Predictive analytics is one of the most useful tools to analyze customer behavior on a particular product or services. This process helps identify customers’ needs and also chalk out a correlation matrix which helps to understand the additional demands. Companies monitor interactions of their clients to predict attrition. Negative consumer sentiment in social media, looking out for issues on the retailer's online knowledge base, and repeat calls to contact center may indicate attrition. It facilitates the next best interaction, monitor transaction details and analyze fraudulent activities. Neither business operations, nor business analytics have the complete information to make data-driven decisions, hence there exist a gap between customer needs and Delivery Company. To overcome this, customer centric ideas have to be taken in consideration. Businesses need a continuous and well-defined program to measure data quality. Establishing data quality standards and monitoring data quality quotient in real-time makes predictive analytics reliable.
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