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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