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Thursday, May 28th, 2015
WE WILL BEGIN SHORTLY
questionpro.com | surveyanalytics.com
Learn How to Make Better Business Dec...
Conjoint Analysis Webinar : Will Begin Shortly….
Presenters
VIVEK BHASKARAN
Founder & CEO
SurveyAnalytics /
QuestionPro
ROB ASERON
Online Research Guru
(Former Director, Z...
AGENDA
 What is Conjoint Analysis?
 How Gaming Giant, Zynga, Won
 Introducing an All-in-One Solution
 Questions and An...
THE BASICS
Conjoint
Discrete Choice
Choice-Based ConjointDCM
CBC
Adaptive Conjoint
ACBC
ACA
Adaptive
Choice-Based
Conjoint...
THE BASICS
Bad news:
You just lost your job.
THE BASICS
Good news:
You have great skills
that give you options.
THE BASICS
Choice Example: Your Job Offers
Salary
(x current)
Travel
(%)
Vacation
(weeks)
Bonus
(%)
Position A 1.2 0 2 10
...
Salary
(x current)
Travel
(%)
Vacation
(weeks)
Bonus
(%)
Position A 1.2 0 2 10
Position B 1.2 25 3 20
Position C 1.2 75 4 ...
THE BASICS
Why Choice Research Adds More Value
LITTLE DIFFERENTIATION
Asking buyers to rate the importance of, or preferen...
THE BASICS
Why Choice Research Adds More Value
Buyers have to make difficult trade-
offs and concessions in real life.
We ...
THE BASICS
How many times have you seen this type of question?
THE BASICS
How many times have you seen this type of question?
Naturally we want it all.
How do you interpret the differen...
THE BASICS
…Or these types of questions?
 How much would you be willing to pay for this?
 At what price would you consid...
THE BASICS
When we force respondents to make trade-offs, we get a
much better picture of the values of the product
attribu...
THE BASICS
Help Me Figure Out
The features that
will best optimize
my product
How many
customers will
pay for a new
featur...
THE BASICS
Terminology
Attributes – the features of your product or service (e.g., price, color,
size, amount of storage, ...
THE BASICS
The Do’s and Don’ts
Don’t think importance scores will tell you what is “good”—they
only tell you where respond...
THE BASICS
The Big Difference
MaxDiff
deals with a single list of
attributes (brands, features,
messages, benefits, images...
THE BASICS
Bringing it All Together
MaxDiff
Conjoint
 Preference or
Importance of Items
 No Pricing
 Feature Configurat...
CASE STUDY
How a Gaming Giant Won Using Max Diff & Conjoint
ROB ASERON
Online Research Guru
(Former Director, Zynga)
Product Naming Questions*
With Broad Applicability
1. What name will get a user to pause in the App Store environment?
2. ...
Naming the Game*
Question 1
* Hypothetical game name situation – never did ‘AntVille’ at Zynga.
Naming the Game*
Question 2
* Hypothetical game name situation – never did ‘AntVille’ at Zynga.
Naming Results*
Question 1
* Hypothetical game name, made up data.
Naming the Game*
Question 3 – Under the Radar
* Hypothetical game name situation – never did ‘AntVille’ at Zynga.
Max Diff Fits a Start Up’s Approach
Lightweight Implementation
– Immediately-understood response format -
complex judgment...
ALL-IN-ONE SOLUTION
One Platform For All Your Conjoint Analysis Needs
VIVEK BHASKARAN
Founder & CEO
SurveyAnalytics /
Ques...
Conjoint / Max Diff Setup : 1
Max Diff : Setup
Max Diff : Settings
Max Diff : Analysis : Share of Preference
Logit Model
Max Diff : Analysis : Filtering
Max Diff : Analysis : Comparisons
Conjoint Analysis : Setup
Conjoint Analysis : Settings
Conjoint : Design Model
Randomized D-Optimal Upload
Conjoint Analysis : Data Exploration
Attribute Importance
Profile Playboard
Market Segmentation
Simulator
Brand Equity
Ret...
Attribute Importance
Profile Playboard
Profile Playboard
Market Segmentation : Simulator
Brand Equity / Retail Price Equivalence
Price Elasticity
QUESTIONS
1 (800) 326-5570
E-mail:
sales-team@surveyanalytics.com
Online Inquiries:
www.surveyanaltics.com/contact
Nico Pe...
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How to run conjoint analysis

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Learn about maxdiff and conjoint analyses and review some examples of how they can be used in your organization.

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How to run conjoint analysis

  1. 1. Thursday, May 28th, 2015 WE WILL BEGIN SHORTLY questionpro.com | surveyanalytics.com Learn How to Make Better Business Decisions
  2. 2. Conjoint Analysis Webinar : Will Begin Shortly….
  3. 3. Presenters VIVEK BHASKARAN Founder & CEO SurveyAnalytics / QuestionPro ROB ASERON Online Research Guru (Former Director, Zynga) NICO PERUZZI, Ph.D. Partner Outsource Research Consulting
  4. 4. AGENDA  What is Conjoint Analysis?  How Gaming Giant, Zynga, Won  Introducing an All-in-One Solution  Questions and Answer Session
  5. 5. THE BASICS Conjoint Discrete Choice Choice-Based ConjointDCM CBC Adaptive Conjoint ACBC ACA Adaptive Choice-Based Conjoint MaxDiff MaxDiff Scaling MBC Best-Worst Scaling Menu-Based Choice All these methods involve making trade-offs, and can be classified under Choice Research Bottom Line
  6. 6. THE BASICS Bad news: You just lost your job.
  7. 7. THE BASICS Good news: You have great skills that give you options.
  8. 8. THE BASICS Choice Example: Your Job Offers Salary (x current) Travel (%) Vacation (weeks) Bonus (%) Position A 1.2 0 2 10 Position B 1.2 25 3 20 Position C 1.2 75 4 30 Position D 1.5 25 2 30 Position E 1.5 75 3 10 Position F 1.5 0 4 20 Position G 1.8 75 2 20 Position H 1.8 25 2 30 Position I 1.8 25 4 10
  9. 9. Salary (x current) Travel (%) Vacation (weeks) Bonus (%) Position A 1.2 0 2 10 Position B 1.2 25 3 20 Position C 1.2 75 4 30 Position D 1.5 25 2 30 Position E 1.5 75 3 10 Position F 1.5 0 4 20 Position G 1.8 75 2 20 Position H 1.8 25 2 30 Position I 1.8 25 4 10 THE BASICS Your Choice Why did you choose? By what process did you choose?
  10. 10. THE BASICS Why Choice Research Adds More Value LITTLE DIFFERENTIATION Asking buyers to rate the importance of, or preference for, a bunch of features/attributes often gives...
  11. 11. THE BASICS Why Choice Research Adds More Value Buyers have to make difficult trade- offs and concessions in real life. We have a way to force respondents to make trade-offs, just like real-world buyers have to do.
  12. 12. THE BASICS How many times have you seen this type of question?
  13. 13. THE BASICS How many times have you seen this type of question? Naturally we want it all. How do you interpret the difference between a mean of 4.2 and 4.4 on a 5-point rating scale? You know the futility of that exercise.
  14. 14. THE BASICS …Or these types of questions?  How much would you be willing to pay for this?  At what price would you consider X “inexpensive,” “expensive,” “too expensive,” and “too cheap?”  But, these methods: • Invite bargaining; can’t trust results; need to follow-up research • Are overused and over-trusted; they feign precision For a new product, with no idea of “what the market will bear,” this can get you near the ballpark.
  15. 15. THE BASICS When we force respondents to make trade-offs, we get a much better picture of the values of the product attributes; we get better discrimination. “What if... ?” We also gain the opportunity to simulate various product configurations to figure out which can lead to the best uptake. We get to ask,
  16. 16. THE BASICS Help Me Figure Out The features that will best optimize my product How many customers will pay for a new features or product My brand equity Whether a new product will cannibalize existing products How much demand will change as we change price How will our product will compete in the current (and future) competitive landscape
  17. 17. THE BASICS Terminology Attributes – the features of your product or service (e.g., price, color, size, amount of storage, etc.) Levels – the type or amount of an attribute (e.g., blue, red, or green color, or 64 GB, 128 GB, or 256 GB) Importance Scores – the maximum impact an attribute can have on product choice Utilities – the preference for a level of an attribute (technically called a part-worth) Share of Preference – interest in a product concept captured through a market simulation None Parameter – captures respondent propensity to not purchase any of the choices in a simulation
  18. 18. THE BASICS The Do’s and Don’ts Don’t think importance scores will tell you what is “good”—they only tell you where respondents’ attention was most focused. Don’t compare utility scores across attributes—only consider them relative gauges of level preference within each attribute Do use simulations to answer your business questions Do use a competitive set and a none parameter to provide realism to your simulations
  19. 19. THE BASICS The Big Difference MaxDiff deals with a single list of attributes (brands, features, messages, benefits, images, copy, claims, etc.). Conjoint deals with attributes that have various “levels” (degrees), and that very often include price in a product profile context.
  20. 20. THE BASICS Bringing it All Together MaxDiff Conjoint  Preference or Importance of Items  No Pricing  Feature Configuration  Product Optimization  Competitive Scenarios  Price Sensitivity  Market Scenarios  Product Demand  Cannibalization  Product Mix Both MaxDiff and Conjoint can be used to feed Segmentation Analysis
  21. 21. CASE STUDY How a Gaming Giant Won Using Max Diff & Conjoint ROB ASERON Online Research Guru (Former Director, Zynga)
  22. 22. Product Naming Questions* With Broad Applicability 1. What name will get a user to pause in the App Store environment? 2. Can we leverage brand halo and frame this new product as an extension of the previous, related product? 3. What naming presentation appeals most to current user base? 4. What naming presentation has greatest attraction for expanding the user base? 5. Where will cross-promotion efforts have best traction? * Example questions chosen because of relevance to many product types, not for representativeness to Zynga research concerns.
  23. 23. Naming the Game* Question 1 * Hypothetical game name situation – never did ‘AntVille’ at Zynga.
  24. 24. Naming the Game* Question 2 * Hypothetical game name situation – never did ‘AntVille’ at Zynga.
  25. 25. Naming Results* Question 1 * Hypothetical game name, made up data.
  26. 26. Naming the Game* Question 3 – Under the Radar * Hypothetical game name situation – never did ‘AntVille’ at Zynga.
  27. 27. Max Diff Fits a Start Up’s Approach Lightweight Implementation – Immediately-understood response format - complex judgment yet low cognitive load – Minimally intrusive (inline responses) – Appropriate for micro-rewards (panel) Data, Data, Data • Cut by play characteristics • Cut by demographics Efficient – Respondent makes 2 judgments • A is Most Preferred • E Least Preferred – We collect 7 data points (of possible10 ) • A > B, A > C, A > D, A > E • B > E, C > E, D > E – Concurrent consideration of pos/neg Fast – Overnight data-based directional read – Iterate and re-field until finalized
  28. 28. ALL-IN-ONE SOLUTION One Platform For All Your Conjoint Analysis Needs VIVEK BHASKARAN Founder & CEO SurveyAnalytics / QuestionPro Choice-Based Conjoint MaxDiff
  29. 29. Conjoint / Max Diff Setup : 1
  30. 30. Max Diff : Setup
  31. 31. Max Diff : Settings
  32. 32. Max Diff : Analysis : Share of Preference Logit Model
  33. 33. Max Diff : Analysis : Filtering
  34. 34. Max Diff : Analysis : Comparisons
  35. 35. Conjoint Analysis : Setup
  36. 36. Conjoint Analysis : Settings
  37. 37. Conjoint : Design Model Randomized D-Optimal Upload
  38. 38. Conjoint Analysis : Data Exploration Attribute Importance Profile Playboard Market Segmentation Simulator Brand Equity Retail Price Equivalence Price Elasticity & Curve
  39. 39. Attribute Importance
  40. 40. Profile Playboard
  41. 41. Profile Playboard
  42. 42. Market Segmentation : Simulator
  43. 43. Brand Equity / Retail Price Equivalence
  44. 44. Price Elasticity
  45. 45. QUESTIONS 1 (800) 326-5570 E-mail: sales-team@surveyanalytics.com Online Inquiries: www.surveyanaltics.com/contact Nico Peruzzi, Ph.D. 1 (408) 202-1521 E-mail: nperuzzi@orconsulting.com Rob Aseron E-mail: rob@onlineresearch.guru

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