Discrete Choice Conjoint that Cuts Through the Clutter Are you sick of messing around with discrete choice conjoint software that’s too complicated? Do you want to run conjoint without all kinds of extras you don’t need? Are you tired of paying too much for conjoint? Do you want to run your conjoint study without reading a manual? In this webinar Survey Analytics CEO Andrew Jeavons and VP Esther LaVielle held a discussion of discrete choice conjoint and gave a demonstration of Survey Analytics' straightforward and powerful conjoint tool.

1. Chainsaw
Conjoint
Andrew Jeavons
CEO, Survey Analytics
Esther LaVielle
Vice President, Survey Analytics

2. About Survey Analytics
A suite of interconnected and easy-to-use information collection and
analysis tools, including online surveys, mobile data collection, advanced
analytics and data visualization.
Enterprise Research Platform
Mobile Visualization & Analytics
Mobile Field Data Collection
Mobile Surveys and Panels
Mobile Passive Data Collection

3. Andrew Jeavons Esther LaVielle
CEO of Survey Analytics Vice President of Client Services
at Survey Analytics
25 years in the market research
industry. Background in Esther is in charge of worldwide
psychology and statistics, and client relations. With the
currently focuses on innovation assistance of her colleagues,
within survey research. Survey Analytics has a solid
support network for clients.

4. Webinar Agenda
1. What do we mean by Chainsaw Conjoint?
2. The theory and logic behind discrete choice conjoint analysis
3. When to use discrete choice conjoint in your research
4. Specific examples of how to use discrete choice conjoint
5. How to design a discrete choice conjoint project
6. How to write a discrete choice conjoint questionnaire
7. How to analyze the results of a discrete choice conjoint project
8. Tips and Best Practices
9. Q & A

5. What Do We Mean by “Chainsaw” Conjoint?
• Simple
• Powerful
• Easy to Use
• Durable
• Impressive
• Draws Attention
• Gets the Job Done

6. What is Conjoint Analysis?
Type of Trade-off Analysis methodology
Developed over the past 50 years by market researchers and statisticians to
predict the kinds of decisions consumers will make about products by using
questions in a survey.
Conjoint analysis questions presents a series of possible products to consumers and
asks them to make a choice about which one they would pick.
The central idea: For any purchase decision consumers evaluate or “trade-off”
the different characteristics of a product and decide what is more important to
them.
Survey Analytics uses Discrete Choice Conjoint Analysis which best simulates the
purchase process of consumers

7. Statistics are...
•Not accurate...
•Not magic...
•As good as your design...
•As good as your sample...

8. The Kitchen
Sink is Not
a Good
Idea...

9. Wanna Buy A Puppy?
• Breed
• Dog Breeder
• Size
• Price
• Care Needed
• Personality
• Life Span

10. Theory & Logic of Conjoint Analysis
It will help you evaluate new products or variations against an existing range of products
already offered by your company or within the marketplace.
It’s much cheaper than developing new products for the marketplace with no guarantee of
success.
Get real-time feedback on new products or variations of existing products.
Simulates the decisions your target consumers would make in the market place.
Gives you an idea how a new product with be received
in the marketplace.
Gauge the affect on the choice/price relationship relative
to existing products and features presented.

11. How do we come up with our numbers ?
Survey Analytics uses a maximum likelihood calculation coupled with
a Nelder-Mead Simplex algorithm.
Design options are random, D-Optimal or your own imported design.
Have greater confidence in the results you receive !

12. Conjoint Analysis
Core Concepts
1)Attributes/Feature:
Define the attributes of the products for your
market. These are the properties of
your product.
Seattle Tourism Study:
#Hours
Time of Day
Tour Type
2) Levels: The different properties of the
attributes. Define at least two levels for each
of the attributes.
Hours - 3 levels
Time of day - 4 levels
Tour Type: 5 levels

13. CORE CONCEPTS
Conjoint Analysis Core Concepts:
3) Utility Value or Part Worth functions:
These are what are produced by the conjoint analysis. These
can then be used to determine how important an attribute
is to the purchase or choice process and in “market
simulations.”
Utility Value of Hrs on Tour:
1-2hrs = .39
2-4hrs = .45
4-6hrs = .32
4) Relative importance:
How important an attribute is in the purchasing/choice
decision ?
Example:Of all features to go on tour –
“Time of day” determined which one most chosen

14. Setting up a Conjoint Analysis Project
Kind of reminds me of
putting together a
jigsaw puzzle…..
All the pieces in the
project should fit
together before fielding
the project!

15. Survey Analytics offers 3
Conjoint Analysis Designs
Random Design
D-Optimal Design
Import Design

16. 3 Conjoint Analysis Designs - Defined
Random: Random design is a purely random sample of the possible
attribute levels. For the number of tasks per respondent
SurveyAnalytics produces a unique set of attribute configurations to
be presented to the respondent.
D-Optimal: This is a design algorithm that will produce an optimal design
for the specified number of tasks per respondent and sample size.
More information on this design algorithm is available in the D-
Optimal section.
Import Design: This allows designs, in the SPSS design format, to be
imported and used by the SurveyAnalytics DCM module. This is useful
when users want to use designs not generated by SurveyAnalytics,
such as fractional factorial orthogonal designs.

17. # How to Set up a Conjoint Analysis Question
Question Setup for
Random, D-Optimal,
and Import Design
are the same:
1.Set up Features/
Attributes
2. Set up Levels for
Each attributes
EXAMPLE:
Feature: Hours
Levels: 1-2hr, 2-4hr

18. How to Set up Conjoint Analysis Parameters
Set up Prohibited Pairs
The engine will not display two levels that have been marked as
"Prohibited" in the same concept (as a product) for the user to
choose.

19. Prohibited Pairs
Example: A Weird Seattle Tour will never be 4-6 hrs long

20. Concept Simulator
This can be used to determine what choices will be
presented to the respondents when your survey is
actually deployed. Use as Guidance.

21. D-Optimal Design
Click on Settings >> Design Type >> Doptimal
>> Select Versions >> Start >> Save Settings

22. D-Optimal Design
Click on Settings >> View Options>> Make changes >> Update Design

23. Import Design
Import Design allows designs, in the SPSS design format, to be imported and used by the
Survey Analytics DCM module. This is useful when users want to use designs not generated
by Survey Analytics, such as fractional factorial orthogonal designs.
Step 1: Start by adding a Conjoint DCM question as
is walked through above.
Ensure that under 'Task Count' and 'Concepts Per
Task' you choose the same numbers as that you
have in the Excel sheet you are
going to import
Step 2: Click on 'Settings'.
In the in-line popup in ’
Design type' choose 'Import’

24. Conjoint Analysis Survey Preview

25. Conjoint Analysis Preview with Pictures

26. Review Data:
Utility Calculation & Relative Importance

27. Relative Importance
Relative Importance of attributes
Displayed as Pie chart
*Shows here that Tour Type
Is the most significant feature/
attribute which determines what
tour they want to take.

28. Relative Importance and Average Utility Table
The tour type is
the most important attribute
Weird is GOOD! Chocolate is popular

29. Best & Worst Profile
The tour type is best liked.
Weird works.
The tour type is best liked.
Weird works.

30. Market Segmentation Simulator
Using existing Data from Conjoint Analysis

31. Market Segment Simulator gives you
Market Segmentation existthe ability to "predict" the market share of new
products and concepts that may not
Simulator
today.
Ability to measure the "Gain" or "Loss" in market share based on changes to existing
products in the given market.
Important steps in Conjoint Simulation:
1- Describe/Identify the different products or concepts that you want to investigate. We
call "Profiles".
Example: Tour Type: Weird, Hours: 1-2 , Time of Day: Evening
2- Find out all the existing products that are available in that market segment and
simulate the market share of the products to establish a baseline.
3-Try out new services and ideas and see how the market share shifts based on new
products and configurations.

32. Setting up a Simulator
1) Click on Online tools >>Name Simulator Profile>>change profiles
2) Click on to see results!

33. Results: Simulator Output Defined
The market simulator uses utility values to project the
probability of choice and hence the market share

34. Now that we know
how to use this . .
What can we ask
and find out with the
Market Segmentation Simulator?

35. Segmentation Simulator
Quick Example: What happens if have a tour of 1-2 hours as
opposed to 4-6 hours in the afternoon for “Weird Seattle” ?
Answer: We find that the 1-2 hour tour would attract about 75%
of the market share.

36. Tips for A Successful Conjoint Analysis Project

37. Best Practices: Where to Begin?
You must use qualitative research first!
What are the top attributes?
What range?
What language?
A focus group or surveys with open-ended
questions will help define your top attributes
needed for your study
Use Crowdsourcing tools: IdeaScale
+ Other survey methods

38. What Sample Size To Start With?
Sample size is a question that comes up very frequently. Richard Johnson, one of the
inventors of conjoint analysis, has presented the following rule of thumb for
sample size in choice based conjoint:
(nta/C) > 1000
Where n = the number of respondents x t= the number of tasks x a=the number of
alternatives per task / C= the largest number of level for any one attribute.
So if you have 500 respondents, 3 tasks per respondent, 2 alternatives per task
and the maximum number of levels on an attribute is 3 you get:
(500 x 3 x 2) / 3 = 1000
Generally speaking sample sizes tend to be around 200 – 1200 respondents, admittedly
a wide range. 300 comes up most often for a single homogeneous group of subjects.

39. Practices & Tips: Surveys with Conjoint Analysis
Keep the options clear and simple as possible
No more than 20 trade-off exercises
No more than 5-6 attributes
Keep the ranges simple
You can ask more intimate questions of current
customers than potential customers, but don’t let that
stop you from trying!
Follow general good online survey techniques
Test your survey
Make it clear responses are kept strictly confidential
Keep survey to 15-20 minutes
Provide incentives

40. Survey Analytics Discrete Choice Conjoint Vs. Competition
Discrete Choice Conjoint Analysis
Flexible pricing available
Most user-friendly conjoint tool on the market
Real-time reporting
Pricing includes integrated research tools that would enhance efficiencies and
depth and research strategies
Dedicated account management and support included

41. Thank
You!
Andrew
Jeavons,
andrew.jeavons@surveyanaly9cs.com
sales-­‐team@surveyanaly9cs.com Esther
LaVielle,
esther.rmah@surveyanaly9cs.com
800-­‐326-­‐5570