The difficulty of sentiment-mining is shown by the example I offered in my earlier sentiment article. A comment posted to Dell's IdeaStorm.com forum, reproduced verbatim packs misspellings, “conversational” punctuation and syntax, and irregular capitalization that is both used for emphasis (“REALLY”) and misused (“ram”) in way that makes it hard to disambiguate the subject of the comment, random-access memory (RAM), from an animal:
Dell really... REALLY need to stop overcharging... and when i say overcharing... i mean atleast double what you would pay to pick up the ram yourself.
Yet while Catherine Cardoso, Associate Insights Manager at Unilever, says “Text analytics is a new methodology for us," she adds, "We were very pleased with the results and the depth of insight. The results were helpful beyond understanding reactions to our campaign. We also gained an understanding of what motivates people on discussion boards, which issues are most important to women in our target group, and how to create better products and messaging for them.” Cardoso sees great potential for text analytics. She says, “We've been thinking about other ways to utilize this technology which would allow us to not only continue to listen to and understand our consumers, but to create a more real-time two-way communication.” 数据挖掘研究院
Customer Experience Management/Enterprise Feedback Management
Customer experience management (CEM) and enterprise feedback management (EFM) initiatives seek to take organizations beyond measurement to active stakeholder engagement. These disciplines are not new; they are long-time staples of customer relationship management (CRM), product design and quality programs that have been given a significant boost by the addition of text analytics, including sentiment extraction, to the analytical mix.
CEM and EFM seek to discern the “voice of the customer” in the many millions of enterprise-customer contact points that may include, per Sid Banerjee, CEO of text-analytics vendor Clarabridge, “survey responses triggered by sale of product or services (either traditional brick-and-mortar or e-business transactions), surveys triggered by calls for support, verbatims triggered by the support process (e-mails, chats, conversation notes stored in a CRM application),” and other forms of interaction. They seek to shift the focus from markets to customers. Banerjee’s colleague, Clarabridge President Justin Langseth, explains, “One of our design goals for 2008 is to make CEM a lot more than just monitoring and analysis, but to actually turn it into a decision-making, what-if-enabled feedback loop where you can do analysis, support a decision, take action and then measure the results of the action later on in terms of better loyalty, higher satisfaction, more sales, retention/loss of customers, etc... i.e., management.”
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