How much linguisitic sophistication is needed in Voice of the Customer/Market applications?
According to Attensity CTO David Bean:
- Voice of the Customer/Market applications require less linguistic sophistication than other text mining applications.
- Hence, Voice of the Customer/Market apps are easier to get running than other text mining applications, which he conjectures is a big part of the reason for burgeoning sales.
I’m guessing most text mining vendors would agree with those views, although they might not agree with his elaborations, which include:
- Attensity’s knowledge extraction technology is more sophisticated than Clarabridge’s or most other competitors’.
- In particular, Clarabridge’s extraction is little more than bag-of-words.
- There’s a good match between companies he thinks have less-sophisticated extraction (e.g., Clarabridge, SAS, SPSS) and companies whose text mining sales are heavily concentrated in Voice of the Customer/Market applications.
So the question arises: Just how much linguistic sophistication is needed in these market-trend-oriented text mining applications?
I actually got onto this subject not just because of what David said, but also via a conversation an hour earlier with Brooke Aker of Expert System, who proposed linguistic sophistication as a key reason for beating the competition (which, however, didn’t include Attensity or Clarabridge) at two accounts. The point Brooke was stressing is that it’s important to be able to extract multiple facts or indicators of sentiment from the same sentence. E.g., “I just had a crummy Chevy, but at least the seats were comfortable” is both a negative indicator about Chevrolet and a positive indicator about Chevrolet’s seats. Attensity captures both of those too, and I think Clarabridge would as well. (If you do comprehensive/ exhaustive extraction, you extract — well, you should extract comprehensively.)
Anyhow, my first-best answer to the question I posed is:
- Sentiment analysis is hard, at least in venues where you have to deal with slang, metaphor, or irony (the real biggie). The more sophisticated, the better.
- Otherwise, the linguistics of customer/marketing applications is pretty straightforward. Just put together the right list of wacky synonyms, and you’re good to go.
But what do you think?
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One Response to “How much linguisitic sophistication is needed in Voice of the Customer/Market applications?”
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Linguistic sophistication is important in lieu of understanding the voice of the customer first hand. Understanding the agents take on a call is not the same as understanding what the customer said care of a voice recording. Additionally, if a customer phones a bank asking the agent to “correct a mistake on a bank statement or I will close my account”, this doesn’t necessarily mean he will actually close his account. Maybe he (or she) is a habitual complainer and knows how to press buttons to get things done.
The voice of the customer software that most vendors offer is not actual voice but more sentiment analysis of the agent’s keyboard entered summary of the call. The linguistic software is trying to infer the customer’s voice from this agent information.
Last year at the text summit, I made a small sideways comment about SAS being the only vendor actively analyzing actual voice. Currently, almost all of my presales support is in the area of voice analysis where I present the extension of work mentioned above into BI reporting software for consumption across an organization.
Voice of the customer is suddenly becoming very hot. It’s not all talk. Well, actually voice is talk, so maybe I should say it IS all talk 😉 While I’ve been speaking about voice analysis for some time, it has only recently gained good traction. Maybe other vendors messaging around “voice” of the customer is not meeting customer expectations of the software. It is certainly helping us.
And, of course, nothing surpasses having the customer personally rate their experience and mining the resulting information.
Manya Mayes
Chief Text Mining Strategist
SAS