Quality assurance in crowdsourcing markets has appeared to be an acute problem over the last years. We propose a quality control method inspired by Statistical Process Control (SPC), commonly used to control output quality in production processes and characterised by relying on time-series data. Behavioural traces of users may play a key role in evaluating the performance of work done on crowdsourcing platforms. Therefore, in our experiment we explore fifteen behavioural traces for their ability to recognise the drop in work quality. Preliminary results indicate that our method has a high potential for real-time detection and signalling a drop in work quality.