How to Run Discrete Choice Conjoint Analysis

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Slide Agenda:

1- What is discrete choice conjoint analysis?

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 & Contact information

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  • How to Run Discrete Choice Conjoint Analysis

    1. 1. How To Run Discrete Choice Conjoint Analysis Andrew Jeavons Esther LaVielle
    2. 2. About Survey AnalyticsStarted in 2002 in Seattle, WASpecialize in online, mobile surveys and panel, conjointanalysis, crowdsourcing, sample, gamification and more!#172 on Inc. 500 Fastest GrowingPrivate Companies#12 on Puget Sound Journals Top 100in Washington Esther LaVielle Vice President of Client Services
    3. 3. Andrew JeavonsPresident of Survey Analytics, Andrew Jeavons25 years in the market research industry.Background in psychology and statistics, and currently focuses on innovation withinsurvey research.Studied Neuropsychology at Birkbeck College in London UKTen years + experience starting software companies, and in a marketing, sales andstrategic development capacity.He has also written articles for ESOMAR, Greenbook, Research Access, and more.
    4. 4. Webinar Agenda1- What is discrete choice conjoint analysis?2- The theory and logic behind discrete choice conjoint analysis3-When to use discrete choice conjoint in your research4-Specific examples of how to use discrete choice conjoint5-How to design a discrete choice conjoint project6- How to write a discrete choice conjoint questionnaire7-How to analyze the results of a discrete choice conjoint project8- Tips and Best Practices and Q & A
    5. 5. What is Conjoint Analysis?Type of Trade-off Analysis methodologyDeveloped over the past 50 years by market researchers and statisticians topredict the kinds of decisions consumers will make about products by using questionsin a survey.Conjoint analysis questions presents a series of possible products to consumers andasks 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 tothem.Survey Analytics uses Discrete Choice Conjoint Analysis whichbest simulates the purchase process of consumers
    6. 6. Wanna Buy A Puppy?BreedDog BreederSizePriceCare NeededPersonalityLife Span
    7. 7. Theory & Logic of Conjoint AnalysisIt will help you evaluate new products or variations against an existing range ofproducts already offered by your company or within the marketplace.It’s much cheaper than developing new products for the marketplace with noguarantee 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 receivedin the marketplace.Gauge the affect on the choice/price relationship relativeto existing products and features presented.
    8. 8. Analysis: How do we come up with our numbers ?Survey Analytics Discrete Choice Module uses a Maximum Likelihoodcalculation 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 !
    9. 9. Conjoint Analysis Core Concepts1)Attributes/Feature:Define the attributes of the products for your market. Theseare the properties ofyour product.Seattle Tourism Study:#HoursTime of DayTour Type2) Levels: The different properties of the attributes. Defineat least two levels for eachof the attributes.Seattle Tourism Study:Hours - 3 levelsTime of day - 4 levelsTour Type: 5 levels
    10. 10. 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 importantan attribute is to the purchase or choice process andin “market simulations.”Utility Value of Hrs on Tour:1-2hrs = .392-4hrs = .454-6hrs = .324) Relative importance:How important an attribute is in the purchasing/choicedecision ?Example: Of all features to go on tour –“Time of day” determined which one most chosen
    11. 11. Setting up a conjoint Analysis ProjectKind of reminds me of putting together a jigsaw puzzle….. All the pieces in the project should fittogether before fielding the project!
    12. 12. Survey Analytics offers 3 Conjoint Analysis DesignsRandom DesignD-Optimal Design Import Design
    13. 13. 3 Conjoint Analysis Designs - DefinedRandom: Random design is a purely random sample of the possible attribute levels. For the number of tasks per respondent Survey Analytics 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 Survey Analytics DCM module. This is useful when users want to use designs not generated by Survey Analytics, such as fractional factorial orthogonal designs.
    14. 14. # How to Set up a Conjoint Analysis QuestionQuestion Set up for all 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
    15. 15. How to Set up a Conjoint Analysis ParametersSet up Prohibited PairsThe engine will not display two levels that have been marked as"Prohibited" in the same concept (as a product) for the user tochoose.
    16. 16. #Prohibited PairsExample: A Weird Seattle Tour will never be 4-6 hrs long
    17. 17. Concept SimulatorThis can be used to determine what choices willbe presented to the respondents when yoursurvey is actually deployed. Use as Guidance.
    18. 18. D-Optimal DesignClick on Settings >> Design Type >> Doptimal >> Select Versions >> Start >> Save Settings
    19. 19. D-Optimal DesignClick on Settings >> View Options>> Make changes >> Update Design
    20. 20. Import DesignImport Design This allows designs, in the SPSS design format, to be imported andused by the Survey Analytics DCM module. This is useful when users want to usedesigns not generated by Survey Analytics, such as fractional factorial orthogonaldesigns.Step 1:Start by adding a Conjoint DCMquestion as is walked through above.Ensure that under Task Count andConcepts Per Task you choose the samenumbers as that you have in the Excelsheet you are going to importStep 2: Click on Settings.In the in-line popup in ’Design type choose Import’
    21. 21. #5 Conjoint Analysis Survey Preview
    22. 22. #5 Conjoint Analysis Preview with Pictures
    23. 23. Review Data:Utility Calculation & Relative Importance
    24. 24. Relative ImportanceRelative Importance of attributesDisplayed as Pie chart*Shows here that Tour TypeIs the most significant feature/attribute which determines whattour they want to take.
    25. 25. Relative Importance and Average Utility TableThe tour type isthe most important attribute Weird is GOOD! Chocolate is popular
    26. 26. Best & Worst ProfileThe tour type is best liked.Weird works. The tour type is best liked. Weird works.
    27. 27. Market Segmentation Simulator Using existing Data from Conjoint Analysis
    28. 28. Market Segment SimulatorMarket Segmentationgivesnot exist ability to "predict" the market share of you the Simulatornew products and concepts that may today.Ability to measure the "Gain" or "Loss" in market share based on changes to existingproducts 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: Evening2- Find out all the existing products that are available in that market segment andsimulate 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 onnew products and configurations.
    29. 29. Setting up a Simulator1) Click on Online tools >>Name Simulator Profile>>change profiles2) Click on to see results!
    30. 30. Results: Simulator Output DefinedThe market simulator uses utility values to project theprobability of choice and hence the market share
    31. 31. Now that we knowhow to use this . .What can we askand find out with theMarket Segmentation Simulator?
    32. 32. Market 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.
    33. 33. Tips for A Successful Conjoint Analysis Project
    34. 34. 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 Crowd-sourcing tools: IdeaScale
    35. 35. What Sample Size To Start With?Sample size is a question that comes up very frequently. Richard Johnson, one of theinventors of conjoint analysis, has presented the following rule of thumb forsample size in choice based conjoint:(nta/C) > 1000Where n = the number of respondents x t= the number of tasks x a=the number ofalternatives 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 taskand the maximum number of levels on an attribute is 3 you get:(500 x 3 x 2) / 3 = 1000Generally speaking sample sizes tend to be around 200 – 1200 respondents, admittedlya wide range. 300 comes up most often for a single homogeneous group of subjects.
    36. 36. Practices & Tips: Surveys with Conjoint AnalysisKeep the options clear and simple as possibleNo more than 20 trade-off exercisesNo more than 5-6 attributesKeep the ranges simpleYou can ask more intimate questions of currentcustomers than potential customers, but don’t letthat stop you from trying!Follow general good online survey techniquesTest your surveyMake it clear responses are kept strictly confidentialKeep survey to 15-20 minutesProvide incentives
    37. 37. # Survey Analytics Discrete Choice Conjoint Discrete Choice Conjoint AnalysisFlexible pricing availableMost User-friendly Conjoint Tool In The MarketReal-time ReportingPricing includes integrated research tools that would enhance efficiencies anddepth and research strategiesDedicated account management and support included
    38. 38. Q&A Thank you for Attending!Esther LaVielleEsther.rmah@surveyanalytics.com http://www.surveyanalytics.comAndrew JeavonsAndrew.jeavons@surveyanalytics.com sales-team@surveyanalytics.com

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