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Strategy & Research

Conjoint analysis informs new product development, bundling, pricing

March 24th 2017

A leading manufacturer of home and garden products needed help with a go-to-market strategy for an innovative product concept. Previous rounds of research had allowed our client to get to a specific point with product development. With the product's several attachments, warranties, starting systems and storage options all commanding different price points under consideration, additional research was needed to maximize product appeal while determining pricing to give the new product the best chance for success. Strategic questions included:

  • Should the new product be offered initially with a single attachment? If so, which attachment(s) would draw the most interest and at what price point(s)?
  • Should it be bundled? If so, how many and which attachments should it include?
  • Should the offer include a warranty? If so, what length will be most impactful?
  • Should a storage option be part of the offer? If so, which?
  • Beyond product and price, are there special promotions (e.g., rebate, BOGO, etc.) that would increase appeal?

THE SOLUTION – Conjoint Analysis

Marcus Thomas recommended adaptive choice-based conjoint analysis (ACBC), commonly used for new product development and bundling decisions to answer these questions.

Conjoint analysis tends to be more reliable than self-reported measures, as it is more realistic of how consumers make choices. The vast majority of purchase decisions are made in the subconscious. Therefore, implicit research methods, like conjoint analysis, are best suited to elicit consumer choices. In conjoint analysis, survey respondents are asked to choose among complete product configurations (like shoppers do during a purchase), as opposed to being asked about their preference for each feature one at a time. The analysis consists of deconstructing consumer choices to examine the implicit trade-offs made during purchase decisions and deriving the relative value placed on each product feature from those choices. In addition to identifying the best product configuration, findings are used to build and test scenarios to address unforeseen changes in later stages of product development (production cost increases, technical limitations preventing production of specific features, etc.).
Sample size was determined based on the number of product configurations to be tested, a multiple of product features and levels under consideration. In total, 1,800 respondents were recruited into an online survey based on ownership of relevant equipment. In all, we evaluated over 30,000 possible configurations. Profiling questions were used to analyze responses across consumer segments such as generation, income level and more. Promotional offers were tested outside of the conjoint exercise and product perceptions were gathered for messaging insights.


Analysis determined the attachments which were essential in the eyes of consumers. We learned that consumers interested in multiple attachments saw the most value in the product. Yet, findings established that offering each attachment individually was a better approach than bundling, as it preserves the flexible nature of the product that consumers like and want. We also determined that specific promotional offers would definitely motivate consumers.