everything about seo/sem, social media, ROI, netnography, gamification, online market research and construction and design of strategic information for organizations.
Michael Bartl’s The Making of Innovation shares a case study on how Nivea co-created a new deodorant with their customers, using online co-creation tools and a social media insight technique called netnography:
Due to the passive and unobtrusive observation of online communities, forums and other social media content companies are able to gain unbiased consumer insights. Instead of directly asking and thus inevitably biasing the consumer’s response the netnography approach aims to understand the emotional, social and cultural context of consumers’ product experiences in a merely observant fashion. As opposed to more quantitative web monitoring approaches, listening to consumers rather than asking them, understanding rather than measuring consumers’ attitudes and behaviors, are core principles of netnography. One of the greatest challenges for researchers conducting netnographies is to identify ‘diamonds in the rough’ – the most relevant and inspiring insights in the abundance of user statements online. For that reason a systematic software-aided five-step process was conceived as illustrated in [the diagram above.]
Michael Bartl talks about co-creation, netnography, and how to learn what your customers really think.
Analise do comportamento humano na internet #netnography #netnografia #sm (Publicado com o Instagram)
OK, this is something new ‘Netnogrphy’ but other than source of data (social media) would seem familiar otherwise.
This is how the creators of the study defined it:
This case study is a form of social media analysis called a netnography—a qualitative, interpretive research methodology that adapts the traditional, in-person ethnographic research techniques of anthropology to the study of online communities.
To write this netnography, NetBase analyzed thousands of posts from consumers about the brand. The posts are automatically sorted into Positive or Negative classifications by our natural language processing (NLP) engine, then we manually sample those posts.