Thanks for checking out the slides from our webinar that aired on December 4th 2013 titled How to Use Conjoint and MaxDiff to Put Your Best Product Forward.
How do people develop preferences for products and services? In this presentation you will learn how using Conjoint Analysis/MaxDiff Scaling make products and services better moving forward. Posing these simple questions can validate your market share and maximize your profits without over investing in an idea.
What is Conjoint Analysis?
A statistical technique used in market research to determine how people value different features that make up an individual product or service
The Objective:
Determine what combination of a limited number of attributes is most influential on respondent choice or decision making
What about MaxDiff Scaling?
MaxDiff assumes that respondents evaluate all possible pairs of items within the displayed set and choose the pair that reflects the maximum difference in preference or importance. These are comparative judgments that can be easily performed, even when the number of attributes is not small (up to 30). The task presents respondents with a set of items, usually 3 to 6, and simply asks them to select the most preferred and the least preferred in the set.
Another name for it : Best/Worst Scaling
Respondents can typically handle a number of these evaluations, and may be asked to respond to a series of maxdiff questions to gather more preference data.
3. “HI FOLKS!”
Esther LaVielle
VP of Client Services
Agenda ...
4 Years with Survey Analytics
7 Years Market Research Experience
Qualitative & Quantitive
“When I’m not working and assisting clients with conjoint
analysis projects, I enjoy being in nature, traveling, cooking
new recipes, eating and trying out new restaurants and food
trucks around Portland,OR and hanging out with my dog,
Cooper.”
Wednesday, December 4, 13
4. How to Use Conjoint & MaxDiff To Put Your
Best Product Forward
Wednesday, December 4, 13
5. AGENDA
•
•
How to set a Conjoint Question in SA
•
Conjoint Analysis 101
•
MaxDiff Definitions
•
MaxDiff vs. Rating Scales
•
New Enhancements on MaxDiff
•
Live Demo of both Conjoint & Maxdiff
•
Wednesday, December 4, 13
Conjoint Definitions
Q &A
7. CHOICE BASED CONJOINT ANALYSIS
Conjoint is like is display case of
doughnuts . . .
Wednesday, December 4, 13
8. CHOICE BASED CONJOINT ANALYSIS
Conjoint is like is display case of
doughnuts . . .
A statistical technique used in market research to
determine how people value different features that make up
an individual product or service
Wednesday, December 4, 13
9. CHOICE BASED CONJOINT ANALYSIS
Conjoint is like is display case of
doughnuts . . .
A statistical technique used in market research to
determine how people value different features that make up
an individual product or service
The objective: Determine what combination of a limited
number of attributes is most influential on respondent
choice or decision making
Wednesday, December 4, 13
10. CHOICE BASED CONJOINT ANALYSIS
Conjoint is like is display case of
doughnuts . . .
A statistical technique used in market research to
determine how people value different features that make up
an individual product or service
The objective: Determine what combination of a limited
number of attributes is most influential on respondent
choice or decision making
Survey Analytics ONLY supports the Choice Based / Discrete
Choice Conjoint Analysis methodology
Wednesday, December 4, 13
11. CHOICE BASED CONJOINT ANALYSIS
Conjoint is like is display case of
doughnuts . . .
A statistical technique used in market research to
determine how people value different features that make up
an individual product or service
The objective: Determine what combination of a limited
number of attributes is most influential on respondent
choice or decision making
Survey Analytics ONLY supports the Choice Based / Discrete
Choice Conjoint Analysis methodology
CBC empowers the shopper to choose what they want to
buy from you. You, the survey creator, are figuratively
placing the survey taker in front of the display (of doughnuts)
Wednesday, December 4, 13
12. CHOICE BASED CONJOINT ANALYSIS
Conjoint is like is display case of
doughnuts . . .
A statistical technique used in market research to
determine how people value different features that make up
an individual product or service
The objective: Determine what combination of a limited
number of attributes is most influential on respondent
choice or decision making
Survey Analytics ONLY supports the Choice Based / Discrete
Choice Conjoint Analysis methodology
CBC empowers the shopper to choose what they want to
buy from you. You, the survey creator, are figuratively
placing the survey taker in front of the display (of doughnuts)
Price, flavors, types of ingredients, texture, time of day
etc. will influence which doughnuts they will buy
Wednesday, December 4, 13
13. WHY CONJOINT ANALYSIS?
If you are trying to determine the best
combination of products/services to sell that will
make you the most money . . .
Wednesday, December 4, 13
14. WHY CONJOINT ANALYSIS?
If you are trying to determine the best
combination of products/services to sell that will
make you the most money . . .
Choice Based Conjoint mimics the decision making process
without actually needing to physically create & sell these
products/services. Selling ideas through surveying your
target consumer.
Wednesday, December 4, 13
15. WHY CONJOINT ANALYSIS?
If you are trying to determine the best
combination of products/services to sell that will
make you the most money . . .
Choice Based Conjoint mimics the decision making process
without actually needing to physically create & sell these
products/services. Selling ideas through surveying your
target consumer.
Will allow you to review estimated market share and run
simulations of concepts before deciding what’s going to give
you the biggest ROI.
Wednesday, December 4, 13
16. WHY CONJOINT ANALYSIS?
If you are trying to determine the best
combination of products/services to sell that will
make you the most money . . .
Choice Based Conjoint mimics the decision making process
without actually needing to physically create & sell these
products/services. Selling ideas through surveying your
target consumer.
Will allow you to review estimated market share and run
simulations of concepts before deciding what’s going to give
you the biggest ROI.
It’s easy to add on to your current online/mobile research
strategy. Survey Analytics has the easiest conjoint set up in
the business.
Wednesday, December 4, 13
17. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
•
Levels / Attributes: An object or
characteristic that is directly related to the
defined features.
•
The features and levels have to be set in stone
PRIOR to running a conjoint project. Critical to
success of a project.
•
Rule of thumb: Generally aim for no more
than 5-7 features and no more than 5-7 levels.
•
Task Count: Number of conjoint cycles you
want to show the respondents.
•
Wednesday, December 4, 13
Features: A prominent or distinctive aspect,
quality, or characteristic that is an important part
of a package of goods.
Concepts per task: Number of concepts or
packages you want to display on each cycle
(page). N/A Option is possible if desired.
18. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
•
Levels / Attributes: An object or
characteristic that is directly related to the
defined features.
•
The features and levels have to be set in stone
PRIOR to running a conjoint project. Critical to
success of a project.
•
Rule of thumb: Generally aim for no more
than 5-7 features and no more than 5-7 levels.
•
Task Count: Number of conjoint cycles you
want to show the respondents.
•
Wednesday, December 4, 13
Features: A prominent or distinctive aspect,
quality, or characteristic that is an important part
of a package of goods.
Concepts per task: Number of concepts or
packages you want to display on each cycle
(page). N/A Option is possible if desired.
19. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
•
Levels / Attributes: An object or
characteristic that is directly related to the
defined features.
•
The features and levels have to be set in stone
PRIOR to running a conjoint project. Critical to
success of a project.
•
Rule of thumb: Generally aim for no more
than 5-7 features and no more than 5-7 levels.
•
Task Count: Number of conjoint cycles you
want to show the respondents.
•
Wednesday, December 4, 13
Features: A prominent or distinctive aspect,
quality, or characteristic that is an important part
of a package of goods.
Concepts per task: Number of concepts or
packages you want to display on each cycle
(page). N/A Option is possible if desired.
20. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
•
Levels / Attributes: An object or
characteristic that is directly related to the
defined features.
•
The features and levels have to be set in stone
PRIOR to running a conjoint project. Critical to
success of a project.
•
Rule of thumb: Generally aim for no more
than 5-7 features and no more than 5-7 levels.
•
Task Count: Number of conjoint cycles you
want to show the respondents.
•
Wednesday, December 4, 13
Features: A prominent or distinctive aspect,
quality, or characteristic that is an important part
of a package of goods.
Concepts per task: Number of concepts or
packages you want to display on each cycle
(page). N/A Option is possible if desired.
21. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
Prohibited Pairs: Prevents specific pairs
of levels from showing up as part of a
concept.
•
*Only on a 1-to-1 level*
•
Fixed Tasks: Allows you to set up a
controlled concept and test against random
or d-optimal generated concepts.
•
Tips for Respondents: Add Additional
Info/Pictures to Conjoint features/Attributes
What does Bacon topping look like? Add
picture and description
•
Where is validation for conjoint?:
Located under Survey Overview
Wednesday, December 4, 13
22. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
Prohibited Pairs: Prevents specific pairs
of levels from showing up as part of a
concept.
•
*Only on a 1-to-1 level*
•
Fixed Tasks: Allows you to set up a
controlled concept and test against random
or d-optimal generated concepts.
•
Tips for Respondents: Add Additional
Info/Pictures to Conjoint features/Attributes
What does Bacon topping look like? Add
picture and description
•
Where is validation for conjoint?:
Located under Survey Overview
Wednesday, December 4, 13
23. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
Prohibited Pairs: Prevents specific pairs
of levels from showing up as part of a
concept.
•
*Only on a 1-to-1 level*
•
Fixed Tasks: Allows you to set up a
controlled concept and test against random
or d-optimal generated concepts.
•
Tips for Respondents: Add Additional
Info/Pictures to Conjoint features/Attributes
What does Bacon topping look like? Add
picture and description
•
Where is validation for conjoint?:
Located under Survey Overview
Wednesday, December 4, 13
24. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
Prohibited Pairs: Prevents specific pairs
of levels from showing up as part of a
concept.
•
*Only on a 1-to-1 level*
•
Fixed Tasks: Allows you to set up a
controlled concept and test against random
or d-optimal generated concepts.
•
Tips for Respondents: Add Additional
Info/Pictures to Conjoint features/Attributes
What does Bacon topping look like? Add
picture and description
•
Where is validation for conjoint?:
Located under Survey Overview
Wednesday, December 4, 13
25. *Cool New Stuff*
CONJOINT SET UP DEFINITIONS
•
Prohibited Pairs: Prevents specific pairs
of levels from showing up as part of a
concept.
•
*Only on a 1-to-1 level*
•
Fixed Tasks: Allows you to set up a
controlled concept and test against random
or d-optimal generated concepts.
•
Tips for Respondents: Add Additional
Info/Pictures to Conjoint features/Attributes
What does Bacon topping look like? Add
picture and description
•
Where is validation for conjoint?:
Located under Survey Overview
Wednesday, December 4, 13
26. *Cool New Stuff*
CONJOINT DESIGN OPTIONS
•
Random: This 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: It is a design algorithm that
will produce an optimal design for the
specified number of tasks per respondent
and sample size. It uses a desired set of
experiments to optimize or investigate a
studied object.
•
Wednesday, December 4, 13
Import: For statistically savvy clients
who want to design your own
conjoint project and have selfdetermined through your own
calculations whether their design will
yield significant output. *NOT just for
anyone...*
27. *Cool New Stuff*
CONJOINT DESIGN OPTIONS
•
Random: This 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: It is a design algorithm that
will produce an optimal design for the
specified number of tasks per respondent
and sample size. It uses a desired set of
experiments to optimize or investigate a
studied object.
•
Wednesday, December 4, 13
Import: For statistically savvy clients
who want to design your own
conjoint project and have selfdetermined through your own
calculations whether their design will
yield significant output. *NOT just for
anyone...*
28. *Cool New Stuff*
CONJOINT DESIGN OPTIONS
•
Random: This 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: It is a design algorithm that
will produce an optimal design for the
specified number of tasks per respondent
and sample size. It uses a desired set of
experiments to optimize or investigate a
studied object.
•
Wednesday, December 4, 13
Import: For statistically savvy clients
who want to design your own
conjoint project and have selfdetermined through your own
calculations whether their design will
yield significant output. *NOT just for
anyone...*
29. *Cool New Stuff*
CONJOINT DESIGN OPTIONS
•
Random: This 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: It is a design algorithm that
will produce an optimal design for the
specified number of tasks per respondent
and sample size. It uses a desired set of
experiments to optimize or investigate a
studied object.
•
Wednesday, December 4, 13
Import: For statistically savvy clients
who want to design your own
conjoint project and have selfdetermined through your own
calculations whether their design will
yield significant output. *NOT just for
anyone...*
30. *Cool New Stuff*
CONJOINT DESIGN OPTIONS
•
Random: This 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: It is a design algorithm that
will produce an optimal design for the
specified number of tasks per respondent
and sample size. It uses a desired set of
experiments to optimize or investigate a
studied object.
•
Wednesday, December 4, 13
Import: For statistically savvy clients
who want to design your own
conjoint project and have selfdetermined through your own
calculations whether their design will
yield significant output. *NOT just for
anyone...*
31. *Cool New Stuff*
CONJOINT DESIGN OPTIONS
•
Random: This 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: It is a design algorithm that
will produce an optimal design for the
specified number of tasks per respondent
and sample size. It uses a desired set of
experiments to optimize or investigate a
studied object.
•
Wednesday, December 4, 13
Import: For statistically savvy clients
who want to design your own
conjoint project and have selfdetermined through your own
calculations whether their design will
yield significant output. *NOT just for
anyone...*
32. WHAT SAMPLE SIZE SHOULD I USE?
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
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.
Example: 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,
300 comes up most often for a single homogeneous group of subjects.
However, if you know you will be working with a smaller homogenous
group of respondents, then use D-Optimal design
Wednesday, December 4, 13
33. ARE YOU READY FOR CONJOINT?
Do the Features and Attributes/Levels appear to be
concrete?
Features and Attributes should be set in stone, otherwise more research is
required (Qual/Quant) to help define the features and attribute list.
Do the options appear to be clear and simple to
understand?
If no, you may want to use the presentation text or the pop up hyperlinks
to define the features/levels. Another option: Redefine features and
attributes using vocabulary familiar to target audience
What is the estimated sample size?
Based on number of completes needed, you should decide ahead of time
which CBC design to run. Random, DOptimal, Import designs.
Additional Tips:
-No more than 20 trade-off exercises
-No more than 5-6 attributes
-Keep the ranges simple
Wednesday, December 4, 13
35. *Cool New Stuff*
CONJOINT RELATIVE IMPORTANCE CALCULATIONS
Relative Importance
Calculates the percentage of which a
particular feature and it’s levels influenced
the concept choice made by the
respondent.
For each Attribute, the difference
between the highest and the lowest PartWorths is calculated. This value divided by
the total across all the attributes is the
relative importance.
https://www.surveyanalytics.com/help/
158.html
Wednesday, December 4, 13
36. *Cool New Stuff*
CONJOINT PARTS WORTH CALCULATIONS
Parts worth calculation determines
which levels within a feature are
more valued than others.
Survey Analytics uses a maximum
likelihood calculation coupled with a
Nelder-Mead Simplex algorithm to
get the parts worth calculation
http://www.scholarpedia.org/article/NelderMead_algorithm
https://www.surveyanalytics.com/help/
702.html
Wednesday, December 4, 13
37. *Cool New Stuff*
CONJOINT PARTS WORTH CALCULATIONS
Parts worth calculation determines
which levels within a feature are
more valued than others.
Survey Analytics uses a maximum
likelihood calculation coupled with a
Nelder-Mead Simplex algorithm to
get the parts worth calculation
http://www.scholarpedia.org/article/NelderMead_algorithm
https://www.surveyanalytics.com/help/
702.html
Wednesday, December 4, 13
38. *Cool New Stuff*
BEST & WORST PROFILE
The Best & Worst Profile highlights highest parts worth
values and lowest parts worth values.
Wednesday, December 4, 13
39. *Cool New Stuff*
MARKET SEGMENTATION SIMULATOR
Market Segment Simulator gives
you the ability to "predict" the
market share of new products and
concepts that may not exist today.
Ability to measure the "Gain" or
"Loss" in market share based on
changes to existing products in
the given market.
Wednesday, December 4, 13
40. *Cool New Stuff*
MARKET SEGMENTATION SIMULATOR
Important steps in
Conjoint Simulation:
1- Describe/Identify the different products or
concepts that you want to investigate. We call
"Profiles".
Example: Vacation Package with On-site
wedding, zoo visit, swimming with dolphins, spa.
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.
Wednesday, December 4, 13
41. *Cool New Stuff*
MARKET SEGMENTATION SIMULATOR
Important steps in
Conjoint Simulation:
1- Describe/Identify the different products or
concepts that you want to investigate. We call
"Profiles".
Example: Vacation Package with On-site
wedding, zoo visit, swimming with dolphins, spa.
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.
Wednesday, December 4, 13
42. *Cool New Stuff*
MARKET SEGMENTATION SIMULATOR
Important steps in
Conjoint Simulation:
1- Describe/Identify the different products or
concepts that you want to investigate. We call
"Profiles".
Example: Vacation Package with On-site
wedding, zoo visit, swimming with dolphins, spa.
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.
Wednesday, December 4, 13
43. SEGMENT SIMULATOR SET UP
1) Click on Online tools >>Name Simulator Profile>>change profiles
2) Click on
Wednesday, December 4, 13
to see results!
47. MAX DIFFERENCE SCALING
MaxDiff assumes that respondents evaluate all
possible pairs of items within the displayed set and
choose the pair that reflects the maximum
difference in preference or importance
Comparative judgments that can be easily
performed, even when the number of attributes
is not small (up to 30).
The task presents respondents with a set of
items, usually 3 to 6, and simply asks them to
select the most preferred and the least preferred
in the set.
Another name for it : Best/Worst Scaling
Respondents can typically handle a number of
these evaluations, and may be asked to respond
to a series of maxdiff questions to gather more
preference data.
Wednesday, December 4, 13
48. MAX DIFFERENCE SCALING
MaxDiff assumes that respondents evaluate all
possible pairs of items within the displayed set and
choose the pair that reflects the maximum
difference in preference or importance
Comparative judgments that can be easily
performed, even when the number of attributes
is not small (up to 30).
The task presents respondents with a set of
items, usually 3 to 6, and simply asks them to
select the most preferred and the least preferred
in the set.
Another name for it : Best/Worst Scaling
Respondents can typically handle a number of
these evaluations, and may be asked to respond
to a series of maxdiff questions to gather more
preference data.
Wednesday, December 4, 13
49. *Cool New Stuff*
MAXDIFF VS. RATING SCALES
MaxDiff has less much less respondent fatigue
compared to rating scale questions.
Survey fatigue is so low that you can run even up to
15-20 different MaxDiff questions if needed.
Most/Least or Love/Hate combos.
Wednesday, December 4, 13
50. *Cool New Stuff*
MAXDIFF VS. RATING SCALES
MaxDiff has less much less respondent fatigue
compared to rating scale questions.
Survey fatigue is so low that you can run even up to
15-20 different MaxDiff questions if needed.
Most/Least or Love/Hate combos.
The MaxDiff Share of Preference Data is either
in percentages up to a 100%, or 100 point count
23% preference to Russell Wilson vs. 20%
Marshawn Lynch = analyze and conclude there is
a 3% difference in preference between the Seattle
Seahawks players.
In rating scales, it’s hard to measure what a 4/5
vs. 2/5 scale really means.
Rating scales are more difficult to quantify than
MaxDiff data output
Wednesday, December 4, 13
51. *Cool New Stuff*
MAXDIFF VS. RATING SCALES
MaxDiff has less much less respondent fatigue
compared to rating scale questions.
Survey fatigue is so low that you can run even up to
15-20 different MaxDiff questions if needed.
Most/Least or Love/Hate combos.
The MaxDiff Share of Preference Data is either
in percentages up to a 100%, or 100 point count
23% preference to Russell Wilson vs. 20%
Marshawn Lynch = analyze and conclude there is
a 3% difference in preference between the Seattle
Seahawks players.
In rating scales, it’s hard to measure what a 4/5
vs. 2/5 scale really means.
Rating scales are more difficult to quantify than
MaxDiff data output
Wednesday, December 4, 13
52. *Cool New Stuff*
MAXDIFF VS. RATING SCALES
MaxDiff has less much less respondent fatigue
compared to rating scale questions.
Survey fatigue is so low that you can run even up to
15-20 different MaxDiff questions if needed.
Most/Least or Love/Hate combos.
The MaxDiff Share of Preference Data is either
in percentages up to a 100%, or 100 point count
23% preference to Russell Wilson vs. 20%
Marshawn Lynch = analyze and conclude there is
a 3% difference in preference between the Seattle
Seahawks players.
In rating scales, it’s hard to measure what a 4/5
vs. 2/5 scale really means.
Rating scales are more difficult to quantify than
MaxDiff data output
Wednesday, December 4, 13
53. *Cool New Stuff*
MAXDIFF FAQS
Can I setup and experimental design where the total items are larger than the
items presented in a single screen?
YES! You can use a large list of attributes
and specify the number of attributes per
page if desired.
Wednesday, December 4, 13
54. *Cool New Stuff*
MAXDIFF FAQS
Can I setup and experimental design where the total items are larger than the
items presented in a single screen?
YES! You can use a large list of attributes
and specify the number of attributes per
page if desired.
What kind of a utility estimation model
does the system use to calculate the
share of preference?
Multinomial Logit model
Co-created with VP & Director of Analytics,
Chris Robson, of ORC International
Wednesday, December 4, 13
55. *Cool New Stuff*
MAXDIFF FAQS
Can I setup and experimental design where the total items are larger than the
items presented in a single screen?
YES! You can use a large list of attributes
and specify the number of attributes per
page if desired.
What kind of a utility estimation model
does the system use to calculate the
share of preference?
Multinomial Logit model
Co-created with VP & Director of Analytics,
Chris Robson, of ORC International
Wednesday, December 4, 13
56. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Wednesday, December 4, 13
57. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
58. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
59. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
60. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
61. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
62. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
63. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
64. *Cool New Stuff*
MAXDIFF SET UP
Attribute Settings:
Maximum Attributes: Define how many attributes
out of the list you created that will be tested for
each respondent.
Example:
All = All attributes tested
6/9 = Respondent will only see 6 out of list of 9
Attributes per task: How many of the attributes
you will see on each page.
Example:
3 Attributes per Task + All from the list = 3 cycles
Images for Maxdiff are now supported!
Wednesday, December 4, 13
65. *Cool New Stuff*
MAXDIFF ANALYSIS
Preference Analysis Overview:
MaxDiff data output is usually represented
either in a 100 point system or in percentage
calculation that must add up to 100%.
Survey Analytics uses the percentage calculation
mode.
Breakdown is Most or Least Preferred:
Each end of the spectrum is calculated
separately in most and least preferred table.
Overall Percentage Pie Chart:
Gives the overall preference calculation
Wednesday, December 4, 13
66. *Cool New Stuff*
MAXDIFF ANALYSIS
Preference Analysis Overview:
MaxDiff data output is usually represented
either in a 100 point system or in percentage
calculation that must add up to 100%.
Survey Analytics uses the percentage calculation
mode.
Breakdown is Most or Least Preferred:
Each end of the spectrum is calculated
separately in most and least preferred table.
Overall Percentage Pie Chart:
Gives the overall preference calculation
Wednesday, December 4, 13
67. *Cool New Stuff*
MAXDIFF ANALYSIS
Preference Analysis Overview:
MaxDiff data output is usually represented
either in a 100 point system or in percentage
calculation that must add up to 100%.
Survey Analytics uses the percentage calculation
mode.
Breakdown is Most or Least Preferred:
Each end of the spectrum is calculated
separately in most and least preferred table.
Overall Percentage Pie Chart:
Gives the overall preference calculation
Wednesday, December 4, 13
69. MAKE MORE MONEY WITH CONJOINT & MAXDIFF
Both conjoint and Maxdiff can allow your company to uncover
additional insights on consumer preferences on products/
services.
Use on both new & existing products/services.
Do you need to create new products/services or repackage
existing, or a combo of both?
Will give you a strong and compelling argument to
recommendations for your company or clients.
As long as your Conjoint and MaxDiff are clear and easy for
people to answer, you can add and create a comprehensive
online or mobile survey and review past with new data.
DIY conjoint and maxdiff: No consultants required!
Wednesday, December 4, 13
70. MAKE MORE MONEY WITH CONJOINT & MAXDIFF
Both conjoint and Maxdiff can allow your company to uncover
additional insights on consumer preferences on products/
services.
Use on both new & existing products/services.
Do you need to create new products/services or repackage
existing, or a combo of both?
Will give you a strong and compelling argument to
recommendations for your company or clients.
As long as your Conjoint and MaxDiff are clear and easy for
people to answer, you can add and create a comprehensive
online or mobile survey and review past with new data.
DIY conjoint and maxdiff: No consultants required!
Wednesday, December 4, 13
71. THANKS EVERYONE!
Q&A
If you have any further questions about
MaxDiff or Conjoint that have not been
addressed or would like me to assist with
an upcoming project in 2014, Cooper and I
are standing by waiting by the computer!
Contact a Survey Analytics Sales
Representative to get started:
sales-team@surveyanalytics.com
1-800-326-5570
My e-mail address:
esther.rmah@surveyanalytics.com
Wednesday, December 4, 13