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INTEllIGENT COMPUTING | COVER STORY

and transactions data, Call Center data, Web browsing
behavior data, Online chat data, email Campaigns data
such as click through rates, Display Advertising data,
Voice data etc. This leads to a number of challenges such
as consistency of message across channels, launch of
offers across channels. Fragmentation of the channels
also means that customer voice and opinion is distributed
across the internet and in various forms – blogs, tweets,
Facebook update etc. Systems need to in place to keep a
real time watch on all this conversation and deliver timely
insights to marketing team to respond in a timely fashion.
Opportunities exist to break digital silos by combining data
such as user reviews with enterprise transaction systems
so that every time a customer gave a lower rating, an alert
ti-modal interfaces, resulting in seamless experiences. is generated which goes to a customer service agent who
Given below are some key enterprise trends from lever- then will connect with the customer.
aging smart environments: Digital Customer 360 helps generate unified customer
l Connect and engage end customers accessing insights based on data from multiple sales and interaction
products and services via multitude of devices such as channels. Enterprises need to leverage customer footprint
mobile, TV, sensors, appliances as well as via multitude of correlation engines which takes slivers of customer data
delivery and interaction channels from multiple interaction channels and builds an accurate
l Embed sensors into the eco-system and supply customer profile with product recommendations specific
chain for enhanced insights and experiences with regard to the channels of interaction. This involves complex event
to humans, goods, products and machines across their processing which co-relates Customer demographics and
life cycle usage transactions data, Call Center data, Web browsing behav-
l Offer location based experiences, services and pay- ior data, Online chat data, email Campaigns data such as
ment processing by leveraging bionic sensors and hand click through rates, Display Advertising data, Voice data
held devices etc. Given below are some key enterprise trends from lev-
eraging predictive analytics driven Customer 360:
PrEdICTIvE aNalyTICS drIvEN CUSTOMEr 360 l Build enterprise level Build Big Data correlation en-
Enterprises need to correlate customer data footprints from gines that generates Customer 360 insights by correlating
across multiple interaction channels and build an accurate data from multiple internal and external customer touch
customer profile with product recommendations specific points as well as open data
to the channels of interaction. This involves complex event l Create engaging experiences across multiple cus-
processing which co-relates Customer demographics tomer touch points by better understanding of customer
behavior using techniques such as text
analytics, natural language processing as
well as social network analysis.

arTIfICIal INTEllIGENCE drIvEN
MUlTI-STrUCTUrEd aNalyTICS
Multi-structured analytics constitutes
combining multiple types of data varied in
terms of their type and frequency includ-
ing structured, unstructured, multimedia
data, streaming data etc. Big data ana-
lytics about people and machines would
give us a historical picture of customer
behaviour, and known elements that con-
stitute a claims fraud and their evolution.

12 | January, 2018 www.dqindia.com A CyberMedia Publication |