New Techniques for Conjoint Analysis

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Product developers and marketers have typically turned to Choice-based Conjoint Analysis for measurement. However, it has some drawbacks. A new technique called Adaptive Choice-based Conjoint Analysis was developed to move beyond these limitations. This adaptive conjoint technique helps you effectively identify features of your product/service that matter most to customers, and thereby impact revenue and profitability.

The webinar is presented by Dan Llanes, Director of Analytics at Hansa GCR. It covers the uses, benefits, and limitations of choice-based conjoint analysis (CBC) and how to structure a better approach using the technique of Adaptive CBC. Watch and learn a better way to measure what's truly important to your customers.

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New Techniques for Conjoint Analysis

  1. 1. New Options and Techniques for Conjoint Analysis April 2013 Entire Contents © 2013 Hansa GCR; Confidential and Proprietary.
  2. 2. Introduction Dan Llanes Director of Analytics Senior analytics specialist, has worked on dozens of conjoint projects across a wide array of industries. Hansa GCR +1 503.295.0210 dllanes@hansagcr.com 2
  3. 3. Objectives• Discuss the uses and benefits of conjoint analysis• Review limitations of choice-based conjoint analysis (CBC)• Examine Adaptive CBC – Improvements over traditional CBC – Questionnaire structure• Conclude with high level overview of potential output• Questions and dialogue 3
  4. 4. Why Conjoint? • Marketers and product developers continuously confront the need to find the best product options for a market. • There are several ways to find this ideal option: • Guessing • Asking customers what they like in focus groups • Doing a simple survey asking customers which option they prefer • The most reliable way to find the product option that customers will most prefer is choice-based conjoint analysis. 4
  5. 5. What is Conjoint Analysis?• Conjoint analysis is used to… • Measure the perceived value of specific product features • Learn how demand for a particular product or service is related to price • Forecast likely uptake of a product if brought to market• Instead of directly asking survey respondents what they prefer in a product, or what attributes they find most important, conjoint analysis gives them the more realistic task of selecting among products with different features.• Each product description includes conjoined product features (hence, the term, conjoint analysis). 5
  6. 6. Choice Tasks• CBC’s assumptions are simple… • Choice tasks mimic what buyers do more closely than ranking or rating product concepts using a scale • Choice tasks generate little fatigue among respondents • Everyone can make choicesAttribute: Product 1 Product 2 Product 3 Product 4Brand A B A DColor Red Blue Green SilverDelivery time 1 week  3 weeks  2 weeks  1 week  (express) (standard) (accelerated) (express)Price $50 $75 $100 $75 6
  7. 7. Limitations of CBC• Randomized concepts may fall well outside the bounds of acceptability relative to a respondent’s ideal.• Respondents do choice tasks too quickly.• Choice exercises typically require a dozen or more tasks to be shown to respondents, which may be perceived as repetitive and boring. 7
  8. 8. Overview of Adaptive Choice-Based Conjoint• ACBC = Adaptive Choice-Based Conjoint – Sawtooth Software product with solid academic underpinnings – It’s traditional Choice-Based Conjoint that has evolved to be: • More capable (can handle more attributes & levels) • More realistic (more modern theory of decision making) • More engaging for respondents (more fun?) 8
  9. 9. Three-Step ACBC Design Considerations Choice Exercise BYO Exercise Screening Exercise Respondent task Configure Build constructed frompreferred product consideration set attributes in consideration set• Each respondent • Respondent • Tournament builds their considers product process to preferred product configurations explore and configuration. similar to their quantify trade- preferred. offs. • Identify threshold, must have & must avoid criteria 9
  10. 10. ACBC Step 1: The BYO Exercise 10
  11. 11. ACBC Step 2: Build Consideration Set 11
  12. 12. ACBC Step 3: Choice Exercise 12
  13. 13. ACBC Design Considerations• Two issues to be mindful of: – Interview length – Concept complexity• Overall survey length is typically in the 15-20 min range; we want to keep the ACBC exercise under 12 minutes (which is still a LONG, intense process for participants)• Methodological constraints: – Recommend 10-12 attributes max – 36-38 total levels (attributes x levels) 13
  14. 14. Next Steps• Data from an ACBC allow us to… – Learn which attributes and levels are most and least appealing – Evaluate the degree of price elasticity – Build product bundles to determine demand for various competing products• Advances in simulation algorithms allow us to factor in material and labor inputs.• More to come over the summer… 14
  15. 15. About Hansa GCR Dan LlanesHansa GCR is a full-service market research andconsulting firm. Looking through the lens of the Analytics Director Hansa GCRcustomer experience and applying psychological +1 503.295.0210 principles of human motivation, we offer best- dllanes@hansagcr.com in-class services in areas relating to Customer Relationship Equity, Market Assessment, Branding, and Product/Service Innovation. Hansa GCR is part of R K SWAMY HANSA, an Michael Cruz, PhDemerging global group with 1,100+ professionals Vice President offering Creative Communication, Market Hansa GCR Research, Data Analytics, Brand Consulting, +1 503.417.1450 Interactive and Healthcare Communication mcruz@hansagcr.com services. For further information about Hansa GCR please visit us on the Web at www.hansagcr.com, contact us via email at Mary Valentacustomresearch@hansagcr.com, or call us at: +1 Marketing Manager 503.241.8036. Hansa Marketing Services To receive future webinar announcements, +1 847.491.6902 please visit our blog site and click on Subscribe Mary.Valenta@Hansa-marketing.com http://blog.hansa-marketing.com Entire Contents © 2013 Hansa GCR; Confidential and Proprietary.

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