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. Don't miss our next free webinar. Register here: http://hub.am/XwTIKo www.HansaMarketing.com @Hansa_Tweets

1. New Options and Techniques for
Conjoint Analysis
April 2013
Entire Contents © 2013 Hansa GCR; Confidential and Proprietary.

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. 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. 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. 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. 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 choices
Attribute: Product 1 Product 2 Product 3 Product 4
Brand A B A D
Color Red Blue Green Silver
Delivery time 1 week 3 weeks 2 weeks 1 week
(express) (standard) (accelerated) (express)
Price $50 $75 $100 $75
6

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. 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. Three-Step ACBC Design Considerations
Choice Exercise
BYO Exercise Screening Exercise Respondent task
Configure Build constructed from
preferred 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. ACBC Step 1: The BYO Exercise
10

11. ACBC Step 2: Build Consideration Set
11

12. ACBC Step 3: Choice Exercise
12

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. 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. About Hansa GCR
Dan Llanes
Hansa GCR is a full-service market research and
consulting firm. Looking through the lens of the
Analytics Director
Hansa GCR
customer 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, PhD
emerging 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 Valenta
customresearch@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.