You actually have a bit of choices for your data. A cluster analysis may be helpful to detect groups of responses, that is, people who tend to answer every question the same way. Another alternative would be correspondence analysis, where you could observe whether the levels of the responses are associated, for instance, whether those who agree that the software is expensive also tend to answer that it is difficult.
Regarding the ranks, I don't know what you mean by that. It is common to present mean or percentages, whatever suits you the best, with likert scale items if that's what you asking, but if you want to know which factor is more important for the consumer's decision you would need some more information and maybe some models. Hope this helps.