I try not to do much self-promotion on this blog, because I find that overly self-promotional blogs are not only boring in the extreme, but narcissistic. So forgive me if I mention a speaking gig that is coming up next week. I will really try not to lay this on too thick.
NetBase, an exciting company out of Palo Alto’s Silicon Valley, has sponsored me to come to the Advertising Research Foundation’s annual conference this year and speak about netnography. If any of you are available for it, the session is going to be held on Tuesday, March 23rd at 11am. I include their poster publicizing the event.
They have also been extremely generous in that they are giving away copies of my new book “Netnography: Doing Ethnographic Research Online” to attendees of the conference (see poster below and on the left for details). I will be on hand after the talk at the NetBase booth to personalize and sign the book and meet people.
So if you are coming to the ARF re:think conference in New York next week, PLEASE stop by, check out the talk, come meet me, and get your book. I’d really enjoy meeting you–so mention the blog.
As per FTC and other sensible guidelines, I’m writing this post of my own free will, and the opinions in it are not constructed, paid for, or endorsed by NetBase, although they did compensate me for writing the white paper and presenting it. So here’s something I think that marketing researchers, netnographers, and people/managers/researchers considering trying netnography might find interesting.
NetBase has developed web crawling software that mines the content on the Internet and also classifies it using a sophisticated semantic recognition engine. That means it is able to recognize certain words and word orders, and then sort the online communications into categories.
So, for example, if someone posts something on a blog that says “The problem with Kozinets is that he is so damn modest,” the engine is able to recognize that the communication is about Kozinets, that it is talking about a problem, and that the problem is about “modest” or “modesty.”
The semantic search engine can also pick out another comment, on Twitter, say, such as “I really like the fact that Kozinets is so incredibly generous.” The engine would know that this is a positive comment, that it is about me, and that the positive thing that is like is “generous.”
It can get quite sophisticated in making grouping of these categories and providing a readout of likes and dislikes through all types of social media, such as blogs, forums, Twitter feed, and so on.
I started talking to Michael Osofsky, the founder of the company, about 3 years ago, and I was immediately intrigued by the potential of this software to be used as a netnographic search engine. Michael has been a great ambassador for his new company. He recognized the usefulness of his tool to netnography from the very beginning, and he has sought to build insights about the netnographic process into each successive version of the software. They even have a “Why Netnography” page on their web-site.
What I am also very enthusiastic about is the way that NetBase’s product can speed up netnography by mining and classifying web-content, and then providing hyperlinks to original sources. So it actually mines conversations on the Net, comes up with relevant and pre-sorted verbata, and then, with a click, allows the user to look at the quotation in its original context. This is very handy when you are performing a netnography. Google and Technorati only can get you so far…something more sophisticated to take you farther.
Michael has been very generous about allowing me to use the NetBase system for netnographies, and I have found it very useful. In particular, recent iterations of the “ConsumerBase” system have helped me to conduct a few netnographies and have easily shaved days off my community identification and data collections research phases.
As I say in my book, computationally-assisted qualitative data analysis software is extremely helpful in conducting full-scale netnographies, and there are many good choices out there to use such as NVivo and Atlas.ti (although I am finding Atlas.ti’s business model a bit onerous and annoying lately). In the same vein, I think that semantic locations, sorting, and recognition software and systems such as NetBase’s ConsumerBase can be a very useful adjunct to all of the hard work involved in a netnography.
For a high-quality netnography, I see this as a powerful adjunct, an assist, and a helper, but not a substitute for the for full-on participant observation. But, just like CAQDAS, a sophisticated semantic engine can definitely speed the research process up and make it more efficient.
NetBase asked me to write a white paper about netnography. Not a promotional piece for them, but a methodological explanation for managers. They are going to be posting it to their web-site very soon, and I’ll include a link here when it is available. I also got to perform a short, illustrative, computationally-assisted netnography of the Listerine brand and its consumer innovations. It was fun to research and write it, and it will be great to share a practical, applied netnography with all of you, rather than the academic kind I usually publish.
We are also hoping to conduct and record a webinar using the ARF Presentation material, and I will let all of you know when it is ready.
I hope to see you in New York at the ARF Conference if you are going. If not, there will be lots of takeaways available through NetBase‘s efforts to get the word out on netnography. Thanks to everyone at NetBase, especially to Michael and Lisa (who has been extremely patient and a wonderful, delightful person to work with). And I’m really looking to continuing to follow their software products and to explore how they can be used to help netnographers everywhere.