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Our Analytics team also developed three live, demonstration choice-based conjoints to give you an example of the work we do:
This example simulates a situation in which a hip joint manufacturer is looking to introduce a new femoral stem to the marketplace but is unsure of what the exact product profile should be. Additionally, they are looking to understand what the market is willing to pay for this new stem. From this information we will be able to find the most preferred set of product features and the price point that maximizes their market share.
This example simulates a situation in which the makers of an over-the-counter heart burn medication are looking to understand the change in the OTC marketplace when the products from two competing companies enter. The data we gather from this conjoint is used to assess market share for each product as well as the impact of differing product features.
This example differs from the other two in the way that the choice scenarios are constructed. Before presenting respondents with a set of competing products we ask them to identify their ideal product up front – this allows us to simplify the choice tasks for respondents and focus on the attributes and features they care about the most. This type of design is most ideal when there is an abundance of potential product configurations all carrying different price tags. In this example, we would be able to find the ideal medical smartphone app as well as what people are willing to pay for each level of each feature. This level of granularity allows us to further understand the trade-offs, in preference, relative to an individual feature as well as its price.