  The maintenance of big cities public transport service quality requires
constant monitoring, which may become an expensive and time-consuming practice.
The perception of quality, from the users point of view is an important aspect
of quality monitoring. In this sense, we proposed a methodology for data
analysis and visualization, supported by software, which allows for the
structuring of estimates and assumptions of where and who seems to be having
unsatisfactory experiences while making use of the public transportation in
populous metropolitan areas. Moreover, it provides support in setting up a plan
for on-site quality surveys. The proposed methodology increases the likelihood
that, with the on-site visits, the interviewer finds users who suffer
inconveniences, which influence their behavior. Simulation comparison and a
small-scale pilot survey stand for the validity of the proposed method.
