Why big data is important in a customer-facing business

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Why big data is important in a
customer-facing business
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Why big data is important in a customer-facing
business
Market research and analysis has always been an
integral component of the strategy-making
process. Since the time when businesses focus
shifted from what-we-want-to-sell to
what-customers-actually-need, data started
gaining prominence. However, data was not as
easily available as it is now. Data collection
used to be an extremely tedious process and
involved several man-hours of surveying and
feedback obtainment.  As digital presence of
customers started existing parallel to their
physical presence, as the world started getting
more and more inter-connected, the data
procurement process became easier. Today
customers are producing heaps of data, which can
prove to be the ultimate gold mines for
businesses. With such an exorbitant amount of
data available and with so much hype about data
being the oil, one would expect that businesses
would be utilizing it to the fullest. A McKinsey
survey reported the contrary. Against the
expectations of the available data being
leveraged to take strategical decisions,
businesses are exhibiting a rather feeble
interest. This is mainly because of the growing
gap between the leaders and the laggards.  The
McKinsey report indicated a clear growth in
revenues and earning for the companies who chose
to use data and analytics for developing a
customer-focused plan. Doing so is especially
critical for the consumer-facing organizations in
this time of rapidly-changing trends and business
scenarios. PayPal co-founder, Max Levchin aptly
said, The world is awash in data and we can see
consumers in a lot clearer ways.  The amount of
data being generated in this interconnected world
can be truly overwhelming. Big data encompasses
massive volumes of structured and unstructured
data sets. All these data sets are valuable only
when they are mined to extract relevant
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Why big data is important in a customer-facing
business
information that can contribute towards improving
a process, product, or service. 21 of the
respondent of the McKinsey survey rated data and
analytics as their number-one key to
success. Although there are a lot of factors at
play that determine the viability of a
customer-focused strategy, big data analytics
significantly increase the probability of a
favorable outcome.  Today, 60 of the business
decision-makers believe that it is better to lose
half of their revenue over losing half of their
data. This distinctly emphasizes the value of
data in the present business landscape. Let us
try to understand how exactly big data and
analytics  contribute to the growth of businesses
today.  Understand your customers   In the world
of cut-throat competition, the ability to deliver
quality at speed is the only differentiator that
can keep a business ahead in the race. While
speed is a non-negotiable factor, quality is
subjective that depends on what customers expect
from a business and how the business was able to
fulfill those expectations.   For meeting the
customer expectations, it is essential to know
and understand the customers. By applying
analytic observation on the past user
experiences, purchase pattern, behavior, and
feedback, businesses can identify the gap areas
in their services. When the areas of
improvement are determined, the strategy can be
customized to address them and optimize the
service as per the customers needs.    Based on
the purchase history and buying pattern, the
customer experience can be personalized using the
information
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Why big data is important in a customer-facing
business

provided by big data analytics. The touch-points
and POS can be customized in such a way that
together create a seamless buying experience for
the customers.   By combining quality delivery
with a personalized experience, businesses can
significantly enhance the customer retention
rate.  Derive actionable insights to make better
decisions  Big data analytics supports a
business to determine which strategy, product, or
service is resonating with the customers, and
which is bouncing back off. This information
allows them to tweak and improve their existing
customer strategy in such a way that all the
bouncing parts are eliminated and only the
working parts remain, thus, generating an
immaculate plan for satisfying the end
users.  Big data analytics empower smart
decision-making. Using the power of automation
and AI-driven analytics it becomes possible to
identify the potential red flags and steer the
business away from risky outcomes. Additionally,
by enabling decision-making, big data increases
operational efficiency and business revenues. 
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Why big data is important in a customer-facing
business

The fundamental objective of big data is
to ensure that businesses make better decisions.
As Carly Fiorina, former executive, president,
and chair of Hewlett-Packard Co. puts it, The
goal is to turn data into information, and
information into insight.  Big data is the
ultimate determinant of all that is happening in
the digital as well as physical world. By putting
analytics on the collected and stored data,
businesses can establish end-to-end transparency
while segregating good ideas from bad
ones.  Ensure compliance, build trust  In this
digital age, privacy has taken the
top-most priority. As businesses scavenge for the
digital footprints of their customers, they must
also adhere to the laws and regulations that
protect the privacy of users.  Big data
analytics can easily narrow down multiple options
to a couple of practical choices, so that the
probability of success increases. While doing so,
the businesses must ensure that they take all the
measures to safeguard the confidentiality of the
sensitive user information. The
growing cyberthreats and data breaches make it
essential that necessary measures are deployed to
secure all the vulnerabilities and security gaps.
By protecting user data, businesses can establish
trust among the customers. 
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Why big data is important in a customer-facing
business

With robust data architecture, fraudulent
activities can be detected and controlled in
real-time. This allows businesses to nip any
potential threat in its bud itself, thus,
building a breach-proof, trustworthy, data
storage ecosystem.  Big data testing for assured
quality  Big data testing operates on three
levels information integration, data collection
and deployment, and scalability. By taking care
of volume, variety, and velocity of data, big
data testing provides assured value for
businesses by enabling superior customer
experiences.  Testing Big Data applications
requires a specific mindset, skillset and deep
understanding of the technologies, and pragmatic
approaches to data science. Cigniti leverages its
experience of having tested large scale data
warehousing and business intelligence
applications to offer a host of Big Data Testing
services and solutions.?Cigniti Testlets offer
point solutions for all the problems that a new
age Big Data Application would have to be go
through before being certified with QA levels
that match industry standards. Connect with our
big data testing experts here.  Read Full Blog
at https//www.cigniti.com/blog/big-data-testing
-customer-experience/
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