You probably also know it can be difficult to import those designs to survey software. Most survey services expect the user to type the questions into a form. Even survey websites that can upload choice designs won’t always use the same data layout as a JMP table. There are many options for structuring the results from a choice experiment, and every software package does things a little bit differently.
Now, Conjoint.ly— a survey service especially for choice designs — is able to easily import JMP choice surveys.
Just create your design in JMP and export the Choice Profiles as a *.csv file.
Conjoint.ly is an excellent survey tool. The interface is clean and easy for your respondents to use. It has features for recruiting participants, filtering out responses from certain IP addresses, and sending survey participants to an external website once they’ve finished the survey. The service is free for academics. JMP users who are not in academia can field a survey designed in JMP for a reduced price.
Conjoint.ly also exports to a *.csv file that you can use to analyze your results in JMP. Just click the Export to JMP button when you’re ready to analyze your results.
Conjoint.ly’s interface is easy to use all by itself, but I’ve written a pair of JMP add-ins for export/import that will make your life easier. The export add-in checks column names to make sure you have the right layout for a Conjoint.ly survey. The import add-in also does a column name check and automatically opens the Choice platform with the right columns populated.
If you're using JMP for choice modeling, I hope you'll try Conjoint.ly's excellent survey software. It really does make fielding choice designs easy!
If you're new to choice modeling, it's an excellent way to answer your business quesitons about what your customers want and how they value trade-offs. Take a look at my colleague Ryan Lekivetz's blog posts about designing surveys for chocolate preferences, and how to rank products (even when your customers aren't great at telling you what they like).