March 5-6, 2019

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How Zappos Uses Conjoint Analysis for Superior Insights and Customer Segmentation

Room 1 | 11:30-12:00 | Tuesday, March 5, 2019

Sourav and Bryan will showcase how choice experiments (also known as choice-based conjoint [CBC] studies) have provided product and business insights at Zappos. We delve into the building blocks of choice-based conjoint methodology and the impact it brought at Zappos with regards to understanding customer needs and preferences. By the end of this session, you’ll understand why CBC brings more rigor, flexibility and realism than traditional concept testing and rating scales.

There is no fun in a presentation without a case study! We’ve got you – we will go over some of the CBC studies conducted at Zappos pertaining to value propositions and retail offering. The case study will start by touching upon the context and design of these studies. Finally, we will wrap it up with the impact of the research, including deliverables like a shareable what-if market simulator and actionable customer segments. We will also discuss the organizational impact of such CBC studies across silos that help bring researchers and stakeholders closer to the customers. By the end of the session, we hope that you’ll be encouraged to answer complex research questions with rigor using an impactful research methodology like CBC.

Hands-on experience will drive home how conjoint analysis works, in an intuitive way. The audience will take five minutes to complete an online conjoint survey and in real-time see their preference scores. To keep things intuitive, we’ll stick to the math everybody learned by the 5th grade: counting and taking averages of numbers. If you didn’t understand conjoint analysis before, you’ll come away with an intuitive understanding of how and why it works so well.

Presentation type:

  • Case Study Presentation

Subjects covered:

  • Predictive analytics


  1. How Zappos is actively using choice-based conjoint to make decisions regarding product development and customer segmentation in an online retail environment.
  2. Choice-based conjoint gets you more than traditional concept testing.
  3. A practical understanding of how conjoint analysis works so that it could be implemented using a variety of commercial or open-source software tools.


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