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Mining consumer-generated text can provide business intelligence to organizations by extracting important knowledge trapped in the form of opinions, thoughts, and ideas expressed by their employees and customers on various aspects relevant to business. The key challenge here is to extract and organize relevant information from noisy text in order to effectively transform it to actionable intelligence. However, there is no formal framework to guide this analytical task. In this work, we present a system that is suitable for purpose-driven mining of free-text customer feedback to convert the knowledge gained to actionable intelligence.