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Digital Consumer Insight – Employing Netnography and Natural Language Processing for Service Development The online word-of-mouth behaviour that exists today in the Web represents new and measurable sources of information. The automated discovery of consumer opinions from these sources is of great importance for operational evaluation, marketing intelligence and service development. Techniques are now being established to effectively and easily mine the consumer opinions from the Web and to timely deliver them to companies. The catalyst for these changes in management ambitions is partly due to a move away from the traditional, linear marketing process to a digital model that is driven by consumer engagement and interaction. Companies are now beginning to explore how they can extract greater value from the social web as a source of information and competitive insight. The next frontier lies in extracting useful insights from the vast quantities of data available online and leveraging them to increase brand awareness and market share and reputation. Following the findings of Kozinets (2002), some early signs of sophisticated Voice of Customer (Customer Intelligence) software have emerged combining several data sources and providing real time actionable insight and real value for business development. Hitherto, the majority of available services simply accrue the information offering meager quantitative analysis and reports i.e. sentiment, volume or the source of discussion without further syntactic or grammatical causality or significance. Addressing the distinct and rapidly growing need to monitor, assess and analyse consumer-generated, the Digital Consumer Insight will be the theme of the future. Understanding digital influencers, the marketing, branding, research, marketing communications and competitive intelligence professionals would be able to analyse consumer discussions, trends and sentiment expressed in virtual world to gain immediate market intelligence. Furthermore, the understanding about what potential and existing customers, competitors and employees are discussing that may have significant effect on a company’s products, reputation, people and sales will be crucial. Displaying evidence from case studies, this research report will enlighten the possibilities of Netnographic research and the possibilities of sophisticated Natural Language Processing tools. The future will be about listening to consumers who are communicating online and being better able to enter into a conversation with bloggers, Twitter followers and Facebook fans, who represent some of the most intelligent, passionate and influential consumers. The ability to quickly, easily and accurately monitor attitudes and opinions provided by consumer insight tool will be critical information when evaluating a company’s reputation in the market. It will become vital that the company is able to monitor and be alerted of conversations about their products, features, services, problems and preferences and gain broader and deeper insight about how customers or prospects think about their company and competitors. Additionally, the ability to better identify new trends in customer perception of their company and its brands – and those of competitors is expected to create significant competitive advantage. Finally, with the help from a sophisticated Digital Consumer Insight tool, the company would be able to capture more detailed and unaided consumer requirements for imminent product design and execution and to enhance management of corporate reputation in the marketplace.