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)

Market Assessment

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

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

The Challenge

Linking technology with needs to develop solutions