In information visualisation, the visual artefacts should have a functional dimension, allowing the analysis of information, and an aesthetic dimension, to seize the users' attention to the information being displayed. However, in the data aesthetics field, the main concern is to produce aesthetically appealing artefacts. With this project, our goal is to try to join these two fields by exploring the aesthetic dimension of a functional visualisation model characterised by a series of parameters that can make the visualisation more functional and/or more aesthetically appealing. In concrete, we propose a framework based on interactive evolutionary computation (IEC) to evolve the parameters of the visualisation model, enabling the user to explore possibilities and to create different aesthetics over the same data. Our case study will be based on a dataset containing the consumption patterns within a Portuguese retail company. Through different validation methods - automatic fitness function, usage scenarios, and a user study - we show that our system is able to create a wide and diverse set of emergent visual artefacts that can be intriguing and aesthetically appealing for the user.