The following technological trends have occurred in parallel and together positioned and enabled the execution of my research: (a) The field of consumer behaviour that focuses on intuitive judgment and perception biases has developed significantly in recent years, (b) Speech and voice technologies have reached a commercial stage, and (c) The Big Data boom and other proprietary data that are owned by large corporates have located the industry in a better position than traditional academic bodies in terms of research capabilities.  These global developments have created the opportunity to conduct this research which aims to explore the relationship between voice and speech attributes and consumer behaviour in the context of telephone based call centre interactions. The access to call centre recordings and their derivative analysis has enhanced this research with the unique experience of a practitioner rather than being limited to an at arm’s length theoretical analysis.  The research questions aim to identify voice and speech attributes that affect (positively or negatively) customer satisfaction levels, and ways in which a company can utilize these attributes to change the way its call centre staff operate.  The research methodology is based on a qualitative survey through which I collected data from a real-world call centre (auditory observation), and a triangulation of this data with that of a focus group session. The data went through a correlation test through a sample survey and a synthesis that processes the research findings into theoretical, published literature.  Following these research insights, I have developed a Hidden Forces Model which is based on the findings arising from the research. This model offers an alternative way to operate call centres considering adjustments in social interaction by the service staff in order to impact and optimise customer satisfaction for the benefit of the company