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QuestionPro Advanced Training Keys to Success - Discrete Conjoint Analysis 101


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Our April 2017 Keys to Success series deep dives into Discrete Choice Conjoint Analysis, an effective and advanced survey technique. In this training, learn to analyze how and why customers choose certain products or services over others. This training discusses research industry best practices on creating a comprehensive end-to-end conjoint analysis project, so that you can address and find solutions to even some of the most complex business objectives.

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QuestionPro Advanced Training Keys to Success - Discrete Conjoint Analysis 101

  1. 1. DISCRETE CHOICE CONJOINT ANALYSIS 101 April 20th, 2017
  2. 2. Esther Lavielle Implementation Manager, QuestionPro Twitter: @esther_qpro Welcome to the Keys To Success Series #K2SQP By QuestionPro
  3. 3. Agenda ❏What is Discrete Choice Conjoint Analysis? ❏Do you Conjoint? Why You Should ❏Conjoint O’ Clock - Best Time to Run a Conjoint Study ❏QuestionPro’s 3-in-1 Design Options ❏Best Practices For Discrete Conjoint Project Design ❏Conjoint Analysis FAQs ❏Live Demo: How to Conjoint
  4. 4. Discrete Choice Conjoint Analysis Trade-off analysis methodology #1 Methodology used research technique for customer purchase decisions For any purchase, consumers evaluate or “trade-off” the different characteristics of a product and decide what is more important to them
  5. 5. Do You Conjoint? Why You Should New Product Research - Evaluate new products or variations against existing range of products in the marketplace Budget Friendly - Cheaper than developing new products for the marketplace with no guarantee of success Simulates Consumer Decision - Captures how target audience react to new products/services within marketplace -Refine the target audience for your study Real Time Data - Need this data quick? Don’t wait. Get real- time feedback on new products or variations of existing products today Analyze Choice vs. $ - Gauge the effect on the choice/price relationship relative to existing products and features presented
  6. 6. QuestionPro’s 3-in-1 Design Options Random Design - Most Popular among QP customer - Easy to program - Easy to analyze - Easy to include in comprehensive surveys D-Optimal Design - This algorithm will produce optimal number of tasks per respondent based on sample size to reach statistical significance Import Design Caution* - Available for those who are statistically savvy. Must be able to calculate margin of error from your own design -Externally create conjoint design with custom algorithm & Import into QuestionPro -SPSS Design Format -Fractional Factorial Orthogonal Designs
  7. 7. Best Time For a Discrete Choice Conjoint Study Business Objective: Market Share Growth New Product/Services Beginning of Innovation Process During Product/Service Planning & Prototyping Cost of Overhead vs. Potential Revenue When you have a Statistically Significant Target Audience
  8. 8. Best Practices Discrete Choice Conjoint Project Design
  9. 9. Where to Get Started ● Qualitative Research - Validate Anecdotal Info ● Identify Top Attributes & Levels for research ● Focus group or surveys with open-ended questions will help define your top attributes needed for your study ● Use Crowd-sourcing tools or forums: QuestionPro Communities or IdeaScale ● Define range & language for target audience
  10. 10. Best Practices ❏ Keep options clear and simple ❏ No more than 20 trade-off exercises ❏ No more than 5-6 attributes ❏ Keep ranges simple ❏ Follow general good online survey techniques ❏ Beta test survey before launch date ❏ Exercise good privacy & confidentiality protocols ❏ Keep survey short & sweet ❏ Provide incentives or rewards $ for long surveys
  11. 11. Best Practices for Sample Size ❏ Sample size recommendation: (nta/C) > 1000 n = number of respondents x t= number of tasks x a= number of alternatives per task / C= 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 (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
  12. 12. FAQ: Analytics Discrete Choice Conjoint Analysis
  13. 13. 4 Discrete Choice Conjoint Reporting Options Attribute Importance Market Share Simulation - Shows how much consumers are willing to spend for each feature they’re considering adding to their brand - Part worth also show if consumers are willing to exchange one feature for another - Simulate market share potentials based on insights collected - Customized based on set features & attributes
  14. 14. Profile Analysis Brand Premium - Highlights Best vs Worst - Customize Profile Output - Allows you to see what was shown to each respondent - Measure Potential Price Elasticity - Based on Features & insights collected 4 Discrete Choice Conjoint Reporting Options
  15. 15. The Analytics How do we come up with our numbers for Parts Worth Calculations? QuestionPro’s Discrete Choice Module uses a Maximum Likelihood calculation coupled with a Nelder-Mead Simplex algorithm Have greater confidence in the results you receive!
  16. 16. What’s the Market Segment Simulator Going to Tell Me? Market Segment Simulator gives ability to "predict" market share of new products and concepts that may not exist now ● Measure the "Gain" or "Loss" in market share based on changes to existing products in the given market Conjoint Simulation Rulebook Identify “Profiles” - different products or concepts to investigate Review existing products in current market segment & simulate market share of the products to establish a baseline Try out new services and ideas. See how the market share shifts based on different products and configurations from data collected
  17. 17. Build it Now How To Conjoint
  18. 18. Recap Ready to Conjoint? Get started Here What Time is Conjoint O’Clock? Pricing, preference analysis new/existing products, innovation, etc. Build a Comprehensive Insights Project Tap into QP’s Tools & Services Want help?
  19. 19. Thank You! Questions? Want to talk Conjoint? Tell me what you want to learn Twitter: @esther_qpro #K2SQP #ConjointOClockQP