I want to run a project where I show different images, some of them should look bigger that others, so I need to add an extra white space to the image so that effect makes my product to look smaller than other ones.

Is it possible to export the detailed part-worth utilities for each attribute level at the individual respondent level, or is only the total utility aggregated by concept available (as shown in the Market Segmentation Report)?

What method is used to calculate the individual utility values displayed in the Market Segmentation Report? We noticed that the values are not based on a simple selection frequency ratio (times selected divided by times displayed), since they can also be negative.

In the Export Displayed Concepts file, there are columns labeled Standard Error, Confidence, and Confidence Interval Range 2. What does each of these metrics represent, and under what conditions are they populated with values other than zero?

While reviewing both the tutorial video and our previous session, we noticed that the Vote Count in the Market Share Simulator sometimes appears as a fractional value (e.g., 17.83) and other times as a whole number. What causes this difference? Is it due to ties being split across concepts, respondent weighting, or another calculation method?

The technical documentation we have, dated 2017, indicates that the simulation model uses a First Choice approach exclusively, without exponential weighting (i.e., no logit-based share-of-preference model). Is this still the current methodology, or has the calculation engine been updated since then?

We confirmed that the survey allows respondents to select a None/N/A option. How is this response incorporated into the utility estimation model and the Market Share Simulation? Is it excluded from the calculations, treated as a separate market share category, or handled in another way?

Does the platform estimate individual utilities using a Hierarchical Bayes (HB) approach, or does it use a different estimation method? We are particularly interested in understanding the stability of the utility estimates, given that each respondent typically completes only 8–12 choice tasks.

Does the platform provide any model fit or predictive performance metrics, such as hit rate, percent certainty, or any equivalent indicator that can be used to assess how well the estimated utilities predict respondents" actual choices?