
Observation Capturing data Reflection and analysis Brainstorming for solutions Developing prototypes of possible solutions