If you make some assumptions about what characterizes a respondent who believes a level is unacceptable, then you might be able to do some sort of analysis. For example, you might make the assumption that across all the tasks in your study, if the respondent never picked a product concept containing a certain level, then it was unacceptable. This would involve exporting the CBC data to a .csv file out of SSI Web and doing some additional analysis in Excel or your favorite software package for analyzing .csv files.
However, this approach has its weaknesses, including:
1. Maybe over the limited number of choice tasks in your study, it was purely chance (due to the experimental design received by this respondent) that the respondent seemed to avoid a particular level and never picked a concept including it.
2. Maybe a respondent truly did think a level was unacceptable, but due to a careless error accidentally picked a concept with that level.
3. Maybe some respondents answered the first few choice tasks well, but then became fatigued and gave some random answers in the end, thus negating your ability to detect that they consistently felt a level was unacceptable.
Our ACBC software provides a way to try to get at unacceptables: observing over a series of choice tasks if a respondent consistently is avoiding a particular level...and then actually prompting the respondent on the screen to confirm or deny that the respondent thinks that level is unacceptable. While this seems like a plausible approach to very accurately identify unacceptable levels, a recent paper by Kevin Lattery found that even under ACBC's approach of identifying unacceptable levels, respondents would choose supposedly unacceptable levels later in holdout choice questions within the same survey. We don't know for certain whether the errors are in the holdouts or in the ACBC survey, but it points out the challenges of assessing unacceptables in conjoint questionnaires.
Academics such as Allenby and Gilbride came out with ways via HB analysis to try to infer unacceptable levels, but to my knowledge no software has been published to do what they proposed.