Transforming Unstructured Data into Market Intelligence: An interview with WiseWindow
At the end of last year, I sat down with my good friend and former colleague Marshall Toplansky to talk about how he is driving marketing innovation at WiseWindow- a company that he helped found and now runs as President. WiseWindow is a company that is taking the unstructured data found on the Internet and social media and turning that into streams of useful data that marketers can use to track customer attitudes around brand and brand attributes.
You will find excerpts from the interview in the video clip below. We talk about the evolution of sentiment analysis, how WiseWindow is driving innovation in this area(7:45), and the benefits that accrue to companies that have chosen to innovate using his technology(12:30).
My core insights from our discussion included the following:
- Sentiment analysis is rapidly gaining acceptance as an alternative/supplement to traditional methods of measuring consumer attitudes including voice of customer, customer satisfaction, and net promoter score.
- In many ways, sentiment analysis is superior because it can account for a much larger population sample on a broader array of topics than traditional methods and do it continuously. This creates the ability to track the changes in attitudes based on tactics that a company might employ to improve positioning in the marketplace. In short, the fact that sentiment analysis is orders of magnitude faster and cheaper, is leading to new paradigms in terms of how companies can track sentiment nearly real time and then focus resources to respond.
- Related to the point above, the predictive power of sentiment analysis is unleashed when companies are able to find relationships between customer attitudes and business performance.
- WiseWindow is driving innovation in this area by using pattern recognition technology to address the fact that different word combinations reflect different sentiments depending on the context in which a company operates. In sum, it is using web crawling technology in conjunction with natural language processing algorithms to not only track what people are saying about its clients, but also what they are saying about the specific attributes of the products, brands, and competitors.
- While financial services businesses have been early adopters of this technology, successful case studies are emerging in media and entertainment, autos, and election tracking.
For access to the full interview (a little over 60 minutes) I have included a podcast version of the talk. Enjoy!
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