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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.