I am designing a study where the objective is to collect the % for low, medium and high to populate probability tables. For example, my objective is to know what is the probability in % to have a {low, medium, high) intention to purchase a new phone given some scenarios where I modify some variables. For the purposes of the data I need % for low, medium and high; however my question is if it would be better to design my data collection questions as:
A) Directly asking for Low, Medium and High, and then I would just do the calculations for the % based on what people responded, very straightforward.
B) Use a 5-point likert scale and then re-scale considering very likely and likely as High, neutral as Medium, and unlikely and very unlikely as Low?
I am worried that for option A it might not be valid due to it not being at least 5 points, or it might be too simplistic that it might deemed not valid; on the other hand I am worried re-scaling as in option B might not be valid either if I do not have enough respondents or it becomes too arbitrary to re-scale as proposed.
I tried to look for other studies as examples but I was unable to find examples of any of both options. Any comment would be much appreciated.