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Companies have also long used predictive analytics techniques to make data-driven business decisions. It started in the insurance industry. Predictions about the risks of insureds were calculated based on various characteristics. “How does Predictive Analytics work?
For example, an insurance agent sells an insurance policy to an elderly lady, knowing that she does not need it because of her advanced age. The insurance agent deliberately uses psychological sales tricks to manipulate the lady into signing the contract in the end. That is, in principle, nothing terrible.
Customer attrition can represent a 24 % average in office supplies, 16 % in the insurance industry and 13 % in banking. Leaving a vendor, in this case, is not a deliberate decision. Identifying the root causes of customer attrition is a process commonly supported by advanced salesanalytics.
Finally, we look at the prominent role of AI and ML in predictive analytics and how they are helping companies make informed decisions, predict future events, and stay competitive. For example, intelligent systems can use ML to analyze large amounts of data and provide relevant insights to make informed decisions.
Finally, we look at the prominent role of AI and ML in predictive analytics and how they are helping companies make informed decisions, predict future events, and stay competitive. For example, intelligent systems can use ML to analyze large amounts of data and provide relevant insights to make informed decisions.
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