Examples of applications in various industries

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Marketing : Creating personalized campaigns based on customer behavior.
Risk management : Assessment of financial and credit risks based on historical data.
Customer Service : Predicting which groups of customers are likely to abandon services and taking corrective action.
Example: Banks and insurance companies were early adopters of advanced predictive analytics to predict credit risk and identify customers likely to churn.

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Predictive analytics enables companies across a variety of sectors to achieve gambling data china better results. Here are some examples of applications in selected industries:

Industry Application of predictive analytics
Banking Credit risk assessment, financial fraud detection
Insurance Forecasting damage costs, identifying customers on the verge of resignation
E-commerce Personalization of offers, anticipation of shopping trends
Production Supply chain optimization, equipment failure prediction
Health service Early detection of diseases, prediction of therapy effectiveness
You can find more about data analysis in marketing in the article: Content marketing B2B – effective strategies .

Why is it worth implementing predictive analytics in your company?
Predictive analytics can help you make better business decisions and increase your competitiveness in the market. Regardless of your industry, its use allows you to: