Predictive modeling is predominantly used in both research and analysis.
Listed below are different types of predictive models:
1. Descriptive Analytics: - It is completely related to the data.
2. Diagnostic Analytics: - It is one step ahead of descriptive analytics.
3. Predictive Analytics: - Uses both data mining, and machine learning to predict the future. The process includes looking at the past data and determining the future prediction.
4. Prescriptive Analytics: - Suggest suitable possible actions to implement for your business based on the historical data.
Advantages of this model:
Reduces human errors by providing accurate data analysis.
It helps you analyze the data and find out new opportunities to retain or attract customers.
Predictive analytics improved advanced decision-making.
It increases revenue and improves the production processes of your organization.
Increases customer engagement by reducing customer churn.
Disadvantages of this model:
Data collected from various sources like surveys, emails, and the company website can vary in format and quality.
Don't always give accurate information.
Read more: https://expressanalytics.com/what-is-predictive-modeling/
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Applications of Predictive Modelling
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