NetBase Post Ties Into Innovation Topics
A new post on the NetBase blog about the social media conversation surrounding a product called Cricut from Provo Craft touches on several key topics in innovation and product positioning.
Specifically, the company’s policy toward third-party software relates to the idea of Lead User Innovation, because the company chooses not to embrace the creativity of users, which can have adverse consequences.
In addition, their policy on pricing puts them at risk for losing market share to a disruptive technology, because their add-on products are comparatively expensive, which potentially opens the door to a company producing a lower-cost alternative.
The blog post 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 the 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.
Specifically, the company’s policy toward third-party software relates to the idea of Lead User Innovation, because the company chooses not to embrace the creativity of users, which can have adverse consequences.
In addition, their policy on pricing puts them at risk for losing market share to a disruptive technology, because their add-on products are comparatively expensive, which potentially opens the door to a company producing a lower-cost alternative.
The blog post 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 the 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.