The notion that listening to your customer’s voice is important is well entrenched. Companies have long depended on data from customer surveys, call center transcripts and focus groups, captured in structured formats and handled through business intelligence applications, to help point the way to improved customer service, product enhancements and competitor vulnerabilities.
But the sheer volume of the customer choir in the Web 2.0 age often leaves companies scrambling to keep up. Publishing is now in the hands of the public, who have a vexing tendency to post with blunt honesty in unstructured formats via blogs, tweets, e-mails and forums about products and services that delight or disappoint them. And those opinions hold weight. A 2007 study by Jupiter Research (since acquired by Forrester), called “Social Networking Sites: Defining Advertising Opportunities in a Competitive Landscape,” found that 30 percent of frequent social networkers trust their peers’ opinions when making a major purchase decision, compared to the 10 percent who trust advertisements.
As Andreas Wiegend, former chief scientist of Amazon.com, predicted in a blog post for the Monitor Talent Group, “In 2009, more data will be generated by individuals than in the entire history of mankind through 2008.” Companies face a very real need not just to acknowledge the impact of unstructured social media on brand and product perception, but to understand and filter it sensibly, and to integrate it with structured customer data and get it into the hands of the right people to make it actionable.
For many companies, the burgeoning text analytics approach of sentiment analysis is becoming a critical component of their overall strategy, giving them a much-needed assist to stay responsive to customers, market opportunities and trends.
What is it?
In his white paper “Text Analytics 2009,” Seth Grimes, analytics strategist at Alta Plana, describes text analytics as “the software and the transformational steps that discover business value in ‘unstructured’ text.”
There’s special business value in discerning opinion, sentiment and subjectivity—the “voice of the customer”—in text as varied as blogs, forum postings, articles, e-mail and survey responses. That field of “customer experience analysis” applies sentiment analysis and other techniques to understand and help predict consumer behavior via text analysis coupled with analysis of customer transactions, profiles and demographics.
Vendors generally use a combination of statistical analysis of word frequency and [continue reading on next page]