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Online researchers are beginning to see the value of replacing focus groups and questionnaires with netnography, which is the online version of traditional ethnography. ConsumerBase is a valuable tool for a key element of netnographic research—namely, discovering consumer likes and dislikes about a product or brand. But that’s only one aspect among many in a comprehensive netnography of a Web subculture. ConsumerBase can also return results on emotions and behaviors, trends over time, and more. Beyond that, there’s a wide range of useful knowledge about a subculture that we could discover with additional ConsumerBase lenses.

For example, we could build lenses to learn more about identities within the subculture. We could identify values, shared experiences, customs, symbols, attitudes, and much more.

Netnography Cover

Cover for Robert Kozinets' book on netnography

Community Aspects

We envision offering a set of lenses for ConsumerBase that will continue to grow and will enable it to discover many more aspects of online communities for netnographers. Here are examples of lenses we could build:

  • Identities
  • Values
  • Experiences
  • Meanings
  • Customs
  • Rituals
  • Beliefs
  • Symbols
  • Sayings
  • Attitudes
  • Behaviors
  • Associations members have between certain ideas
  • Social interactions
  • Practices
  • Events

Two unusual aspects that have linguistic patterns a ConsumerBase lens could identify are:

  • Competitiveness—Knowing to what degree members of a community are competitive has practical applications. For example, Professor Robert Kozinets, netnography pioneer, found that in the PriusChat community, members demonstrate competitiveness in knowledge about the car and the category, and about problem-solving, gas consumption, and so on.
  • Helpfulness—It’s also useful to know the degree to which members of a community are helpful to each other. In the PriusChat community, members were found to be helpful.

Regarding the members of a community, we could also identify, for example, who the influential people are, who has been thanked a lot, and other characteristics.

Applications

Using the lenses above, researchers could find communities on a particular subject and rank them according to the richness of the social interactions, competitiveness, helpfulness, and much more. This ranking of communities could help researchers find the best communities for participatory netnography, and could help consumers find the best communities to participate in.

Lens Requests?

We’d like to know what lenses you’d like us to build for ConsumerBase. Are there ones we should add to the above list? Please respond with any requests and ideas—we’re very interested to hear what lenses researchers and marketers believe would help them understand their audiences and do their jobs better.

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