Text mining is the discovery of patterns and relationships
from large sets of unstructured data—the kind
of data we generate in e-mails, phone conversations,
blog postings, online customer surveys, and tweets.
The mobile digital platform has amplified the
explosion in digital information, with hundreds of
millions of people calling, texting, searching,
“apping” (using applications), buying goods, and
writing billions of e-mails on the go.
Consumers today are more than just consumers:
they have more ways to collaborate, share information,
and influence the opinions of their friends and
peers, and the data they create in doing so have
significant value to businesses. Unlike structured
data, which are generated from events such as
completing a purchase transaction, unstructured data
have no distinct form. Nevertheless, managers
believe such data may offer unique insights into customer
behavior and attitudes that were much more
difficult to determine years ago.
For example, in 2007, JetBlue experienced
unprecedented levels of customer discontent in the
wake of a February ice storm that resulted in
widespread flight cancellations and planes stranded
on Kennedy Airport runways. The airline received
15,000 e-mails per day from customers during the
storm and immediately afterwards, up from its usual
daily volume of 400. The volume was so much larger
than usual that JetBlue had no simple way to read
everything its customers were saying.
Fortunately, the company had recently contracted
with Attensity, a leading vendor of text analytics
software, and was able to use the software to analyze
all of the e-mail it had received within two days.
According to JetBlue research analyst Bryan
Jeppsen, Attensity Analyze for Voice of the Customer
(VoC) enabled JetBlue to rapidly extract customer
sentiments, preferences, and requests it couldn’t find
any other way. This tool uses a proprietary technology
to automatically identify facts, opinions,...
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