Capturing and understanding feedback received from customers in an efficient manner plays a critical role inareas such as Customer relationship management (CRM).Measures of customersȁ9; attitude towards a product or serviceare traditionally obtained using questionnaires formatted as xpointLikert scales, with results typically displayed numericallyand sometimes presented in graphic forms. Current ȁ8;affectiveȁ9;CRM solutions have focused on customer emotion detection by recognising non-verbal cues and physiological signals from customers (Input related research). However, these methods, although technologically advanced are only at a conceptual level and lack the viability and flexibility required by current CRM solutions. This paper presents a system prototype for Non-Verbal Affective User Feedback based on output related affective research. The system converts multi-criteria based estimates of a customerȁ9;s attitude towards a product or service,obtained using traditional CRM surveys, into a non-verbalrepresentation in the form of virtual facial expressions, oremoticons. Real facial expressions provide a feedback in aconcise pictorial form whose emotional content is readilyrecognisable. We focus on enabling the system to choose thoseemoticons that, with regards to their emotional content, would be unambiguously legible by users. Our approach is intended to improve the efficiency of the representation mode of CRM survey data making it visually comprehensible ȁ8;at-a-glanceȁ9;.
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