FEATURE: COGNITIVE CRM
W
ith this in mind, the first
generation of CRM systems
emerged which helped by
building up a central customer hub
where a customer’s relationship with
the organisation would be visible to
everyone within the company. This
provided information that empowered
marketing, sales and customer service
functions by providing them with the
appropriate tools and data to perform
one simple task “serve the customer”.
However, traditional first generation
CRMs relied on the structured data
about the customer captured across
multiple systems within the enterprise,
based on which decision making for
marketing, sales and customer services
was reliant on human Intelligence.
With increased build-up of structured
data and advances in business
intelligence technologies, a new
class of CRM called ‘Analytical CRM’
emerged. This however required
building up, predictive analytics and
statistical models, which although
not an impossible task required deep
technology, statistical and business
acumen. But again these models were
based on structured data for ‘what if’
analysis and forecasting.
With the explosion of social media
a new stream of unstructured data
emerged in the form of Facebook
posts, blogs and twitter feeds among
other social platforms. This led to
the emergence of socially integrated
CRMs mostly reliant on enabling
communication across said platforms. A
commonly agreed upon statistic is that
around 80 per cent of all data being
generated globally comes in the form of
unstructured data. This is a significant
amount, and making sense of it
requires an intelligent model mirroring
human cognition. Thus, traditional
CRM’s are ill equipped to make sense
out of this plethora of data.
Human Interaction however remains
vital. Customer perception is shaped
by the tone of the agent handling
the customer call regardless of data
patterns available along with a sales
COGNITIVE COMPUTING, HOWEVER, PROVIDES A PROMISE
TO SOLVE PROBLEMS OF TRADITIONAL CRMS. IT IS THE
LATEST BREAKTHROUGH IN TECHNOLOGY PROVIDING
NATURAL LANGUAGE PROCESSING, MACHINE LEARNING,
HUMAN SENTIMENT ANALYSIS, TONE ANALYSIS AND
TRADE OFF ANALYTICS
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