Displayr

Users are able to add prohibitions with conjoint but not with MaxDiff designs.

Currently, our MaxDiff tools cannot analyze anchored MaxDiff data. Instead, a customer needs to construct new variables that incorporate the anchoring data into a legacy Ranking question. See https://wiki.q-researchsoftware.com/wiki/Anchored_MaxDiff This process is often quite tedious and challenging for a user. They need to create often hundreds of new variables, programming them all by hand. Updating our R-based analysis tools to incorporate anchoring data would dramatically simplify the analysis for our users.

This maxdiff tool is currently only available in Q: https://wiki.q-researchsoftware.com/wiki/Marketing_-_MaxDiff_-_Analyze_with_Ranking_Question_(Legacy)_-_MaxDiff_Ranking_Question_from_Design_and_Choice_Data However, when analyzing some types of Anchored MaxDiff https://wiki.q-researchsoftware.com/wiki/Anchored_MaxDiff , it’s necessary to create new maxdiff variables instead of the standard best/worst variables. In a moderately sized maxdiff this will involve generating hundreds of new variables by hand. The QScript above automates the process of creating those variables, making it much simpler to analyze an Anchored MaxDiff. Alternatively, expanding our R-based tools to analyze Anchored MaxDiff data would make this unnecessary.

For example, show the Mean score from MaxDiff as a individual chart

This has come up twice in the past six months with two different clients.

From our ebook: Sparse MaxDiff / Random question allocation The simplest and often best strategy is to create a large design and then randomly allocate respondents to different questions. For example, if a design has 20 questions, each respondent may be randomly allocated ten. While this is a simple strategy, it is also a good strategy in that it is both simple and tends to produce good quality designs. Add an option to the design that will do the random allocation for each respondent.

Add Bandit MaxDiff to menu.

Update MaxDiff functions to be able to work better with different data formats based on programming limitations in Qualtrics.

The user was after a built-in way to run MaxDiff analysis filtered by each brand. Their solution was to use custom code to loop the analysis code. However, the issue here is that the analysis would time out. In this case, the request would be for users who know that their code is going to take a long time to run and want to be able to create a cloud instance that allows it to run while not necessarily having their document open. Most likely an enterprise feature.