If you have conducted or are considering utilizing conjoint analysis, you are likely interested in answering questions like ‘what will happen if we change the price of our product?’ or ‘how can we best optimize our product offering?’

You probably already know that the output of a conjoint study begins with a set of utilities. Utilities are quantifications of respondents’ preferences for each level of each attribute tested in your conjoint study. But what can you actually do with utility data?

To many market researchers, working with the utility data may be too abstract. So, how can you make your conjoint results more tangible and easy to use from a commercial perspective?

Simulate how the market will react

In the webcast below, you can learn about our most common deliverable to our clients: the choice-modeling market simulator.

Based in Excel, a market simulator is a powerful analysis tool and the most important deliverable resulting from a conjoint analysis project. Through the webcast tutorial, you can learn how to use a market simulator tool to find the answers to your business questions and navigate through different respondent segments.


How SKIMulator market simulation can help you

Simulators transform the utility data from your conjoint study into a tangible tool that you and your end-clients can use.

By simulating the choices of respondents in different scenarios, you can play what-if games and answer the questions from your conjoint study. By capturing preferences which occur at the individual or group level, one can predict the market preference for different product offerings or product enhancements. Because it is in Excel, you can easily share it with colleagues and end-clients to maximize use.

There are many benefits to using conjoint simulations based on the individual instead of aggregate utility data:

  • Observing cross-effects among different brands or product features
  • Reflecting interaction effects between attributes
  • Determining how well your product(s) will compete in the market
  • Understanding the price sensitivity for different brands or attributes
  • Identifying which product formulations will appeal to which groups of respondents