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Problem with the levels which are not mutually exclusive


I am conducting CBC analysis for my masters thesis and basically the topic is launching a sunscreen 'for men'. I have "skin type" attribute and levels are "for all skin types" (which is already existing in the market) and "for men". Since for all skin types level actually includes both genders; these levels are not mutually exclusive.
However, creating an attribute with all potential combinations of these features did not make sense because the aim of research is to see if men want gender specific sunscreen.
In other case, formulating two separate attributes each with two levels also did not make sense to me.

Also, I've already done with data collection and now I am interpreting the results. But I wanted to be make sure about those levels to not interpret something problematic. I've also found interaction effect between "skin type" (2 levels) and "sunscreen type" (3 levels: milk, spray, mousse). However, gain in Pct. Cert. over Main Effects was 0.57% so I decided not to include the interaction effect into HB analysis according to your previous recommendations.

Could you please provide suggestions to this issue? Thanks in advance!
asked Oct 16, 2018 by Irem
Irem, it's a little hard to know what problems you may encounter if we don't know what interpretations you're trying to make.  Can you provide some more details?
My research question is:
To what extent does 'for men' specification affect male consumer preferences compared to other product attributes when buying sunscreen?

I distributed the survey only to males, hence there was  no question about gender.  Besides seeing the effect of 'for men', product line optimization and cannibalization effects are also my research's concern since there is no such product in the NL. I am not sure what kind of details I can provide further to be more clear. If you have any specific questions regarding my research, please let me know.

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