Data from phone interactions can help
address customers’ complaints, and
predict their future purchasing behavior.
BY J.P. SHIM, J. KOH, S. FISTER, AND H. Y. SEO
SINCE THE MID-2000S, few business topics have
received as much attention as big data and business
analytics, 5, 8, 11, 13 including unstructured data derived
from social media, blogs, chat, and email messages.
In addition to unstructured data, You Tube, Vimeo,
and other video sources represent another aspect of
organizations’ customer services. A 2011 IBM survey of
more than 4,000 IT professionals from 93 countries and
25 industries7 identified big data and business analytics
as a major business trend for most organizations, along
with mobile, cloud, and social business technologies.
This trend is also reflected in a number
of professional reports and academic
journals, including McKinsey Quarterly
and MIS Quarterly. The related skills
can also potentially help give organizations a competitive advantage.
Big data takes many forms, including Web and social-media data, machine-to-machine data, transaction
data, biometric data, and human-generated data. Human-generated data is
our focus here, including vast quantities of unstructured data (such as call-center agents’ notes, voice recordings,
email messages, paper documents,
surveys, and electronic medical records). A number of call analytics technologies are available, including voice
searching and indexing for call centers
through company-specific phonic-indexing technology. One important
application is real-time monitoring
that, in a call-center setting, can help
address agitated callers and get supervisors involved more quickly. Analytics
can process hundreds of hours of audio files in a day, depending on server
load, and provide organizations detailed reports on ways to improve customer calls and related job functions,
detect problems in operational sectors, and even uncover root problems
in products. These systems capture,
categorize, store, and analyze unstructured data and can be customized for
each customer to include language
identification, audio entity extraction,
and real-time monitoring.
Here, we review speech and call analytics, especially phonetic search-pattern technology and actual use of voice
and Big Data:
˽ Practitioners and academic researchers
are paying increased attention to big
data and business analytics in various
industries, notably in call centers.
˽ The benefits of speech and call analytics
and voice searching/indexing technologies
can be fully understood only through real-world data and corporate cases.
˽ Such understanding involves learning
the technology, as well as its legal,
marketing, customer psychology, and