Conjoint Analysis or Configurator in New Product Research?

November 21st, 2018
Michele Sims | Vice President, Research Management, TRC
Hero Image: Conjoint Analysis or Configurator in New Product Research?

We at TRC conduct a lot of marketing research projects using conjoint analysis method. Conjoint is a very powerful tool for determining preferences for the various components that make up a product or service. The power of conjoint comes from having consumers make mental trade-offs in evaluating products against each other. Do they prefer a lower cost product that contains few features, or a higher priced product that provides many benefits? How willing are they to choose a product that meets 2 or 3 of their criteria, but not all? Conjoint forces consumers to make these decisions, and the results can then be simulated to determine purchase preferences in a variety of scenarios.

But not all product development problems can be solved with conjoint. Conjoint requires certain steps in the development cycle to have already been taken (defined features, some idea of pricing – see my previous blog on the topic.)

In some cases, though, you may be at a stage in which conjoint is feasible, but a different approach may be more appropriate, such as a configurator. In a configurator, otherwise known as a “build-your-own” approach, you would use the same product features as in a conjoint, but instead of pitting potential products against one another, the consumer “builds their own” ideal product.

So why choose one technique over the other? There are many reasons, but here are a few:

1. Choose Conjoint – if determining overall product price sensitivity is the goal. Conjoint will produce scores that assess both the importance of price overall as well as price tolerance for the product as features are included or excluded.

2. Choose Configurator – if you just want to know which features are the most popular, or which ones are selected when choosing or not choosing other features. In an a la carte scenario, respondents can choose which items to throw in their shopping cart and which ones to leave on the shelf. Getting simple counts on which features are popular and which ones are not – and in what combinations – can be very useful information, and it’s an easier task for respondents. Keep in mind though that the configurator works best if each feature is pre-assigned a price (to keep respondents from piling on).

3. Choose Conjoint – if understanding competitive advantage/disadvantage is paramount. Conjoint allows you to include “brand” as a feature, and the results will link brand to the product price to see if respondents are willing to pay more (or less) for your product vs. that of a key competitor. You can also simulate competitive market scenarios. While you can include brand in a configurator, modeling the trade-off between brand and product price is far less robust.

4. Choose Configurator – if you have a lot of features, or complex relationships between the features. It’s much easier for a respondent to sift through a long list of features and build their ideal product just once than to choose between products with a gigantic feature list multiple times. Conjoint works best when the features are not dependent on one another; a long list of restrictions on the features can disqualify conjoint as a viable solution from a design perspective.

There are plenty of times when a technique may present itself as an obvious choice, and other times when the choice may be more subtle. And in those cases, we turn to our senior analysts who use their expertise and understanding of the research objectives to make sound recommendations.