Significance of Data Analytics
Today, businesses can
collect data along with every point of the customer journey. This information
might include mobile app usage, digital clicks, interactions on social media,
and more, all contributing to a knowledge fingerprint that's unique to its
owner. However, at some point not too way back, the thought of consumers
sharing information like what time they awakened, what they ate for breakfast,
or where they went on holiday, would are a bizarre consideration, to mention
the smallest amount.
Pro-activity & Anticipating Needs:
Organizations are
increasingly under competitive pressure to not only acquire customers but also
understand their customers’ needs to be able to optimize customer experience
and develop longstanding relationships. By sharing their data and allowing
relaxed privacy in its use, customers expect companies to know them, form
relevant interactions, and provide a seamless experience across all touchpoints.
Warranty issues give way to IoT solution:
At Rockwell Automation,
a project came to the analytics team through the merchandise quality group at
the corporate.
“We were challenged
with a guaranty management issue,” says Sangeeta Edwin, director of business
intelligence at Rockwell Automation. “Instead of just watching the matter
presented, we stretched our data analytics team to specialize in identifying
the basis cause for the returns.”
By tracing the info
back to the machine-level, the team found a producing defect that correlated
assembly failures to warranty returns. This helped evolve our strategy and
platform to incorporate IoT [internet of things] machine data analytics,
Mitigating Risk & Fraud:
Security and fraud
analytics aims to guard all physical, financial, and intellectual assets against
misuse by internal and external threats. Efficient data and analytics
capabilities will deliver optimum levels of fraud prevention and overall
organizational security: deterrence requires mechanisms that allow companies to
quickly detect potentially fraudulent activity and anticipate future activity,
as well as identifying and tracking perpetrators.
Personalization & Service:
Companies are still
battling structured data, and wish to be extremely aware of deal with the
volatility created by customers engaging via digital technologies today. Being
able to react in real-time and make the customer feel personally valued is
merely possible through advanced analytics. Big data offers the opportunity for
interactions to be based on the personality of the customer, by understanding
their attitudes and considering factors such as real-time location to help
deliver personalization in a multi-channel service environment.
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