What I learned this week …came from an article in The New York Times by Alex Wright. The article, Mining the Web for Feelings not Facts, was a great look into a concept that is new to me, an emerging field called “sentiment analysis.” The article defines sentiment analysis as “translating the vagaries of human emotion into hard data.” The examples show companies using data analysis techniques to gain insight into what social media (such as social networks and blogs) are saying about their company. My thoughts immediately turned to the value this information would have to product developers to understand how customers feel about their products, and what a great tool this could be in the social computing toolkit for PLM.
I won’t repeat all of the fascinating things the article says, and instead recommend you take a few minutes to read it. It is very interesting, and an exciting new concept. Here are some of the key points from my perspective:
- Sentiment analysis opens a “window into the collective consciousness of Internet users”
- Opinions are a kind of “virtual currency“
- Social media offers a “rich vein of market intelligence“
The article points out that this is a new, imperfect science and mentions some interesting pioneers of the concept. It also introduces a new book which is on my “to read” list titled Opinion Mining and Sentiment Analysis by Bo Pang and Lillian Lee.
My Thoughts – Sentiment Analysis in PLM
So how can this social computing approach be used to develop more profitable products? If we can gather feedback on products, product ideas and competitive offerings rapidly it gives us the opportunity to react early to – or ahead of – a trend. Many manufacturers are starting to monitor social networking sites like Twitter to see what people are saying, but for the most part it is manual except for filtering on keywords. Currently, the review and analysis depends on people. This is not a sustainable approach for product managers and product marketers to sift through mountains of comments, at least in my opinion. But if social computing techniques can detect and alert them to potential changes in market opinion that they should pay attention to, that could provide the input needed to help steer product development (or at least product marketing, if changing the product quickly is not an option).
Product managers are already overwhelmed with input, and the Internet is creating even more every day. The information is valuable, but takes time to review and interpret. If computing algorithms can help decipher and summarize, then product developers can focus on the important trends as opposed to sifting through the haystack to find them.
Implications for Manufacturers
This is just one more example of how companies are trying to leverage social computing to improve their product innovation, product development, and engineering performance. There is clearly something going on here, something that offers significant advantages to the manufacturers that can figure it out and use social computing to their benefit. This example is part of what I call “social discovery,” which is a more advanced concept than more straight-forward uses of social computing in PLM such as enhancing collaboration. For more thoughts on social computing in PLM, you can click on the “social computing” tag on the ClarityonPLM site, or start with these thoughts on social product development and social computing in PLM.
So can we mine the web for emotions and use that market intelligence to drive product development? I think there is some real potential, among other opportunities that social computing and social networking are opening up. I hope you found it interesting. Who knew? I didn’t, if you did let us know about it.
Note: No, the picture has absolutely nothing to do with mining social networks, but I Googled “mind reading machines” and this is what came up. It made me smile, so I thought I would share it with you.