Conjoint Choice Introduction-overview

7/28/2019 Conjoint Choice Introduction-overview

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Choice-Based Conjoint Workshop

October, 2010

With information provided by

Sawtooth Software


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Outline

Introduction to Conjoint Analysis

Formulating Experiments

Conjoint Methods -types Use CBC software

Introduction to CBC analysis


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Introduction to Conjoint Analysis

Identify Your Goal

Design your experiment 5 stages

Interpreting part-worths and importance

A brief introduction to market simulations


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Different Perspectives, Different Goals

Public wants all of the most desirable features of

environmental assets at lowest possible cost

Providers want to maximize welfare by:1) minimizing costs of providing features

2) providing products/services that offer greater overall value than

other alternatives


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Demand or Preference Side of Equation

Focus first on demand/preference side of the

equation

After figuring out what consumer wants, next assesswhether it can be built/provided in a cost- effective

manner


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Products/Services are Composed of

Features/Attributes

Olive Oil Source, Price, Aroma, Size

Forest Harvesting Program

Live trees after harvesting, Cost , Dead trees

after harvesting, % of forest set aside from

harvest

Plastic Bag Management Cost/tax, % wildlife impact, durability, waste


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Breaking the Problem Down

If we learn how consumer values the components ofa product, we are in a better position to design those

that improve profitability

If we learn how the public values the components of

environmental goods and services, we are in a better

position to design those goods and services to

maximize societal welfare


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How to Learn What Customers/Public Want?

One way: Ask Direct Questions about preference

What Brand do you prefer?

How much would you pay for it?

What color do you prefer What size of container would you like?

Answers often trivial and unenlightening (e.g.

respondents prefer low fees to high fees, mediumsize than large etc..)


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How to Learn What Is Important?

One way: Ask Direct Questions about Importances

How important is it that you get the > that you want?


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Stated Importances

Importance Ratings often have low discrimination:


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Stated Importances

Answers often have low discrimination, with most

answers falling in very important categories

If they were not important, we probably wouldnt have

included them in the research!

Answers sometimes useful for segmenting market,

but still not very actionable

We still dont exactly what product they want


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What is Conjoint Analysis?

Research technique developed in early 70s

Measures how buyers value components of aproduct/service bundle

Dictionary definition-- Conjoint: Joined together,combined.

Marketers catch-phrase-- Features CONsideredJOINTly


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How Does Conjoint Analysis Work?

We vary the product/service features (independent variables) to buildmany (usually 12 or more) product concepts

We ask respondents to rate/rank or choose among a subset ofthoseproduct concepts (dependent variable)

Based on the respondents evaluations of the product concepts, wefigure out how much unique value (utility) each of the features(attributes) added

(Regress dependent variable on independent variables; estimatedbetas equal to part worth utilities.)


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Important Early Articles

Luce, Duncan and John Tukey (1964), Simultaneous Conjoint Measurement: A

New Type of Fundamental Measurement,Journal of Mathematical Psychology, 1,

1-27

Green, Paul and Vithala Rao (1971), Conjoint Measurement for Quantifying

Judgmental Data,Journal of Marketing Research, 8 (Aug), 355-363

Johnson, Richard (1974), Trade-off Analysis of Consumer Values,Journal ofMarketing Research, 11 (May), 121-127

Green, Paul and V. Srinivasan (1978), Conjoint Analysis in Marketing: New

Development with Implications for Research and Practice,Journal of Marketing,

54 (Oct), 3-19

Louviere, Jordan and George Woodworth (1983), Design and Analysis ofSimulated Consumer Choice or Allocation Experiments,Journal of Marketing

Research, 20 (Nov), 350-367


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Traditional, Less-Effective Questions

How important is horsepower to you in a

vehicle?

How important is fuel efficiency to you in a

vehicle?

Which is more important to you, horsepower

or fuel efficiency?


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Whats So Good about Conjoint?

More realistic questions:Which product would you prefer . . .

- 210 horsepower or - 140 horsepower

- 17 MPG - 28 MPG

If choose left, you prefer Power. If you choose right, you

prefer Fuel Economy

Rather than ask directly whether you prefer Power over Fuel

Economy, we present realistic tradeoff scenarios and infer

preferences from your product choices


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Whats So Good about Conjoint? (cont.)

When respondents are forced to make difficult

tradeoffs, we learn what they truly value

These values (utility scores) are associated with

specific and actionable attribute levels relevant to

the problem at hand


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Building a Model


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Building a Model

Inputs:

Attributes

Levels

Respondents

Prior Knowledge External Data

Experimental

Design

Conjoint Method

Outputs:

Utility Scores for each

level

Importance Scores for

each attribute

Ability to perform

Simulations


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Defining Attributes

Attributes are independent aspects of a product or aservice (Brand, Price, Size, Color etc.)

How many attributes?

-Depends on research objectives One rule of thumb was that no more than 6 0r 7 attributes

is too much May cause respondents to simplify, looking only at 2-3 most

important

Attributes should be independent, mutually exclusive Brand, quality and product life expectancy may all measure

the same thing

Each attribute has varying degrees, or levels Cost: $1, $2, $3


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Rules for Formulating Attribute

Levels

Attributes are assumed to be mutually

exclusive

Attribute: Add-on features

Level 1= Sun roof

Level 2= GPS system

Level 3=DVD player

If you define levels in this way, you cannotdetermine the value of providing 2 or 3 of these

features at the same time (or none of them)


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Solutions

8 level Attribute:

Features

None

Sunroof GPS system

DVD Player

Sunroof, GPS

Sunroof, DVD

GPS, DVD

Sunroof, GPS, DVD

3 Binary Attributes:

Sunroof:

None

Sunroof

GPS System

None

GPS

DVD Player

None

DVD Player


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Levels

Levels should have concrete/unambiguous

meaning

very expensive vs costs $575

weight: 5-7 kilos vs weight 6 kilos

-One description leaves meaning up toindividual interpretation, while the other does

not


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Levels

Dont include too many levels for any one

attribute

The usual number is about 3-5 levels per attribute

Make sure levels from your attributes can

combine freely with one another without resulting

in utterly impossible combinations (very unlikely

combinations OK)


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Attribute Examples

Cost

$1

$2

$3

Brand

A

B

C

ColorRed

Black

Blue

or graphics as well can be levels.


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Suggestions for Determining Which

Attributes & Levels to Include

Talk to all stakeholders

Focus Groups

Search of competitors websites, sales materials


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Other Inputs into the Model


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Conjoint Utilities (Part Worths)

Numeric values that reflect how desirable differentfeatures are:

Feature Utility

Vanilla 2.5Chocolate 1.8

25 5.335 3.2

50 1.4

The higher the utility, the better


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Interpreting Conjoint Utilities

Interval scaled data (no ratio operations!)

You cannot compare one level from one attribute

with one level from another attribute, since conjoint

utilities are scaled to an arbitrary constant withineach attribute (often zero-centered)

You CAN compare differences between two levels of

one attribute versus two levels of another attribute

(an addition operation)


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Conjoint Importances

Ratio scaled data Measure of how much influence each attribute has on peoples

choices

Best minus worst level of each attribute, then percentaged:

Vanilla - Chocolate (2.5 - 1.8) = 0.7 15.2%25 - 50 (5.3 - 1.4) = 3.9 84.8%

----- --------Totals: 4.6 100.0%

Importances are directly affected by the range of levels youchoose for each attribute


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Market Simulations

Make alternative program/services scenarios and predict

which program/services respondents would choose

Accumulate (aggregate) respondent predictions to make

Shares of Preference (some refer to them as marketshares)


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Market Simulation Example

Predict market shares for 35 Vanilla cone vs. 25 Chocolate

cone for Respondent #1:

Vanilla (2.5) + 35 (3.2) = 5.7

Chocolate (1.8) + 25 (5.3) = 7.1

Respondent #1 chooses 25 Chocolate cone!

Repeat for rest of respondents. . .


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Market Simulation Results

Predict responses for 500 respondents, and we might seeshares of preference like:

65% of respondents prefer the 25 Chocolate cone

35%

65%

Vanilla @ 35

Chocolate @ 25


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So you want to do a conjoint..


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Step 1: Begin With the End in Mind

What is the objective of the research?

How much will public be willing to pay for biologicalcontrol feature?

Will farmers switch and adopt a different varieties?

The better you define the root problem, thebetter your research will be!


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Step 2: Plan Your Analysis

Identify how clients need to use data

Deliver analysis plan to clients as part of research

proposal Makes sure that objectives and deliverables are clear


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Step 3: Define Attributes and Levels

How many attributes? Depends on researchobjectives

More than 6 attributes may cause respondents to

simplify, looking only at 3-4 most important Attributes should be independent, mutually

exclusive

Brand, quality, product life expectancy may all

measure the same thing


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Rules for Formulating

Attribute Levels

Levels are assumed to be mutually exclusive

Attribute: Add-on features

level 1: Manuallevel 2: Biological Controllevel 3: Chemical

If you define levels in this way, you cannot determine thevalue of providing two or three of these features at thesame time (or none of them)


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Attribute Levels

Dont include too many levels for any one attribute The usual number is about 3 to 5 levels per attribute

One temptation is to include many levels for price, so we canestimate peoples preferences for each

Better approach usually is to interpolate between fewermore precisely measured levels for not asked aboutprices

Cover the range of probable values


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Attribute Levels

Make sure levels from your attributes can combine freely withone another without resulting in utterly impossiblecombinations (very unlikely combinations OK)


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Representing Levels

Text High Performance Sports Car

Pictures / Graphics

Sample boards Allows respondents to touch or feel samples for tactile attributes

(towel softness, greeting card paper quality, etc.)

Null Level Has Stereo vs. __________

Low

Medium

High


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Step 3: Choose a conjoint method

Step 4: Identify Research Constraints Sample issues

Sample Population >200

Length of survey (how long can I keep theirattention)

Fielding issues

Budget

Client sophistication

Example of a Pair of Soda Product Profile


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Attributes Program A: Program B:Cost $.50 $.25

Color Red Silver

Size .33 l .75 l

Sugar level Diet/light Regular

Example of a Pair of Soda Product Profile

Scenarios


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How to tell if you are in over your

head

You should be okay if

Small number of attributes

Attributes freely combine with one another Large sample, even after adjusting for subgroup

analysis

Your client can describe the analysis, attributes inone paragraph or less, and you can then explain it

to a six year old with little difficulty!


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Section 2

Intro to Choice-Based Conjoint (Discrete

Choice Modeling)


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Setting Up CBC Interview (Definitions)

Concept 1 Concept 2 Concept 3 Concept 4

How many concepts per task?

How many tasks per survey?

Task


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How Many Concepts per Task?

Generally, 2 to 5 concepts are used

Attribute text length, graphical representation affect the

decision


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How Many Tasks per Survey?

Respondents are expensive to recruit. It makes sense toask respondents multiple choice tasks.

Respondents take about 7 minutes on average to answer20 tasks (~20 seconds per task)

CBC is very flexible in terms of how many tasks to include.Minimum is just one task! (but youll need huge samplesize, and will face limitations in analysis)

Typical choice is 12 to 18 choice tasks


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Test CBC Design

What is a Design? The sum total of information about the

attribute levels being shown in the CBC tasks across all

respondents. (The independent variable matrix)

If you use ANY prohibitions, or use few questionnaire

versions, you MUST test your design

Failure to test the design can invalidate your study

CBC/Web automatically tests your design when it generates

the design file--pay attention to the test!


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The None Concept

Pros:

Respondents arent forced to choose a product concept

that they really dont like

Lets you capture information about whether respondents

(or segments) are more or less interested in buying the

product concept

Cons:

Choices of None provide much less information for

estimating utilities than other choices (reduces the

effectiveness of your sample size)

None utilities and Shares of Preference for None are

difficult to interpret

Design Stage of CCE


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Design Stage of CCE


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Exercise

Decide on topic

Discuss how you are going to decide the

attributes and the levels

Begin to think about attitudes

Assign team members tasks for the above

Be efficient

Conjoint Choice Introduction-overview

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